Incorporation of quantum statistical features in molecular dynamics

International Nuclear Information System (INIS)

Ohnishi, Akira; Randrup, J.

1995-01-01

We formulate a method for incorporating quantum fluctuations into molecular-dynamics simulations of many-body systems, such as those employed for energetic nuclear collision processes. Based on Fermi's Golden Rule, we allow spontaneous transitions to occur between the wave packets which are not energy eigenstates. The ensuing diffusive evolution in the space of the wave packet parameters exhibits appealing physical properties, including relaxation towards quantum-statistical equilibrium. (author)

Modelling sediment dynamics due to hillslope-river interactions : incorporating fluvial behaviour in landscape evolution model LAPSUS

NARCIS (Netherlands)

Baartman, Jantiene E. M.; van Gorp, Wouter; Temme, Arnaud J. A. M.; Schoorl, Jeroen M.

Landscape evolution models (LEMs) simulate the three-dimensional development of landscapes over time. Different LEMs have different foci, e.g. erosional behaviour, river dynamics, the fluvial domain, hillslopes or a combination. LEM LAPSUS is a relatively simple cellular model operating on

Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

International Nuclear Information System (INIS)

Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

2006-01-01

Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

New systematic methodology for incorporating dynamic heat transfer modelling in multi-phase biochemical reactors.

Science.gov (United States)

Fernández-Arévalo, T; Lizarralde, I; Grau, P; Ayesa, E

2014-09-01

This paper presents a new modelling methodology for dynamically predicting the heat produced or consumed in the transformations of any biological reactor using Hess's law. Starting from a complete description of model components stoichiometry and formation enthalpies, the proposed modelling methodology has integrated successfully the simultaneous calculation of both the conventional mass balances and the enthalpy change of reaction in an expandable multi-phase matrix structure, which facilitates a detailed prediction of the main heat fluxes in the biochemical reactors. The methodology has been implemented in a plant-wide modelling methodology in order to facilitate the dynamic description of mass and heat throughout the plant. After validation with literature data, as illustrative examples of the capability of the methodology, two case studies have been described. In the first one, a predenitrification-nitrification dynamic process has been analysed, with the aim of demonstrating the easy integration of the methodology in any system. In the second case study, the simulation of a thermal model for an ATAD has shown the potential of the proposed methodology for analysing the effect of ventilation and influent characterization. Copyright © 2014 Elsevier Ltd. All rights reserved.

A dynamical model of terrorism

Directory of Open Access Journals (Sweden)

Firdaus Udwadia

2006-01-01

Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.

Incorporating nitrogen fixing cyanobacteria in the global biogeochemical model HAMOCC

Science.gov (United States)

Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina

2015-04-01

Nitrogen fixation by marine diazotrophs plays a fundamental role in the oceanic nitrogen and carbon cycle as it provides a major source of 'new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Since most global biogeochemical models include nitrogen fixation only diagnostically, they are not able to capture its spatial pattern sufficiently. Here we present the incorporation of an explicit, dynamic representation of diazotrophic cyanobacteria and the corresponding nitrogen fixation in the global ocean biogeochemical model HAMOCC (Hamburg Ocean Carbon Cycle model), which is part of the Max Planck Institute for Meteorology Earth system model (MPI-ESM). The parameterization of the diazotrophic growth is thereby based on available knowledge about the cyanobacterium Trichodesmium spp., which is considered as the most significant pelagic nitrogen fixer. Evaluation against observations shows that the model successfully reproduces the main spatial distribution of cyanobacteria and nitrogen fixation, covering large parts of the tropical and subtropical oceans. Besides the role of cyanobacteria in marine biogeochemical cycles, their capacity to form extensive surface blooms induces a number of bio-physical feedback mechanisms in the Earth system. The processes driving these interactions, which are related to the alteration of heat absorption, surface albedo and momentum input by wind, are incorporated in the biogeochemical and physical model of the MPI-ESM in order to investigate their impacts on a global scale. First preliminary results will be shown.

Modelling, simulation and applications of longitudinal train dynamics

Science.gov (United States)

Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

2017-10-01

Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

CFTSIM-ITER dynamic fuel cycle model

International Nuclear Information System (INIS)

Busigin, A.; Gierszewski, P.

1998-01-01

Dynamic system models have been developed for specific tritium systems with considerable detail and for integrated fuel cycles with lesser detail (e.g. D. Holland, B. Merrill, Analysis of tritium migration and deposition in fusion reactor systems, Proceedings of the Ninth Symposium Eng. Problems of Fusion Research (1981); M.A. Abdou, E. Vold, C. Gung, M. Youssef, K. Shin, DT fuel self-sufficiency in fusion reactors, Fusion Technol. (1986); G. Spannagel, P. Gierszewski, Dynamic tritium inventory of a NET/ITER fuel cycle with lithium salt solution blanket, Fusion Eng. Des. (1991); W. Kuan, M.A. Abdou, R.S. Willms, Dynamic simulation of a proposed ITER tritium processing system, Fusion Technol. (1995)). In order to provide a tool to understand and optimize the behavior of the ITER fuel cycle, a dynamic fuel cycle model called CFTSIM is under development. The CFTSIM code incorporates more detailed ITER models, specifically for the important isotope separation system, and also has an easier-to-use graphical interface. This paper provides an overview of CFTSIM Version 1.0. The models included are those with significant and varying tritium inventories over a test campaign: fueling, plasma and first wall, pumping, fuel cleanup, isotope separation and storage. An illustration of the results is shown. (orig.)

3.5D dynamic PET image reconstruction incorporating kinetics-based clusters

International Nuclear Information System (INIS)

Lu Lijun; Chen Wufan; Karakatsanis, Nicolas A; Rahmim, Arman; Tang Jing

2012-01-01

Standard 3D dynamic positron emission tomographic (PET) imaging consists of independent image reconstructions of individual frames followed by application of appropriate kinetic model to the time activity curves at the voxel or region-of-interest (ROI). The emerging field of 4D PET reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple frames within the image reconstruction task. Here we propose a novel reconstruction framework aiming to enhance quantitative accuracy of parametric images via introduction of priors based on voxel kinetics, as generated via clustering of preliminary reconstructed dynamic images to define clustered neighborhoods of voxels with similar kinetics. This is then followed by straightforward maximum a posteriori (MAP) 3D PET reconstruction as applied to individual frames; and as such the method is labeled ‘3.5D’ image reconstruction. The use of cluster-based priors has the advantage of further enhancing quantitative performance in dynamic PET imaging, because: (a) there are typically more voxels in clusters than in conventional local neighborhoods, and (b) neighboring voxels with distinct kinetics are less likely to be clustered together. Using realistic simulated 11 C-raclopride dynamic PET data, the quantitative performance of the proposed method was investigated. Parametric distribution-volume (DV) and DV ratio (DVR) images were estimated from dynamic image reconstructions using (a) maximum-likelihood expectation maximization (MLEM), and MAP reconstructions using (b) the quadratic prior (QP-MAP), (c) the Green prior (GP-MAP) and (d, e) two proposed cluster-based priors (CP-U-MAP and CP-W-MAP), followed by graphical modeling, and were qualitatively and quantitatively compared for 11 ROIs. Overall, the proposed dynamic PET reconstruction methodology resulted in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) for parametric DV

Rich dynamics of a food chain model with ratio-dependent type III ...

African Journals Online (AJOL)

user

prey dynamics is to incorporate discrete delay into the predator equations. ... models may be found in classical books of Gopalsamy (1992), Macdonald (1989) .... Model (1) has 10 parameters in all, which make mathematical analysis complex.

Incorporation of ice sheet models into an Earth system model: Focus on methodology of coupling

Science.gov (United States)

Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Nevecherja, Artiom

2018-03-01

Elaboration of a modern Earth system model (ESM) requires incorporation of ice sheet dynamics. Coupling of an ice sheet model (ICM) to an AOGCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmospheric and oceanic components. To overcome this difficulty, we apply two different approaches for the incorporation of ice sheets into an ESM. Coupling of the Antarctic ice sheet model (AISM) to the AOGCM is accomplished via using procedures of resampling, interpolation and assigning to the AISM grid points annually averaged meanings of air surface temperature and precipitation fields generated by the AOGCM. Surface melting, which takes place mainly on the margins of the Antarctic peninsula and on ice shelves fringing the continent, is currently ignored. AISM returns anomalies of surface topography back to the AOGCM. To couple the Greenland ice sheet model (GrISM) to the AOGCM, we use a simple buffer energy- and water-balance model (EWBM-G) to account for orographically-driven precipitation and other sub-grid AOGCM-generated quantities. The output of the EWBM-G consists of surface mass balance and air surface temperature to force the GrISM, and freshwater run-off to force thermohaline circulation in the oceanic block of the AOGCM. Because of a rather complex coupling procedure of GrIS compared to AIS, the paper mostly focuses on Greenland.

Tantalum strength model incorporating temperature, strain rate and pressure

Science.gov (United States)

Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Integrating microbial diversity in soil carbon dynamic models parameters

Science.gov (United States)

Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie

2015-04-01

Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten

A dynamic model of the greenhouse effect and its control

International Nuclear Information System (INIS)

Perman, R.; Nisbet, R.; Ma, Y.

1991-01-01

A dynamic model is developed for the analysis of programmes to control the greenhouse effect. The model uses simplified representations of physical processes determining climate change, linked to an economic model of emissions and emissions abatement. Feedbacks between physical and economic processes are incorporated, and the costs of emissions reduction are compared with the benefits through averted damage. Simulation analyses explore the relative merits of several intervention scenarios, each of which is compared with non intervention. Throughout the paper, emphasis is placed upon the long term consequences of behaviour, and the patterns of dynamic adjustment over time. (author)

Incorporating parametric uncertainty into population viability analysis models

Science.gov (United States)

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

Debris flow analysis with a one dimensional dynamic run-out model that incorporates entrained material

Science.gov (United States)

Luna, Byron Quan; Remaître, Alexandre; van Asch, Theo; Malet, Jean-Philippe; van Westen, Cees

2010-05-01

Estimating the magnitude and the intensity of rapid landslides like debris flows is fundamental to evaluate quantitatively the hazard in a specific location. Intensity varies through the travelled course of the flow and can be described by physical features such as deposited volume, velocities, height of the flow, impact forces and pressures. Dynamic run-out models are able to characterize the distribution of the material, its intensity and define the zone where the elements will experience an impact. These models can provide valuable inputs for vulnerability and risk calculations. However, most dynamic run-out models assume a constant volume during the motion of the flow, ignoring the important role of material entrained along its path. Consequently, they neglect that the increase of volume enhances the mobility of the flow and can significantly influence the size of the potential impact area. An appropriate erosion mechanism needs to be established in the analyses of debris flows that will improve the results of dynamic modeling and consequently the quantitative evaluation of risk. The objective is to present and test a simple 1D debris flow model with a material entrainment concept based on limit equilibrium considerations and the generation of excess pore water pressure through undrained loading of the in situ bed material. The debris flow propagation model is based on a one dimensional finite difference solution of a depth-averaged form of the Navier-Stokes equations of fluid motions. The flow is treated as a laminar one phase material, which behavior is controlled by a visco-plastic Coulomb-Bingham rheology. The model parameters are evaluated and the model performance is tested on a debris flow event that occurred in 2003 in the Faucon torrent (Southern French Alps).

Incorporating H2 Dynamics and Inhibition into a Microbially Based Methanogenesis Model for Restored Wetland Sediments

Science.gov (United States)

Pal, David; Jaffe, Peter

2015-04-01

Estimates of global CH4 emissions from wetlands indicate that wetlands are the largest natural source of CH4 to the atmosphere. In this paper, we propose that there is a missing component to these models that should be addressed. CH4 is produced in wetland sediments from the microbial degradation of organic carbon through multiple fermentation steps and methanogenesis pathways. There are multiple sources of carbon for methananogenesis; in vegetated wetland sediments, microbial communities consume root exudates as a major source of organic carbon. In many methane models propionate is used as a model carbon molecule. This simple sugar is fermented into acetate and H2, acetate is transformed to methane and CO2, while the H2 and CO2 are used to form an additional CH4 molecule. The hydrogenotrophic pathway involves the equilibrium of two dissolved gases, CH4 and H2. In an effort to limit CH4 emissions from wetlands, there has been growing interest in finding ways to limit plant transport of soil gases through root systems. Changing planted species, or genetically modifying new species of plants may control this transport of soil gases. While this may decrease the direct emissions of methane, there is little understanding about how H2 dynamics may feedback into overall methane production. The results of an incubation study were combined with a new model of propionate degradation for methanogenesis that also examines other natural parameters (i.e. gas transport through plants). This presentation examines how we would expect this model to behave in a natural field setting with changing sulfate and carbon loading schemes. These changes can be controlled through new plant species and other management practices. Next, we compare the behavior of two variations of this model, with or without the incorporation of H2 interactions, with changing sulfate, carbon loading and root volatilization. Results show that while the models behave similarly there may be a discrepancy of nearly

Incorporating free-floating car-sharing into an activity-based dynamic user equilibrium model : a demand-side model

NARCIS (Netherlands)

Li, Q.; Liao, F.; Timmermans, H.J.P.; Huang, H-J; Zhou, J.

2018-01-01

Free-floating car-sharing (FFC) has recently received increasing attention due to the flexibility in mobility services. Existing studies related to FFC mainly focus on the analysis of operational management and user preferences. Efforts to model the dynamic choices of free-floating shared cars (SCs)

The general dynamic model

DEFF Research Database (Denmark)

Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

2016-01-01

Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

Science.gov (United States)

Welstead, Jason

2014-01-01

This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

MDESRAP: a model for understanding the dynamics of electricity supply, resources and pollution

International Nuclear Information System (INIS)

Qudrat-Ullah, H.

2005-01-01

The inherent dynamic complexity of the energy policy design problem makes the conventional 'closed-form' solution impossible. This paper contributes a dynamic simulation model as a possible solution. The model captures the dynamics of underlying sectors of electricity demand, investment, capital, resource, production, environment and costs and pricing. The existing feedback loops, nonlinearity and time-lag characteristics present in the real world electricity systems are incorporated in the model. The model is calibrated to Pakistan's case data. How the model has been used in policy assessments and the design of the alternative energy policies subject to various environmental and resource constraints is also discussed. (author)

Dynamic Intellectual Capital Model in a Company

Directory of Open Access Journals (Sweden)

Vladimir Shatrevich

2015-06-01

Full Text Available The aim of this paper is to indicate the relations between company’s value added (VA and intangible assets. Authors declare that Intellectual capital (IC is one of the most relevant intangibles for a company, and the concept with measurement, and the relation with value creation is necessary for modern markets. Since relationship between IC elements and VA are complicated, this paper is aimed to create a usable dynamic model for building company’s value added through intellectual capital. The model is incorporating that outputs from IC elements are not homogeneously received and made some contributions to dynamic nature of IC relation and VA. Variables that will help companies to evaluate contribution of each element of IC are added to the model. This paper emphasizes the importance of a company’s IC and the positive interaction between them in generating profits for company.

Incorporating groundwater flow into the WEPP model

Science.gov (United States)

William Elliot; Erin Brooks; Tim Link; Sue Miller

2010-01-01

The water erosion prediction project (WEPP) model is a physically-based hydrology and erosion model. In recent years, the hydrology prediction within the model has been improved for forest watershed modeling by incorporating shallow lateral flow into watershed runoff prediction. This has greatly improved WEPP's hydrologic performance on small watersheds with...

Optimal parameters for the FFA-Beddoes dynamic stall model

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

1999-03-01

Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

An Extended Non-Lane-Based Optimal Velocity Model with Dynamic Collaboration

Directory of Open Access Journals (Sweden)

Zhipeng Li

2013-01-01

Full Text Available Incorporating the effects of the lane width in traffic, in this paper, we propose a dynamical model based on the strategy of three-vehicle cooperation driving. We obtain the smoother acceleration distribution in the new model through considering the dynamic collaboration with the nearest preceding vehicle and the nearest following vehicle. It is proved that the stability of the new model is greatly improved compared to the early non-lane-based car following model by using the linear stability theory. We find that when the parameter of lateral separation distance is identified, the amplitude of traffic congestion decreases with increasing the strength of dynamic collaboration in the simulation experiments. In addition, we apply the new extended model to simulate the motions of cars starting from a traffic signal and the dissipating of the traffic congestion; it is found that our new model can predict realistic delay time and kinematic wave speed and obtained a faster dissipation speed of traffic congestion than the traffic flow model without considering the dynamic collaboration.

Dynamic modelling and hardware-in-the-loop testing of PEMFC

Energy Technology Data Exchange (ETDEWEB)

Vath, Andreas; Soehn, Matthias; Nicoloso, Norbert; Hartkopf, Thomas [Technische Universitaet Darmstadt/Institut fuer Elektrische Energie wand lung, Landgraf-Georg-Str. 4, D-64283 Darmstadt (Germany); Lemes, Zijad; Maencher, Hubert [MAGNUM Automatisierungstechnik GmbH, Bunsenstr. 22, D-64293 Darmstadt (Germany)

2006-07-03

Modelling and hardware-in-the-loop (HIL) testing of fuel cell components and entire systems open new ways for the design and advance development of FCs. In this work proton exchange membrane fuel cells (PEMFC) are dynamically modelled within MATLAB-Simulink at various operation conditions in order to establish a comprehensive description of their dynamic behaviour as well as to explore the modelling facility as a diagnostic tool. Set-up of a hardware-in-the-loop (HIL) system enables real time interaction between the selected hardware and the model. The transport of hydrogen, nitrogen, oxygen, water vapour and liquid water in the gas diffusion and catalyst layers of the stack are incorporated into the model according to their physical and electrochemical characteristics. Other processes investigated include, e.g., the membrane resistance as a function of the water content during fast load changes. Cells are modelled three-dimensionally and dynamically. In case of system simulations a one-dimensional model is preferred to reduce computation time. The model has been verified by experiments with a water-cooled stack. (author)

Torsional Dynamics of Steerable Needles: Modeling and Fluoroscopic Guidance

Science.gov (United States)

Swensen, John P.; Lin, MingDe; Okamura, Allison M.; Cowan, Noah J.

2017-01-01

Needle insertions underlie a diversity of medical interventions. Steerable needles provide a means by which to enhance existing needle-based interventions and facilitate new ones. Tip-steerable needles follow a curved path and can be steered by twisting the needle base during insertion, but this twisting excites torsional dynamics that introduce a discrepancy between the base and tip twist angles. Here, we model the torsional dynamics of a flexible rod—such as a tip-steerable needle—during subsurface insertion and develop a new controller based on the model. The torsional model incorporates time-varying mode shapes to capture the changing boundary conditions inherent during insertion. Numerical simulations and physical experiments using two distinct setups—stereo camera feedback in semi-transparent artificial tissue and feedback control with real-time X-ray imaging in optically opaque artificial tissue— demonstrate the need to account for torsional dynamics in control of the needle tip. PMID:24860026

Chaotic Dynamics in Smart Grid and Suppression Scheme via Generalized Fuzzy Hyperbolic Model

NARCIS (Netherlands)

Sun, Q.; Wang, Y.; Yang, J.; Qiu, Y.; Zhang, H.

2014-01-01

This paper presents a method to control chaotic behavior of a typical Smart Grid based on generalized fuzzy hyperbolic model (GFHM). As more and more distributed generations (DG) are incorporated into the Smart Grid, the chaotic behavior occurs increasingly. To verify the behavior, a dynamic model

Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

Science.gov (United States)

Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

2012-04-01

Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

The System Dynamics Model for Development of Organic Agriculture

Science.gov (United States)

Rozman, Črtomir; Škraba, Andrej; Kljajić, Miroljub; Pažek, Karmen; Bavec, Martina; Bavec, Franci

2008-10-01

Organic agriculture is the highest environmentally valuable agricultural system, and has strategic importance at national level that goes beyond the interests of agricultural sector. In this paper we address development of organic farming simulation model based on a system dynamics methodology (SD). The system incorporates relevant variables, which affect the development of the organic farming. The group decision support system (GDSS) was used in order to identify most relevant variables for construction of causal loop diagram and further model development. The model seeks answers to strategic questions related to the level of organically utilized area, levels of production and crop selection in a long term dynamic context and will be used for simulation of different policy scenarios for organic farming and their impact on economic and environmental parameters of organic production at an aggregate level.

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

Science.gov (United States)

Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

2014-04-01

The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.

A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

Directory of Open Access Journals (Sweden)

Roman Bauer

Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

Dynamical regimes due to technological change in a microeconomical model of production

Science.gov (United States)

Hamacher, K.

2012-09-01

We develop a microeconomical model to investigate the impact of technological change onto production decisions of suppliers—modeling an effective feedback mechanism of the market. An important property—the time horizon of production planning—is related to the Kolmogorov entropy of the one-dimensional maps describing price dynamics. We simulate this price dynamics in an ensemble representing the whole macroeconomy. We show how this model can be used to support ongoing research in economic growth and incorporate the obtained microeconomic findings into the discussion about appropriate macroeconomic quantities such as the production function—thus effectively underpinning macroeconomics with microeconomical dynamics. From there we can show that the model exhibits different dynamical regimes (suggesting "phase transitions") with respect to an order parameter. The non-linear feedback under technological change was found to be the crucial mechanism. The implications of the obtained regimes are finally discussed.

CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

Science.gov (United States)

Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

2012-12-01

The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and

A modified social force model for crowd dynamics

Science.gov (United States)

Hassan, Ummi Nurmasyitah; Zainuddin, Zarita; Abu-Sulyman, Ibtesam M.

2017-08-01

The Social Force Model (SFM) is one of the most successful models in microscopic pedestrian studies that is used to study the movement of pedestrians. Many modifications have been done to improvise the SFM by earlier researchers such as the incorporation of a constant respect factor into the self-stopping mechanism. Before the new mechanism is introduced, the researchers found out that a pedestrian will immediately come to a halt if other pedestrians are near to him, which seems to be an unrealistic behavior. Therefore, researchers introduce a self-slowing mechanism to gradually stop a pedestrian when he is approaching other pedestrians. Subsequently, the dynamic respect factor is introduced into the self-slowing mechanism based on the density of the pedestrians to make the model even more realistic. In real life situations, the respect factor of the pedestrians should be dynamic values instead of a constant value. However, when we reproduce the simulation of the dynamic respect factor, we found that the movement of the pedestrians are unrealistic because the pedestrians are lacking perception of the pedestrians in front of him. In this paper, we adopted both dynamic respect factor and dynamic angular parameter, called modified dynamic respect factor, which is dependent on the density of the pedestrians. Simulations are performed in a normal unidirectional walkway to compare the simulated pedestrians' movements produced by both models. The results obtained showed that the modified dynamic respect factor produces more realistic movement of the pedestrians which conform to the real situation. Moreover, we also found that the simulations endow the pedestrian with a self-slowing mechanism and a perception of other pedestrians in front of him.

Incorporating direct marketing activity into latent attrition models

NARCIS (Netherlands)

Schweidel, David A.; Knox, George

2013-01-01

When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

2017-07-01

Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

An approach to incorporate the detonation shock dynamics into the calculation of explosive acceleration of metals

International Nuclear Information System (INIS)

Li Qingzhong; Sun Chengwei; Zhao Feng; Gao Wen; Wen Shanggang; Liu Wenhan

1999-11-01

The generalized geometrical optics model for the detonation shock dynamics (DSD) has been incorporated into the two dimensional hydro-code WSU to form a combination code ADW for numerical simulation of explosive acceleration of metals. An analytical treatment of the coupling conditions at the nodes just behind the detonation front is proposed. The experiments on two kinds of explosive-flyer assemblies with different length/diameter ratio were carried out to verify the ADW calculations, where the tested explosive was HMX or TATB based. It is found that the combination of DSD and hydro-code can improve the calculation precision, and has advantages in larger meshes and less CPU time

Dynamic model for the assessment of radiological exposure to marine biota

Energy Technology Data Exchange (ETDEWEB)

Vives i Batlle, J. [Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria CA24 3LN (United Kingdom)], E-mail: jordi.vives@westlakes.ac.uk; Wilson, R.C.; Watts, S.J.; Jones, S.R.; McDonald, P.; Vives-Lynch, S. [Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria CA24 3LN (United Kingdom)

2008-11-15

A generic approach has been developed to simulate dynamically the uptake and turnover of radionuclides by marine biota. The approach incorporates a three-compartment biokinetic model based on first order linear kinetics, with interchange rates between the organism and its surrounding environment. Model rate constants are deduced as a function of known parameters: biological half-lives of elimination, concentration factors and a sample point of the retention curve, allowing for the representation of multi-component release. The new methodology has been tested and validated in respect of non-dynamic assessment models developed for regulatory purposes. The approach has also been successfully tested against research dynamic models developed to represent the uptake of technetium and radioiodine by lobsters and winkles. Assessments conducted on two realistic test scenarios demonstrated the importance of simulating time-dependency for ecosystems in which environmental levels of radionuclides are not in equilibrium.

Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

Science.gov (United States)

Filo, Maurice G.

This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

DEFF Research Database (Denmark)

Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

2009-01-01

We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

Thermodynamic model of a thermal storage air conditioning system with dynamic behavior

International Nuclear Information System (INIS)

Fleming, Evan; Wen, Shaoyi; Shi, Li; Silva, Alexandre K. da

2013-01-01

Highlights: • We developed an automotive thermal storage air conditioning system model. • The thermal storage unit utilizes phase change materials. • We use semi-analytic solution to the coupled phase change and forced convection. • We model the airside heat exchange using the NTU method. • The system model can incorporate dynamic inputs, e.g. variable inlet airflow. - Abstract: A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system’s dynamic behavior, such as a dynamic air flow rate into the vehicle’s cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle’s cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid–air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semi-analytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid–air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system

A mathematical model for incorporating biofeedback into human postural control

Directory of Open Access Journals (Sweden)

Ersal Tulga

2013-02-01

Full Text Available Abstract Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1 to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2 to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional

A mathematical model for incorporating biofeedback into human postural control

Science.gov (United States)

2013-01-01

Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP) to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional torque to the postural

Dynamic process model of a plutonium oxalate precipitator. Final report

Energy Technology Data Exchange (ETDEWEB)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

Dynamic process model of a plutonium oxalate precipitator. Final report

International Nuclear Information System (INIS)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

MO-E-17A-02: Incorporation of Contrast Medium Dynamics in Anthropomorphic Phantoms: The Advent of 5D XCAT Models

Energy Technology Data Exchange (ETDEWEB)

Sahbaee, P [NC State University, Raleigh, NC (United States); Samei, E [Duke University Medical Center, Durham, NC (United States); Segars, W [Duke University, Durham, NC (United States)

2014-06-15

Purpose: To develop a unique method to incorporate the dynamics of contrast-medium propagation into the anthropomorphic phantom, to generate a five-dimensional (5D) patient model for multimodality imaging studies. Methods: A compartmental model of blood circulation network within the body was embodied into an extended cardiac-torso (4D-XCAT) patient model. To do so, a computational physiologic model of the human cardiovascular system was developed which includes a series of compartments representing heart, vessels, and organs. Patient-specific cardiac output and blood volume were used as inputs influenced by the weight, height, age, and gender of the patient's model. For a given injection protocol and given XCAT model, the contrast-medium transmission within the body was described by a series of mass balance differential equations, the solutions to which provided the contrast enhancement-time curves for each organ; thereby defining the tissue materials including the contrastmedium within the XCAT model. A library of time-dependent organ materials was then defined. Each organ in each voxelized 4D-XCAT phantom was assigned to a corresponding time-varying material to create the 5D-XCAT phantom in which the fifth dimension is blood/contrast-medium within the temporal domain. Results: The model effectively predicts the time-varying concentration behavior of various contrast-medium administration in each organ for different patient models as function of patient size (weight/height) and different injection protocol factors (injection rate and pattern, iodine concentration or volume). The contrast enhanced XCAT patient models was developed based on the concentration of iodine as a function of time after injection. Conclusion: Majority of medical imaging systems take advantage of contrast-medium administration in terms of better image quality, the effect of which was ignored in previous optimization studies. The study enables a comprehensive optimization of contrast

Modeling opinion dynamics: Theoretical analysis and continuous approximation

International Nuclear Information System (INIS)

Pinasco, Juan Pablo; Semeshenko, Viktoriya; Balenzuela, Pablo

2017-01-01

Highlights: • We study a simple model of persuasion dynamics with long range pairwise interactions. • The continuous limit of the master equation is a nonlinear, nonlocal, first order partial differential equation. • We compute the analytical solutions to this equation, and compare them with the simulations of the dynamics. - Abstract: Frequently we revise our first opinions after talking over with other individuals because we get convinced. Argumentation is a verbal and social process aimed at convincing. It includes conversation and persuasion and the agreement is reached because the new arguments are incorporated. Given the wide range of opinion formation mathematical approaches, there are however no models of opinion dynamics with nonlocal pair interactions analytically solvable. In this paper we present a novel analytical framework developed to solve the master equations with non-local kernels. For this we used a simple model of opinion formation where individuals tend to get more similar after each interactions, no matter their opinion differences, giving rise to nonlinear differential master equation with non-local terms. Simulation results show an excellent agreement with results obtained by the theoretical estimation.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Directory of Open Access Journals (Sweden)

Mark G Orr

Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Science.gov (United States)

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

An FDTD algorithm for simulation of EM waves propagation in laser with static and dynamic gain models

KAUST Repository

Al-Jabr, Ahmad Ali; Alsunaidi, Mohammad A.; Ooi, Boon S.

2013-01-01

This paper presents methods of simulating gain media in the finite difference time-domain (FDTD) algorithm utilizing a generalized polarization formulation. The gain can be static or dynamic. For static gain, Lorentzian and non-Lorentzian models are presented and tested. For the dynamic gain, rate equations for two-level and four-level models are incorporated in the FDTD scheme. The simulation results conform with the expected behavior of wave amplification and dynamic population inversion.

A Langevin model for fluctuating contact angle behaviour parametrised using molecular dynamics.

Science.gov (United States)

Smith, E R; Müller, E A; Craster, R V; Matar, O K

2016-12-06

Molecular dynamics simulations are employed to develop a theoretical model to predict the fluid-solid contact angle as a function of wall-sliding speed incorporating thermal fluctuations. A liquid bridge between counter-sliding walls is studied, with liquid-vapour interface-tracking, to explore the impact of wall-sliding speed on contact angle. The behaviour of the macroscopic contact angle varies linearly over a range of capillary numbers beyond which the liquid bridge pinches off, a behaviour supported by experimental results. Nonetheless, the liquid bridge provides an ideal test case to study molecular scale thermal fluctuations, which are shown to be well described by Gaussian distributions. A Langevin model for contact angle is parametrised to incorporate the mean, fluctuation and auto-correlations over a range of sliding speeds and temperatures. The resulting equations can be used as a proxy for the fully-detailed molecular dynamics simulation allowing them to be integrated within a continuum-scale solver.

ITER Dynamic Tritium Inventory Modeling Code

International Nuclear Information System (INIS)

Cristescu, Ioana-R.; Doerr, L.; Busigin, A.; Murdoch, D.

2005-01-01

A tool for tritium inventory evaluation within each sub-system of the Fuel Cycle of ITER is vital, with respect to both the process of licensing ITER and also for operation. It is very likely that measurements of total tritium inventories may not be possible for all sub-systems, however tritium accounting may be achieved by modeling its hold-up within each sub-system and by validating these models in real-time against the monitored flows and tritium streams between the systems. To get reliable results, an accurate dynamic modeling of the tritium content in each sub-system is necessary. In order to optimize the configuration and operation of the ITER fuel cycle, a dynamic fuel cycle model was developed progressively in the decade up to 2000-2001. As the design for some sub-systems from the fuel cycle (i.e. Vacuum pumping, Neutral Beam Injectors (NBI)) have substantially progressed meanwhile, a new code developed under a different platform to incorporate these modifications has been developed. The new code is taking over the models and algorithms for some subsystems, such as Isotope Separation System (ISS); where simplified models have been previously considered, more detailed have been introduced, as for the Water Detritiation System (WDS). To reflect all these changes, the new code developed inside EU participating team was nominated TRIMO (Tritium Inventory Modeling), to emphasize the use of the code on assessing the tritium inventory within ITER

Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.

Science.gov (United States)

Suresh, Krithika; Taylor, Jeremy M G; Spratt, Daniel E; Daignault, Stephanie; Tsodikov, Alexander

2017-11-01

Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. To circumvent the assumptions and computational burden associated with a joint model, approximate methods for dynamic prediction have been proposed. One such method is landmarking, which fits a Cox model at a sequence of landmark times, and thus is not a comprehensive probability model of the marker process and the event time. Considering an illness-death model, we derive the residual time distribution and demonstrate that the structure of the Cox model baseline hazard and covariate effects under the landmarking approach do not have simple form. We suggest some extensions of the landmark Cox model that should provide a better approximation. We compare the performance of the landmark models with joint models using simulation studies and cognitive aging data from the PAQUID study. We examine the predicted probabilities produced under both methods using data from a prostate cancer study, where metastatic clinical failure is a time-dependent covariate for predicting death following radiation therapy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Framework for optimal power flow incorporating dynamic system security

International Nuclear Information System (INIS)

El-Kady, M.A.; Owayedh, M.S.

2006-01-01

This paper introduces a novel framework and methodologies which are capable of tackling the complex issue of power system economy versus security in a practical and effective manner. At heart of achieving such a challenging and far-reaching objective is the incorporation of the Dyanamic Security Assessment (DSA) into production optimization techniques using the Transient Energy Function (TEF) method. In addition, and in parallel with the already well established concept of the system security, two new concepts pertaining to power system performance will be introduced in this paper, namely the concept of system dynamic susceptibility, which measures the level of systems weakness to a particular contingency and the concept of system consequent restorability, which measures the extent of contingency severity in terms of the required subsequent system restoration work should a particular contingency occur. (author)

Progress and problems in modelling HTR core dynamics

International Nuclear Information System (INIS)

Scherer, W.; Gerwin, H.

1991-01-01

In recent years greater effort has been made to establish theoretical models for HTR core dynamics. At KFA Juelich the TINTE (TIme dependent Neutronics and TEmperatures) code system has been developed, which is able to model the primary circuit of an HTR plant using modern numerical techniques and taking into account the mutual interference of the relevant physical variables. The HTR core is treated in 2-D R-Z geometry for both nucleonics and thermo-fluid-dynamics. 2-energy-group diffusion theory is used in the nuclear part including 6 groups of delayed neutron precursors and 14 groups of decay heat producers. Local and non-local heat sources are incorporated, thus simulating gamma ray transport. The thermo-fluid-dynamics module accounts for heterogeneity effects due to the pebble bed structure. Pipes and other components of the primary loop are modelled in 1-D geometry. Forced convection may be treated as well as natural convection in case of blower breakdown accidents. Validation of TINTE has started using the results of a comprehensive experimental program that has been performed at the Arbeitsgemeinschaft Versuchsreaktor GmbH (AVR) high temperature pebble bed reactor at Juelich. In the frame of this program power transients were initiated by varying the helium blower rotational speed or by moving the control rods. In most cases a good accordance between experiment and calculation was found. Problems in modelling the special AVR reactor geometry in two dimensions are described and suggestions for overcoming the uncertainties of experimentally determined control rod reactivities are given. The influence of different polynomial expansions of xenon cross sections to long term transients is discussed together with effects of burnup during that time. Up to now the TINTE code has proven its general applicability to operational core transients of HTR. The effects of water ingress on reactivity, fuel element corrosion and cooling gas properties are now being

Stability of a general delayed virus dynamics model with humoral immunity and cellular infection

Science.gov (United States)

Elaiw, A. M.; Raezah, A. A.; Alofi, A. S.

2017-06-01

In this paper, we investigate the dynamical behavior of a general nonlinear model for virus dynamics with virus-target and infected-target incidences. The model incorporates humoral immune response and distributed time delays. The model is a four dimensional system of delay differential equations where the production and removal rates of the virus and cells are given by general nonlinear functions. We derive the basic reproduction parameter R˜0 G and the humoral immune response activation number R˜1 G and establish a set of conditions on the general functions which are sufficient to determine the global dynamics of the models. We use suitable Lyapunov functionals and apply LaSalle's invariance principle to prove the global asymptotic stability of the all equilibria of the model. We confirm the theoretical results by numerical simulations.

Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters

Directory of Open Access Journals (Sweden)

Wen Xu

2016-10-01

Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.

Robust and efficient parameter estimation in dynamic models of biological systems.

Science.gov (United States)

Gábor, Attila; Banga, Julio R

2015-10-29

Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

True dose from incorporated activities. Models for internal dosimetry

International Nuclear Information System (INIS)

Breustedt, B.; Eschner, W.; Nosske, D.

2012-01-01

The assessment of doses after incorporation of radionuclides cannot use direct measurements of the doses, as for example dosimetry in external radiation fields. The only observables are activities in the body or in excretions. Models are used to calculate the doses based on the measured activities. The incorporated activities and the resulting doses can vary by more than seven orders of magnitude between occupational and medical exposures. Nevertheless the models and calculations applied in both cases are similar. Since the models for the different applications have been developed independently by ICRP and MIRD different terminologies have been used. A unified terminology is being developed. (orig.)

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems.

Science.gov (United States)

Webb, Matthew H; Terauds, Aleks; Tulloch, Ayesha; Bell, Phil; Stojanovic, Dejan; Heinsohn, Robert

2017-10-01

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence-background (i.e., presence-only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine-resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine-resolution data). The occupancy models produced significantly (P increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists. © 2017 Society for Conservation Biology.

Equivalent Dynamic Models.

Science.gov (United States)

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Incorporating interfacial phenomena in solidification models

Science.gov (United States)

Beckermann, Christoph; Wang, Chao Yang

1994-01-01

A general methodology is available for the incorporation of microscopic interfacial phenomena in macroscopic solidification models that include diffusion and convection. The method is derived from a formal averaging procedure and a multiphase approach, and relies on the presence of interfacial integrals in the macroscopic transport equations. In a wider engineering context, these techniques are not new, but their application in the analysis and modeling of solidification processes has largely been overlooked. This article describes the techniques and demonstrates their utility in two examples in which microscopic interfacial phenomena are of great importance.

High-Strain Rate Failure Modeling Incorporating Shear Banding and Fracture

Science.gov (United States)

2017-11-22

High Strain Rate Failure Modeling Incorporating Shear Banding and Fracture The views, opinions and/or findings contained in this report are those of...SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6. AUTHORS...Report as of 05-Dec-2017 Agreement Number: W911NF-13-1-0238 Organization: Columbia University Title: High Strain Rate Failure Modeling Incorporating

Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks

DEFF Research Database (Denmark)

Hedegaard, Karsten; Balyk, Olexandr

2013-01-01

Individual compression heat pumps constitute a potentially valuable resource in supporting wind power integration due to their economic competitiveness and possibilities for flexible operation. When analysing the system benefits of flexible heat pump operation, effects on investments should...... be taken into account. In this study, we present a model that facilitates analysing individual heat pumps and complementing heat storages in integration with the energy system, while optimising both investments and operation. The model incorporates thermal building dynamics and covers various heat storage...... of operating heat pumps flexibly. This includes prioritising heat pump operation for hours with low marginal electricity production costs, and peak load shaving resulting in a reduced need for peak and reserve capacity investments....

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study.

Science.gov (United States)

Hamaker, E L; Asparouhov, T; Brose, A; Schmiedek, F; Muthén, B

2018-04-06

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent-but mostly unresolved-issues in the area of dynamic multilevel modeling.

Development of Dynamic Environmental Effect Calculation Model

International Nuclear Information System (INIS)

Jeong, Chang Joon; Ko, Won Il

2010-01-01

The short-term, long-term decay heat, and radioactivity are considered as main environmental parameters of SF and HLA. In this study, the dynamic calculation models for radioactivity, short-term decay heat, and long-term heat load of the SF are developed and incorporated into the Doneness code. The spent fuel accumulation has become a major issue for sustainable operation of nuclear power plants. If a once-through fuel cycle is selected, the SF will be disposed into the repository. Otherwise, in case of fast reactor or reuse cycle, the SF will be reprocessed and the high level waste will be disposed

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

Science.gov (United States)

Nash, C. J.; Cole, D. J.

2018-05-01

A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

A general science-based framework for dynamical spatio-temporal models

Science.gov (United States)

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

Incorporating intelligence into structured radiology reports

Science.gov (United States)

Kahn, Charles E.

2014-03-01

The new standard for radiology reporting templates being developed through the Integrating the Healthcare Enterprise (IHE) and DICOM organizations defines the storage and exchange of reporting templates as Hypertext Markup Language version 5 (HTML5) documents. The use of HTML5 enables the incorporation of "dynamic HTML," in which documents can be altered in response to their content. HTML5 documents can employ JavaScript, the HTML Document Object Model (DOM), and external web services to create intelligent reporting templates. Several reporting templates were created to demonstrate the use of scripts to perform in-template calculations and decision support. For example, a template for adrenal CT was created to compute contrast washout percentage from input values of precontrast, dynamic postcontrast, and delayed adrenal nodule attenuation values; the washout value can used to classify an adrenal nodule as a benign cortical adenoma. Dynamic templates were developed to compute volumes and apply diagnostic criteria, such as those for determination of internal carotid artery stenosis. Although reporting systems need not use a web browser to render the templates or their contents, the use of JavaScript creates innumerable opportunities to construct highly sophisticated HTML5 reporting templates. This report demonstrates the ability to incorporate dynamic content to enhance the use of radiology reporting templates.

Hpm of Estrogen Model on the Dynamics of Breast Cancer

Science.gov (United States)

Govindarajan, A.; Balamuralitharan, S.; Sundaresan, T.

2018-04-01

We enhance a deterministic mathematical model involving universal dynamics on breast cancer with immune response. This is population model so includes Normal cells class, Tumor cells, Immune cells and Estrogen. The eects regarding Estrogen are below incorporated in the model. The effects show to that amount the arrival of greater Estrogen increases the danger over growing breast cancer. Furthermore, approximate solution regarding nonlinear differential equations is arrived by Homotopy Perturbation Method (HPM). Hes HPM is good and correct technique after solve nonlinear differential equation directly. Approximate solution learnt with the support of that method is suitable same as like the actual results in accordance with this models.

Dynamics and Collapse in a Power System Model with Voltage Variation: The Damping Effect.

Science.gov (United States)

Ma, Jinpeng; Sun, Yong; Yuan, Xiaoming; Kurths, Jürgen; Zhan, Meng

2016-01-01

Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems.

Incorporation of fractional-order dynamics into an existing PI/PID DC motor control loop.

Science.gov (United States)

Tepljakov, Aleksei; Gonzalez, Emmanuel A; Petlenkov, Eduard; Belikov, Juri; Monje, Concepción A; Petráš, Ivo

2016-01-01

The problem of changing the dynamics of an existing DC motor control system without the need of making internal changes is considered in the paper. In particular, this paper presents a method for incorporating fractional-order dynamics in an existing DC motor control system with internal PI or PID controller, through the addition of an external controller into the system and by tapping its original input and output signals. Experimental results based on the control of a real test plant from MATLAB/Simulink environment are presented, indicating the validity of the proposed approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A Non-Isothermal Chemical Lattice Boltzmann Model Incorporating Thermal Reaction Kinetics and Enthalpy Changes

Directory of Open Access Journals (Sweden)

Stuart Bartlett

2017-08-01

Full Text Available The lattice Boltzmann method is an efficient computational fluid dynamics technique that can accurately model a broad range of complex systems. As well as single-phase fluids, it can simulate thermohydrodynamic systems and passive scalar advection. In recent years, it also gained attention as a means of simulating chemical phenomena, as interest in self-organization processes increased. This paper will present a widely-used and versatile lattice Boltzmann model that can simultaneously incorporate fluid dynamics, heat transfer, buoyancy-driven convection, passive scalar advection, chemical reactions and enthalpy changes. All of these effects interact in a physically accurate framework that is simple to code and readily parallelizable. As well as a complete description of the model equations, several example systems will be presented in order to demonstrate the accuracy and versatility of the method. New simulations, which analyzed the effect of a reversible reaction on the transport properties of a convecting fluid, will also be described in detail. This extra chemical degree of freedom was utilized by the system to augment its net heat flux. The numerical method outlined in this paper can be readily deployed for a vast range of complex flow problems, spanning a variety of scientific disciplines.

Incorporating the life course model into MCH nutrition leadership education and training programs.

Science.gov (United States)

Haughton, Betsy; Eppig, Kristen; Looney, Shannon M; Cunningham-Sabo, Leslie; Spear, Bonnie A; Spence, Marsha; Stang, Jamie S

2013-01-01

Life course perspective, social determinants of health, and health equity have been combined into one comprehensive model, the life course model (LCM), for strategic planning by US Health Resources and Services Administration's Maternal and Child Health Bureau. The purpose of this project was to describe a faculty development process; identify strategies for incorporation of the LCM into nutrition leadership education and training at the graduate and professional levels; and suggest broader implications for training, research, and practice. Nineteen representatives from 6 MCHB-funded nutrition leadership education and training programs and 10 federal partners participated in a one-day session that began with an overview of the models and concluded with guided small group discussions on how to incorporate them into maternal and child health (MCH) leadership training using obesity as an example. Written notes from group discussions were compiled and coded emergently. Content analysis determined the most salient themes about incorporating the models into training. Four major LCM-related themes emerged, three of which were about training: (1) incorporation by training grants through LCM-framed coursework and experiences for trainees, and similarly framed continuing education and skills development for professionals; (2) incorporation through collaboration with other training programs and state and community partners, and through advocacy; and (3) incorporation by others at the federal and local levels through policy, political, and prevention efforts. The fourth theme focused on anticipated challenges of incorporating the model in training. Multiple methods for incorporating the LCM into MCH training and practice are warranted. Challenges to incorporating include the need for research and related policy development.

Modeling capillary bridge dynamics and crack healing between surfaces of nanoscale roughness

Science.gov (United States)

Soylemez, Emrecan; de Boer, Maarten P.

2017-12-01

Capillary bridge formation between adjacent surfaces in humid environments is a ubiquitous phenomenon. It strongly influences tribological performance with respect to adhesion, friction and wear. Only a few studies, however, assess effects due to capillary dynamics. Here we focus on how capillary bridge evolution influences crack healing rates. Experimental results indicated a logarithmic decrease in average crack healing velocity as the energy release rate increases. Our objective is to model that trend. We assume that capillary dynamics involve two mechanisms: capillary bridge growth and subsequently nucleation followed by growth. We show that by incorporating interface roughness details and the presence of an adsorbed water layer, the behavior of capillary force dynamics can be understood quantitatively. We identify three important regimes that control the healing process, namely bridge growth, combined bridge growth and nucleation, and finally bridge nucleation. To fully capture the results, however, the theoretical model for nucleation time required an empirical modification. Our model enables significant insight into capillary bridge dynamics, with a goal of attaining a predictive capability for this important microelectromechanical systems (MEMS) reliability failure mechanism.

Incorporating Daily Flood Control Objectives Into a Monthly Stochastic Dynamic Programing Model for a Hydroelectric Complex

Science.gov (United States)

Druce, Donald J.

1990-01-01

A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model establishes the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

Incorporating daily flood control objectives into a monthly stochastic dynamic programming model for a hydroelectric complex

Energy Technology Data Exchange (ETDEWEB)

Druce, D.J. (British Columbia Hydro and Power Authority, Vancouver, British Columbia (Canada))

1990-01-01

A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model established the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

Development of Dynamic Spent Nuclear Fuel Environmental Effect Analysis Model

International Nuclear Information System (INIS)

Jeong, Chang Joon; Ko, Won Il; Lee, Ho Hee; Cho, Dong Keun; Park, Chang Je

2010-07-01

The dynamic environmental effect evaluation model for spent nuclear fuel has been developed and incorporated into the system dynamic DANESS code. First, the spent nuclear fuel isotope decay model was modeled. Then, the environmental effects were modeled through short-term decay heat model, short-term radioactivity model, and long-term heat load model. By using the developed model, the Korean once-through nuclear fuel cycles was analyzed. The once-through fuel cycle analysis was modeled based on the Korean 'National Energy Basic Plan' up to 2030 and a postulated nuclear demand growth rate until 2150. From the once-through results, it is shown that the nuclear power demand would be ∼70 GWe and the total amount of the spent fuel accumulated by 2150 would be ∼168000 t. If the disposal starts from 2060, the short-term decay heat of Cs-137 and Sr-90 isotopes are W and 1.8x10 6 W in 2100. Also, the total long-term heat load in 2100 will be 4415 MW-y. From the calculation results, it was found that the developed model is very convenient and simple for evaluation of the environmental effect of the spent nuclear fuel

75 FR 20265 - Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes

Science.gov (United States)

2010-04-19

... Office, 1701 Columbia Avenue, College Park, Georgia 30337; telephone: (404) 474-5524; facsimile: (404... Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes AGENCY: Federal Aviation...-08- 05, which applies to certain Liberty Aerospace Incorporated Model XL-2 airplanes. AD 2009-08-05...

A new modified resource budget model for nonlinear dynamics in citrus production

International Nuclear Information System (INIS)

Ye, Xujun; Sakai, Kenshi

2016-01-01

Highlights: • A theoretical modeling and simulation study of the nonlinear dynamics in citrus is conducted. • New leaf growth is incorporated into the model as a major factor responsible for the yield oscillations. • A Ricker-type equation for the relationship between costs for flowering and fruiting is proposed. • A generic form of the resource budget model for the nonlinear dynamics in citrus is obtained. • The new model is tested with experimental data for two citrus trees. - Abstract : Alternate bearing or masting is a general yield variability phenomenon in perennial tree crops. This paper first presents a theoretical modeling and simulation study of the mechanism for this dynamics in citrus, and then provides a test of the proposed models using data from a previous 16-year experiment in a citrus orchard. Our previous studies suggest that the mutual effects between vegetative and reproductive growths caused by resource allocation and budgeting in plant body might be considered as a major factor responsible for the yield oscillations in citrus. Based on the resource budget model proposed by Isagi et al. (J Theor Biol. 1997;187:231-9), we first introduce the new leaf growth as a major energy consumption component into the model. Further, we introduce a nonlinear Ricker-type equation to replace the linear relationship between costs for flowering and fruiting used in Isagi's model. Model simulations demonstrate that the proposed new models can successfully simulate the reproductive behaviors of citrus trees with different fruiting dynamics. These results may enrich the mechanical dynamics in tree crop reproductive models and help us to better understand the dynamics of vegetative-reproductive growth interactions in a real environment.

Dynamics of an HBV/HCV infection model with intracellular delay and cell proliferation

Science.gov (United States)

Zhang, Fengqin; Li, Jianquan; Zheng, Chongwu; Wang, Lin

2017-01-01

A new mathematical model of hepatitis B/C virus (HBV/HCV) infection which incorporates the proliferation of healthy hepatocyte cells and the latent period of infected hepatocyte cells is proposed and studied. The dynamics is analyzed via Pontryagin's method and a newly proposed alternative geometric stability switch criterion. Sharp conditions ensuring stability of the infection persistent equilibrium are derived by applying Pontryagin's method. Using the intracellular delay as the bifurcation parameter and applying an alternative geometric stability switch criterion, we show that the HBV/HCV infection model undergoes stability switches. Furthermore, numerical simulations illustrate that the intracellular delay can induce complex dynamics such as persistence bubbles and chaos.

Development of an end-of-life vehicle recovery model using system dynamics and future research needs

Science.gov (United States)

Mohamad-Ali, N.; Ghazilla, R. A. R.; Abdul-Rashid, S. H.; Sakundarini, N.; Ahmad-Yazid, A.; Stephenie, L.

2017-06-01

The implementation of end-of-life vehicle (ELV) recovery policy in Malaysia has led vehicle manufacturers to look at different ways to improve design and development of vehicles. Nowadays, it is crucial to incorporate end-of-life (EOL) design strategies into the vehicle design in order to enhance the effectiveness of the ELV recovery network. Although recent studies have shown that product design has a significant effect on the product recovery rate, there is a lack of studies on how EOL design strategies affects the effectiveness of ELV recovery, particularly when there are dynamic changes in the behaviour of the product recovery network. Thus, in this study, we developed a preliminary model based on the system dynamics approach in order to predict the effectiveness of ELV recovery in response to dynamic changes of various factors (including EOL design strategies) in the business environment. We developed this model based on preliminary data that we had gathered from unstructured interviews with the key stakeholders of ELV management in Malaysia. We believe that our model will greatly benefit product designers in incorporating the appropriate EOL design strategies in order to boost ELV recovery effectiveness in Malaysia.

Integrating count and detection–nondetection data to model population dynamics

Science.gov (United States)

Zipkin, Elise F.; Rossman, Sam; Yackulic, Charles B.; Wiens, David; Thorson, James T.; Davis, Raymond J.; Grant, Evan H. Campbell

2017-01-01

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

Science.gov (United States)

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

Directory of Open Access Journals (Sweden)

Yunpeng Xiao

2012-01-01

Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

Ab Initio Molecular Dynamics of Uranium Incorporated in Goethite (α-FeOOH): Interpretation of X-ray Absorption Spectroscopy of Trace Polyvalent Metals.

Science.gov (United States)

Kerisit, Sebastien; Bylaska, Eric J; Massey, Michael S; McBriarty, Martin E; Ilton, Eugene S

2016-11-21

Incorporation of economically or environmentally consequential polyvalent metals into iron (oxyhydr)oxides has applications in environmental chemistry, remediation, and materials science. A primary tool for characterizing the local coordination environment of such metals, and therefore building models to predict their behavior, is extended X-ray absorption fine structure spectroscopy (EXAFS). Accurate structural information can be lacking yet is required to constrain and inform data interpretation. In this regard, ab initio molecular dynamics (AIMD) was used to calculate the local coordination environment of minor amounts of U incorporated in the structure of goethite (α-FeOOH). U oxidation states (VI, V, and IV) and charge compensation schemes were varied. Simulated trajectories were used to calculate the U L III -edge EXAFS function and fit experimental EXAFS data for U incorporated into goethite under reducing conditions. Calculations that closely matched the U EXAFS of the well-characterized mineral uraninite (UO 2 ), and constrained the S 0 2 parameter to be 0.909, validated the approach. The results for the U-goethite system indicated that U(V) substituted for structural Fe(III) in octahedral uranate coordination. Charge balance was achieved by the loss of one structural proton coupled to addition of one electron into the solid (-1 H + , +1 e - ). The ability of AIMD to model higher energy states thermally accessible at room temperature is particularly relevant for protonated systems such as goethite, where proton transfers between adjacent octahedra had a dramatic effect on the calculated EXAFS. Vibrational effects as a function of temperature were also estimated using AIMD, allowing separate quantification of thermal and configurational disorder. In summary, coupling AIMD structural modeling and EXAFS experiments enables modeling of the redox behavior of polyvalent metals that are incorporated in conductive materials such as iron (oxyhydr)oxides, with

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

Science.gov (United States)

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Dynamic simulation of knee-joint loading during gait using force-feedback control and surrogate contact modelling.

Science.gov (United States)

Walter, Jonathan P; Pandy, Marcus G

2017-10-01

The aim of this study was to perform multi-body, muscle-driven, forward-dynamics simulations of human gait using a 6-degree-of-freedom (6-DOF) model of the knee in tandem with a surrogate model of articular contact and force control. A forward-dynamics simulation incorporating position, velocity and contact force-feedback control (FFC) was used to track full-body motion capture data recorded for multiple trials of level walking and stair descent performed by two individuals with instrumented knee implants. Tibiofemoral contact force errors for FFC were compared against those obtained from a standard computed muscle control algorithm (CMC) with a 6-DOF knee contact model (CMC6); CMC with a 1-DOF translating hinge-knee model (CMC1); and static optimization with a 1-DOF translating hinge-knee model (SO). Tibiofemoral joint loads predicted by FFC and CMC6 were comparable for level walking, however FFC produced more accurate results for stair descent. SO yielded reasonable predictions of joint contact loading for level walking but significant differences between model and experiment were observed for stair descent. CMC1 produced the least accurate predictions of tibiofemoral contact loads for both tasks. Our findings suggest that reliable estimates of knee-joint loading may be obtained by incorporating position, velocity and force-feedback control with a multi-DOF model of joint contact in a forward-dynamics simulation of gait. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Aggregated Residential Load Modeling Using Dynamic Bayesian Networks

Energy Technology Data Exchange (ETDEWEB)

Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai

2014-09-28

Abstract—It is already obvious that the future power grid will have to address higher demand for power and energy, and to incorporate renewable resources of different energy generation patterns. Demand response (DR) schemes could successfully be used to manage and balance power supply and demand under operating conditions of the future power grid. To achieve that, more advanced tools for DR management of operations and planning are necessary that can estimate the available capacity from DR resources. In this research, a Dynamic Bayesian Network (DBN) is derived, trained, and tested that can model aggregated load of Heating, Ventilation, and Air Conditioning (HVAC) systems. DBNs can provide flexible and powerful tools for both operations and planing, due to their unique analytical capabilities. The DBN model accuracy and flexibility of use is demonstrated by testing the model under different operational scenarios.

Stochastic Wilson–Cowan models of neuronal network dynamics with memory and delay

International Nuclear Information System (INIS)

Goychuk, Igor; Goychuk, Andriy

2015-01-01

We consider a simple Markovian class of the stochastic Wilson–Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around −1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence. (paper)

A System Dynamics Model for Planning Cardiovascular Disease Interventions

Science.gov (United States)

Homer, Jack; Evans, Elizabeth; Zielinski, Ann

2010-01-01

Planning programs for the prevention and treatment of cardiovascular disease (CVD) is a challenge to every community that wants to make the best use of its limited resources. Selecting programs that provide the greatest impact is difficult because of the complex set of causal pathways and delays that link risk factors to CVD. We describe a system dynamics simulation model developed for a county health department that incorporates and tracks the effects of those risk factors over time on both first-time and recurrent events. We also describe how the model was used to evaluate the potential impacts of various intervention strategies for reducing the county's CVD burden and present the results of those policy tests. PMID:20167899

3D Dynamic Modeling of the Head-Neck Complex for Fast Eye and Head Orientation Movements Research

Directory of Open Access Journals (Sweden)

Daniel A. Sierra

2011-01-01

Full Text Available A 3D dynamic computer model for the movement of the head-neck complex is presented. It incorporates anatomically correct information about the diverse elements forming the system. The skeleton is considered as a set of interconnected rigid 3D bodies following the Newton-Euler laws of movement. The muscles are modeled using Enderle's linear model, which shows equivalent dynamic characteristics to Loeb's virtual muscle model. The soft tissues, namely, the ligaments, intervertebral disks, and facet joints, are modeled considering their physiological roles and dynamics. In contrast with other head and neck models developed for safety research, the model is aimed to study the neural control of the complex during fast eye and head movements, such as saccades and gaze shifts. In particular, the time-optimal hypothesis and the feedback control ones are discussed.

Dynamics modeling for a rigid-flexible coupling system with nonlinear deformation field

International Nuclear Information System (INIS)

Deng Fengyan; He Xingsuo; Li Liang; Zhang Juan

2007-01-01

In this paper, a moving flexible beam, which incorporates the effect of the geometrically nonlinear kinematics of deformation, is investigated. Considering the second-order coupling terms of deformation in the longitudinal and transverse deflections, the exact nonlinear strain-displacement relations for a beam element are described. The shear strains formulated by the present modeling method in this paper are zero, so it is reasonable to use geometrically nonlinear deformation fields to demonstrate and simplify a flexible beam undergoing large overall motions. Then, considering the coupling terms of deformation in two dimensions, finite element shape functions of a beam element and Lagrange's equations are employed for deriving the coupling dynamical formulations. The complete expression of the stiffness matrix and all coupling terms are included in the formulations. A model consisting of a rotating planar flexible beam is presented. Then the frequency and dynamical response are studied, and the differences among the zero-order model, first-order coupling model and the new present model are discussed. Numerical examples demonstrate that a 'stiffening beam' can be obtained, when more coupling terms of deformation are added to the longitudinal and transverse deformation field. It is shown that the traditional zero-order and first-order coupling models may not provide an exact dynamic model in some cases

Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

Science.gov (United States)

Onorante, Luca; Raftery, Adrian E

2016-01-01

Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

Incorporating territory compression into population models

NARCIS (Netherlands)

Ridley, J; Komdeur, J; Sutherland, WJ; Sutherland, William J.

The ideal despotic distribution, whereby the lifetime reproductive success a territory's owner achieves is unaffected by population density, is a mainstay of behaviour-based population models. We show that the population dynamics of an island population of Seychelles warblers (Acrocephalus

Radionuclide Incorporation and Long Term Performance of Apatite Waste Forms

Energy Technology Data Exchange (ETDEWEB)

Wang, Jianwei [Louisiana State Univ., Baton Rouge, LA (United States); Lian, Jie [Rensselaer Polytechnic Inst., Troy, NY (United States); Gao, Fei [Univ. of Michigan, Ann Arbor, MI (United States)

2016-01-04

This project aims to combines state-of-the-art experimental and characterization techniques with atomistic simulations based on density functional theory (DFT) and molecular dynamics (MD) simulations. With an initial focus on long-lived I-129 and other radionuclides such as Cs, Sr in apatite structure, specific research objectives include the atomic scale understanding of: (1) incorporation behavior of the radionuclides and their effects on the crystal chemistry and phase stability; (2) stability and microstructure evolution of designed waste forms under coupled temperature and radiation environments; (3) incorporation and migration energetics of radionuclides and release behaviors as probed by DFT and molecular dynamics (MD) simulations; and (4) chemical durability as measured in dissolution experiments for long term performance evaluation and model validation.

Dynamic simulation of sustainable farm development scenarios using cognitive modeling

Directory of Open Access Journals (Sweden)

Tuzhyk Kateryna

2017-03-01

Full Text Available Dynamic simulation of sustainable farm development scenarios using cognitive modeling. The paper presents a dynamic simulation system of sustainable development scenarios on farms using cognitive modeling. The system incorporates relevant variables which affect the sustainable development of farms. Its user provides answers to strategic issues connected with the level of farm sustainability over a long-term perspective of dynamic development. The work contains a description of the model structure as well as the results of simulations carried out on 16 farms in northern Ukraine. The results show that the process of sustainability is based mainly on the potential for innovation in agricultural production and biodiversity. The user is able to simulate various scenarios for the sustainable development of a farm and visualize the influence of factors on the economic and social situation, as well as on environmental aspects. Upon carrying out a series of simulations, it was determined that the development of farms characterized by sustainable development is based on additional profit, which serves as the main motivation for transforming a conventional farm into a sustainable one. Nevertheless, additional profit is not the only driving force in the system of sustainable development. The standard of living, market condition, and legal regulations as well as government support also play a significant motivational role.

Modelling and simulation of dynamic recrystallization (DRX) in OFHC copper at very high strain rates

Science.gov (United States)

Testa, G.; Bonora, N.; Ruggiero, A.; Iannitti, G.; Persechino, I.; Hörnqvist, M.; Mortazavi, N.

2017-01-01

At high strain rates, deformation processes are essentially adiabatic and if the plastic work is large enough dynamic recrystallization can occur. In this work, an examination on microstructure evolution of OFHC copper in Dynamic Tensile Extrusion (DTE) test, performed at 400 m/s, was carried out. EBSD investigations, along the center line of the fragment remaining in the extrusion die, showed a progressive elongation of the grains, and an accompanying development of a strong + dual fiber texture. Discontinuous dynamic recrystallization (DRX) occurred at larger strains, and it was showed that nucleation occurred during straining. A criterion for DRX to occur, based on the evolution of Zener-Hollomon parameter during the dynamic deformation process, is proposed. Finally, DTE test was simulated using the modified Rusinek-Klepaczko constitutive model incorporating a model for the prediction of DRX initiation.

Coupling fast fluid dynamics and multizone airflow models in Modelica Buildings library to simulate the dynamics of HVAC systems

Energy Technology Data Exchange (ETDEWEB)

Tian, Wei [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sevilla, Thomas Alonso [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Zuo, Wangda [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.

2017-06-08

Historically, multizone models are widely used in building airflow and energy performance simulations due to their fast computing speed. However, multizone models assume that the air in a room is well mixed, consequently limiting their application. In specific rooms where this assumption fails, the use of computational fluid dynamics (CFD) models may be an alternative option. Previous research has mainly focused on coupling CFD models and multizone models to study airflow in large spaces. While significant, most of these analyses did not consider the coupled simulation of the building airflow with the building's Heating, Ventilation, and Air-Conditioning (HVAC) systems. This paper tries to fill the gap by integrating the models for HVAC systems with coupled multizone and CFD simulations for airflows, using the Modelica simul ation platform. To improve the computational efficiency, we incorporated a simplified CFD model named fast fluid dynamics (FFD). We first introduce the data synchronization strategy and implementation in Modelica. Then, we verify the implementation using two case studies involving an isothermal and a non-isothermal flow by comparing model simulations to experiment data. Afterward, we study another three cases that are deemed more realistic. This is done by attaching a variable air volume (VAV) terminal box and a VAV system to previous flows to assess the capability of the models in studying the dynamic control of HVAC systems. Finally, we discuss further research needs on the coupled simulation using the models.

Thermodynamic model of a thermal storage air conditioning system with dynamic behavior

Energy Technology Data Exchange (ETDEWEB)

Fleming, E; Wen, SY; Shi, L; da Silva, AK

2013-12-01

A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system's dynamic behavior, such as a dynamic air flow rate into the vehicle's cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle's cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid-air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semianalytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid-air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system experimental data for solidification using paraffin wax as the PCM. Through modeling, we demonstrate the importance of capturing the airside heat exchange impact on system performance, and we investigate system response to dynamic operating conditions, e.g., air recirculation. (C) 2013 Elsevier Ltd. All rights reserved.

Incorporation of the capillary hysteresis model HYSTR into the numerical code TOUGH

International Nuclear Information System (INIS)

Niemi, A.; Bodvarsson, G.S.; Pruess, K.

1991-11-01

As part of the work performed to model flow in the unsaturated zone at Yucca Mountain Nevada, a capillary hysteresis model has been developed. The computer program HYSTR has been developed to compute the hysteretic capillary pressure -- liquid saturation relationship through interpolation of tabulated data. The code can be easily incorporated into any numerical unsaturated flow simulator. A complete description of HYSTR, including a brief summary of the previous hysteresis literature, detailed description of the program, and instructions for its incorporation into a numerical simulator are given in the HYSTR user's manual (Niemi and Bodvarsson, 1991a). This report describes the incorporation of HYSTR into the numerical code TOUGH (Transport of Unsaturated Groundwater and Heat; Pruess, 1986). The changes made and procedures for the use of TOUGH for hysteresis modeling are documented

Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

DEFF Research Database (Denmark)

Bork, Lasse; Møller, Stig Vinther

2015-01-01

We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

Organic production in a dynamic CGE model

DEFF Research Database (Denmark)

Jacobsen, Lars Bo

2004-01-01

for conventional production into land for organic production, a period of two years must pass before the land being transformed can be used for organic production. During that time, the land is counted as land of the organic industry, but it can only produce the conventional product. To handle this rule, we make......Concerns about the impact of modern agriculture on the environment have in recent years led to an interest in supporting the development of organic farming. In addition to environmental benefits, the aim is to encourage the provision of other “multifunctional” properties of organic farming...... such as rural amenities and rural development that are spillover benefit additional to the supply of food. In this paper we further develop an existing dynamic general equilibrium model of the Danish economy to specifically incorporate organic farming. In the model and input-output data each primary...

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

Science.gov (United States)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

Science.gov (United States)

Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

2013-05-28

Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms.

A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.

Science.gov (United States)

Huffaker, Ray; Bittelli, Marco

2015-01-01

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

Modeling dynamic swarms

KAUST Repository

Ghanem, Bernard

2013-01-01

This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.

Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

Directory of Open Access Journals (Sweden)

Céline Christiansen-Jucht

2015-05-01

Full Text Available Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response and Actuator Constraints

Science.gov (United States)

Welstead, Jason; Crouse, Gilbert L., Jr.

2014-01-01

Empirical sizing guidelines such as tail volume coefficients have long been used in the early aircraft design phases for sizing stabilizers, resulting in conservatively stable aircraft. While successful, this results in increased empty weight, reduced performance, and greater procurement and operational cost relative to an aircraft with optimally sized surfaces. Including flight dynamics in the conceptual design process allows the design to move away from empirical methods while implementing modern control techniques. A challenge of flight dynamics and control is the numerous design variables, which are changing fluidly throughout the conceptual design process, required to evaluate the system response to some disturbance. This research focuses on addressing that challenge not by implementing higher order tools, such as computational fluid dynamics, but instead by linking the lower order tools typically used within the conceptual design process so each discipline feeds into the other. In thisresearch, flight dynamics and control was incorporated into the conceptual design process along with the traditional disciplines of vehicle sizing, weight estimation, aerodynamics, and performance. For the controller, a linear quadratic regulator structure with constant gains has been specified to reduce the user input. Coupling all the disciplines in the conceptual design phase allows the aircraft designer to explore larger design spaces where stabilizers are sized according to dynamic response constraints rather than historical static margin and volume coefficient guidelines.

The Effects of Dynamic Root Distribution on Land–Atmosphere Carbon and Water Fluxes in the Community Earth System Model (CESM1.2.0

Directory of Open Access Journals (Sweden)

Yuanyuan Wang

2018-03-01

Full Text Available Roots are responsible for the uptake of water and nutrients by plants, and they have the plasticity to respond dynamically to different environmental conditions. However, currently, most climate models only prescribe rooting profiles as a function of the vegetation type of the land component, with no consideration of the surroundings. In this study, a dynamic rooting scheme describing root growth as a compromise between water and nitrogen availability in the subsurface was incorporated into the Community Earth System Model 1.2.0 (CESM1.2.0. The dynamic rooting scheme was incorporated to investigate the effects of land–atmosphere carbon and water fluxes, and their subsequent influences on climate. The modeling results of global land–atmosphere coupling simulations from 1982 to 2005 show that the dynamic rooting scheme can improve gross primary production (GPP and evapotranspiration (ET in most tropical regions, and in some high-latitude regions with lower mean biases (MBEs and root mean square errors (RMSEs. Obvious differences in 2-m air temperature were found in low-latitude areas, with decreases of up to 2 °C. Under the influence of local land-surface feedback and large-scale moisture advection, total precipitation in the northeastern area of the Amazon and the west coast of Africa increased by 200 mm year−1, and that of South America, central Africa, and Indonesia increased by 50 to 100 mm year−1. Overall, the model incorporating the dynamic rooting scheme may reveal cooling and humidifying effects, especially for tropical regions.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

Science.gov (United States)

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Modeling the dynamic crush of impact mitigating materials

International Nuclear Information System (INIS)

Logan, R.W.; McMichael, L.D.

1995-01-01

Crushable materials are commonly utilized in the design of structural components to absorb energy and mitigate shock during the dynamic impact of a complex structure, such as an automobile chassis or drum-type shipping container. The development and application of several finite-element material models which have been developed at various times at LLNL for DYNA3D will be discussed. Between the models, they are able to account for several of the predominant mechanisms which typically influence the dynamic mechanical behavior of crushable materials. One issue we addressed was that no single existing model would account for the entire gambit of constitutive features which are important for crushable materials. Thus, we describe the implementation and use of an additional material model which attempts to provide a more comprehensive model of the mechanics of crushable material behavior. This model combines features of the pre-existing DYNA models and incorporates some new features as well in an invariant large-strain formulation. In addition to examining the behavior of a unit cell in uniaxial compression, two cases were chosen to evaluate the capabilities and accuracy of the various material models in DYNA. In the first case, a model for foam filled box beams was developed and compared to test data from a 4-point bend test. The model was subsequently used to study its effectiveness in energy absorption in an aluminum extrusion, spaceframe, vehicle chassis. The second case examined the response of the AT-400A shipping container and the performance of the overpack material during accident environments selected from 10CFR71 and IAEA regulations

Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

Science.gov (United States)

Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

2015-11-01

Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems

International Nuclear Information System (INIS)

Shin, Seung Ki; Seong, Poong Hyun

2008-01-01

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables

Dynamic Inversion for Hydrological Process Monitoring with Electrical Resistance Tomography Under Model Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Lehikoinen, A.; Huttunen, J.M.J.; Finsterle, S.; Kowalsky, M.B.; Kaipio, J.P.

2009-08-01

We propose an approach for imaging the dynamics of complex hydrological processes. The evolution of electrically conductive fluids in porous media is imaged using time-lapse electrical resistance tomography. The related dynamic inversion problem is solved using Bayesian filtering techniques, that is, it is formulated as a sequential state estimation problem in which the target is an evolving posterior probability density of the system state. The dynamical inversion framework is based on the state space representation of the system, which involves the construction of a stochastic evolution model and an observation model. The observation model used in this paper consists of the complete electrode model for ERT, with Archie's law relating saturations to electrical conductivity. The evolution model is an approximate model for simulating flow through partially saturated porous media. Unavoidable modeling and approximation errors in both the observation and evolution models are considered by computing approximate statistics for these errors. These models are then included in the construction of the posterior probability density of the estimated system state. This approximation error method allows the use of approximate - and therefore computationally efficient - observation and evolution models in the Bayesian filtering. We consider a synthetic example and show that the incorporation of an explicit model for the model uncertainties in the state space representation can yield better estimates than a frame-by-frame imaging approach.

Dynamic temperature dependence patterns in future energy demand models in the context of climate change

International Nuclear Information System (INIS)

Hekkenberg, M.; Moll, H.C.; Uiterkamp, A.J.M. Schoot

2009-01-01

Energy demand depends on outdoor temperature in a 'u' shaped fashion. Various studies have used this temperature dependence to investigate the effects of climate change on energy demand. Such studies contain implicit or explicit assumptions to describe expected socio-economic changes that may affect future energy demand. This paper critically analyzes these implicit or explicit assumptions and their possible effect on the studies' outcomes. First we analyze the interaction between the socio-economic structure and the temperature dependence pattern (TDP) of energy demand. We find that socio-economic changes may alter the TDP in various ways. Next we investigate how current studies manage these dynamics in socio-economic structure. We find that many studies systematically misrepresent the possible effect of socio-economic changes on the TDP of energy demand. Finally, we assess the consequences of these misrepresentations in an energy demand model based on temperature dependence and climate scenarios. Our model results indicate that expected socio-economic dynamics generally lead to an underestimation of future energy demand in models that misrepresent such dynamics. We conclude that future energy demand models should improve the incorporation of socio-economic dynamics. We propose dynamically modeling several key parameters and using direct meteorological data instead of degree days. (author)

Hierarchical modelling of temperature and habitat size effects on population dynamics of North Atlantic cod

DEFF Research Database (Denmark)

Mantzouni, Irene; Sørensen, Helle; O'Hara, Robert B.

2010-01-01

and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified......Understanding how temperature affects cod (Gadus morhua) ecology is important for forecasting how populations will develop as climate changes in future. The effects of spawning-season temperature and habitat size on cod recruitment dynamics have been investigated across the North Atlantic. Ricker...

Dynamic simulation of a beta-type Stirling engine with cam-drive mechanism via the combination of the thermodynamic and dynamic models

Energy Technology Data Exchange (ETDEWEB)

Cheng, Chin-Hsiang; Yu, Ying-Ju [Department of Aeronautics and Astronautics, National Cheng Kung University, No. 1, Ta-Shieh Road, Tainan, Taiwan (China)

2011-02-15

Dynamic simulation of a beta-type Stirling engine with cam-drive mechanism used in concentrating solar power system has been performed. A dynamic model of the mechanism is developed and then incorporated with the thermodynamic model so as to predict the transient behavior of the engine in the hot-start period. In this study, the engine is started from an initial rotational speed. The torques exerted by the flywheel of the engine at any time instant can be calculated by the dynamic model as long as the gas pressures in the chambers, the mass inertia, the friction force, and the external load have been evaluated. The instantaneous rotation speed of the engine is then determined by integration of the equation of rotational motion with respect to time, which in return affects the instantaneous variations in pressure and other thermodynamic properties of the gas inside the chambers. Therefore, the transient variations in gas properties inside the engine chambers and the dynamic behavior of the engine mechanism should be handled simultaneously via the coupling of the thermodynamic and dynamic models. An extensive parametric study of the effects of different operating and geometrical parameters has been performed, and results regarding the effects of mass moment of inertia of the flywheel, initial rotational speed, initial charged pressure, heat source temperature, phase angle, gap size, displacer length, and piston stroke on the engine transient behavior are investigated. (author)

An ocular biomechanic model for dynamic simulation of different eye movements.

Science.gov (United States)

Iskander, J; Hossny, M; Nahavandi, S; Del Porto, L

2018-04-11

Simulating and analysing eye movement is useful for assessing visual system contribution to discomfort with respect to body movements, especially in virtual environments where simulation sickness might occur. It can also be used in the design of eye prosthesis or humanoid robot eye. In this paper, we present two biomechanic ocular models that are easily integrated into the available musculoskeletal models. The model was previously used to simulate eye-head coordination. The models are used to simulate and analyse eye movements. The proposed models are based on physiological and kinematic properties of the human eye. They incorporate an eye-globe, orbital suspension tissues and six muscles with their connective tissues (pulleys). Pulleys were incorporated in rectus and inferior oblique muscles. The two proposed models are the passive pulleys and the active pulleys models. Dynamic simulations of different eye movements, including fixation, saccade and smooth pursuit, are performed to validate both models. The resultant force-length curves of the models were similar to the experimental data. The simulation results show that the proposed models are suitable to generate eye movement simulations with results comparable to other musculoskeletal models. The maximum kinematic root mean square error (RMSE) is 5.68° and 4.35° for the passive and active pulley models, respectively. The analysis of the muscle forces showed realistic muscle activation with increased muscle synergy in the active pulley model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

Science.gov (United States)

Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

2017-10-01

A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

Science.gov (United States)

Onorante, Luca; Raftery, Adrian E.

2015-01-01

Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

Tracking the sleep onset process: an empirical model of behavioral and physiological dynamics.

Directory of Open Access Journals (Sweden)

Michael J Prerau

2014-10-01

Full Text Available The sleep onset process (SOP is a dynamic process correlated with a multitude of behavioral and physiological markers. A principled analysis of the SOP can serve as a foundation for answering questions of fundamental importance in basic neuroscience and sleep medicine. Unfortunately, current methods for analyzing the SOP fail to account for the overwhelming evidence that the wake/sleep transition is governed by continuous, dynamic physiological processes. Instead, current practices coarsely discretize sleep both in terms of state, where it is viewed as a binary (wake or sleep process, and in time, where it is viewed as a single time point derived from subjectively scored stages in 30-second epochs, effectively eliminating SOP dynamics from the analysis. These methods also fail to integrate information from both behavioral and physiological data. It is thus imperative to resolve the mismatch between the physiological evidence and analysis methodologies. In this paper, we develop a statistically and physiologically principled dynamic framework and empirical SOP model, combining simultaneously-recorded physiological measurements with behavioral data from a novel breathing task requiring no arousing external sensory stimuli. We fit the model using data from healthy subjects, and estimate the instantaneous probability that a subject is awake during the SOP. The model successfully tracked physiological and behavioral dynamics for individual nights, and significantly outperformed the instantaneous transition models implicit in clinical definitions of sleep onset. Our framework also provides a principled means for cross-subject data alignment as a function of wake probability, allowing us to characterize and compare SOP dynamics across different populations. This analysis enabled us to quantitatively compare the EEG of subjects showing reduced alpha power with the remaining subjects at identical response probabilities. Thus, by incorporating both

Aspects of the incorporation of spatial data into radioecological and restoration analysis

International Nuclear Information System (INIS)

Beresford, N.A.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.; Arkhipov, A.; Voigt, G.

2002-01-01

In the last decade geographical information systems have been increasingly used to incorporate spatial data into radioecological analysis. This has allowed the development of models with spatially variable outputs. Two main approaches have been adopted in the development of spatial models. Empirical Tag based models applied across a range of spatial scales utilize underlying soil type maps and readily available radioecological data. Soil processes can also be modelled to allow the dynamic prediction of radionuclide soil to plant transfer. We discuss a dynamic semi-mechanistic radiocaesium soil to plant-transfer model, which utilizes readily available spatially variable soil parameters. Both approaches allow the identification of areas that may be vulnerable to radionuclide deposition, therefore enabling the targeting of intervention measures. Improved estimates of radionuclide fluxes and ingestion doses can be achieved by incorporating spatially varying inputs such as agricultural production and dietary habits in to these models. In this paper, aspects of such models, including data requirements, implementation and outputs are discussed and critically evaluated. The relative merits and disadvantages of the two spatial model approaches adopted within radioecology are discussed. We consider the usefulness of such models to aid decision-makers and access the requirements and potential of further application within radiological protection. (author)

Seasonal PCB bioaccumulation in an arctic marine ecosystem: a model analysis incorporating lipid dynamics, food-web productivity and migration.

Science.gov (United States)

Laender, Frederik De; Oevelen, Dick Van; Frantzen, Sylvia; Middelburg, Jack J; Soetaert, Karline

2010-01-01

Primary production and species' lipid contents in Arctic ecosystems are notoriously seasonal. Additionally, seasonal migration patterns of fish may alter prey availability and thus diet. Taking the southern Barents Sea as a study region and PCBs as model contaminants, we examined to what extent each of these factors cause bioaccumulation in fish to change throughout the year. Data on physiology and standing stocks of multiple trophic levels were used to estimated season-specific carbon budgets and by inference also corresponding values for food ingestion and production of cod, capelin, and herring. When combining these values with Arctic lipid dynamics for bioaccumulation model parameter setting, we predicted bioaccumulation factors (BAFs) that were in good agreement with BAFs for cod and capelin observed between 1998 and 2008. BAFs in all fish were 10 times lower in summer than in spring and fall/winter and were mainly driven by lipid dynamics. Trophic magnification factors (TMFs: increase in BAF per unit increase in trophic level as derived from our carbon budgets) were highest for PCB 153 during spring (2.3-2.4) and lowest for PCB 52 in summer and fall/winter (1.5-1.6) and were driven by seasonal shifts in trophic level and lipid dynamics.

Incorporating time and income constraints in dynamic agent-based models of activity generation and time use : Approach and illustration

NARCIS (Netherlands)

Arentze, Theo; Ettema, D.F.; Timmermans, Harry

Existing theories and models in economics and transportation treat households’ decisions regarding allocation of time and income to activities as a resource-allocation optimization problem. This stands in contrast with the dynamic nature of day-by-day activity-travel choices. Therefore, in the

Dynamic Latent Classification Model

DEFF Research Database (Denmark)

Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

Modeling viral coevolution: HIV multi-clonal persistence and competition dynamics

Science.gov (United States)

Bagnoli, F.; Liò, P.; Sguanci, L.

2006-07-01

The coexistence of different viral strains (quasispecies) within the same host are nowadays observed for a growing number of viruses, most notably HIV, Marburg and Ebola, but the conditions for the formation and survival of new strains have not yet been understood. We present a model of HIV quasispecies competition, which describes the conditions of viral quasispecies coexistence under different immune system conditions. Our model incorporates both T and B cells responses, and we show that the role of B cells is important and additive to that of T cells. Simulations of coinfection (simultaneous infection) and superinfection (delayed secondary infection) scenarios in the early stages (days) and in the late stages of the infection (years) are in agreement with emerging molecular biology findings. The immune response induces a competition among similar phenotypes, leading to differentiation (quasispeciation), escape dynamics and complex oscillations of viral strain abundance. We found that the quasispecies dynamics after superinfection or coinfection has time scales of several months and becomes even slower when the immune system response is weak. Our model represents a general framework to study the speed and distribution of HIV quasispecies during disease progression, vaccination and therapy.

Modeling and dynamics of an autothermal JP5 fuel reformer for marine fuel cell applications

International Nuclear Information System (INIS)

Tsourapas, Vasilis; Sun, Jing; Nickens, Anthony

2008-01-01

In this work, a dynamic model of an integrated autothermal reformer (ATR) and proton exchange membrane fuel cell (PEM FC) system and model-based evaluation of its dynamic characteristics are presented. The ATR reforms JP5 fuel into a hydrogen rich flow. The hydrogen is extracted from the reformate flow by a separator membrane (SEP), then supplied to the PEM FC for power generation. A catalytic burner (CB) and a turbine are also incorporated to recuperate energy from the remaining SEP flow that would otherwise be wasted. A dynamic model of this system, based on the ideal gas law and energy balance principles, is developed and used to explore the effects of the operating setpoint selection of the SEP on the overall system efficiency. The analysis reveals that a trade-off exists between the SEP efficiency and the overall system efficiency. Finally the open loop system simulation results are presented and conclusions are drawn on the SEP operation

Stability and bifurcation in a model for the dynamics of stem-like cells in leukemia under treatment

Science.gov (United States)

Rǎdulescu, I. R.; Cândea, D.; Halanay, A.

2012-11-01

A mathematical model for the dynamics of leukemic cells during treatment is introduced. Delay differential equations are used to model cells' evolution and are based on the Mackey-Glass approach, incorporating Goldie-Coldman law. Since resistance is propagated by cells that have the capacity of self-renewal, a population of stem-like cells is studied. Equilibrium points are calculated and their stability properties are investigated.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

Science.gov (United States)

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Modeling dynamic swarms

KAUST Repository

Ghanem, Bernard; Ahuja, Narendra

2013-01-01

This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal

Models of Easter Island Human-Resource Dynamics: Advances and Gaps

Directory of Open Access Journals (Sweden)

Agostino Merico

2017-12-01

Full Text Available Finding solutions to the entangled problems of human population growth, resource exploitation, ecosystem degradation, and biodiversity loss is considered humanity's grand challenge. Small and isolated societies of the past, such as the Rapanui of Easter Island, constitute ideal laboratories for understanding the consequences of human-driven environmental degradation and associated crises. By integrating different processes into a coherent and quantitative framework, mathematical models can be effective tools for investigating the ecological and socioeconomic history of these ancient civilizations. Most models of Easter Island are grounded around the Malthusian theory of population growth and designed as Lotka-Volterra predator-prey systems. Within ranges of plausible parameter values, these dynamic systems models predict a population overshoot and collapse sequence, in line with the ecocidal view about the Rapanui. With new archaeological evidence coming to light, casting doubts on the classical narrative of a human-induced collapse, models have begun to incorporate the new pieces of evidence and started to describe a more complex historical ecology, in line with the view of a resilient society that suffered genocide after the contact with Europeans. Uncertainties affecting the archaeological evidence contribute to the formulation of contradictory narratives. Surprisingly, no agent-based models have been applied to Easter Island. I argue that these tools offer appealing possibilities for overcoming the limits of dynamic systems models and the uncertainties in the available archaeological data.

Incorporating neurophysiological concepts in mathematical thermoregulation models

Science.gov (United States)

Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

2014-01-01

Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

Incorporation of tritium into planctonic algae in a continuous culture under dynamic conditions

International Nuclear Information System (INIS)

Strack, S.; Kistner, G.; Emeis, C.C.

1979-01-01

For the purpose of modelling the ecologic behaviour of organically bound tritium (OBT) in aquatic food chains under dynamic conditions (i.e. by changing tritium concentrations), a continuous culture of algae was chosen to which tritium was added by a single injection as tritiated water (HTO). The culture was working according to the chemostatic principle where the concentration of cells is in a steady state. Therefore, according to the growth of algae, tritium is incorporated into the organic substance, while in a parallel process HTO and algae are eliminated from the system at the same rate. From these two processes of first-order kinetics, a special function resulted for the concentration process of OBT in the fermenter that is well known in the field of drug kinetics. Initially it increases until it reaches a maximum value where it intersects the elimination curve of HTO, then decreases and asymptotically approaches the time axis - in the same manner as the elimination curve - only at a superior level. A comparison of this theoretically calculated function with the concentration actually found shows that also under dynamic conditions tritium is undergoing discrimination because of isotopic effects up to a ratio of I=0.80. The calculation of the ratios R=(OBT)/(HTO) in the continuous culture by comparing the function for OBT with the elimination curve for HTO shows a linear increase of R-values during the experiment. At maximum tritium concentration in the algae, the ratio becomes greater than one, and at the end of the experiment it reaches a value of about 6. However, by extrapolating to a time of 40 half-lives, when the absolute concentration of HTO has already decreased by a factor of 10 -12 , a ratio of about 25 was found. The discrimination enters the estimation of R-values at a constant factor of 0.80. (author)

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

Science.gov (United States)

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion

Incorporation of composite defects from ultrasonic NDE into CAD and FE models

Science.gov (United States)

Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

2017-02-01

Fiber-reinforced composites are widely used in aerospace industry due to their combined properties of high strength and low weight. However, owing to their complex structure, it is difficult to assess the impact of manufacturing defects and service damage on their residual life. While, ultrasonic testing (UT) is the preferred NDE method to identify the presence of defects in composites, there are no reasonable ways to model the damage and evaluate the structural integrity of composites. We have developed an automated framework to incorporate flaws and known composite damage automatically into a finite element analysis (FEA) model of composites, ultimately aiding in accessing the residual life of composites and make informed decisions regarding repairs. The framework can be used to generate a layer-by-layer 3D structural CAD model of the composite laminates replicating their manufacturing process. Outlines of structural defects, such as delaminations, are automatically detected from UT of the laminate and are incorporated into the CAD model between the appropriate layers. In addition, the framework allows for direct structural analysis of the resulting 3D CAD models with defects by automatically applying the appropriate boundary conditions. In this paper, we show a working proof-of-concept for the composite model builder with capabilities of incorporating delaminations between laminate layers and automatically preparing the CAD model for structural analysis using a FEA software.

Modeling near-road air quality using a computational fluid dynamics model, CFD-VIT-RIT.

Science.gov (United States)

Wang, Y Jason; Zhang, K Max

2009-10-15

It is well recognized that dilution is an important mechanism governing the near-road air pollutant concentrations. In this paper, we aim to advance our understanding of turbulent mixing mechanisms on and near roadways using computation fluid dynamics. Turbulent mixing mechanisms can be classified into three categories according to their origins: vehicle-induced turbulence (VIT), road-induced turbulence (RIT), and atmospheric boundary layer turbulence. RIT includes the turbulence generated by road embankment, road surface thermal effects, and roadside structures. Both VIT and RIT are affected by the roadway designs. We incorporate the detailed treatment of VIT and RIT into the CFD (namely CFD-VIT-RIT) and apply the model in simulating the spatial gradients of carbon monoxide near two major highways with different traffic mix and roadway configurations. The modeling results are compared to the field measurements and those from CALINE4 and CFD without considering VIT and RIT. We demonstrate that the incorporation of VIT and RIT considerably improves the modeling predictions, especially on vertical gradients and seasonal variations of carbon monoxide. Our study implies that roadway design can significantly influence the near-road air pollution. Thus we recommend that mitigating near-road air pollution through roadway designs be considered in the air quality and transportation management In addition, thanks to the rigorous representation of turbulent mixing mechanisms, CFD-VIT-RIT can become valuable tools in the roadway designs process.

Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

DEFF Research Database (Denmark)

Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

2001-01-01

We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... cod in these areas, suggesting that key biotic and abiotic processes can be successfully incorporated into recruitment models....... survival of early life stages and varying systematically among spawning sites were incorporated into stock-recruitment models, first for major cod spawning sites and then combined for the entire Central Baltic. Variables identified included potential egg production by the spawning stock, abiotic conditions...

Multiscale, multiphysics beam dynamics framework design and applications

International Nuclear Information System (INIS)

Amundson, J F; Spentzouris, P; Dechow, D; Stoltz, P; McInnes, L; Norris, B

2008-01-01

Modern beam dynamics simulations require nontrivial implementations of multiple physics models. We discuss how component framework design in combination with the Common Component Architecture's component model and implementation eases the process of incorporation of existing state-of-the-art models with newly-developed models. We discuss current developments in componentized beam dynamics software, emphasizing design issues and distribution issues

A modelling approach for exploring muscle dynamics during cyclic contractions.

Directory of Open Access Journals (Sweden)

Stephanie A Ross

2018-04-01

Full Text Available Hill-type muscle models are widely used within the field of biomechanics to predict and understand muscle behaviour, and are often essential where muscle forces cannot be directly measured. However, these models have limited accuracy, particularly during cyclic contractions at the submaximal levels of activation that typically occur during locomotion. To address this issue, recent studies have incorporated effects into Hill-type models that are oftentimes neglected, such as size-dependent, history-dependent, and activation-dependent effects. However, the contribution of these effects on muscle performance has yet to be evaluated under common contractile conditions that reflect the range of activations, strains, and strain rates that occur in vivo. The purpose of this study was to develop a modelling framework to evaluate modifications to Hill-type muscle models when they contract in cyclic loops that are typical of locomotor muscle function. Here we present a modelling framework composed of a damped harmonic oscillator in series with a Hill-type muscle actuator that consists of a contractile element and parallel elastic element. The intrinsic force-length and force-velocity properties are described using Bézier curves where we present a system to relate physiological parameters to the control points for these curves. The muscle-oscillator system can be geometrically scaled while preserving dynamic and kinematic similarity to investigate the muscle size effects while controlling for the dynamics of the harmonic oscillator. The model is driven by time-varying muscle activations that cause the muscle to cyclically contract and drive the dynamics of the harmonic oscillator. Thus, this framework provides a platform to test current and future Hill-type model formulations and explore factors affecting muscle performance in muscles of different sizes under a range of cyclic contractile conditions.

Dynamics of a delay differential equation model of hepatitis B virus infection.

Science.gov (United States)

Gourley, Stephen A; Kuang, Yang; Nagy, John D

2008-04-01

We formulate and systematically study the global dynamics of a simple model of hepatitis B virus in terms of delay differential equations. This model has two important and novel features compared to the well-known basic virus model in the literature. Specifically, it makes use of the more realistic standard incidence function and explicitly incorporates a time delay in virus production. As a result, the infection reproduction number is no longer dependent on the patient liver size (number of initial healthy liver cells). For this model, the existence and the component values of the endemic steady state are explicitly dependent on the time delay. In certain biologically interesting limiting scenarios, a globally attractive endemic equilibrium can exist regardless of the time delay length.

Advanced Modeling and Uncertainty Quantification for Flight Dynamics; Interim Results and Challenges

Science.gov (United States)

Hyde, David C.; Shweyk, Kamal M.; Brown, Frank; Shah, Gautam

2014-01-01

As part of the NASA Vehicle Systems Safety Technologies (VSST), Assuring Safe and Effective Aircraft Control Under Hazardous Conditions (Technical Challenge #3), an effort is underway within Boeing Research and Technology (BR&T) to address Advanced Modeling and Uncertainty Quantification for Flight Dynamics (VSST1-7). The scope of the effort is to develop and evaluate advanced multidisciplinary flight dynamics modeling techniques, including integrated uncertainties, to facilitate higher fidelity response characterization of current and future aircraft configurations approaching and during loss-of-control conditions. This approach is to incorporate multiple flight dynamics modeling methods for aerodynamics, structures, and propulsion, including experimental, computational, and analytical. Also to be included are techniques for data integration and uncertainty characterization and quantification. This research shall introduce new and updated multidisciplinary modeling and simulation technologies designed to improve the ability to characterize airplane response in off-nominal flight conditions. The research shall also introduce new techniques for uncertainty modeling that will provide a unified database model comprised of multiple sources, as well as an uncertainty bounds database for each data source such that a full vehicle uncertainty analysis is possible even when approaching or beyond Loss of Control boundaries. Methodologies developed as part of this research shall be instrumental in predicting and mitigating loss of control precursors and events directly linked to causal and contributing factors, such as stall, failures, damage, or icing. The tasks will include utilizing the BR&T Water Tunnel to collect static and dynamic data to be compared to the GTM extended WT database, characterizing flight dynamics in off-nominal conditions, developing tools for structural load estimation under dynamic conditions, devising methods for integrating various modeling elements

Incorporating time-delays in S-System model for reverse engineering genetic networks.

Science.gov (United States)

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in

Dynamic Model for the Z Accelerator Vacuum Section Based on Transmission Line Code%Dynamic Model for the Z Accelerator Vacuum Section Based on Transmission Line Code

Institute of Scientific and Technical Information of China (English)

呼义翔; 雷天时; 吴撼宇; 郭宁; 韩娟娟; 邱爱慈; 王亮平; 黄涛; 丛培天; 张信军; 李岩; 曾正中; 孙铁平

2011-01-01

The transmission-line-circuit model of the Z accelerator, developed originally by W. A. STYGAR, P. A. CORCORAN, et al., is revised. The revised model uses different calculations for the electron loss and flow impedance in the magnetically insulated transmission line system of the Z accelerator before and after magnetic insulation is established. By including electron pressure and zero electric field at the cathode, a closed set of equations is obtained at each time step, and dynamic shunt resistance （used to represent any electron loss to the anode） and flow impedance are solved, which have been incorporated into the transmission line code for simulations of the vacuum section in the Z accelerator. Finally, the results are discussed in comparison with earlier findings to show the effectiveness and limitations of the model.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Science.gov (United States)

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Directory of Open Access Journals (Sweden)

Johannes P M Heinonen

Full Text Available Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

2012-11-15

Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

A climatological model for risk computations incorporating site- specific dry deposition influences

International Nuclear Information System (INIS)

Droppo, J.G. Jr.

1991-07-01

A gradient-flux dry deposition module was developed for use in a climatological atmospheric transport model, the Multimedia Environmental Pollutant Assessment System (MEPAS). The atmospheric pathway model computes long-term average contaminant air concentration and surface deposition patterns surrounding a potential release site incorporating location-specific dry deposition influences. Gradient-flux formulations are used to incorporate site and regional data in the dry deposition module for this atmospheric sector-average climatological model. Application of these formulations provide an effective means of accounting for local surface roughness in deposition computations. Linkage to a risk computation module resulted in a need for separate regional and specific surface deposition computations. 13 refs., 4 figs., 2 tabs

Corruption dynamics model

Science.gov (United States)

Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

2017-07-01

The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

Global sensitivity analysis of a dynamic model for gene expression in Drosophila embryos

Science.gov (United States)

McCarthy, Gregory D.; Drewell, Robert A.

2015-01-01

It is well known that gene regulation is a tightly controlled process in early organismal development. However, the roles of key processes involved in this regulation, such as transcription and translation, are less well understood, and mathematical modeling approaches in this field are still in their infancy. In recent studies, biologists have taken precise measurements of protein and mRNA abundance to determine the relative contributions of key factors involved in regulating protein levels in mammalian cells. We now approach this question from a mathematical modeling perspective. In this study, we use a simple dynamic mathematical model that incorporates terms representing transcription, translation, mRNA and protein decay, and diffusion in an early Drosophila embryo. We perform global sensitivity analyses on this model using various different initial conditions and spatial and temporal outputs. Our results indicate that transcription and translation are often the key parameters to determine protein abundance. This observation is in close agreement with the experimental results from mammalian cells for various initial conditions at particular time points, suggesting that a simple dynamic model can capture the qualitative behavior of a gene. Additionally, we find that parameter sensitivites are temporally dynamic, illustrating the importance of conducting a thorough global sensitivity analysis across multiple time points when analyzing mathematical models of gene regulation. PMID:26157608

Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.

Science.gov (United States)

Liu, Shiyong; Triantis, Konstantinos P; Zhao, Li; Wang, Youfa

2018-01-01

In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data

Incorporating Handling Qualities Analysis into Rotorcraft Conceptual Design

Science.gov (United States)

Lawrence, Ben

2014-01-01

This paper describes the initial development of a framework to incorporate handling qualities analyses into a rotorcraft conceptual design process. In particular, the paper describes how rotorcraft conceptual design level data can be used to generate flight dynamics models for handling qualities analyses. Also, methods are described that couple a basic stability augmentation system to the rotorcraft flight dynamics model to extend analysis to beyond that of the bare airframe. A methodology for calculating the handling qualities characteristics of the flight dynamics models and for comparing the results to ADS-33E criteria is described. Preliminary results from the application of the handling qualities analysis for variations in key rotorcraft design parameters of main rotor radius, blade chord, hub stiffness and flap moment of inertia are shown. Varying relationships, with counteracting trends for different handling qualities criteria and different flight speeds are exhibited, with the action of the control system playing a complex part in the outcomes. Overall, the paper demonstrates how a broad array of technical issues across flight dynamics stability and control, simulation and modeling, control law design and handling qualities testing and evaluation had to be confronted to implement even a moderately comprehensive handling qualities analysis of relatively low fidelity models. A key outstanding issue is to how to 'close the loop' with an overall design process, and options for the exploration of how to feedback handling qualities results to a conceptual design process are proposed for future work.

Using Scenario Visioning and Participatory System Dynamics Modeling to Investigate the Future: Lessons from Minnesota 2050

Directory of Open Access Journals (Sweden)

Kathryn J. Draeger

2010-08-01

Full Text Available Both scenario visioning and participatory system dynamics modeling emphasize the dynamic and uncontrollable nature of complex socio-ecological systems, and the significance of multiple feedback mechanisms. These two methodologies complement one another, but are rarely used together. We partnered with regional organizations in Minnesota to design a future visioning process that incorporated both scenarios and participatory system dynamics modeling. The three purposes of this exercise were: first, to assist regional leaders in making strategic decisions that would make their communities sustainable; second, to identify research gaps that could impede the ability of regional and state groups to plan for the future; and finally, to introduce more systems thinking into planning and policy-making around environmental issues. We found that scenarios and modeling complemented one another, and that both techniques allowed regional groups to focus on the sustainability of fundamental support systems (energy, food, and water supply. The process introduced some creative tensions between imaginative scenario visioning and quantitative system dynamics modeling, and between creating desired futures (a strong cultural norm and inhabiting the future (a premise of the Minnesota 2050 exercise. We suggest that these tensions can stimulate more agile, strategic thinking about the future.

Dynamic Linear Models with R

CERN Document Server

Campagnoli, Patrizia; Petris, Giovanni

2009-01-01

State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

Science.gov (United States)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

Model dynamic behaviour analysis with chaotic noise using fuzzy logic based control

International Nuclear Information System (INIS)

Silva, Glauco Antonio Santos da

2002-01-01

This work presents an application of fuzzy control on dynamical system models. It has been observed that fuzzy controllers maybe used as a good alternative to the classical PI controller, once it incorporates human line behavior. Three implication relationships were used for the fussy controllers, namely, Mamdani Min, Larsen and Takagi-Sugeno. Performance comparisons were made aiming at achieving the best performance for each model used. The PI controller was used as a minimum standard, once it has been present in the industry for many years, giving acceptable performances and some degree of reliability . Two kinds of perturbations were introduced in the models to test the controllers: a ramp and chaotic perturbations. The first one is a monotonic, standard increase of an input parameter. The second one presents non-periodicity and irregularity in such a way to be quite rough to the controllers. The chaotic signal, as an analysis tool to dynamical systems, is an interesting contribution of this work. As a general conclusion it can be said the best performance, in this work, was achieved by the Takagi-Sugeno fuzzy controller. (author)

Methods improvements incorporated into the SAPHIRE ASP models

International Nuclear Information System (INIS)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.; Smith, C.L.; Rasmuson, D.M.

1994-01-01

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methodology, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

Methods improvements incorporated into the SAPHIRE ASP models

International Nuclear Information System (INIS)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.

1995-01-01

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methods, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

Dynamical Analysis of bantam-Regulated Drosophila Circadian Rhythm Model

Science.gov (United States)

Li, Ying; Liu, Zengrong

MicroRNAs (miRNAs) interact with 3‧untranslated region (UTR) elements of target genes to regulate mRNA stability or translation, and play a crucial role in regulating many different biological processes. bantam, a conserved miRNA, is involved in several functions, such as regulating Drosophila growth and circadian rhythm. Recently, it has been discovered that bantam plays a crucial role in the core circadian pacemaker. In this paper, based on experimental observations, a detailed dynamical model of bantam-regulated circadian clock system is developed to show the post-transcriptional behaviors in the modulation of Drosophila circadian rhythm, in which the regulation of bantam is incorporated into a classical model. The dynamical behaviors of the model are consistent with the experimental observations, which shows that bantam is an important regulator of Drosophila circadian rhythm. The sensitivity analysis of parameters demonstrates that with the regulation of bantam the system is more sensitive to perturbations, indicating that bantam regulation makes it easier for the organism to modulate its period against the environmental perturbations. The effectiveness in rescuing locomotor activity rhythms of mutated flies shows that bantam is necessary for strong and sustained rhythms. In addition, the biological mechanisms of bantam regulation are analyzed, which may help us more clearly understand Drosophila circadian rhythm regulated by other miRNAs.

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

KAUST Repository

Kachalo, Së ma; Naveed, Hammad; Cao, Youfang; Zhao, Jieling; Liang, Jie

2015-01-01

development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating

Modelling dynamic roughness during floods

NARCIS (Netherlands)

Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.

2007-01-01

In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most

A gas dynamics scheme for a two moments model of radiative transfer

International Nuclear Information System (INIS)

Buet, Ch.; Despres, B.

2007-01-01

We address the discretization of the Levermore's two moments and entropy model of the radiative transfer equation. We present a new approach for the discretization of this model: first we rewrite the moment equations as a Compressible Gas Dynamics equation by introducing an additional quantity that plays the role of a density. After that we discretize using a Lagrange-projection scheme. The Lagrange-projection scheme permits us to incorporate the source terms in the fluxes of an acoustic solver in the Lagrange step, using the well-known piecewise steady approximation and thus to capture correctly the diffusion regime. Moreover we show that the discretization is entropic and preserve the flux-limited property of the moment model. Numerical examples illustrate the feasibility of our approach. (authors)

Incorporating Vibration Test Results for the Advanced Stirling Convertor into the System Dynamic Model

Science.gov (United States)

Meer, David W.; Lewandowski, Edward J.

2010-01-01

The U.S. Department of Energy (DOE), Lockheed Martin Corporation (LM), and NASA Glenn Research Center (GRC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. As part of the extended operation testing of this power system, the Advanced Stirling Convertors (ASC) at NASA GRC undergo a vibration test sequence intended to simulate the vibration history that an ASC would experience when used in an ASRG for a space mission. During these tests, a data system collects several performance-related parameters from the convertor under test for health monitoring and analysis. Recently, an additional sensor recorded the slip table position during vibration testing to qualification level. The System Dynamic Model (SDM) integrates Stirling cycle thermodynamics, heat flow, mechanical mass, spring, damper systems, and electrical characteristics of the linear alternator and controller. This Paper presents a comparison of the performance of the ASC when exposed to vibration to that predicted by the SDM when exposed to the same vibration.

Forecasting the shortage of neurosurgeons in Iran using a system dynamics model approach.

Science.gov (United States)

Rafiei, Sima; Daneshvaran, Arman; Abdollahzade, Sina

2018-01-01

Shortage of physicians particularly in specialty levels is considered as an important issue in Iran health system. Thus, in an uncertain environment, long-term planning is required for health professionals as a basic priority on a national scale. This study aimed to estimate the number of required neurosurgeons using system dynamic modeling. System dynamic modeling was applied to predict the gap between stock and number of required neurosurgeons in Iran up to 2020. A supply and demand simulation model was constructed for neurosurgeons using system dynamic approach. The demand model included epidemiological, demographic, and utilization variables along with supply model-incorporated current stock of neurosurgeons and flow variables such as attrition, migration, and retirement rate. Data were obtained from various governmental databases and were analyzed by Vensim PLE Version 3.0 to address the flow of health professionals, clinical infrastructure, population demographics, and disease prevalence during the time. It was forecasted that shortage in number of neurosurgeons would disappear at 2020. The most dominant determinants on predicted number of neurosurgeons were the prevalence of neurosurgical diseases, the rate for service utilization, and medical capacity of the region. Shortage of neurosurgeons in some areas of the country relates to maldistribution of the specialists. Accordingly, there is a need to reconsider the allocation system for health professionals within the country instead of increasing the overall number of acceptance quota in training positions.

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

Science.gov (United States)

Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

2017-09-01

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

Computational model to simulate the interplay effect in dynamic IMRT delivery

International Nuclear Information System (INIS)

Yoganathan, S A; Maria Das, K J; Kumar, Shaleen

2014-01-01

The purpose of this study was to develop and experimentally verify a patient specific model for simulating the interplay effect in a DMLC based IMRT delivery. A computational model was developed using MATLAB program to incorporate the interplay effect in a 2D beams eye view fluence of dynamic IMRT fields. To simulate interplay effect, the model requires two inputs: IMRT field (DMLC file with dose rate and MU) and the patient specific respiratory motion. The interplay between the DMLC leaf motion and target was simulated for three lung patients. The target trajectory data was acquired using RPM system during the treatment simulation. The model was verified experimentally for the same patients using Imatrix 2D array device placed over QUASAR motion platform in CL2100 linac. The simulated fluences and measured fluences were compared with the TPS generated static fluence (no motion) using an in-house developed gamma evaluation program (2%/2mm). The simulated results were well within agreement with the measured. Comparison of the simulated and measured fluences with the TPS static fluence resulted 55.3% and 58.5% pixels passed the gamma criteria. A patient specific model was developed and validated for simulating the interplay effect in the dynamic IMRT delivery. This model can be clinically used to quantify the dosimetric uncertainty due to the interplay effect prior to the treatment delivery.

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

Science.gov (United States)

Pei, Jing; Derry, Stephen D.; Zhou Zhiqiang; Newsom, Jerry R.

2014-01-01

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

An electricity generation planning model incorporating demand response

International Nuclear Information System (INIS)

Choi, Dong Gu; Thomas, Valerie M.

2012-01-01

Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

"Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Nibbs, Faith G.

2007-08-24

While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.

A Computational Fluid Dynamic Model for a Novel Flash Ironmaking Process

Science.gov (United States)

Perez-Fontes, Silvia E.; Sohn, Hong Yong; Olivas-Martinez, Miguel

A computational fluid dynamic model for a novel flash ironmaking process based on the direct gaseous reduction of iron oxide concentrates is presented. The model solves the three-dimensional governing equations including both gas-phase and gas-solid reaction kinetics. The turbulence-chemistry interaction in the gas-phase is modeled by the eddy dissipation concept incorporating chemical kinetics. The particle cloud model is used to track the particle phase in a Lagrangian framework. A nucleation and growth kinetics rate expression is adopted to calculate the reduction rate of magnetite concentrate particles. Benchmark experiments reported in the literature for a nonreacting swirling gas jet and a nonpremixed hydrogen jet flame were simulated for validation. The model predictions showed good agreement with measurements in terms of gas velocity, gas temperature and species concentrations. The relevance of the computational model for the analysis of a bench reactor operation and the design of an industrial-pilot plant is discussed.

A rheonomic model for the dynamical analysis of the structure-soil interaction

International Nuclear Information System (INIS)

Chiroiu, V.; Nicolae, V.

1993-01-01

The dynamical analysis of the structure-soil interaction requires an adequate modeling of the geometrical radiation phenomenon (g.r.) i.e. the propagation of the vibrating energy of the structure in the infinite medium. Newton's law of motion is not including the g.r., considered in this paper like an irreversible phenomenon. To incorporate this, a new wave motion equation is proposed, according to a complete analysis of the structure-soil interactions with an adequate formulation of the g.r. By using a system of fundamental dynamical solutions, the rheonom constraint applied to the half-space is represented as a restriction to the displacement solutions. A dimensionless formulation of the problem and the variation of dynamical and energetical quantities in respect to the frequency, as according to the diagram of the characteristic curve of g.r. are presented numerically. Sample results showing the importance of radiation energy for several motions are also shown

Dynamical analysis of a model of social behavior: Criminal vs non-criminal population

International Nuclear Information System (INIS)

Abbas, Syed; Tripathi, Jai Prakash; Neha, A.A.

2017-01-01

Highlights: • A new social model of interaction between criminal and non-criminal population is proposed • The effect of law enforcement is studied • Many real life situations are analyzed • List of open problems is given for future work. - Abstract: In this paper, we construct a model motivated by the well known predator-prey model to study the interaction between criminal population and non-criminal population. Our aim is to study various possibilities of interactions between them. First we model it using simple predator-prey model, then we modify it by considering the logistic growth of non-criminal population. We clearly deduce that the model with logistic growth is better than classical one. More precisely, the role of carrying capacity on the dynamics of criminal minded population is discussed. Further, we incorporate law enforcement term in the model and study its effect. The result obtained suggest that by incorporating enforcement law, the criminal population reduces from the very beginning, which resembles with real life situation. Our result indicates that the criminal minded population exist as long as coefficient of enforcement l_c does not cross a threshold value and after this value the criminal minded population extinct. In addition, we also discuss the occurrence of saddle-node bifurcation in case of model system with law enforcement. Numerical examples and simulations are presented to illustrate the obtained results.

An excitable cortex and memory model successfully predicts new pseudopod dynamics.

Directory of Open Access Journals (Sweden)

Robert M Cooper

Full Text Available Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.

Models for dynamic analysis of backup ball bearings of an AMB-system

Science.gov (United States)

Halminen, Oskari; Aceituno, Javier F.; Escalona, José L.; Sopanen, Jussi; Mikkola, Aki

2017-10-01

Two detailed models of backup bearing are introduced for dynamic analysis of the dropdown event of a rotor supported by an active magnetic bearing (AMB). The proposed two-dimensional models of the backup bearings are based on a multibody approach. All parts of the bearing are modeled as rigid bodies with geometrical surfaces and the bodies interact with each other through contact forces. The first model describes a backup bearing without a cage, and the second model describes a backup bearing with a cage. The introduced models, which incorporate a realistic elastic contact model, are compared with previously presented simplified models through parametric study. In order to ensure the durability of backup bearings in challenging applications where ball bearings with an oversized bore are necessary, analysis of the forces affecting the bearing's cage and balls is required, and the models introduced in this work assist in this task as they enable optimal properties for the bearing's cage and balls to be found.

Advanced High-Temperature Reactor Dynamic System Model Development: April 2012 Status

Energy Technology Data Exchange (ETDEWEB)

Qualls, A L; Cetiner, M S; Wilson, Jr, T L

2012-04-30

system relate to flows within the reactor vessel during severe events and the resulting temperature profiles (temperature and duration) for major components. Critical components include the fuel, reactor vessel, primary piping, and the primary-to-intermediate heat exchangers (P-IHXs). The major AHTR power system loops are shown in Fig. 3. The intermediate heat transfer system is a group of three pumped salt loops that transports the energy produced in the primary system to the power conversion system. Two dynamic system models are used to analyze the AHTR. A Matlab/Simulink-based model initiated in 2011 has been updated to reflect the evolving design parameters related to the heat flows associated with the reactor vessel. The Matlab model utilizes simplified flow assumptions within the vessel and incorporates an empirical representation of the Direct Reactor Auxiliary Cooling System (DRACS). A Dymola/Modelica model incorporates a more sophisticated representation of primary coolant flow and a physics-based representation of the three-loop DRACS thermal hydraulics. This model is not currently operating in a fully integrated mode. The Matlab model serves as a prototype and provides verification for the Dymola model, and its use will be phased out as the Dymola model nears completion. The heat exchangers in the system are sized using spreadsheet-based, steady-state calculations. The detail features of the heat exchangers are programmed into the dynamic models, and the overall dimensions are used to generate realistic plant designs. For the modeling cases where the emphasis is on understanding responses within the intermediate and primary systems, the power conversion system may be modeled as a simple boundary condition at the intermediate-to-power conversion system heat exchangers.

Modelling MIZ dynamics in a global model

Science.gov (United States)

Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

2016-04-01

Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

Dynamic modeling of sludge compaction and consolidation processes in wastewater secondary settling tanks.

Science.gov (United States)

Abusam, A; Keesman, K J

2009-01-01

The double exponential settling model is the widely accepted model for wastewater secondary settling tanks. However, this model does not estimate accurately solids concentrations in the settler underflow stream, mainly because sludge compression and consolidation processes are not considered. In activated sludge systems, accurate estimation of the solids in the underflow stream will facilitate the calibration process and can lead to correct estimates of particularly kinetic parameters related to biomass growth. Using principles of compaction and consolidation, as in soil mechanics, a dynamic model of the sludge consolidation processes taking place in the secondary settling tanks is developed and incorporated to the commonly used double exponential settling model. The modified double exponential model is calibrated and validated using data obtained from a full-scale wastewater treatment plant. Good agreement between predicted and measured data confirmed the validity of the modified model.

Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

International Nuclear Information System (INIS)

Chen Wu; Zhou Xingxi; Deng Shiming

2005-01-01

Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results

Multiscale Modeling of Blood Flow: Coupling Finite Elements with Smoothed Dissipative Particle Dynamics

KAUST Repository

Moreno Chaparro, Nicolas; Vignal, Philippe; Li, Jun; Calo, Victor M.

2013-01-01

A variational multi scale approach to model blood flow through arteries is proposed. A finite element discretization to represent the coarse scales (macro size), is coupled to smoothed dissipative particle dynamics that captures the fine scale features (micro scale). Blood is assumed to be incompressible, and flow is described through the Navier Stokes equation. The proposed cou- pling is tested with two benchmark problems, in fully coupled systems. Further refinements of the model can be incorporated in order to explicitly include blood constituents and non-Newtonian behavior. The suggested algorithm can be used with any particle-based method able to solve the Navier-Stokes equation.

Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

Energy Technology Data Exchange (ETDEWEB)

Chen Wu; Zhou Xingxi; Deng Shiming E-mail: 02900058r@polyu.edu.hk

2005-02-01

Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results.

Multiscale Modeling of Blood Flow: Coupling Finite Elements with Smoothed Dissipative Particle Dynamics

KAUST Repository

Moreno Chaparro, Nicolas

2013-06-01

A variational multi scale approach to model blood flow through arteries is proposed. A finite element discretization to represent the coarse scales (macro size), is coupled to smoothed dissipative particle dynamics that captures the fine scale features (micro scale). Blood is assumed to be incompressible, and flow is described through the Navier Stokes equation. The proposed cou- pling is tested with two benchmark problems, in fully coupled systems. Further refinements of the model can be incorporated in order to explicitly include blood constituents and non-Newtonian behavior. The suggested algorithm can be used with any particle-based method able to solve the Navier-Stokes equation.

Modeling fish community dynamics in Florida Everglades: Role of temperature variation

Science.gov (United States)

Al-Rabai'ah, H. A.; Koh, H. L.; DeAngelis, Donald L.; Lee, Hooi-Ling

2002-01-01

Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years.

Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

Science.gov (United States)

Thomas, M. Y.; Bhat, H. S.

2017-12-01

Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

International Nuclear Information System (INIS)

Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A.

2013-01-01

High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damage and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments – which involve moderate to extensive levels of particle damage – are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 × 105 grains are presented.

Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

Energy Technology Data Exchange (ETDEWEB)

Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A. [Engineer Research and Development Center - Cold Regions Research and Engineering Laboratory, 72 Lyme Rd., Hanover, NH 03755 (United States)

2013-06-18

High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damage and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments - which involve moderate to extensive levels of particle damage - are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 Multiplication-Sign 105 grains are presented.

Dynamic Evolution Of Off-Fault Medium During An Earthquake: A Micromechanics Based Model

Science.gov (United States)

Thomas, Marion Y.; Bhat, Harsha S.

2018-05-01

Geophysical observations show a dramatic drop of seismic wave speeds in the shallow off-fault medium following earthquake ruptures. Seismic ruptures generate, or reactivate, damage around faults that alter the constitutive response of the surrounding medium, which in turn modifies the earthquake itself, the seismic radiation, and the near-fault ground motion. We present a micromechanics based constitutive model that accounts for dynamic evolution of elastic moduli at high-strain rates. We consider 2D in-plane models, with a 1D right lateral fault featuring slip-weakening friction law. The two scenarios studied here assume uniform initial off-fault damage and an observationally motivated exponential decay of initial damage with fault normal distance. Both scenarios produce dynamic damage that is consistent with geological observations. A small difference in initial damage actively impacts the final damage pattern. The second numerical experiment, in particular, highlights the complex feedback that exists between the evolving medium and the seismic event. We show that there is a unique off-fault damage pattern associated with supershear transition of an earthquake rupture that could be potentially seen as a geological signature of this transition. These scenarios presented here underline the importance of incorporating the complex structure of fault zone systems in dynamic models of earthquakes.

Dynamic accelerator modeling

International Nuclear Information System (INIS)

Nishimura, Hiroshi.

1993-05-01

Object-Oriented Programming has been used extensively to model the LBL Advanced Light Source 1.5 GeV electron storage ring. This paper is on the present status of the class library construction with emphasis on a dynamic modeling

Incorporating Dynamical Systems into the Traditional Curriculum.

Science.gov (United States)

Natov, Jonathan

2001-01-01

Presents a brief overview of dynamical systems. Gives examples from dynamical systems and where they fit into the current curriculum. Points out that these examples are accessible to undergraduate freshmen and sophomore students, add continuity to the standard curriculum, and are worth including in classes. (MM)

Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

OpenAIRE

Min Yan; Xin Tian; Zengyuan Li; Erxue Chen; Xufeng Wang; Zongtao Han; Hong Sun

2016-01-01

This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 mo...

Dynamic Modelling Of A SCARA Robot

Science.gov (United States)

Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

1987-10-01

This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

INCORPORATING MULTIPLE OBJECTIVES IN PLANNING MODELS OF LOW-RESOURCE FARMERS

OpenAIRE

Flinn, John C.; Jayasuriya, Sisira; Knight, C. Gregory

1980-01-01

Linear goal programming provides a means of formally incorporating the multiple goals of a household into the analysis of farming systems. Using this approach, the set of plans which come as close as possible to achieving a set of desired goals under conditions of land and cash scarcity are derived for a Filipino tenant farmer. A challenge in making LGP models empirically operational is the accurate definition of the goals of the farm household being modelled.

System Dynamics Modelling for a Balanced Scorecard

DEFF Research Database (Denmark)

Nielsen, Steen; Nielsen, Erland Hejn

2008-01-01

/methodology/approach - We use a case study model to develop time or dynamic dimensions by using a System Dynamics modelling (SDM) approach. The model includes five perspectives and a number of financial and non-financial measures. All indicators are defined and related to a coherent number of different cause...... have a major influence on other indicators and profit and may be impossible to predict without using a dynamic model. Practical implications - The model may be used as the first step in quantifying the cause-and-effect relationships of an integrated BSC model. Using the System Dynamics model provides......Purpose - To construct a dynamic model/framework inspired by a case study based on an international company. As described by the theory, one of the main difficulties of BSC is to foresee the time lag dimension of different types of indicators and their combined dynamic effects. Design...

INCORPORATION OF MECHANISTIC INFORMATION IN THE ARSENIC PBPK MODEL DEVELOPMENT PROCESS

Science.gov (United States)

INCORPORATING MECHANISTIC INSIGHTS IN A PBPK MODEL FOR ARSENICElaina M. Kenyon, Michael F. Hughes, Marina V. Evans, David J. Thomas, U.S. EPA; Miroslav Styblo, University of North Carolina; Michael Easterling, Analytical Sciences, Inc.A physiologically based phar...

Peri-dynamics

International Nuclear Information System (INIS)

Littlewood, D.

2015-01-01

Peri-dynamics, a nonlocal extension of continuum mechanics, is a natural framework for capturing constitutive response and modelling pervasive material failure and fracture. Unlike classical approaches incorporating partial derivatives, the peri-dynamic governing equations utilise integral expressions that remain valid in the presence of discontinuities such as cracks. The mathematical theory of peri-dynamics unifies the mechanics of continuous media, cracks, and discrete particles. The result is a consistent framework for capturing a wide range of constitutive responses, including inelasticity, in combination with robust material failure laws. Peri-dynamics has been implemented in a number of computational simulation codes, including the open source code Peridigm and the Sierra/SolidMechanics analysis code at Sandia National Laboratories. (author)

Dynamic information architecture system (DIAS) : multiple model simulation management

International Nuclear Information System (INIS)

Simunich, K. L.; Sydelko, P.; Dolph, J.; Christiansen, J.

2002-01-01

Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application contexts. The modeling domain of a specific DIAS-based simulation is determined by (1) software Entity (domain-specific) objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. In DIAS, models communicate only with Entity objects, never with each other. Each Entity object has a number of Parameter and Aspect (of behavior) objects associated with it. The Parameter objects contain the state properties of the Entity object. The Aspect objects represent the behaviors of the Entity object and how it interacts with other objects. DIAS extends the ''Object'' paradigm by abstraction of the object's dynamic behaviors, separating the ''WHAT'' from the ''HOW.'' DIAS object class definitions contain an abstract description of the various aspects of the object's behavior (the WHAT), but no implementation details (the HOW). Separate DIAS models/applications carry the implementation of object behaviors (the HOW). Any model deemed appropriate, including existing legacy-type models written in other languages, can drive entity object behavior. The DIAS design promotes plug-and-play of alternative models, with minimal recoding of existing applications. The DIAS Context Builder object builds a constructs or scenario for the simulation, based on developer specification and user inputs. Because DIAS is a discrete event simulation system, there is a Simulation Manager object with which all events are processed. Any class that registers to receive events must implement an event handler (method) to process the event during execution. Event handlers can schedule other events; create or remove Entities from the

Travelling wave solutions for the Richards equation incorporating non-equilibrium effects in the capillarity pressure

NARCIS (Netherlands)

van Duijn, C. J.; Mitra, K.; Pop, I. S.

2018-01-01

The Richards equation is a mathematical model for unsaturated flow through porous media. This paper considers an extension of the Richards equation, where non-equilibrium effects like hysteresis and dynamic capillarity are incorporated in the relationship that relates the water pressure and the

System dynamics modeling of social/political factors in nuclear power plant operations

International Nuclear Information System (INIS)

Hansen, K.F.; Turek, M.G.; Eubanks, C.K.

1995-01-01

The safety and performance of nuclear power plants are a function of many technical factors such as initial design, service and maintenance programs, and utility investment in improvements. Safety and performance are also a function of the social/political influences that affect requirements on personnel, practices and procedures, and resource availability. This paper describes a process for constructing models of the social/political influences on plant operations using the system dynamics technique. The model incorporates representation of internal utility actions and decisions as affected by external factors such as public opinion, intervenor actions, safety and economic regulation, and the financial community. The feedback between external agents and plant performance is explicitly modeled. The resulting model can be used to simulate performance under a variety of different external and internal policy choices. In particular, the model can be used to study means of improving performance in response to externally imposed regulations

A code reviewer assignment model incorporating the competence differences and participant preferences

Directory of Open Access Journals (Sweden)

Wang Yanqing

2016-03-01

Full Text Available A good assignment of code reviewers can effectively utilize the intellectual resources, assure code quality and improve programmers’ skills in software development. However, little research on reviewer assignment of code review has been found. In this study, a code reviewer assignment model is created based on participants’ preference to reviewing assignment. With a constraint of the smallest size of a review group, the model is optimized to maximize review outcomes and avoid the negative impact of “mutual admiration society”. This study shows that the reviewer assignment strategies incorporating either the reviewers’ preferences or the authors’ preferences get much improvement than a random assignment. The strategy incorporating authors’ preference makes higher improvement than that incorporating reviewers’ preference. However, when the reviewers’ and authors’ preference matrixes are merged, the improvement becomes moderate. The study indicates that the majority of the participants have a strong wish to work with reviewers and authors having highest competence. If we want to satisfy the preference of both reviewers and authors at the same time, the overall improvement of learning outcomes may be not the best.

Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks

International Nuclear Information System (INIS)

Hedegaard, Karsten; Balyk, Olexandr

2013-01-01

Individual compression heat pumps constitute a potentially valuable resource in supporting wind power integration due to their economic competitiveness and possibilities for flexible operation. When analysing the system benefits of flexible heat pump operation, effects on investments should be taken into account. In this study, we present a model that facilitates analysing individual heat pumps and complementing heat storages in integration with the energy system, while optimising both investments and operation. The model incorporates thermal building dynamics and covers various heat storage options: passive heat storage in the building structure via radiator heating, active heat storage in concrete floors via floor heating, and use of thermal storage tanks for space heating and hot water. It is shown that the model is well qualified for analysing possibilities and system benefits of operating heat pumps flexibly. This includes prioritising heat pump operation for hours with low marginal electricity production costs, and peak load shaving resulting in a reduced need for peak and reserve capacity investments. - Highlights: • Model optimising heat pumps and heat storages in integration with the energy system. • Optimisation of both energy system investments and operation. • Heat storage in building structure and thermal storage tanks included. • Model well qualified for analysing system benefits of flexible heat pump operation. • Covers peak load shaving and operation prioritised for low electricity prices

Sustainable infrastructure system modeling under uncertainties and dynamics

Science.gov (United States)

Huang, Yongxi

Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

Modelling nitrogen dynamics and distributions in the River Tweed, Scotland: an application of the INCA model

Directory of Open Access Journals (Sweden)

H. P. Jarvie

2002-01-01

Full Text Available The INCA (Integrated Nitrogen in Catchments model was applied to the River Tweed in the Scottish Borders, a large-scale (4400km2, spatially heterogeneous catchment, draining a wide range of agricultural land-use types, and which contributes approximately 20% of UK river flows to the North Sea. The model was calibrated for the first four years' data record (1994 to 1997 and tested over the following three years (1998 to 2000. The model calibration and testing periods incorporated a high degree of variability in climatic conditions and river flows within the Tweed catchment. The ability of the INCA model to reproduce broad-scale spatial patterns and seasonal dynamics in river flows and nitrate concentrations suggests that the processes controlling first order variability in river water nitrate concentrations have been represented successfully within the model. The tendency of the model to overestimate summer/early autumn baseflow nitrate concentrations during dry years may be linked to the operation of aquatic plant uptake effects. It is, therefore, suggested that consideration be given to incorporating a spatially and temporally variable in-stream plant uptake term for the application of INCA to lowland eutrophic rivers. Scenarios to examine possible impacts of environmental change on nitrate concentrations on the Tweed are examined. These include the effects of (i implementing different recommendations for fertiliser use and land use change under the Nitrate Sensitive Areas (NSA Scheme and the Scottish Code of Good Agricultural Practice, (ii worst case scenario changes linked to a dramatic reduction in livestock numbers as a result of a crisis in UK livestock farming and (iii changes in atmospheric nitrogen deposition. Keywords: Nitrate, nitrogen, modelling, Tweed, INCA

Functional dynamic factor models with application to yield curve forecasting

KAUST Repository

Hays, Spencer

2012-09-01

Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

A stochastic spatial model of HIV dynamics with an asymmetric battle between the virus and the immune system

International Nuclear Information System (INIS)

Lin Hai; Shuai, J W

2010-01-01

A stochastic spatial model based on the Monte Carlo approach is developed to study the dynamics of human immunodeficiency virus (HIV) infection. We aim to propose a more detailed and realistic simulation frame by incorporating many important features of HIV dynamics, which include infections, replications and mutations of viruses, antigen recognitions, activations and proliferations of lymphocytes, and diffusions, encounters and interactions of virions and lymphocytes. Our model successfully reproduces the three-phase pattern observed in HIV infection, and the simulation results for the time distribution from infection to AIDS onset are also in good agreement with the clinical data. The interactions of viruses and the immune system in all the three phases are investigated. We assess the relative importance of various immune system components in the acute phase. The dynamics of how the two important factors, namely the viral diversity and the asymmetric battle between HIV and the immune system, result in AIDS are investigated in detail with the model.

Generative Models of Conformational Dynamics

Science.gov (United States)

Langmead, Christopher James

2014-01-01

Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

Directory of Open Access Journals (Sweden)

Sabine Prezenski

2017-08-01

Full Text Available Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

Science.gov (United States)

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from

Particle dynamics during electronic sputtering of solid krypton

DEFF Research Database (Denmark)

Dutkiewicz, L.; Pedrys, R.; Schou, Jørgen

1995-01-01

We have modeled electronic sputtering of solid krypton by excimer production with molecular dynamics. Both excimer evolution in the solid and deexcitation processes have been incorporated in the simulation. The excimer dynamics in the lattice has been analyzed: the excimers formed near the surface...

Unsteady Vibration Aerodynamic Modeling and Evaluation of Dynamic Derivatives Using Computational Fluid Dynamics

Directory of Open Access Journals (Sweden)

Xu Liu

2015-01-01

Full Text Available Unsteady aerodynamic system modeling is widely used to solve the dynamic stability problems encountering aircraft design. In this paper, single degree-of-freedom (SDF vibration model and forced simple harmonic motion (SHM model for dynamic derivative prediction are developed on the basis of modified Etkin model. In the light of the characteristics of SDF time domain solution, the free vibration identification methods for dynamic stability parameters are extended and applied to the time domain numerical simulation of blunted cone calibration model examples. The dynamic stability parameters by numerical identification are no more than 0.15% deviated from those by experimental simulation, confirming the correctness of SDF vibration model. The acceleration derivatives, rotary derivatives, and combination derivatives of Army-Navy Spinner Rocket are numerically identified by using unsteady N-S equation and solving different SHV patterns. Comparison with the experimental result of Army Ballistic Research Laboratories confirmed the correctness of the SHV model and dynamic derivative identification. The calculation result of forced SHM is better than that by the slender body theory of engineering approximation. SDF vibration model and SHM model for dynamic stability parameters provide a solution to the dynamic stability problem encountering aircraft design.

Dynamic Airspace Managment - Models and Algorithms

OpenAIRE

Cheng, Peng; Geng, Rui

2010-01-01

This chapter investigates the models and algorithms for implementing the concept of Dynamic Airspace Management. Three models are discussed. First two models are about how to use or adjust air route dynamically in order to speed up air traffic flow and reduce delay. The third model gives a way to dynamically generate the optimal sector configuration for an air traffic control center to both balance the controller’s workload and save control resources. The first model, called the Dynami...

RETRAN dynamic slip model

International Nuclear Information System (INIS)

McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

1981-01-01

A time dependent equation for the slip velocity in a two-phase flow condition has been incorporated into a developmental version of the RETRAN computer code. This model addition has been undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. In this paper, the development of the slip model is summarized and the corresponding constitutive equations are discussed. Comparisons of RETRAN analyses with steady-state void fraction data and data from the Semiscale S-02-6 small break test are also presented

Modeling dynamic behavior of Radon-222 in the planetary boundary layer

International Nuclear Information System (INIS)

Yuan, Y.C.; Stunder, M.J.

1983-01-01

A model has been used to simulate the dynamic behavior of radon concentration in the lower atmosphere from naturally occurring sources. The model includes prediction of radon exhalation rate from the surface of the ground due to convection and diffusion processes and the radon concentration profile in the planetary boundary layer. A time-dependent radon exhalation rate, variable mixing height, and altitude-dependent diffusivity are incorporated into the diffusion model by transforming the governing equation. The Galerkin finite-element technique and Crank-Nicholson finite different time marching are used in solving the discretized differential equations. The model-simulated time-varying radon concentrations near the ground agree well with measurements made over a period of seven days. It has been demonstrated that the model provides a reasonably good prediction of ambient radon concentration. As a general tool, with the input of actual radon concentration measurements, the model is also capable of estimating average radon exhalation rate from the ground surface. With current techniques, radon flux measurement is still a time-consuming and difficult task

Development of control method and dynamic model for multi-evaporator air conditioners (MEAC)

Energy Technology Data Exchange (ETDEWEB)

Chen Wu; Deng Shiming [Hong Kong Polytechnic University (China). Dept. of Building Services Engineering; Zhou Xingxi [Shanghai Jiao Tong University (China). Institute of Refrigeration and Cryogenics

2005-02-01

Interference between operation parameters among the different evaporators makes the desirable control of MEAC hard to realize. A novel control strategy is herein proposed. The suction pressure was taken as the controlled variable to modulate the speed of its compressor, and at the same time, the room air temperatures were taken to regulate the openings of individual electronic expansion valves (EEV). A self tuning fuzzy control algorithm with a modifying factor was incorporated in the controller. A controllability test was conducted with a dynamic thermodynamic model developed with a special modeling methodology. The controllability test has shown that the control strategy and algorithm are feasible and can achieve desirable control results. (author)

Constraining Distributed Catchment Models by Incorporating Perceptual Understanding of Spatial Hydrologic Behaviour

Science.gov (United States)

Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

2016-04-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models tend to contain a large number of poorly defined and spatially varying model parameters which are therefore computationally expensive to calibrate. Insufficient data can result in model parameter and structural equifinality, particularly when calibration is reliant on catchment outlet discharge behaviour alone. Evaluating spatial patterns of internal hydrological behaviour has the potential to reveal simulations that, whilst consistent with measured outlet discharge, are qualitatively dissimilar to our perceptual understanding of how the system should behave. We argue that such understanding, which may be derived from stakeholder knowledge across different catchments for certain process dynamics, is a valuable source of information to help reject non-behavioural models, and therefore identify feasible model structures and parameters. The challenge, however, is to convert different sources of often qualitative and/or semi-qualitative information into robust quantitative constraints of model states and fluxes, and combine these sources of information together to reject models within an efficient calibration framework. Here we present the development of a framework to incorporate different sources of data to efficiently calibrate distributed catchment models. For each source of information, an interval or inequality is used to define the behaviour of the catchment system. These intervals are then combined to produce a hyper-volume in state space, which is used to identify behavioural models. We apply the methodology to calibrate the Penn State Integrated Hydrological Model (PIHM) at the Wye catchment, Plynlimon, UK. Outlet discharge behaviour is successfully simulated when perceptual understanding of relative groundwater levels between lowland peat, upland peat

Computer Modelling of Dynamic Processes

Directory of Open Access Journals (Sweden)

B. Rybakin

2000-10-01

Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

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...

Comparison of Two Mechanistic Microbial Growth Models to Estimate Shelf Life of Perishable Food Package under Dynamic Temperature Conditions

Directory of Open Access Journals (Sweden)

Dong Sun Lee

2014-01-01

Full Text Available Two mechanistic microbial growth models (Huang’s model and model of Baranyi and Roberts given in differential and integrated equation forms were compared in predicting the microbial growth and shelf life under dynamic temperature storage and distribution conditions. Literatures consistently reporting the microbial growth data under constant and changing temperature conditions were selected to obtain the primary model parameters, set up the secondary models, and apply them to predict the microbial growth and shelf life under fluctuating temperatures. When evaluated by general estimation behavior, bias factor, accuracy factor, and root-mean-square error, Huang’s model was comparable to Baranyi and Roberts’ model in the capability to estimate microbial growth under dynamic temperature conditions. Its simple form of single differential equation incorporating directly the growth rate and lag time may work as an advantage to be used in online shelf life estimation by using the electronic device.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

Science.gov (United States)

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

Science.gov (United States)

Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

2016-01-01

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

Dynamic wake meandering modeling

Energy Technology Data Exchange (ETDEWEB)

Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)

2007-06-15

We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as

Incorporation particle creation and annihilation into Bohm's Pilot Wave model

Energy Technology Data Exchange (ETDEWEB)

Sverdlov, Roman [Raman Research Institute, C.V. Raman Avenue, Sadashiva Nagar, Bangalore, Karnataka, 560080 (India)

2011-07-08

The purpose of this paper is to come up with a Pilot Wave model of quantum field theory that incorporates particle creation and annihilation without sacrificing determinism; this theory is subsequently coupled with gravity.

Dynamic modelling of nuclear steam generators

International Nuclear Information System (INIS)

Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.

1980-01-01

Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)

Towards a comprehensive framework for cosimulation of dynamic models with an emphasis on time stepping

Science.gov (United States)

Hoepfer, Matthias

Over the last two decades, computer modeling and simulation have evolved as the tools of choice for the design and engineering of dynamic systems. With increased system complexities, modeling and simulation become essential enablers for the design of new systems. Some of the advantages that modeling and simulation-based system design allows for are the replacement of physical tests to ensure product performance, reliability and quality, the shortening of design cycles due to the reduced need for physical prototyping, the design for mission scenarios, the invoking of currently nonexisting technologies, and the reduction of technological and financial risks. Traditionally, dynamic systems are modeled in a monolithic way. Such monolithic models include all the data, relations and equations necessary to represent the underlying system. With increased complexity of these models, the monolithic model approach reaches certain limits regarding for example, model handling and maintenance. Furthermore, while the available computer power has been steadily increasing according to Moore's Law (a doubling in computational power every 10 years), the ever-increasing complexities of new models have negated the increased resources available. Lastly, modern systems and design processes are interdisciplinary, enforcing the necessity to make models more flexible to be able to incorporate different modeling and design approaches. The solution to bypassing the shortcomings of monolithic models is cosimulation. In a very general sense, co-simulation addresses the issue of linking together different dynamic sub-models to a model which represents the overall, integrated dynamic system. It is therefore an important enabler for the design of interdisciplinary, interconnected, highly complex dynamic systems. While a basic co-simulation setup can be very easy, complications can arise when sub-models display behaviors such as algebraic loops, singularities, or constraints. This work frames the

Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

Science.gov (United States)

Dey, S.; Saksena, S.; Merwade, V.

2017-12-01

Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

A two-site mean field model of discontinuous dynamic recrystallization

International Nuclear Information System (INIS)

Bernard, P.; Bag, S.; Huang, K.; Loge, R.E.

2011-01-01

Highlights: → Discontinuous dynamic recrystallization (DDRX) is modelled at the grain scale. → The two-site mean field approach allows introducing topological information. → DDRX kinetics, flow stress curves and recrystallized grain size are well predicted. → Temperature, strain rate and initial grain size effects are successfully described. → Grain size dependence naturally emerges from the model and agrees with experiment. - Abstract: The paper describes a new model of discontinuous dynamic recrystallization (DDRX) which can operate in constant or variable thermomechanical conditions. The model considers the elementary physical phenomena at the grain scale such as strain hardening, recovery, grain boundary migration, and nucleation. The microstructure is represented through a set of representative grains defined by their size and dislocation density. It is linked to a constitutive law giving access to the polycrystal flow stress. Interaction between representative grains and the surrounding material is idealized using a two-site approach whereby two homogeneous equivalent media with different dislocation densities are considered. Topological information is incorporated into the model by prescribing the relative weight of these two equivalent media as a function of their volume fractions. This procedure allows accounting for the well-known necklace structures. The model is applied to the prediction of DDRX in 304 L stainless steel, with parameters identified using an inverse methodology based on a genetic algorithm. Results show good agreement with experimental data at different temperatures and strain rates, predicting recrystallization kinetics, recrystallized grain size and stress-strain curve. Parameters identified with one initial grain size lead to accurate results for another initial grain size without introducing any additional parameter.

CERES: a model of forest stand biomass dynamics for predicting trace contaminant, nutrient, and water effects. I. Model description

Energy Technology Data Exchange (ETDEWEB)

Dixon, K R; Luxmoore, R J; Begovich, C L

1978-06-01

CERES is a forest stand growth model which incorporates sugar transport in order to predict both short-term effects and long-term accumulation of trace contaminants and/or nutrients when coupled with the soil chemistry model (SCHEM), and models of solute uptake (DIFMAS and DRYADS) of the Unified Transport Model, UTM. An important feature of CERES is its ability to interface with the soil--plant--atmosphere water model (PROSPER) as a means of both predicting and studying the effects of plant water status on growth and solute transport. CERES considers the biomass dynamics of plants, standing dead and litter with plants divided into leaves, stems, roots, and fruits. The plant parts are divided further into sugar substrate, storage, and in the case of stems and roots, heartwood components. Each ecosystem omponent is described by a mass balance equation written as a first-order ordinary differential equation.

A paradigm for modeling and computation of gas dynamics

Science.gov (United States)

Xu, Kun; Liu, Chang

2017-02-01

modeling methods, such as DSMC, particle in cell, and smooth particle hydrodynamics, play a dominant role to incorporate the flow physics into the algorithm construction directly. It is fully legitimate to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equations but to model flow dynamics as well. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

Mathematical modeling of alignment dynamics in active motor-filament systems

Science.gov (United States)

Swaminathan, Sumanth

The formation of the cytoskeleton, via motor-mediated microtubule self-organization, is an important subject of study in the biological sciences as well as in nonequilibrium, soft matter physics. Accurate modeling of the dynamics is a formidable task as it involves intrinsic nonlinearities, structural anisotropies, nonequilibrium processes, and a broad window of time scales, length scales, and densities. In this thesis, we study the ordering dynamics and pattern formations arising from motor-mediated microtubule self-organization in dilute and semi-dilute filament solutions. In the dilute case, we use a probabilistic model in which microtubules interact through motor induced, inelastic binary collisions. This model shows that initially disordered filament solutions exhibit an ordering transition resulting in the emergence of well aligned rod bundles. We study the existence and dynamic interaction of microtubule bundles analytically and numerically. Our results show a long term attraction and coalescing of bundles indicating a clear coarsening in the system; microtubule bundles concentrate into fewer orientations on a slow logarithmic time scale. In the semi-dilute case, multiple motors can bind a filament to several others and, for a critical motor density, induce a transition to an ordered state with a nonzero mean orientation. We develop a spatially homogeneous, mean-field theory that explicitly accounts for motor forcing and thermal fluctuations which enter into the model as multiplicative and additive noises respectively. Our model further incorporates a force-dependent detachment rate of motors, which in turn affects the mean and the fluctuations of the net force acting on a filament. We demonstrate that the transition to the oriented state changes from second order to first order when the force-dependent detachment becomes important. In our final analysis, we add complex spatial inhomogeneities to our mean field theory. The revised model consists of a system

BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

Science.gov (United States)

Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

2010-12-01

BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

An Agent Model Integrating an Adaptive Model for Environmental Dynamics

NARCIS (Netherlands)

Treur, J.; Umair, M.

2011-01-01

The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

Science.gov (United States)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

Supply based on demand dynamical model

Science.gov (United States)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

Dynamic neural network models of the premotoneuronal circuitry controlling wrist movements in primates.

Science.gov (United States)

Maier, M A; Shupe, L E; Fetz, E E

2005-10-01

Dynamic recurrent neural networks were derived to simulate neuronal populations generating bidirectional wrist movements in the monkey. The models incorporate anatomical connections of cortical and rubral neurons, muscle afferents, segmental interneurons and motoneurons; they also incorporate the response profiles of four populations of neurons observed in behaving monkeys. The networks were derived by gradient descent algorithms to generate the eight characteristic patterns of motor unit activations observed during alternating flexion-extension wrist movements. The resulting model generated the appropriate input-output transforms and developed connection strengths resembling those in physiological pathways. We found that this network could be further trained to simulate additional tasks, such as experimentally observed reflex responses to limb perturbations that stretched or shortened the active muscles, and scaling of response amplitudes in proportion to inputs. In the final comprehensive network, motor units are driven by the combined activity of cortical, rubral, spinal and afferent units during step tracking and perturbations. The model displayed many emergent properties corresponding to physiological characteristics. The resulting neural network provides a working model of premotoneuronal circuitry and elucidates the neural mechanisms controlling motoneuron activity. It also predicts several features to be experimentally tested, for example the consequences of eliminating inhibitory connections in cortex and red nucleus. It also reveals that co-contraction can be achieved by simultaneous activation of the flexor and extensor circuits without invoking features specific to co-contraction.

Dynamic information architecture system (DIAS) : multiple model simulation management.

Energy Technology Data Exchange (ETDEWEB)

Simunich, K. L.; Sydelko, P.; Dolph, J.; Christiansen, J.

2002-05-13

Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application contexts. The modeling domain of a specific DIAS-based simulation is determined by (1) software Entity (domain-specific) objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. In DIAS, models communicate only with Entity objects, never with each other. Each Entity object has a number of Parameter and Aspect (of behavior) objects associated with it. The Parameter objects contain the state properties of the Entity object. The Aspect objects represent the behaviors of the Entity object and how it interacts with other objects. DIAS extends the ''Object'' paradigm by abstraction of the object's dynamic behaviors, separating the ''WHAT'' from the ''HOW.'' DIAS object class definitions contain an abstract description of the various aspects of the object's behavior (the WHAT), but no implementation details (the HOW). Separate DIAS models/applications carry the implementation of object behaviors (the HOW). Any model deemed appropriate, including existing legacy-type models written in other languages, can drive entity object behavior. The DIAS design promotes plug-and-play of alternative models, with minimal recoding of existing applications. The DIAS Context Builder object builds a constructs or scenario for the simulation, based on developer specification and user inputs. Because DIAS is a discrete event simulation system, there is a Simulation Manager object with which all events are processed. Any class that registers to receive events must implement an event handler (method) to process the event during execution. Event handlers

Incorporating Twitter, Instagram, and Facebook in Economics Classrooms

Science.gov (United States)

Al-Bahrani, Abdullah; Patel, Darshak

2015-01-01

Social media is one of the most current and dynamic developments in education. In general, the field of economics has lagged behind other disciplines in incorporating technologies in the classroom. In this article, the authors provide a guide for economics educators on how to incorporate Twitter, Instagram, and Facebook inside and outside of the…

Testing and modeling the dynamic response of foam materials for blast protection

Science.gov (United States)

Fitek, John H.

The pressure wave released from an explosion can cause injury to the lungs. A personal armor system concept for blast lung injury protection consists of a polymer foam layer behind a rigid armor plate to be worn over the chest. This research develops a method for testing and modeling the dynamic response of foam materials to be used for down-selection of materials for this application. Constitutive equations for foam materials are incorporated into a lumped parameter model of the combined armor plate and foam system. Impact testing and shock tube testing are used to measure the foam model parameters and validate the model response to a pressure wave load. The plate and foam armor model is then coupled to a model of the human thorax. With a blast pressure wave input, the armor model is evaluated based on how it affects the injury-causing mechanism of chest wall motion. Results show that to reduce chest wall motion, the foam must compress at a relatively constant stress level, which requires a sufficient foam thickness.

An age-structured model for the coupled dynamics of HIV and HSV-2.

Science.gov (United States)

Kapitanov, Georgi; Alvey, Christina; Vogt-Geisse, Katia; Feng, Zhilan

2015-08-01

Evidence suggests a strong correlation between the prevalence of HSV-2 (genital herpes) and the perseverance of the HIV epidemic. HSV-2 is an incurable viral infection, characterized by periodic reactivation. We construct a model of the co-infection dynamics between the two diseases by incorporating a time-since-infection variable to track the alternating periods of infectiousness of HSV-2. The model considers only heterosexual relationships and distinguishes three population groups: males, general population females, and female sex workers. We calculate the basic reproduction numbers for each disease that provide threshold conditions, which determine whether a disease dies out or becomes endemic in the absence of the other disease. We also derive the invasion reproduction numbers that determine whether or not a disease can invade into a population in which the other disease is endemic. The calculations of the invasion reproduction numbers suggest a new aspect in their interpretation - the class from which the initial disease carrier arises is important for understanding the invasion dynamics and biological interpretation of the expressions of the reproduction numbers. Sensitivity analysis is conducted to examine the role of model parameters in influencing the model outcomes. The results are discussed in the last section.

Dynamic fuel cell models and their application in hardware in the loop simulation

Energy Technology Data Exchange (ETDEWEB)

Lemes, Zijad; Maencher, H. [MAGNUM Automatisierungstechnik GmbH, Bunsenstr. 22, D-64293 Darmstadt (Germany); Vath, Andreas; Hartkopf, Th. [Technische Universitaet Darmstadt/Institut fuer Elektrische Energiewandlung, Landgraf-Georg-Str. 4, D-64283 Darmstadt (Germany)

2006-03-21

Currently, fuel cell technology plays an important role in the development of alternative energy converters for mobile, portable and stationary applications. With the help of physical based models of fuel cell systems and appropriate test benches it is possible to design different applications and investigate their stationary and dynamic behaviour. The polymer electrolyte membrane (PEM) fuel cell system model includes gas humidifier, air and hydrogen supply, current converter and a detailed stack model incorporating the physical characteristics of the different layers. In particular, the use of these models together with hardware in the loop (HIL) capable test stands helps to decrease the costs and accelerate the development of fuel cell systems. The interface program provides fast data exchange between the test bench and the physical model of the fuel cell or any other systems in real time. So the flexibility and efficiency of the test bench increase fundamentally, because it is possible to replace real components with their mathematical models. (author)

Computational fluid dynamics modelling in cardiovascular medicine.

Science.gov (United States)

Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

2016-01-01

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission

Dynamic modeling of IGCC power plants

International Nuclear Information System (INIS)

Casella, F.; Colonna, P.

2012-01-01

Integrated Gasification Combined Cycle (IGCC) power plants are an effective option to reduce emissions and implement carbon-dioxide sequestration. The combination of a very complex fuel-processing plant and a combined cycle power station leads to challenging problems as far as dynamic operation is concerned. Dynamic performance is extremely relevant because recent developments in the electricity market push toward an ever more flexible and varying operation of power plants. A dynamic model of the entire system and models of its sub-systems are indispensable tools in order to perform computer simulations aimed at process and control design. This paper presents the development of the lumped-parameters dynamic model of an entrained-flow gasifier, with special emphasis on the modeling approach. The model is implemented into software by means of the Modelica language and validated by comparison with one set of data related to the steady operation of the gasifier of the Buggenum power station in the Netherlands. Furthermore, in order to demonstrate the potential of the proposed modeling approach and the use of simulation for control design purposes, a complete model of an exemplary IGCC power plant, including its control system, has been developed, by re-using existing models of combined cycle plant components; the results of a load dispatch ramp simulation are presented and shortly discussed. - Highlights: ► The acausal dynamic model of an entrained gasifier has been developed. ► The model can be used to perform system optimization and control studies. ► The model has been validated using field data. ► Model use is illustrated with an example showing the transient of an IGCC plant.

Dynamic Mean-Variance Asset Allocation

OpenAIRE

Basak, Suleyman; Chabakauri, Georgy

2009-01-01

Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

Directory of Open Access Journals (Sweden)

Paul Brocklehurst

Full Text Available We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM. Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

Science.gov (United States)

Brocklehurst, Paul; Ni, Haibo; Zhang, Henggui; Ye, Jianqiao

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano

CFD modeling of the IRIS pressurizer dynamic

International Nuclear Information System (INIS)

Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R.; Bezerra, Jair L.; Lira, Carlos A.B. Oliveira

2015-01-01

Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)

CFD modeling of the IRIS pressurizer dynamic

Energy Technology Data Exchange (ETDEWEB)

Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R., E-mail: rsanz@instec.cu, E-mail: mmontesi@instec.cu, E-mail: cgh@instec.cu, E-mail: leored1984@gmail.com [Instituto Superior de Tecnologias y Ciencias Aplicadas (InSTEC), La Habana (Cuba); Bezerra, Jair L.; Lira, Carlos A.B. Oliveira, E-mail: jair.lima@ufpe.br, E-mail: cabol@ufpe.br [Universida Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear

2015-07-01

Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)

Parameters in dynamic models of complex traits are containers of missing heritability.

Directory of Open Access Journals (Sweden)

Yunpeng Wang

Full Text Available Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.

Dynamic term structure models

DEFF Research Database (Denmark)

Andreasen, Martin Møller; Meldrum, Andrew

This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models with at most four...

Energy Balance Models and Planetary Dynamics

Science.gov (United States)

Domagal-Goldman, Shawn

2012-01-01

We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

Science.gov (United States)

Ward, Jonathan A.; Grindrod, Peter

2014-07-01

Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

Multi-Body Ski Jumper Model with Nonlinear Dynamic Inversion Muscle Control for Trajectory Optimization

Directory of Open Access Journals (Sweden)

Patrick Piprek

2018-02-01

Full Text Available This paper presents an approach to model a ski jumper as a multi-body system for an optimal control application. The modeling is based on the constrained Newton-Euler-Equations. Within this paper the complete multi-body modeling methodology as well as the musculoskeletal modeling is considered. For the musculoskeletal modeling and its incorporation in the optimization model, we choose a nonlinear dynamic inversion control approach. This approach uses the muscle models as nonlinear reference models and links them to the ski jumper movement by a control law. This strategy yields a linearized input-output behavior, which makes the optimal control problem easier to solve. The resulting model of the ski jumper can then be used for trajectory optimization whose results are compared to literature jumps. Ultimately, this enables the jumper to get a very detailed feedback of the flight. To achieve the maximal jump length, exact positioning of his body with respect to the air can be displayed.

Discrete dynamic modeling of cellular signaling networks.

Science.gov (United States)

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Energy Technology Data Exchange (ETDEWEB)

Sullivan, P.; Eurek, K.; Margolis, R.

2014-07-01

Because solar power is a rapidly growing component of the electricity system, robust representations of solar technologies should be included in capacity-expansion models. This is a challenge because modeling the electricity system--and, in particular, modeling solar integration within that system--is a complex endeavor. This report highlights the major challenges of incorporating solar technologies into capacity-expansion models and shows examples of how specific models address those challenges. These challenges include modeling non-dispatchable technologies, determining which solar technologies to model, choosing a spatial resolution, incorporating a solar resource assessment, and accounting for solar generation variability and uncertainty.

System dynamics modelling of situation awareness

CSIR Research Space (South Africa)

Oosthuizen, R

2015-11-01

Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...

Modelling biased human trust dynamics

NARCIS (Netherlands)

Hoogendoorn, M.; Jaffry, S.W.; Maanen, P.P. van; Treur, J.

2013-01-01

Abstract. Within human trust related behaviour, according to the literature from the domains of Psychology and Social Sciences often non-rational behaviour can be observed. Current trust models that have been developed typically do not incorporate non-rational elements in the trust formation

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

Science.gov (United States)

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling

Directory of Open Access Journals (Sweden)

Ismail eAdeniran

2013-07-01

Full Text Available Introduction Genetic forms of the Short QT Syndrome (SQTS arise due to cardiac ion channel mutations leading to accelerated ventricular repolarisation, arrhythmias and sudden cardiac death. Results from experimental and simulation studies suggest that changes to refractoriness and tissue vulnerability produce a substrate favourable to re-entry. Potential electromechanical consequences of the SQTS are less well understood. The aim of this study was to utilize electromechanically coupled human ventricle models to explore electromechanical consequences of the SQTS. Methods and results: The Rice et al. mechanical model was coupled to the ten Tusscher et al. ventricular cell model. Previously validated K+ channel formulations for SQT variants 1 and 3 were incorporated. Functional effects of the SQTS mutations on transients, sarcomere length shortening and contractile force at the single cell level were evaluated with and without the consideration of stretch activated channel current (Isac. Without Isac, the SQTS mutations produced dramatic reductions in the amplitude of transients, sarcomere length shortening and contractile force. When Isac was incorporated, there was a considerable attenuation of the effects of SQTS-associated action potential shortening on Ca2+ transients, sarcomere shortening and contractile force. Single cell models were then incorporated into 3D human ventricular tissue models. The timing of maximum deformation was delayed in the SQTS setting compared to control. Conclusion: The incorporation of Isac appears to be an important consideration in modelling functional effects of SQT 1 and 3 mutations on cardiac electro-mechanical coupling. Whilst there is little evidence of profoundly impaired cardiac contractile function in SQTS patients, our 3D simulations correlate qualitatively with reported evidence for dissociation between ventricular repolarization and the end of mechanical systole.

Investigations of incorporating source directivity into room acoustics computer models to improve auralizations

Science.gov (United States)

Vigeant, Michelle C.

Room acoustics computer modeling and auralizations are useful tools when designing or modifying acoustically sensitive spaces. In this dissertation, the input parameter of source directivity has been studied in great detail to determine first its effect in room acoustics computer models and secondly how to better incorporate the directional source characteristics into these models to improve auralizations. To increase the accuracy of room acoustics computer models, the source directivity of real sources, such as musical instruments, must be included in the models. The traditional method for incorporating source directivity into room acoustics computer models involves inputting the measured static directivity data taken every 10° in a sphere-shaped pattern around the source. This data can be entered into the room acoustics software to create a directivity balloon, which is used in the ray tracing algorithm to simulate the room impulse response. The first study in this dissertation shows that using directional sources over an omni-directional source in room acoustics computer models produces significant differences both in terms of calculated room acoustics parameters and auralizations. The room acoustics computer model was also validated in terms of accurately incorporating the input source directivity. A recently proposed technique for creating auralizations using a multi-channel source representation has been investigated with numerous subjective studies, applied to both solo instruments and an orchestra. The method of multi-channel auralizations involves obtaining multi-channel anechoic recordings of short melodies from various instruments and creating individual channel auralizations. These auralizations are then combined to create a total multi-channel auralization. Through many subjective studies, this process was shown to be effective in terms of improving the realism and source width of the auralizations in a number of cases, and also modeling different

GIS and dynamic phenomena modeling

Czech Academy of Sciences Publication Activity Database

Klimešová, Dana

2006-01-01

Roč. 4, č. 4 (2006), s. 11-15 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : dynamic modelling * temporal analysis * dynamics evaluation * temporal space Subject RIV: BC - Control Systems Theory

Making a difference: incorporating theories of autonomy into models of informed consent.

Science.gov (United States)

Delany, C

2008-09-01

Obtaining patients' informed consent is an ethical and legal obligation in healthcare practice. Whilst the law provides prescriptive rules and guidelines, ethical theories of autonomy provide moral foundations. Models of practice of consent, have been developed in the bioethical literature to assist in understanding and integrating the ethical theory of autonomy and legal obligations into the clinical process of obtaining a patient's informed consent to treatment. To review four models of consent and analyse the way each model incorporates the ethical meaning of autonomy and how, as a consequence, they might change the actual communicative process of obtaining informed consent within clinical contexts. An iceberg framework of consent is used to conceptualise how ethical theories of autonomy are positioned and underpin the above surface, and visible clinical communication, including associated legal guidelines and ethical rules. Each model of consent is critically reviewed from the perspective of how it might shape the process of informed consent. All four models would alter the process of obtaining consent. Two models provide structure and guidelines for the content and timing of obtaining patients' consent. The two other models rely on an attitudinal shift in clinicians. They provide ideas for consent by focusing on underlying values, attitudes and meaning associated with the ethical meaning of autonomy. The paper concludes that models of practice that explicitly incorporate the underlying ethical meaning of autonomy as their basis, provide less prescriptive, but more theoretically rich guidance for healthcare communicative practices.

A Lagrangian dynamic subgrid-scale model turbulence

Science.gov (United States)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

PWR plant operator training used full scope simulator incorporated MAAP model

International Nuclear Information System (INIS)

Matsumoto, Y.; Tabuchi, T.; Yamashita, T.; Komatsu, Y.; Tsubouchi, K.; Banka, T.; Mochizuki, T.; Nishimura, K.; Iizuka, H.

2015-01-01

NTC makes an effort with the understanding of plant behavior of core damage accident as part of our advanced training. For the Fukushima Daiichi Nuclear Power Station accident, we introduced the MAAP model into PWR operator training full scope simulator and also made the Severe Accident Visual Display unit. From 2014, we will introduce new training program for a core damage accident with PWR operator training full scope simulator incorporated the MAAP model and the Severe Accident Visual Display unit. (author)

Incorporating modelled subglacial hydrology into inversions for basal drag

Directory of Open Access Journals (Sweden)

C. P. Koziol

2017-12-01

Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.

Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

Science.gov (United States)

Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

2017-01-01

Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

Optimization,Modeling, and Control: Applications to Klystron Designing and Hepatitis C Virus Dynamics

Science.gov (United States)

Lankford, George Bernard

In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python). The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost

Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model

Science.gov (United States)

Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P.; Russell, MacKenzie R.; Jones, Robert M.; King, Matt; Betterton, Eric A.; Sáez, A. Eduardo

2014-01-01

Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition. PMID:25621085

Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model.

Science.gov (United States)

Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P; Russell, MacKenzie R; Jones, Robert M; King, Matt; Betterton, Eric A; Sáez, A Eduardo

2014-09-01

Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition.

Modeling of metal thin film growth: Linking angstrom-scale molecular dynamics results to micron-scale film topographies

Science.gov (United States)

Hansen, U.; Rodgers, S.; Jensen, K. F.

2000-07-01

A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.

Modelling group dynamic animal movement

DEFF Research Database (Denmark)

Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.

2014-01-01

makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias......, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual......Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However...

Modelling forest dynamics along climate gradients in Bolivia

NARCIS (Netherlands)

Seiler, C.; Hutjes, R.W.A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V.K.; Melton, J.R.; Hickler, T.; Kabat, P.

2014-01-01

Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model

Absorptive capacity, technological innovation, and product life cycle: a system dynamics model.

Science.gov (United States)

Zou, Bo; Guo, Feng; Guo, Jinyu

2016-01-01

While past research has recognized the importance of the dynamic nature of absorptive capacity, there is limited knowledge on how to generate a fair and comprehensive analytical framework. Based on interviews with 24 Chinese firms, this study develops a system-dynamics model that incorporates an important feedback loop among absorptive capacity, technological innovation, and product life cycle (PLC). The simulation results reveal that (1) PLC affects the dynamic process of absorptive capacity; (2) the absorptive capacity of a firm peaks in the growth stage of PLC, and (3) the market demand at different PLC stages is the main driving force in firms' technological innovations. This study also explores a sensitivity simulation using the variables of (1) time spent in founding an external knowledge network, (2) research and development period, and (3) knowledge diversity. The sensitivity simulation results show that the changes of these three variables have a greater impact on absorptive capacity and technological innovation during growth and maturity stages than in the introduction and declining stages of PLC. We provide suggestions on how firms can adjust management policies to improve their absorptive capacity and technological innovation performance during different PLC stages.

Slow [Na+]i dynamics impacts arrhythmogenesis and spiral wave reentry in cardiac myocyte ionic model.

Science.gov (United States)

Krogh-Madsen, Trine; Christini, David J

2017-09-01

Accumulation of intracellular Na + is gaining recognition as an important regulator of cardiac myocyte electrophysiology. The intracellular Na + concentration can be an important determinant of the cardiac action potential duration, can modulate the tissue-level conduction of excitation waves, and can alter vulnerability to arrhythmias. Mathematical models of cardiac electrophysiology often incorporate a dynamic intracellular Na + concentration, which changes much more slowly than the remaining variables. We investigated the dependence of several arrhythmogenesis-related factors on [Na + ] i in a mathematical model of the human atrial action potential. In cell simulations, we found that [Na + ] i accumulation stabilizes the action potential duration to variations in several conductances and that the slow dynamics of [Na + ] i impacts bifurcations to pro-arrhythmic afterdepolarizations, causing intermittency between different rhythms. In long-lasting tissue simulations of spiral wave reentry, [Na + ] i becomes spatially heterogeneous with a decreased area around the spiral wave rotation center. This heterogeneous region forms a functional anchor, resulting in diminished meandering of the spiral wave. Our findings suggest that slow, physiological, rate-dependent variations in [Na + ] i may play complex roles in cellular and tissue-level cardiac dynamics.

Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

Science.gov (United States)

Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

2017-05-01

Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery

Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

Science.gov (United States)

Denys Yemshanov; Frank H Koch; Mark Ducey

2015-01-01

Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

A dynamic model-based estimate of the value of a vanadium redox flow battery for frequency regulation in Texas

International Nuclear Information System (INIS)

Fares, Robert L.; Meyers, Jeremy P.; Webber, Michael E.

2014-01-01

Highlights: • A model is implemented to describe the dynamic voltage of a vanadium flow battery. • The model is used with optimization to maximize the utility of the battery. • A vanadium flow battery’s value for regulation service is approximately $1500/kW. - Abstract: Building on past work seeking to value emerging energy storage technologies in grid-based applications, this paper introduces a dynamic model-based framework to value a vanadium redox flow battery (VRFB) participating in Texas’ organized electricity market. Our model describes the dynamic behavior of a VRFB system’s voltage and state of charge based on the instantaneous charging or discharging power required from the battery. We formulate an optimization problem that incorporates the model to show the potential value of a VRFB used for frequency regulation service in Texas. The optimization is implemented in Matlab using the large-scale, interior-point, nonlinear optimization algorithm, with the objective function gradient, nonlinear constraint gradients, and Hessian matrix specified analytically. Utilizing market prices and other relevant data from the Electric Reliability Council of Texas (ERCOT), we find that a VRFB system used for frequency regulation service could be worth approximately $1500/kW

Application of a two-pool model to soil carbon dynamics under elevated CO2.

Science.gov (United States)

van Groenigen, Kees Jan; Xia, Jianyang; Osenberg, Craig W; Luo, Yiqi; Hungate, Bruce A

2015-12-01

Elevated atmospheric CO2 concentrations increase plant productivity and affect soil microbial communities, with possible consequences for the turnover rate of soil carbon (C) pools and feedbacks to the atmosphere. In a previous analysis (Van Groenigen et al., 2014), we used experimental data to inform a one-pool model and showed that elevated CO2 increases the decomposition rate of soil organic C, negating the storage potential of soil. However, a two-pool soil model can potentially explain patterns of soil C dynamics without invoking effects of CO2 on decomposition rates. To address this issue, we refit our data to a two-pool soil C model. We found that CO2 enrichment increases decomposition rates of both fast and slow C pools. In addition, elevated CO2 decreased the carbon use efficiency of soil microbes (CUE), thereby further reducing soil C storage. These findings are consistent with numerous empirical studies and corroborate the results from our previous analysis. To facilitate understanding of C dynamics, we suggest that empirical and theoretical studies incorporate multiple soil C pools with potentially variable decomposition rates. © 2015 John Wiley & Sons Ltd.

Dynamic panel data models

NARCIS (Netherlands)

Bun, M.J.G.; Sarafidis, V.

2013-01-01

This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.

Simple Models for the Dynamic Modeling of Rotating Tires

Directory of Open Access Journals (Sweden)

J.C. Delamotte

2008-01-01

Full Text Available Large Finite Element (FE models of tires are currently used to predict low frequency behavior and to obtain dynamic model coefficients used in multi-body models for riding and comfort. However, to predict higher frequency behavior, which may explain irregular wear, critical rotating speeds and noise radiation, FE models are not practical. Detailed FE models are not adequate for optimization and uncertainty predictions either, as in such applications the dynamic solution must be computed a number of times. Therefore, there is a need for simpler models that can capture the physics of the tire and be used to compute the dynamic response with a low computational cost. In this paper, the spectral (or continuous element approach is used to derive such a model. A circular beam spectral element that takes into account the string effect is derived, and a method to simulate the response to a rotating force is implemented in the frequency domain. The behavior of a circular ring under different internal pressures is investigated using modal and frequency/wavenumber representations. Experimental results obtained with a real untreaded truck tire are presented and qualitatively compared with the simple model predictions with good agreement. No attempt is made to obtain equivalent parameters for the simple model from the real tire results. On the other hand, the simple model fails to represent the correct variation of the quotient of the natural frequency by the number of circumferential wavelengths with the mode count. Nevertheless, some important features of the real tire dynamic behavior, such as the generation of standing waves and part of the frequency/wavenumber behavior, can be investigated using the proposed simplified model.

Incorporating Resilience into Dynamic Social Models

Science.gov (United States)

2016-07-20

form contains classified information, stamp classification level on the top and bottom of this page. 17. LIMITATION OF ABSTRACT. This block must be...resilience as a multi- level resilience and study their resilience at individual, family and society levels . However, having more than one level on a...4] U. Fischbacher, S. Gächter, and E. Fehr, “Are People Conditionally Cooperative ? Evidence from a Public Goods Experiment,” Econ . Lett., vol

Opinion dynamics model based on quantum formalism

Energy Technology Data Exchange (ETDEWEB)

Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

2016-03-11

Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

Differential equation models for sharp threshold dynamics.

Science.gov (United States)

Schramm, Harrison C; Dimitrov, Nedialko B

2014-01-01

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

A thermal and electrical dynamic mathematical model for squirrel cage induction motors; Modelamento matematico dinamico termico e eletrico de motores de inducao

Energy Technology Data Exchange (ETDEWEB)

Sousa, Ronaldo Martins de

1996-01-01

A thermal and electrical dynamic mathematical model for squirrel cage induction motors is presented. The electrical model is described by Park equation and the torque equation, while the thermal model is described by a system of four first order differential equations that represent the motor heat transfer process. The model presented can be used to determine thermal and electrical performance for any operation condition. However, it is suitable mainly for machines operating under continuously transient condition. The presented mathematical model also incorporate variation of rotor winding electrical parameters due to skin effect. (author)

Coupling population dynamics with earth system models: the POPEM model.

Science.gov (United States)

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

Predator-prey-subsidy population dynamics on stepping-stone domains with dispersal delays.

Science.gov (United States)

Eide, Ragna M; Krause, Andrew L; Fadai, Nabil T; Van Gorder, Robert A

2018-08-14

We examine the role of the travel time of a predator along a spatial network on predator-prey population interactions, where the predator is able to partially or fully sustain itself on a resource subsidy. The impact of access to food resources on the stability and behaviour of the predator-prey-subsidy system is investigated, with a primary focus on how incorporating travel time changes the dynamics. The population interactions are modelled by a system of delay differential equations, where travel time is incorporated as discrete delay in the network diffusion term in order to model time taken to migrate between spatial regions. The model is motivated by the Arctic ecosystem, where the Arctic fox consumes both hunted lemming and scavenged seal carcass. The fox travels out on sea ice, in addition to quadrennially migrating over substantial distances. We model the spatial predator-prey-subsidy dynamics through a "stepping-stone" approach. We find that a temporal delay alone does not push species into extinction, but rather may stabilize or destabilize coexistence equilibria. We are able to show that delay can stabilize quasi-periodic or chaotic dynamics, and conclude that the incorporation of dispersal delay has a regularizing effect on dynamics, suggesting that dispersal delay can be proposed as a solution to the paradox of enrichment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Swarm Intelligence for Urban Dynamics Modelling

International Nuclear Information System (INIS)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

2009-01-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Swarm Intelligence for Urban Dynamics Modelling

Science.gov (United States)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

2009-04-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

Hydration dynamics near a model protein surface

International Nuclear Information System (INIS)

Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

2003-01-01

The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces

Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models.

Science.gov (United States)

Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C; Noé, Frank

2013-11-07

The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.

Adaptive numerical modeling of dynamic crack propagation

International Nuclear Information System (INIS)

Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.

2006-01-01

We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)

A particle based simulation model for glacier dynamics

Directory of Open Access Journals (Sweden)

J. A. Åström

2013-10-01

Full Text Available A particle-based computer simulation model was developed for investigating the dynamics of glaciers. In the model, large ice bodies are made of discrete elastic particles which are bound together by massless elastic beams. These beams can break, which induces brittle behaviour. At loads below fracture, beams may also break and reform with small probabilities to incorporate slowly deforming viscous behaviour in the model. This model has the advantage that it can simulate important physical processes such as ice calving and fracturing in a more realistic way than traditional continuum models. For benchmarking purposes the deformation of an ice block on a slip-free surface was compared to that of a similar block simulated with a Finite Element full-Stokes continuum model. Two simulations were performed: (1 calving of an ice block partially supported in water, similar to a grounded marine glacier terminus, and (2 fracturing of an ice block on an inclined plane of varying basal friction, which could represent transition to fast flow or surging. Despite several approximations, including restriction to two-dimensions and simplified water-ice interaction, the model was able to reproduce the size distributions of the debris observed in calving, which may be approximated by universal scaling laws. On a moderate slope, a large ice block was stable and quiescent as long as there was enough of friction against the substrate. For a critical length of frictional contact, global sliding began, and the model block disintegrated in a manner suggestive of a surging glacier. In this case the fragment size distribution produced was typical of a grinding process.

Modelling the Dynamics of an Aedes albopictus Population

Directory of Open Access Journals (Sweden)

Thomas Anung Basuki

2010-08-01

Full Text Available We present a methodology for modelling population dynamics with formal means of computer science. This allows unambiguous description of systems and application of analysis tools such as simulators and model checkers. In particular, the dynamics of a population of Aedes albopictus (a species of mosquito and its modelling with the Stochastic Calculus of Looping Sequences (Stochastic CLS are considered. The use of Stochastic CLS to model population dynamics requires an extension which allows environmental events (such as changes in the temperature and rainfalls to be taken into account. A simulator for the constructed model is developed via translation into the specification language Maude, and used to compare the dynamics obtained from the model with real data.

Modeling the Dynamic Digestive System Microbiome†

OpenAIRE

Estes, Anne M.

2015-01-01

“Modeling the Dynamic Digestive System Microbiome” is a hands-on activity designed to demonstrate the dynamics of microbiome ecology using dried pasta and beans to model disturbance events in the human digestive system microbiome. This exercise demonstrates how microbiome diversity is influenced by: 1) niche availability and habitat space and 2) a major disturbance event, such as antibiotic use. Students use a pictorial key to examine prepared models of digestive system microbiomes to determi...

An individual-based model of Zebrafish population dynamics accounting for energy dynamics

DEFF Research Database (Denmark)

Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

Dynamic dielectrophoresis model of multi-phase ionic fluids.

Directory of Open Access Journals (Sweden)

Ying Yan

Full Text Available Ionic-based dielectrophoretic microchips have attracted significant attention due to their wide-ranging applications in electro kinetic and biological experiments. In this work, a numerical method is used to simulate the dynamic behaviors of ionic droplets in a microchannel under the effect of dielectrophoresis. When a discrete liquid dielectric is encompassed within a continuous fluid dielectric placed in an electric field, an electric force is produced due to the dielectrophoresis effect. If either or both of the fluids are ionic liquids, the magnitude and even the direction of the force will be changed because the net ionic charge induced by an electric field can affect the polarization degree of the dielectrics. However, using a dielectrophoresis model, assuming ideal dielectrics, results in significant errors. To avoid the inaccuracy caused by the model, this work incorporates the electrode kinetic equation and defines a relationship between the polarization charge and the net ionic charge. According to the simulation conditions presented herein, the electric force obtained in this work has an error exceeding 70% of the actual value if the false effect of net ionic charge is not accounted for, which would result in significant issues in the design and optimization of experimental parameters. Therefore, there is a clear motivation for developing a model adapted to ionic liquids to provide precise control for the dielectrophoresis of multi-phase ionic liquids.

Dynamic dielectrophoresis model of multi-phase ionic fluids.

Science.gov (United States)

Yan, Ying; Luo, Jing; Guo, Dan; Wen, Shizhu

2015-01-01

Ionic-based dielectrophoretic microchips have attracted significant attention due to their wide-ranging applications in electro kinetic and biological experiments. In this work, a numerical method is used to simulate the dynamic behaviors of ionic droplets in a microchannel under the effect of dielectrophoresis. When a discrete liquid dielectric is encompassed within a continuous fluid dielectric placed in an electric field, an electric force is produced due to the dielectrophoresis effect. If either or both of the fluids are ionic liquids, the magnitude and even the direction of the force will be changed because the net ionic charge induced by an electric field can affect the polarization degree of the dielectrics. However, using a dielectrophoresis model, assuming ideal dielectrics, results in significant errors. To avoid the inaccuracy caused by the model, this work incorporates the electrode kinetic equation and defines a relationship between the polarization charge and the net ionic charge. According to the simulation conditions presented herein, the electric force obtained in this work has an error exceeding 70% of the actual value if the false effect of net ionic charge is not accounted for, which would result in significant issues in the design and optimization of experimental parameters. Therefore, there is a clear motivation for developing a model adapted to ionic liquids to provide precise control for the dielectrophoresis of multi-phase ionic liquids.

Understanding and Modeling Teams As Dynamical Systems

Science.gov (United States)

Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

2017-01-01

By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

Static and Dynamic Mechanical Properties of Graphene Oxide-Incorporated Woven Carbon Fiber/Epoxy Composite

Science.gov (United States)

Adak, Nitai Chandra; Chhetri, Suman; Kim, Nam Hoon; Murmu, Naresh Chandra; Samanta, Pranab; Kuila, Tapas

2018-03-01

This study investigates the synergistic effects of graphene oxide (GO) on the woven carbon fiber (CF)-reinforced epoxy composites. The GO nanofiller was incorporated into the epoxy resin with variations in the content, and the CF/epoxy composites were manufactured using a vacuum-assisted resin transfer molding process and then cured at 70 and 120 °C. An analysis of the mechanical properties of the GO (0.2 wt.%)/CF/epoxy composites showed an improvement in the tensile strength, Young's modulus, toughness, flexural strength and flexural modulus by 34, 20, 83, 55 and 31%, respectively, when compared to the CF/epoxy composite. The dynamic mechanical analysis of the composites exhibited an enhancement of 56, 114 and 22% in the storage modulus, loss modulus and damping capacity (tan δ), respectively, at its glass transition temperature. The fiber-matrix interaction was studied using a Cole-Cole plot analysis.

A computational growth model for measuring dynamic cortical development in the first year of life.

Science.gov (United States)

Nie, Jingxin; Li, Gang; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2012-10-01

Human cerebral cortex develops extremely fast in the first year of life. Quantitative measurement of cortical development during this early stage plays an important role in revealing the relationship between cortical structural and high-level functional development. This paper presents a computational growth model to simulate the dynamic development of the cerebral cortex from birth to 1 year old by modeling the cerebral cortex as a deformable elastoplasticity surface driven via a growth model. To achieve a high accuracy, a guidance model is also incorporated to estimate the growth parameters and cortical shapes at later developmental stages. The proposed growth model has been applied to 10 healthy subjects with longitudinal brain MR images acquired at every 3 months from birth to 1 year old. The experimental results show that our proposed method can capture the dynamic developmental process of the cortex, with the average surface distance error smaller than 0.6 mm compared with the ground truth surfaces, and the results also show that 1) the curvedness and sharpness decrease from 2 weeks to 12 months and 2) the frontal lobe shows rapidly increasing cortical folding during this period, with relatively slower increase of the cortical folding in the occipital and parietal lobes.

Modeling interactions of soil hydrological dynamics and soil thermal and permafrost dynamics and their effects on carbon cycling in northern high latitudes

Science.gov (United States)

Zhuang, Q.; Tang, J.

2008-12-01

Large areas of northern high latitude ecosystems are underlain with permafrost. The warming temperature and fires deteriorate the stability of those permafrost, altering hydrological cycle, and consequently soil temperature and active layer depth. These changes will determine the fate of large carbon pools in soils and permafrost over the region. We developed a modeling framework of hydrology, permafrost, and biogeochemical dynamics based on our existing modules of these components. The framework was incorporated with a new snow dynamics module and the effects of soil moisture on soil thermal properties. The framework was tested for tundra and boreal forest ecosystems at field sites with respect to soil thermal and hydrological regimes in Alaska and was then applied to the whole Alaskan ecosystems for the period of 1923-2000 at a daily time step. Our two sets of simulations with and without considering soil moisture effects indicated that the soil temperature profile and active layer depth between two simulations are significant different. The differences of soil thermal regime would expect to result in different carbon dynamics. Next, we will verify the framework with the observed data of soil moisture and soil temperature at poor-drain, moderate-drain, and well-drain boreal forest sites in Alaska. With the verified framework, we will evaluate the effects of interactions of soil thermal and hydrological dynamics on carbon dynamics for the whole northern high latitudes.

Incorporation of a wind generator model into a dynamic power flow analysis; Incorporacion de un modelo de generador eolico al analisis de flujos dinamicos de potencia

Energy Technology Data Exchange (ETDEWEB)

Angeles Camacho, C.; Banuelos Ruedas, F. [Instituto de Ingenieria, Universidad Nacional Autonoma de Mexico (Mexico)]. E-mail: cangelesc@iingen.unam.mx; fbanuelosr@iingen.unam.mx

2011-07-15

Wind energy is nowadays one of the most cost-effective and practical options for electric generation from renewable resources. However, increased penetration of wind generation causes the power networks to be more depend on, and vulnerable to, the varying wind speed. Modeling is a tool which can provide valuable information about the interaction between wind farms and the power network to which they are connected. This paper develops a realistic characterization of a wind generator. The wind generator model is incorporated into an algorithm to investigate its contribution to the stability of the power network in the time domain. The tool obtained is termed dynamic power flow. The wind generator model takes on account the wind speed and the reactive power consumption by induction generators. Dynamic power flow analysis is carried-out using real wind data at 10-minute time intervals collected for one meteorological station. The generation injected at one point into the network provides active power locally and is found to reduce global power losses. However, the power supplied is time-varying and causes fluctuations in voltage magnitude and power flows in transmission lines. [Spanish] La energia eolica es hoy en dia una de las opciones mas efectivas y practicas para la generacion de electricidad a partir de energias renovables. Sin embargo, el incremento de la penetracion de energia eolica provoca que los sistemas de potencia se vuelvan mas dependientes y vulnerables a las variaciones de la velocidad del viento. El modelado es una herramienta que provee informacion valiosa de la interaccion dinamica entre las turbinas eolicas y las redes de potencia a las que se conectan. El presente articulo desarrolla una caracterizacion realista de un modelo de la turbina eolica. El modelo de la turbina eolica se incorpora a un algoritmo para el analisis de su contribucion a la estabilidad de una red electrica en el dominio del tiempo. La herramienta obtenida se conoce como flujos

System dynamics and control with bond graph modeling

CERN Document Server

Kypuros, Javier

2013-01-01

Part I Dynamic System ModelingIntroduction to System DynamicsIntroductionSystem Decomposition and Model ComplexityMathematical Modeling of Dynamic SystemsAnalysis and Design of Dynamic SystemsControl of Dynamic SystemsDiagrams of Dynamic SystemsA Graph-Centered Approach to ModelingSummaryPracticeExercisesBasic Bond Graph ElementsIntroductionPower and Energy VariablesBasic 1-Port ElementsBasic 2-Ports ElementsJunction ElementsSimple Bond Graph ExamplesSummaryPracticeExercisesBond Graph Synthesis and Equation DerivationIntroductionGeneral GuidelinesMechanical TranslationMechanical RotationElectrical CircuitsHydraulic CircuitsMixed SystemsState Equation DerivationState-Space RepresentationsAlgebraic Loops and Derivative CausalitySummaryPracticeExercisesImpedance Bond GraphsIntroductionLaplace Transform of the State-Space EquationBasic 1-Port ImpedancesImpedance Bond Graph SynthesisJunctions, Transformers, and GyratorsEffort and Flow DividersSign ChangesTransfer Function DerivationAlternative Derivation of Transf...

Modeling fraud detection and the incorporation of forensic specialists in the audit process

DEFF Research Database (Denmark)

Sakalauskaite, Dominyka

Financial statement audits are still comparatively poor in fraud detection. Forensic specialists can play a significant role in increasing audit quality. In this paper, based on prior academic research, I develop a model of fraud detection and the incorporation of forensic specialists in the audit...... process. The intention of the model is to identify the reasons why the audit is weak in fraud detection and to provide the analytical framework to assess whether the incorporation of forensic specialists can help to improve it. The results show that such specialists can potentially improve the fraud...... detection in the audit, but might also cause some negative implications. Overall, even though fraud detection is one of the main topics in research there are very few studies done on the subject of how auditors co-operate with forensic specialists. Thus, the paper concludes with suggestions for further...

Multistability and complex dynamics in a simple discrete economic model

International Nuclear Information System (INIS)

Peng Mingshu; Jiang Zhonghao; Jiang Xiaoxia; Hu Jiping; Qu Youli

2009-01-01

In this paper, we will propose a generalized Cournot duopoly model with Z 2 symmetry. We demonstrate that cost functions incorporating an interfirm externality lead to a system of couple one-dimensional maps. In the situation where agents take turns, we find in an analytic way that there coexist multiple unstable/stable period-2 cycles or synchronized/asynchronized periodic orbits. Coupling one-dimension chaos can be observed. In a more general situation, where agents move simultaneously, a closer analysis reveals some well-known local bifurcations and global bifurcations which typically occur in two-parameter families of two-dimensional discrete time dynamical systems, including codimension-one (fold-, flip-, Neimark-Sacker-) bifurcations, codimension-two (fold/flip, 1:2 resonance, 1:3 resonance and 1:4 resonance) bifurcations, and hetero-clinic, homo-clinic bifurcations, etc. Multistability, including the coexistence of synchronized/asynchronized solutions are also discussed.

Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Zhang, Pengpeng, E-mail: zhangp@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

2014-02-01

Purpose: We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs). Methods and Materials: We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTV{sub orig}) in 3 equispaced steps to the predicted residue (PTV{sub pred}). Patients were treated with a uniform prescription dose to PTV{sub orig}. By contrast, PTP optimization started with the same prescription dose to PTV{sub orig} but linearly increased the dose at each step, until reaching the highest dose achievable to PTV{sub pred} consistent with OAR limits. This method is compared with midcourse adaptive replanning. Results: Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm{sup 3}. On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTV{sub orig} at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach. Conclusions: PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

Explanatory Item Response Modeling of Children's Change on a Dynamic Test of Analogical Reasoning

Science.gov (United States)

Stevenson, Claire E.; Hickendorff, Marian; Resing, Wilma C. M.; Heiser, Willem J.; de Boeck, Paul A. L.

2013-01-01

Dynamic testing is an assessment method in which training is incorporated into the procedure with the aim of gauging cognitive potential. Large individual differences are present in children's ability to profit from training in analogical reasoning. The aim of this experiment was to investigate sources of these differences on a dynamic test of…

Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

Science.gov (United States)

Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

2017-12-01

Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

Do environmental dynamics matter in fate models? Exploring scenario dynamics for a terrestrial and an aquatic system.

Science.gov (United States)

Morselli, Melissa; Terzaghi, Elisa; Di Guardo, Antonio

2018-01-24

Nowadays, there is growing interest in inserting more ecological realism into risk assessment of chemicals. On the exposure evaluation side, this can be done by studying the complexity of exposure in the ecosystem, niche partitioning, e.g. variation of the exposure scenario. Current regulatory predictive approaches, to ensure simplicity and predictive ability, generally keep the scenario as static as possible. This could lead to under or overprediction of chemical exposure depending on the chemical and scenario simulated. To account for more realistic exposure conditions, varying temporally and spatially, additional scenario complexity should be included in currently used models to improve their predictive ability. This study presents two case studies (a terrestrial and an aquatic one) in which some polychlorinated biphenyls (PCBs) were simulated with the SoilPlusVeg and ChimERA models to show the importance of scenario variation in time (biotic and abiotic compartments). The results outlined the importance of accounting for planetary boundary layer variation and vegetation dynamics to accurately predict air concentration changes and the timing of chemical dispersion from the source in terrestrial systems. For the aquatic exercise, the results indicated the need to account for organic carbon forms (particulate and dissolved organic carbon) and vegetation biomass dynamics. In both cases the range of variation was up to two orders of magnitude depending on the congener and scenario, reinforcing the need for incorporating such knowledge into exposure assessment.

A Dynamic Model of Sustainment Investment

Science.gov (United States)

2015-02-01

Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

Science.gov (United States)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Model-based dynamic resistive wall mode identification and feedback control in the DIII-D tokamak

International Nuclear Information System (INIS)

In, Y.; Kim, J.S.; Edgell, D.H.; Strait, E.J.; Humphreys, D.A.; Walker, M.L.; Jackson, G.L.; Chu, M.S.; Johnson, R.; La Haye, R.J.; Okabayashi, M.; Garofalo, A.M.; Reimerdes, H.

2006-01-01

A new model-based dynamic resistive wall mode (RWM) identification and feedback control algorithm has been developed. While the overall RWM structure can be detected by a model-based matched filter in a similar manner to a conventional sensor-based scheme, it is significantly influenced by edge-localized-modes (ELMs). A recent study suggested that such ELM noise might cause the RWM control system to respond in an undesirable way. Thus, an advanced algorithm to discriminate ELMs from RWM has been incorporated into this model-based control scheme, dynamic Kalman filter. Specifically, the DIII-D [J. L. Luxon, Nucl. Fusion 42, 614 (2002)] resistive vessel wall was modeled in two ways: picture frame model or eigenmode treatment. Based on the picture frame model, the first real-time, closed-loop test results of the Kalman filter algorithms during DIII-D experimental operation are presented. The Kalman filtering scheme was experimentally confirmed to be effective in discriminating ELMs from RWM. As a result, the actuator coils (I-coils) were rarely excited during ELMs, while retaining the sensitivity to RWM. However, finding an optimized set of operating parameters for the control algorithm requires further analysis and design. Meanwhile, a more advanced Kalman filter based on a more accurate eigenmode model has been developed. According to this eigenmode approach, significant improvement in terms of control performance has been predicted, while maintaining good ELM discrimination

Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

Institute of Scientific and Technical Information of China (English)

Akihiko Murai; Q. Youn Hong; Katsu Yamane; Jessica K. Hodgins

2017-01-01

Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation (movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence (slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

Institute of Scientific and Technical Information of China (English)

Akihiko Murai; Q.Youn Hong; Katsu Yamane; Jessica K.Hodgins

2017-01-01

Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation(movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence(slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

Science.gov (United States)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over

High-energy outer radiation belt dynamic modeling

International Nuclear Information System (INIS)

Chiu, Y.T.; Nightingale, R.W.; Rinaldi, M.A.

1989-01-01

Specification of the average high-energy radiation belt environment in terms of phenomenological montages of satellite measurements has been available for some time. However, for many reasons both scientific and applicational (including concerns for a better understanding of the high-energy radiatino background in space), it is desirable to model the dynamic response of the high-energy radiation belts to sources, to losses, and to geomagnetic activity. Indeed, in the outer electron belt, this is the only mode of modeling that can handle the large intensity fluctuations. Anticipating the dynamic modeling objective of the upcoming Combined Release and Radiation Effects Satellite (CRRES) program, we have undertaken to initiate the study of the various essential elements in constructing a dynamic radiation belt model based on interpretation of satellite data according to simultaneous radial and pitch-angle diffusion theory. In order to prepare for the dynamic radiation belt modeling based on a large data set spanning a relatively large segment of L-values, such as required for CRRES, it is important to study a number of test cases with data of similar characteristics but more restricted in space-time coverage. In this way, models of increasing comprehensiveness can be built up from the experience of elucidating the dynamics of more restrictive data sets. The principal objectives of this paper are to discuss issues concerning dynamic modeling in general and to summarize in particular the good results of an initial attempt at constructing the dynamics of the outer electron radiation belt based on a moderately active data period from Lockheed's SC-3 instrument flown on board the SCATHA (P78-2) spacecraft. Further, we shall discuss the issues brought out and lessons learned in this test case

System Dynamics Modeling for Supply Chain Information Sharing

Science.gov (United States)

Feng, Yang

In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.

Incorporating damage mechanics into explosion simulation models

International Nuclear Information System (INIS)

Sammis, C.G.

1993-01-01

The source region of an underground explosion is commonly modeled as a nested series of shells. In the innermost open-quotes hydrodynamic regimeclose quotes pressures and temperatures are sufficiently high that the rock deforms as a fluid and may be described using a PVT equation of state. Just beyond the hydrodynamic regime, is the open-quotes non-linear regimeclose quotes in which the rock has shear strength but the deformation is nonlinear. This regime extends out to the open-quotes elastic radiusclose quotes beyond which the deformation is linear. In this paper, we develop a model for the non-linear regime in crystalline source rock where the nonlinearity is mostly due to fractures. We divide the non-linear regime into a open-quotes damage regimeclose quotes in which the stresses are sufficiently high to nucleate new fractures from preexisting ones and a open-quotes crack-slidingclose quotes regime where motion on preexisting cracks produces amplitude dependent attenuation and other non-linear effects, but no new cracks are nucleated. The boundary between these two regimes is called the open-quotes damage radius.close quotes The micromechanical damage mechanics recently developed by Ashby and Sammis (1990) is used to write an analytic expression for the damage radius in terms of the initial fracture spectrum of the source rock, and to develop an algorithm which may be used to incorporate damage mechanics into computer source models for the damage regime. Effects of water saturation and loading rate are also discussed

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

Science.gov (United States)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

The FFA dynamic stall model. The Beddoes-Leishman dynamic stall model modified for lead-lag oscillations

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden)

1997-08-01

For calculations of the dynamics of wind turbines the inclusion of a dynamic stall model is necessary in order to obtain reliable results at high winds. For blade vibrations in the lead-lag motion the velocity relative to the blade will vary in time. In the present paper modifications to the Beddoes-Leishman model is presented in order to improve the model for calculations of cases with a varying relative velocity. Comparisons with measurement are also shown and the influence on the calculated aerodynamic damping by the modifications are investigated. (au)

Effect of food microstructure on growth dynamics of Listeria monocytogenes in fish-based model systems.

Science.gov (United States)

Verheyen, Davy; Bolívar, Araceli; Pérez-Rodríguez, Fernando; Baka, Maria; Skåra, Torstein; Van Impe, Jan F

2018-06-01

Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was

Fractional-order in a macroeconomic dynamic model

Science.gov (United States)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

Modeling Dynamic Regulatory Processes in Stroke

Science.gov (United States)

McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

2012-01-01

The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

Dynamic models in research and management of biological invasions.

Science.gov (United States)

Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

2017-07-01

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analytical dynamic modeling of fast trilayer polypyrrole bending actuators

International Nuclear Information System (INIS)

Amiri Moghadam, Amir Ali; Moavenian, Majid; Tahani, Masoud; Torabi, Keivan

2011-01-01

Analytical modeling of conjugated polymer actuators with complicated electro-chemo-mechanical dynamics is an interesting area for research, due to the wide range of applications including biomimetic robots and biomedical devices. Although there have been extensive reports on modeling the electrochemical dynamics of polypyrrole (PPy) bending actuators, mechanical dynamics modeling of the actuators remains unexplored. PPy actuators can operate with low voltage while producing large displacement in comparison to robotic joints, they do not have friction or backlash, but they suffer from some disadvantages such as creep and hysteresis. In this paper, a complete analytical dynamic model for fast trilayer polypyrrole bending actuators has been proposed and named the analytical multi-domain dynamic actuator (AMDDA) model. First an electrical admittance model of the actuator will be obtained based on a distributed RC line; subsequently a proper mechanical dynamic model will be derived, based on Hamilton's principle. The purposed modeling approach will be validated based on recently published experimental results

Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

Science.gov (United States)

Nijland, Linda; Arentze, Theo; Timmermans, Harry

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach.

Energy demand projections based on an uncertain dynamic system modeling approach

International Nuclear Information System (INIS)

Dong, S.

2000-01-01

Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

Multiscale model for pedestrian and infection dynamics during air travel

Science.gov (United States)

Namilae, Sirish; Derjany, Pierrot; Mubayi, Anuj; Scotch, Mathew; Srinivasan, Ashok

2017-05-01

In this paper we develop a multiscale model combining social-force-based pedestrian movement with a population level stochastic infection transmission dynamics framework. The model is then applied to study the infection transmission within airplanes and the transmission of the Ebola virus through casual contacts. Drastic limitations on air-travel during epidemics, such as during the 2014 Ebola outbreak in West Africa, carry considerable economic and human costs. We use the computational model to evaluate the effects of passenger movement within airplanes and air-travel policies on the geospatial spread of infectious diseases. We find that boarding policy by an airline is more critical for infection propagation compared to deplaning policy. Enplaning in two sections resulted in fewer infections than the currently followed strategy with multiple zones. In addition, we found that small commercial airplanes are better than larger ones at reducing the number of new infections in a flight. Aggregated results indicate that passenger movement strategies and airplane size predicted through these network models can have significant impact on an event like the 2014 Ebola epidemic. The methodology developed here is generic and can be readily modified to incorporate the impact from the outbreak of other directly transmitted infectious diseases.

Analysis of in vitro and in vivo function of total knee replacements using dynamic contact models

Science.gov (United States)

Zhao, Dong

Despite the high incidence of osteoarthritis in human knee joint, its causes remain unknown. Total knee replacement (TKR) has been shown clinically to be effective in restoring the knee function. However, wear of ultra-high molecular weight polyethylene has limited the longevity of TKRs. To address these important issues, it is necessary to investigate the in vitro and in vivo function of total knee replacements using dynamic contact models. A multibody dynamic model of an AMTI knee simulator was developed. Incorporating a wear prediction model into the contact model based on elastic foundation theory enables the contact surface to take into account creep and wear during the dynamic simulation. Comparisons of the predicted damage depth, area, and volume lost with worn retrievals from a physical machine were made to validate the model. In vivo tibial force distributions during dynamic and high flexion activities were investigated using the dynamic contact model. In vivo medial and lateral contact forces experienced by a well-aligned instrumented knee implant, as well as upper and lower bounds on contact pressures for a variety of activities were studied. For all activities, the predicted medial and lateral contact forces were insensitive to the selected material model. For this patient, the load split during the mid-stance phase of gait and during stair is more equal than anticipated. The external knee adduction torque has been proposed as a surrogate measure for medial compartment load during gait. However, a direct link between these two quantities has not been demonstrated using in vivo measurement of medial compartment load. In vivo data collected from a subject with an instrumented knee implant were analyzed to evaluate this link. The subject performed five different overground gait motions (normal, fast, slow, wide, and toe out) while instrumented implant, video motion, and ground reaction data were simultaneously collected. The high correlation coefficient

Reservoir resistivity characterization incorporating flow dynamics

KAUST Repository

Arango, Santiago

2016-04-07

Systems and methods for reservoir resistivity characterization are provided, in various aspects, an integrated framework for the estimation of Archie\\'s parameters for a strongly heterogeneous reservoir utilizing the dynamics of the reservoir are provided. The framework can encompass a Bayesian estimation/inversion method for estimating the reservoir parameters, integrating production and time lapse formation conductivity data to achieve a better understanding of the subsurface rock conductivity properties and hence improve water saturation imaging.

Reservoir resistivity characterization incorporating flow dynamics

KAUST Repository

Arango, Santiago; Sun, Shuyu; Hoteit, Ibrahim; Katterbauer, Klemens

2016-01-01

Systems and methods for reservoir resistivity characterization are provided, in various aspects, an integrated framework for the estimation of Archie's parameters for a strongly heterogeneous reservoir utilizing the dynamics of the reservoir are provided. The framework can encompass a Bayesian estimation/inversion method for estimating the reservoir parameters, integrating production and time lapse formation conductivity data to achieve a better understanding of the subsurface rock conductivity properties and hence improve water saturation imaging.

A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)

OpenAIRE

Weber, Michael

2004-01-01

The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...

Incorporating vehicle mix in stimulus-response car-following models

Directory of Open Access Journals (Sweden)

Saidi Siuhi

2016-06-01

Full Text Available The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three sub-models were developed for different pairs of following vehicles including “automobile following automobile,” “automobile following truck,” and “truck following automobile.” The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers' behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Incorporating microbiota data into epidemiologic models: examples from vaginal microbiota research.

Science.gov (United States)

van de Wijgert, Janneke H; Jespers, Vicky

2016-05-01

Next generation sequencing and quantitative polymerase chain reaction technologies are now widely available, and research incorporating these methods is growing exponentially. In the vaginal microbiota (VMB) field, most research to date has been descriptive. The purpose of this article is to provide an overview of different ways in which next generation sequencing and quantitative polymerase chain reaction data can be used to answer clinical epidemiologic research questions using examples from VMB research. We reviewed relevant methodological literature and VMB articles (published between 2008 and 2015) that incorporated these methodologies. VMB data have been analyzed using ecologic methods, methods that compare the presence or relative abundance of individual taxa or community compositions between different groups of women or sampling time points, and methods that first reduce the complexity of the data into a few variables followed by the incorporation of these variables into traditional biostatistical models. To make future VMB research more clinically relevant (such as studying associations between VMB compositions and clinical outcomes and the effects of interventions on the VMB), it is important that these methods are integrated with rigorous epidemiologic methods (such as appropriate study designs, sampling strategies, and adjustment for confounding). Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.

Science.gov (United States)

Palmer, Erika; Wilson, Benedicte

2018-04-01

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.

Quantifying the dynamics of coupled networks of switches and oscillators.

Directory of Open Access Journals (Sweden)

Matthew R Francis

Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.

Automated adaptive inference of phenomenological dynamical models

Science.gov (United States)

Daniels, Bryan

Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

Chaotic Dynamics in Smart Grid and Suppression Scheme via Generalized Fuzzy Hyperbolic Model

Directory of Open Access Journals (Sweden)

Qiuye Sun

2014-01-01

Full Text Available This paper presents a method to control chaotic behavior of a typical Smart Grid based on generalized fuzzy hyperbolic model (GFHM. As more and more distributed generations (DG are incorporated into the Smart Grid, the chaotic behavior occurs increasingly. To verify the behavior, a dynamic model which describes a power system with DG is presented firstly. Then, the simulation result shows that the power system can lead to chaos under certain initial conditions. Based on the universal approximation of GFHM, we confirm that the chaotic behavior could be suppressed by a new controller, which is designed by means of solving a linear matrix inequality (LMI. This approach could make a good application to suppress the chaos in Smart Grid. Finally, a numerical example is given to demonstrate the effectiveness of the proposed chaotic suppression strategy.

Modelling and dynamic simulation of processes with 'MATLAB'. An application of a natural gas installation in a power plant

International Nuclear Information System (INIS)

Gonzalez-Bustamante, J.A.; Sala, J.M.; Lopez-Gonzalez, L.M.; Miguez, J.L.; Flores, I.

2007-01-01

In this paper, it is proposed to incorporate the analysis of the dynamic performance of the process into the design and engineering stage of projects as a means of analysing and resolving this type of problem. The following contributions are made with this objective in mind:(a)The barriers in the way of dynamic analysis are identified. (b)Software tools which make dynamic analysis accessible during the design and engineering phase of the project are proposed. To achieve this goal, modelling and mathematical simulation are used, with the following features: *strict modelling of mass, momentum and energy conservation equations as well as state equations, and *utilisation of the 'Matlab-Simulink' package as the base-software tool. (c)The procedure and tool proposed for dynamic analysis during the design phase should enable these studies to be carried out at a reasonable cost and time for regular industrial projects, and not just for large research projects or nuclear power plants. To complete this paper, we apply our method to a natural gas installation in a power plant. The model is applied to study the transients of a natural gas supply line to a steam-electric power plant. The results of the model have been validated with the actual data on the boiler trip obtained from the distributed control system of a steam-electric power plant

Tuning hardness in calcite by incorporation of amino acids.

Science.gov (United States)

Kim, Yi-Yeoun; Carloni, Joseph D; Demarchi, Beatrice; Sparks, David; Reid, David G; Kunitake, Miki E; Tang, Chiu C; Duer, Melinda J; Freeman, Colin L; Pokroy, Boaz; Penkman, Kirsty; Harding, John H; Estroff, Lara A; Baker, Shefford P; Meldrum, Fiona C

2016-08-01

Structural biominerals are inorganic/organic composites that exhibit remarkable mechanical properties. However, the structure-property relationships of even the simplest building unit-mineral single crystals containing embedded macromolecules-remain poorly understood. Here, by means of a model biomineral made from calcite single crystals containing glycine (0-7 mol%) or aspartic acid (0-4 mol%), we elucidate the origin of the superior hardness of biogenic calcite. We analysed lattice distortions in these model crystals by using X-ray diffraction and molecular dynamics simulations, and by means of solid-state nuclear magnetic resonance show that the amino acids are incorporated as individual molecules. We also demonstrate that nanoindentation hardness increased with amino acid content, reaching values equivalent to their biogenic counterparts. A dislocation pinning model reveals that the enhanced hardness is determined by the force required to cut covalent bonds in the molecules.

Dynamics of a delayed intraguild predation model with harvesting

Science.gov (United States)

Collera, Juancho A.; Balilo, Aldrin T.

2018-03-01

In [1], a delayed three-species intraguild predation (IGP) model was considered. This particular tri-trophic community module includes a predator and its prey which share a common basal resource for their sustenance [3]. Here, it is assumed that in the absence of predation, the growth of the basal resource follows the delayed logistic equation. Without delay time, the IGP model in [1] reduces to the system considered in [7] where it was shown that IGP may induce chaos even if the functional responses are linear. Meanwhile, in [2] the delayed IGP model in [1] was generalized to include harvesting. Under the assumption that the basal resource has some economic value, a constant harvesting term on the basal resource was incorporated. However, both models in [1] and [2] use the delay time as the main parameter. In this research, we studied the delayed IGP model in [1] with the addition of linear harvesting term on each of the three species. The dynamical behavior of this system is examined using the harvesting rates as main parameter. In particular, we give conditions on the existence, stability, and bifurcations of equilibrium solutions of this system. This allows us to better understand the effects of harvesting in terms of the survival or extinction of one or more species in our system. Numerical simulations are carried out to illustrate our results. In fact, we show that the chaotic behavior in [7] unfolds when the harvesting rate parameter is varied.

Dynamic mapping of conical intersection seams: A general method for incorporating the geometric phase in adiabatic dynamics in polyatomic systems.

Science.gov (United States)

Xie, Changjian; Malbon, Christopher L; Yarkony, David R; Guo, Hua

2017-07-28

The incorporation of the geometric phase in single-state adiabatic dynamics near a conical intersection (CI) seam has so far been restricted to molecular systems with high symmetry or simple model Hamiltonians. This is due to the fact that the ab initio determined derivative coupling (DC) in a multi-dimensional space is not curl-free, thus making its line integral path dependent. In a recent work [C. L. Malbon et al., J. Chem. Phys. 145, 234111 (2016)], we proposed a new and general approach based on an ab initio determined diabatic representation consisting of only two electronic states, in which the DC is completely removable, so that its line integral is path independent in the simply connected domains that exclude the CI seam. Then with the CIs included, the line integral of the single-valued DC can be used to construct the complex geometry-dependent phase needed to exactly eliminate the double-valued character of the real-valued adiabatic electronic wavefunction. This geometry-dependent phase gives rise to a vector potential which, when included in the adiabatic representation, rigorously accounts for the geometric phase in a system with an arbitrary locus of the CI seam and an arbitrary number of internal coordinates. In this work, we demonstrate this approach in a three-dimensional treatment of the tunneling facilitated dissociation of the S 1 state of phenol, which is affected by a C s symmetry allowed but otherwise accidental seam of CI. Here, since the space is three-dimensional rather than two-dimensional, the seam is a curve rather than a point. The nodal structure of the ground state vibronic wavefunction is shown to map out the seam of CI.

Urban eco-efficiency and system dynamics modelling

Energy Technology Data Exchange (ETDEWEB)

Hradil, P., Email: petr.hradil@vtt.fi

2012-06-15

Assessment of urban development is generally based on static models of economic, social or environmental impacts. More advanced dynamic models have been used mostly for prediction of population and employment changes as well as for other macro-economic issues. This feasibility study was arranged to test the potential of system dynamic modelling in assessing eco-efficiency changes during urban development. (orig.)

Incorporating Social Anxiety Into a Model of College Problem Drinking: Replication and Extension

OpenAIRE

Ham, Lindsay S.; Hope, Debra A.

2006-01-01

Although research has found an association between social anxiety and alcohol use in noncollege samples, results have been mixed for college samples. College students face many novel social situations in which they may drink to reduce social anxiety. In the current study, the authors tested a model of college problem drinking, incorporating social anxiety and related psychosocial variables among 228 undergraduate volunteers. According to structural equation modeling (SEM) results, social anxi...

GDP-tubulin incorporation into growing microtubules modulates polymer stability.

Science.gov (United States)

Valiron, Odile; Arnal, Isabelle; Caudron, Nicolas; Job, Didier

2010-06-04

Microtubule growth proceeds through the endwise addition of nucleotide-bound tubulin dimers. The microtubule wall is composed of GDP-tubulin subunits, which are thought to come exclusively from the incorporation of GTP-tubulin complexes at microtubule ends followed by GTP hydrolysis within the polymer. The possibility of a direct GDP-tubulin incorporation into growing polymers is regarded as hardly compatible with recent structural data. Here, we have examined GTP-tubulin and GDP-tubulin incorporation into polymerizing microtubules using a minimal assembly system comprised of nucleotide-bound tubulin dimers, in the absence of free nucleotide. We find that GDP-tubulin complexes can efficiently co-polymerize with GTP-tubulin complexes during microtubule assembly. GDP-tubulin incorporation into microtubules occurs with similar efficiency during bulk microtubule assembly as during microtubule growth from seeds or centrosomes. Microtubules formed from GTP-tubulin/GDP-tubulin mixtures display altered microtubule dynamics, in particular a decreased shrinkage rate, apparently due to intrinsic modifications of the polymer disassembly properties. Thus, although microtubules polymerized from GTP-tubulin/GDP-tubulin mixtures or from homogeneous GTP-tubulin solutions are both composed of GDP-tubulin subunits, they have different dynamic properties, and this may reveal a novel form of microtubule "structural plasticity."

Benchmarking novel approaches for modelling species range dynamics.

Science.gov (United States)

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

2016-08-01

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

Complex networks under dynamic repair model

Science.gov (United States)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Brand Equity Evolution: a System Dynamics Model

Directory of Open Access Journals (Sweden)

Edson Crescitelli

2009-04-01

Full Text Available One of the greatest challenges in brand management lies in monitoring brand equity over time. This paper aimsto present a simulation model able to represent this evolution. The model was drawn on brand equity concepts developed by Aaker and Joachimsthaler (2000, using the system dynamics methodology. The use ofcomputational dynamic models aims to create new sources of information able to sensitize academics and managers alike to the dynamic implications of their brand management. As a result, an easily implementable model was generated, capable of executing continuous scenario simulations by surveying casual relations among the variables that explain brand equity. Moreover, the existence of a number of system modeling tools will allow extensive application of the concepts used in this study in practical situations, both in professional and educational settings

Dynamic hysteretic sensing model of bending-mode Galfenol transducer

International Nuclear Information System (INIS)

Cao, Shuying; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei

2015-01-01

A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device

Dynamic hysteretic sensing model of bending-mode Galfenol transducer

Energy Technology Data Exchange (ETDEWEB)

Cao, Shuying, E-mail: shuying-cao@hebut.edu.cn; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei [Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin 300130 (China)

2015-05-07

A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.

Incorporating ligament laxity in a finite element model for the upper cervical spine.

Science.gov (United States)

Lasswell, Timothy L; Cronin, Duane S; Medley, John B; Rasoulinejad, Parham

2017-11-01

Predicting physiological range of motion (ROM) using a finite element (FE) model of the upper cervical spine requires the incorporation of ligament laxity. The effect of ligament laxity can be observed only on a macro level of joint motion and is lost once ligaments have been dissected and preconditioned for experimental testing. As a result, although ligament laxity values are recognized to exist, specific values are not directly available in the literature for use in FE models. The purpose of the current study is to propose an optimization process that can be used to determine a set of ligament laxity values for upper cervical spine FE models. Furthermore, an FE model that includes ligament laxity is applied, and the resulting ROM values are compared with experimental data for physiological ROM, as well as experimental data for the increase in ROM when a Type II odontoid fracture is introduced. The upper cervical spine FE model was adapted from a 50th percentile male full-body model developed with the Global Human Body Models Consortium (GHBMC). FE modeling was performed in LS-DYNA and LS-OPT (Livermore Software Technology Group) was used for ligament laxity optimization. Ordinate-based curve matching was used to minimize the mean squared error (MSE) between computed load-rotation curves and experimental load-rotation curves under flexion, extension, and axial rotation with pure moment loads from 0 to 3.5 Nm. Lateral bending was excluded from the optimization because the upper cervical spine was considered to be primarily responsible for flexion, extension, and axial rotation. Based on recommendations from the literature, four varying inputs representing laxity in select ligaments were optimized to minimize the MSE. Funding was provided by the Natural Sciences and Engineering Research Council of Canada as well as GHMBC. The present study was funded by the Natural Sciences and Engineering Research Council of Canada to support the work of one graduate student

Nonlinear Dynamic Models in Advanced Life Support

Science.gov (United States)

Jones, Harry

2002-01-01