Incorporating Resilience into Dynamic Social Models
2016-07-20
resiliency, computational modeling, computational social science /systems, modeling and simulation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...system. The relationships between random variables are given as conditional probability rules. BKBs are represented as a directed graph with...and BKB inferencing methods can be found in Santos et al [20]. 4.1. BKB Definition and Inferencing A BKB is a directed , bipartite graph consisting
Incorporating the Hayflick Limit into a model of Telomere Dynamics
Cyrenne, Benoit M
2013-01-01
A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced two-compartment model that incorporates stem cells as progenitors of new cells, imposes the Hayflick Limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected. In addition, qualitatively different results are obtained for the evolution of the total cell population. Last, in comparison to available leukocyte baboon data, this new model is shown to provide a better fit to biological data.
Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model
Barata, Raquel A.; Drewry, Darren
2012-01-01
The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.
Nine challenges in incorporating the dynamics of behaviour in infectious diseases models.
Funk, Sebastian; Bansal, Shweta; Bauch, Chris T; Eames, Ken T D; Edmunds, W John; Galvani, Alison P; Klepac, Petra
2015-03-01
Traditionally, the spread of infectious diseases in human populations has been modelled with static parameters. These parameters, however, can change when individuals change their behaviour. If these changes are themselves influenced by the disease dynamics, there is scope for mechanistic models of behaviour to improve our understanding of this interaction. Here, we present challenges in modelling changes in behaviour relating to disease dynamics, specifically: how to incorporate behavioural changes in models of infectious disease dynamics, how to inform measurement of relevant behaviour to parameterise such models, and how to determine the impact of behavioural changes on observed disease dynamics. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
Global dynamics of a PDE model for aedes aegypti mosquitoe incorporating female sexual preference
Parshad, Rana
2011-01-01
In this paper we study the long time dynamics of a reaction diffusion system, describing the spread of Aedes aegypti mosquitoes, which are the primary cause of dengue infection. The system incorporates a control attempt via the sterile insect technique. The model incorporates female mosquitoes sexual preference for wild males over sterile males. We show global existence of strong solution for the system. We then derive uniform estimates to prove the existence of a global attractor in L-2(Omega), for the system. The attractor is shown to be L-infinity(Omega) regular and posess state of extinction, if the injection of sterile males is large enough. We also provide upper bounds on the Hausdorff and fractal dimensions of the attractor.
A molecular dynamics model of rhodamine-labeled phospholipid incorporated into a lipid bilayer
Kyrychenko, Alexander
2010-01-01
Phospholipids, labeled covalently by a fluorescent dye, are commonly applied in membrane biophysics. In this work, a molecular dynamics model of sulforhodamine attached covalently to a headgroup of 1,2-dipalmitoyl- sn-glycero-3-phosphoethanolamine is developed. It is found that the incorporation of rhodamine-labeled phospholipids into a DPPC bilayer at the low concentration results in small perturbation of the bilayer. In the dye-labeled membrane, the sulforhodamine moiety binds favorably to a polar membrane interface, forming the tilt angle 44° ± 8° to the bilayer normal. The deep location and binding of a bulk sulforhodamine fluorophore lead, therefore, to some 'softening' of the membrane structure.
Bellmore, J. Ryan; Benjamin, Joseph R.; Newsom, Michael; Bountry, Jennifer A.; Dombroski, Daniel
2017-01-01
Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration planning we constructed a model that links river food web dynamics to in-stream physical habitat and riparian vegetation conditions. We present an application of the model to the Methow River, Washington (USA), a location of on-going restoration aimed at recovering salmon. Three restoration strategies were simulated: riparian vegetation restoration, nutrient augmentation via salmon carcass addition, and side-channel reconnection. We also added populations of nonnative aquatic snails and fish to the modeled food web to explore how changes in food web structure mediate responses to restoration. Simulations suggest that side-channel reconnection may be a better strategy than carcass addition and vegetation planting for improving conditions for salmon in this river segment. However, modeled responses were strongly sensitive to changes in the structure of the food web. The addition of nonnative snails and fish modified pathways of energy through the food web, which negated restoration improvements. This finding illustrates that forecasting responses to restoration may require accounting for the structure of food webs, and that changes in this structure—as might be expected with the spread of invasive species—could compromise restoration outcomes. Unlike habitat-based approaches to restoration assessment that focus on the direct effects of physical habitat conditions on single species of interest, our approach dynamically links the success of target organisms to the success of competitors, predators, and prey. By elucidating the direct and indirect pathways by which restoration affects target species
Incorporation of a Wind Generator Model into a Dynamic Power Flow Analysis
Directory of Open Access Journals (Sweden)
Angeles-Camacho C.
2011-07-01
Full Text Available 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 fl ows in transmission lines.
Directory of Open Access Journals (Sweden)
Yanhua Jiang
2014-09-01
Full Text Available This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments.
Turner, Sean; Galelli, Stefano; Wilcox, Karen
2015-04-01
Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating
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
Saksala, Timo
2016-10-01
This paper deals with numerical modelling of rock fracture under dynamic loading. For this end, a combined continuum damage-embedded discontinuity model is applied in finite element modelling of crack propagation in rock. In this model, the strong loading rate sensitivity of rock is captured by the rate-dependent continuum scalar damage model that controls the pre-peak nonlinear hardening part of rock behaviour. The post-peak exponential softening part of the rock behaviour is governed by the embedded displacement discontinuity model describing the mode I, mode II and mixed mode fracture of rock. Rock heterogeneity is incorporated in the present approach by random description of the rock mineral texture based on the Voronoi tessellation. The model performance is demonstrated in numerical examples where the uniaxial tension and compression tests on rock are simulated. Finally, the dynamic three-point bending test of a semicircular disc is simulated in order to show that the model correctly predicts the strain rate-dependent tensile strengths as well as the failure modes of rock in this test. Special emphasis is laid on modelling the loading rate sensitivity of tensile strength of Laurentian granite.
Peace, Angela; Zhao, Yuqin; Loladze, Irakli; Elser, James J; Kuang, Yang
2013-08-01
There has been important progress in understanding ecological dynamics through the development of the theory of ecological stoichiometry. For example, modeling under this framework allows food quality to affect consumer dynamics. While the effects of nutrient deficiency on consumer growth are well understood, recent discoveries in ecological stoichiometry suggest that consumer dynamics are not only affected by insufficient food nutrient content (low phosphorus (P): carbon (C) ratio) but also by excess food nutrient content (high P:C). This phenomenon is known as the stoichiometric knife edge, in which animal growth is reduced not only by food with low P content but also by food with high P content, and needs to be incorporated into mathematical models. Here we present a Lotka-Volterra type model to investigate the growth response of Daphnia to algae of varying P:C ratios capturing the mechanism of the stoichiometric knife edge.
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.
A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming
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Wushan Cheng
2014-12-01
Full Text Available In order to maintain the stability and security of the power system, the uncertainty and intermittency of wind power must be taken into account in economic dispatch (ED problems. In this paper, a dynamic economic dispatch (DED model based on chance constrained programming is presented and an improved particle swarm optimization (PSO approach is proposed to solve the problem. Wind power is regarded as a random variable and is included in the chance constraint. New formulation of up and down spinning reserve constraints are presented under expectation meaning. The improved PSO algorithm combines a feasible region adjustment strategy with a hill climbing search operation based on the basic PSO. Simulations are performed under three distinct test systems with different generators. Results show that both the proposed DED model and the improved PSO approach are effective.
Carli, S.; Bonifetto, R.; Savoldi, L.; Zanino, R.
2015-09-01
A model based on Artificial Neural Networks (ANNs) is developed for the heated line portion of a cryogenic circuit, where supercritical helium (SHe) flows and that also includes a cold circulator, valves, pipes/cryolines and heat exchangers between the main loop and a saturated liquid helium (LHe) bath. The heated line mimics the heat load coming from the superconducting magnets to their cryogenic cooling circuits during the operation of a tokamak fusion reactor. An ANN is trained, using the output from simulations of the circuit performed with the 4C thermal-hydraulic (TH) code, to reproduce the dynamic behavior of the heated line, including for the first time also scenarios where different types of controls act on the circuit. The ANN is then implemented in the 4C circuit model as a new component, which substitutes the original 4C heated line model. For different operational scenarios and control strategies, a good agreement is shown between the simplified ANN model results and the original 4C results, as well as with experimental data from the HELIOS facility confirming the suitability of this new approach which, extended to an entire magnet systems, can lead to real-time control of the cooling loops and fast assessment of control strategies for heat load smoothing to the cryoplant.
J. Ryan Bellmore; Joseph R. Benjamin; Michael Newsom; Jennifer A. Bountry; Daniel Dombroski
2017-01-01
Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration...
Baartman, Jantiene E. M.; van Gorp, Wouter; Temme, Arnaud J. A. M.; Schoorl, Jeroen M.
2012-01-01
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 timescale
Institute of Scientific and Technical Information of China (English)
QIN Peihua; XIE Zhenghui; YUAN Xing
2013-01-01
To improve the capability of numerical modeling of climate-groundwater interactions,a groundwater component and new surface/subsurface runoff schemes were incorporated into the regional climate model RegCM3,renamed RegCM3_Hydro.20-year simulations from both models were used to investigate the effects of groundwater dynamics and surface/subsurface runoff parameterizations on regional climate over seven river basins in China.A comparison of results shows that RegCM3_Hydro reduced the positive biases of annual and summer (June,July,August) precipitation over six river basins,while it slightly increased the bias over the Huaihe River Basin in eastern China.RegCM3_Hydro also reduced the cold bias of surface air temperature from RegCM3 across years,especially for the Haihe and the Huaihe river basins,with significant bias reductions of 0.80℃ and 0.88℃,respectively.The spatial distribution and seasonal variations of water table depth were also well captured.With the new surface and subsurface runoff schemes,RegCM3_Hydro increased annual surface runoff by 0.11-0.62 mm d-1 over the seven basins.Though previous studies found that incorporating a groundwater component tends to increase soil moisture due to the consideration of upward groundwater recharge,our present work shows that the modified runoff schemes cause less infiltration,which outweigh the recharge from groundwater and result in drier soil,and consequently cause less latent heat and more sensible heat over most of the basins.
INCORPORATING DYNAMIC 3D SIMULATION INTO PRA
Energy Technology Data Exchange (ETDEWEB)
Steven R Prescott; Curtis Smith
2011-07-01
provide superior results and insights. We also couple the state model with the dynamic 3D simulation analysis representing events (such as flooding) to determine which (if any) components fail. Not only does the simulation take into account any failed items from the state model, but any failures caused by the simulation are incorporated back into the state model and factored into the overall results. Using this method we incorporate accurate 3D simulation results, eliminate static-based PRA issues, and have time ordered failure information.
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.
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Anastasia Gribik; Doona Guillen, PhD; Daniel Ginosar, PhD
2008-09-01
Currently multi-tubular fixed bed reactors, fluidized bed reactors, and slurry bubble column reactors (SBCRs) are used in commercial Fischer Tropsch (FT) synthesis. There are a number of advantages of the SBCR compared to fixed and fluidized bed reactors. The main advantage of the SBCR is that temperature control and heat recovery are more easily achieved. The SBCR is a multiphase chemical reactor where a synthesis gas, comprised mainly of H2 and CO, is bubbled through a liquid hydrocarbon wax containing solid catalyst particles to produce specialty chemicals, lubricants, or fuels. The FT synthesis reaction is the polymerization of methylene groups [-(CH2)-] forming mainly linear alkanes and alkenes, ranging from methane to high molecular weight waxes. The Idaho National Laboratory is developing a computational multiphase fluid dynamics (CMFD) model of the FT process in a SBCR. This paper discusses the incorporation of absorption and reaction kinetics into the current hydrodynamic model. A phased approach for incorporation of the reaction kinetics into a CMFD model is presented here. Initially, a simple kinetic model is coupled to the hydrodynamic model, with increasing levels of complexity added in stages. The first phase of the model includes incorporation of the absorption of gas species from both large and small bubbles into the bulk liquid phase. The driving force for the gas across the gas liquid interface into the bulk liquid is dependent upon the interfacial gas concentration in both small and large bubbles. However, because it is difficult to measure the concentration at the gas-liquid interface, coefficients for convective mass transfer have been developed for the overall driving force between the bulk concentrations in the gas and liquid phases. It is assumed that there are no temperature effects from mass transfer of the gas phases to the bulk liquid phase, since there are only small amounts of dissolved gas in the liquid phase. The product from the
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Lewellen, W.S.; Sykes, R.I.; Parker, S.F.; Henn, D.S.; Seaman, N.L.; Stauffer, D.R.; Warner, T.T.
1989-02-01
An existing mesoscale model (the Penn State University/National Center for Atmospheric Research mesoscale model) was extended for use with a PUFF-type plume model. By including a fine-mesh 2 km nested-grid and the assimilation of 4-dimensional data, horizontally variable hourly-average meteorological conditions can be simulated up to 300 km downwind of stack emissions in complex terrain. In 4 days of tests (32 90-minute periods) against meteorological observations obtained in moderately complex terrain, wind-speed uncertainties are usually less than 3.3 m/s, and direction errors are less than 40/degree/ for winds less than 1 m/s. The performance of this model was also compared on 3 days (20 hours) with a locally homogeneous meteorological data assimilation model when both were coupled to a new second order closure integrated puff model (SCIPUFF). Use of the new mesoscale model slightly reduced the deviations between simulated and observed concentrations of SF/sub 6/ tracer, even within 50 km. At distances longer than 50 km (not tested) it is expected that use of the mesoscale model would further improve dispersion simulations. 8 refs., 26 figs., 6 tabs.
Incorporation, plurality, and the incorporation of plurals: a dynamic approach
de Swart, H.E.; Farkas, D. F.
2004-01-01
This paper deals with the semantic properties of incorporated nominals that are present at clausal syntax. Such nominals exhibit a complex cluster of semantic properties, ranging from argument structure, scope, and number to discourse transparency. We develop an analysis of incorporation in the fram
Carotenoid incorporation into microsomes: yields, stability and membrane dynamics
Socaciu, Carmen; Jessel, Robert; Diehl, Horst A.
2000-12-01
The carotenoids β-carotene (BC), lycopene (LYC), lutein (LUT), zeaxanthin (ZEA), canthaxanthin (CTX) and astaxanthin (ASTA) have been incorporated into pig liver microsomes. Effective incorporation concentrations in the range of about 1-6 nmol/mg microsomal protein were obtained. A stability test at room temperature revealed that after 3 h BC and LYC had decayed totally whereas, gradually, CTX (46%), LUT (21%), ASTA (17%) and ZEA (5%) decayed. Biophysical parameters of the microsomal membrane were changed hardly by the incorporation of carotenoids. A small rigidification may occur. Membrane anisotropy seems to offer only a small tolerance for incorporation of carotenoids and seems to limit the achievable incorporation concentrations of the carotenoids into microsomes. Microsomes instead of liposomes should be preferred as a membrane model to study mutual effects of carotenoids and membrane dynamics.
Benedetti, Lorenzo; Belia, Evangelina; Cierkens, Katrijn; Flameling, Tony; De Baets, Bernard; Nopens, Ingmar; Weijers, Stefan
2013-01-01
This paper illustrates how a dynamic model can be used to evaluate a plant upgrade on the basis of post-upgrade performance data. The case study is that of the Eindhoven wastewater treatment plant upgrade completed in 2006. As a first step, the design process based on a static model was thoroughly analyzed and the choices regarding variability and uncertainty (i.e. safety factors) were made explicit. This involved the interpretation of the design guidelines and other assumptions made by the engineers. As a second step, a (calibrated) dynamic model of the plant was set up, able to reproduce the anticipated variability (duration and frequency). The third step was to define probability density functions for the parameters assumed to be uncertain, and propagate that uncertainty with the dynamic model by means of Monte Carlo simulations. The last step was the statistical evaluation and interpretation of the simulation results. This work should be regarded as a 'learning exercise' increasing the understanding of how and to what extent variability and uncertainty are currently incorporated in design guidelines used in practice and how model-based post-project appraisals could be performed.
Keivani, Maryam; Koochi, Ali; Kanani, Abolfazl; Abadyan, Mohamadreza
2016-05-01
Nanoscale beams might not be considered uniform isotropic since the energy of the surface layer and microstructure of the bulk material highly affect the mechanical characteristics of the beams. Herein, the simultaneous effects of energy of the surface and microstructure of the bulk on the dynamic response and stability of beam-type electromechanical nanocantilevers are investigated. A bilayer model has been developed which incorporates the strain energy of the surface atoms as well as the microstructure-dependent strain energy of the bulk. The Gurtin-Murdoch surface elasticity in conjunction with the modified couple stress theory (MCST) is applied to derive the governing equation. Since the classical assumption for zero normal surface stresses is not consistent with the surface equilibrium assumption in Gurtin-Murdoch elasticity, the presence of normal surface stresses is incorporated. The von Karman nonlinear strain is employed to derive the governing equation. The presence of gas rarefaction at various Knudsen numbers is considered as well as the edge effect on the distribution of Coulomb and dispersion forces. The mode shapes of the nanobeam are determined as a function of the surface and microstructure parameter and the nonlinear governing equation is solved using Galerkin method. The dynamic response, phase plane and stability threshold of the nanocantilever are discussed.
Energy Technology Data Exchange (ETDEWEB)
Sykes, R.I.; Lewellen, W.S.; Parker, S.F.; Henn, D.S.
1989-01-01
The Second Order Closure Integrated Puff Model (SCIPUFF) is the intermediate resolution member of a hierarchy of models. It simulates the expected values of plume concentration downwind of a fossil-fueled power plant stack, along with an estimate of the variation around this value. To represent the turbulent atmosphere surrounding the plume compatibly with available meteorological data, a second order closure sub-model is used. SCIPUFF represents the plume by a series of Gaussian puffs, typically 10 seconds apart; plume growth is calculated by a random walk phase combined with plume expansion calculated from the volume integrals of the equations used in the Stack Exhaust Model (SEM), the highest resolution model. Meteorological uncertainty is accounted for by means of extra dispersion terms. SCIPUFF was tested against more than 250 hours of plume data including both a level site and a moderately complex terrain site; approximately 200 samplers were used. Model predictions were evaluated by comparing the measured ground level concentration distribution to that simulated by the model. Further, the simulated and actual distributions of deviations between simulated or observed and expected values were compared. The predicted distributions were close to the measured ones. The overall results from SCIPUFF were similar to those from the lowest resolution model, SCIMP. The advantage of SCIPUFF is its flexibility for including future improvements. When combined with a suitable mesoscale model, SCIPUFF may be able to simulate plume dispersion beyond the 50 km limit of other available models. The ability to cover a wide range of time and space scales in a single calculation is another valuable feature. 3 refs., 10 figs., 4 tabs.
Motional displacements in proteins incorporating dynamical diversity
Vural, Derya; Smith, Jeremy; Glyde, Henry
The average mean square displacement (MSD), , of hydrogen H in proteins is measured using incoherent neutron scattering methods. The observed MSD shows a marked increase in magnitude at a temperature TD ~= 240 K. This is widely interpreted as a dynamical transition to large MSDs which make function possible in proteins. However, when the data is interpreted in terms of a single averaged MSD, the extracted depends on the neutron momentum transfer, ℏQ , used in the measurement. We have shown recently that this apparent dependence on Q arises because the dynamical diversity of the H in the protein is neglected[2]. We present models of the dynamical diversity of H in Lysosyme that when used in the analysis of simulated neutron data lead to consistent, Q independent values for the average MSD and for the diversity model.2. D. Vural and L. Hong, J. C. Smith and H. R. Glyde. Phys. Rev. E 91, 052705 (2015). Supported in part by Office of Basic Energy Sciences, USDOE, ER46680.
Hati, Sanchita; Bhattacharyya, Sudeep
2016-01-01
A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and…
Dynamic analyses of viscoelastic dielectric elastomers incorporating viscous damping effect
Zhang, Junshi; Zhao, Jianwen; Chen, Hualing; Li, Dichen
2017-01-01
In this paper, based on the standard linear solid rheological model, a dynamics model of viscoelastic dielectric elastomers (DEs) is developed with incorporation of viscous damping effect. Numerical calculations are employed to predict the damping effect on the dynamic performance of DEs. With increase of damping force, the DEs show weak nonlinearity and vibration strength. Phase diagrams and Poincaré maps are utilized to detect the dynamic stability of DEs, and the results indicate that a transition from aperiodic vibration to quasi-periodic vibration occurs with enlargement of damping force. The resonance properties of DEs including damping effect are subsequently analyzed, demonstrating a reduction of resonant frequency and resonance peak with increase of damping force.
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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
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
Incorporating phenology into yield models
Gray, J. M.; Friedl, M. A.
2015-12-01
Because the yields of many crops are sensitive to meteorological forcing during specific growth stages, phenological information has potential utility in yield mapping and forecasting exercises. However, most attempts to explain the spatiotemporal variability in crop yields with weather data have relied on growth stage definitions that do not change from year-to-year, even though planting, maturity, and harvesting dates show significant interannual variability. We tested the hypothesis that quantifying temperature exposures over dynamically determined growth stages would better explain observed spatiotemporal variability in crop yields than statically defined time periods. Specifically, we used National Agricultural and Statistics Service (NASS) crop progress data to identify the timing of the start of the maize reproductive growth stage ("silking"), and examined the correlation between county-scale yield anomalies and temperature exposures during either the annual or long-term average silking period. Consistent with our hypothesis and physical understanding, yield anomalies were more correlated with temperature exposures during the actual, rather than the long-term average, silking period. Nevertheless, temperature exposures alone explained a relatively low proportion of the yield variability, indicating that other factors and/or time periods are also important. We next investigated the potential of using remotely sensed land surface phenology instead of NASS progress data to retrieve crop growth stages, but encountered challenges related to crop type mapping and subpixel crop heterogeneity. Here, we discuss the potential of overcoming these challenges and the general utility of remotely sensed land surface phenology in crop yield mapping.
Incorporating groundwater flow into the WEPP model
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...
Reservoir resistivity characterization incorporating flow dynamics
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.
Ultrastrong optomechanics incorporating the dynamical Casimir effect
Nation, P. D.; Suh, J.; Blencowe, M. P.
2016-02-01
We propose a superconducting circuit comprising a dc superconducting quantum interference device with a mechanically compliant arm embedded in a coplanar microwave cavity that realizes an optomechanical system with a degenerate or nondegenerate parametric interaction generated via the dynamical Casimir effect. For experimentally feasible parameters, this setup is capable of reaching the single-photon ultrastrong-coupling regime while simultaneously possessing a parametric coupling strength approaching the renormalized cavity frequency. This opens up the possibility of observing the interplay between these two fundamental nonlinearities at the single-photon level.
Incorporating vegetation feedbacks in regional climate modeling over West Africa
Erfanian, A.; Wang, G.; Yu, M.; Ahmed, K. F.; Anyah, R. O.
2015-12-01
Despite major advancements in modeling of the climate system, incorporating vegetation dynamics into climate models is still at the initial stages making it an ongoing research topic. Only few of GCMs participating in CMIP5 simulations included the vegetation dynamics component. Consideration for vegetation dynamics is even less common in RCMs. In this study, RegCM4.3.4-CLM4-CN-DV, a regional climate model synchronously coupled with a land surface component that includes both Carbon-Nitrogen (CN) and Dynamic-Vegetation (DV) processes is used to simulate and project regional climate over West Africa. Due to its unique regional features, West Africa climate is known for being susceptible to land-atmosphere interactions, enhancing the importance of including vegetation dynamics in modeling climate over this region. In this study the model is integrated for two scenarios (present-day and future) using outputs from four GCMs participating in CMIP5 (MIROC, CESM, GFDL and CCSM4) as lateral boundary conditions, which form the basis of a multi-model ensemble. Results of model validation indicates that ensemble of all models outperforms each of individual models in simulating present-day temperature and precipitation. Therefore, the ensemble set is used to analyze the impact of including vegetation dynamics in the RCM on future projection of West Africa's climate. Results from the ensemble analysis will be presented, together with comparison among individual models.
Armbruster, Benjamin
2011-01-01
We analyze random networks that change over time. First we analyze a dynamic Erdos-Renyi model, whose edges change over time. We describe its stationary distribution, its convergence thereto, and the SI contact process on the network, which has relevance for connectivity and the spread of infections. Second, we analyze the effect of node turnover, when nodes enter and leave the network, which has relevance for network models incorporating births, deaths, aging, and other demographic factors.
Incorporating immigrant flows into microsimulation models.
Duleep, Harriet Orcutt; Dowhan, Daniel J
2008-01-01
Building on the research on immigrant earnings reviewed in the first article of this series, "Research on Immigrant Earnings," the preceding article, "Adding Immigrants to Microsimulation Models," linked research results to various issues essential for incorporating immigrant earnings into microsimulation models. The discussions of that article were in terms of a closed system. That is, it examined a system in which immigrant earnings and emigration are forecast for a given population represented in the base sample in the microsimulation model. This article, the last in the series, addresses immigrant earnings projections for open systems--microsimulation models that include projections of future immigration. The article suggests a simple method to project future immigrants and their earnings. Including the future flow of immigrants in microsimulation models can dramatically affect the projected Social Security benefits of some groups.
Incorporating neurophysiological concepts in mathematical thermoregulation models
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 temperature. This study shows that (1) thermal reception and neurophysiological pathways involved in thermoregulatory SBF control can be captured in a mathematical model, and (2) 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 RAM techniques into simulation modeling
Energy Technology Data Exchange (ETDEWEB)
Nelson, S.C. Jr.; Haire, M.J.; Schryver, J.C.
1995-07-01
This work concludes that reliability, availability, and maintainability (RAM) analytical techniques can be incorporated into computer network simulation modeling to yield an important new analytical tool. This paper describes the incorporation of failure and repair information into network simulation to build a stochastic computer model represents the RAM Performance of two vehicles being developed for the US Army: The Advanced Field Artillery System (AFAS) and the Future Armored Resupply Vehicle (FARV). The AFAS is the US Army`s next generation self-propelled cannon artillery system. The FARV is a resupply vehicle for the AFAS. Both vehicles utilize automation technologies to improve the operational performance of the vehicles and reduce manpower. The network simulation model used in this work is task based. The model programmed in this application requirements a typical battle mission and the failures and repairs that occur during that battle. Each task that the FARV performs--upload, travel to the AFAS, refuel, perform tactical/survivability moves, return to logistic resupply, etc.--is modeled. Such a model reproduces a model reproduces operational phenomena (e.g., failures and repairs) that are likely to occur in actual performance. Simulation tasks are modeled as discrete chronological steps; after the completion of each task decisions are programmed that determine the next path to be followed. The result is a complex logic diagram or network. The network simulation model is developed within a hierarchy of vehicle systems, subsystems, and equipment and includes failure management subnetworks. RAM information and other performance measures are collected which have impact on design requirements. Design changes are evaluated through ``what if`` questions, sensitivity studies, and battle scenario changes.
Incorporating territory compression into population models
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
Nevo, Ofra; Wiseman, Hadas
2002-01-01
The Developmental Career Counseling model incorporates the following principles of Short-Term Dynamic Psychotherapy: life-span approach, limited time, working alliance, rapid and early assessment, central focus, active and directive counselor participation, therapeutic flexibility, and termination issues. The model enables career and personal…
Incorporating evolutionary processes into population viability models.
Pierson, Jennifer C; Beissinger, Steven R; Bragg, Jason G; Coates, David J; Oostermeijer, J Gerard B; Sunnucks, Paul; Schumaker, Nathan H; Trotter, Meredith V; Young, Andrew G
2015-06-01
We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco-evo PVA using individual-based models with individual-level genotype tracking and dynamic genotype-phenotype mapping to model emergent population-level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco-evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.
Incorporating infiltration modelling in urban flood management
Directory of Open Access Journals (Sweden)
A. S. Jumadar
2008-06-01
Full Text Available Increasing frequency and intensity of flood events in urban areas can be linked to increase in impervious area due to urbanization, exacerbated by climate change. The established approach of conveying storm water by conventional drainage systems has contributed to magnification of runoff volume and peak flows beyond those of undeveloped catchments. Furthermore, the continuous upgrading of such conventional systems is costly and unsustainable in the long term. Sustainable drainage systems aim at addressing the adverse effects associated with conventional systems, by mimicking the natural drainage processes, encouraging infiltration and storage of storm water. In this study we model one of the key components of SuDS, the infiltration basins, in order to assert the benefits of the approach. Infiltration modelling was incorporated in the detention storage unit within the one-dimensional urban storm water management model, EPA-SWMM 5.0. By introduction of infiltration modelling in the storage, the flow attenuation performance of the unit was considerably improved. The study also examines the catchment scale impact of both source and regional control storage/infiltration systems. Based on the findings of two case study areas modelled with the proposed options, it was observed that source control systems have a greater and much more natural impact at a catchment level, with respect to flow attenuation, compared to regional control systems of which capacity is equivalent to the sum of source control capacity at the catchment.
Incorporation of salinity in Water Availability Modeling
Wurbs, Ralph A.; Lee, Chihun
2011-10-01
SummaryNatural salt pollution from geologic formations in the upper watersheds of several large river basins in the Southwestern United States severely constrains the use of otherwise available major water supply sources. The Water Rights Analysis Package modeling system has been routinely applied in Texas since the late 1990s in regional and statewide planning studies and administration of the state's water rights permit system, but without consideration of water quality. The modeling system was recently expanded to incorporate salinity considerations in assessments of river/reservoir system capabilities for supplying water for environmental, municipal, agricultural, and industrial needs. Salinity loads and concentrations are tracked through systems of river reaches and reservoirs to develop concentration frequency statistics that augment flow frequency and water supply reliability metrics at pertinent locations for alternative water management strategies. Flexible generalized capabilities are developed for using limited observed salinity data to model highly variable concentrations imposed upon complex river regulation infrastructure and institutional water allocation/management practices.
Incorporation of Mach's Principle in ΛFRW Cosmology that depends dynamically of the distance range
Falcon, N.
2017-07-01
It postulates a FRW cosmological model without dark matter and cosmological term depending the distance scale, in addition to incorporate Mach's principle, is consistent with the observations: rotation curves of the galaxies, the nucleosynthesis primordial and CMB. The dynamic expression of Cosmological term is an alternative to non-baryonic dark matter and a reinterpretation of dark energy.
A Financial Market Model Incorporating Herd Behaviour.
Wray, Christopher M; Bishop, Steven R
2016-01-01
Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market
Modal aerosol dynamics modeling
Energy Technology Data Exchange (ETDEWEB)
Whitby, E.R.; McMurry, P.H.; Shankar, U.; Binkowski, F.S.
1991-02-01
The report presents the governing equations for representing aerosol dynamics, based on several different representations of the aerosol size distribution. Analytical and numerical solution techniques for these governing equations are also reviewed. Described in detail is a computationally efficient numerical technique for simulating aerosol behavior in systems undergoing simultaneous heat transfer, fluid flow, and mass transfer in and between the gas and condensed phases. The technique belongs to a general class of models known as modal aerosol dynamics (MAD) models. These models solve for the temporal and spatial evolution of the particle size distribution function. Computational efficiency is achieved by representing the complete aerosol population as a sum of additive overlapping populations (modes), and solving for the time rate of change of integral moments of each mode. Applications of MAD models for simulating aerosol dynamics in continuous stirred tank aerosol reactors and flow aerosol reactors are provided. For the application to flow aerosol reactors, the discussion is developed in terms of considerations for merging a MAD model with the SIMPLER routine described by Patankar (1980). Considerations for incorporating a MAD model into the U.S. Environmental Protection Agency's Regional Particulate Model are also described. Numerical and analytical techniques for evaluating the size-space integrals of the modal dynamics equations (MDEs) are described. For multimodal logonormal distributions, an analytical expression for the coagulation integrals of the MDEs, applicable for all size regimes, is derived, and is within 20% of accurate numerical evaluation of the same moment coagulation integrals. A computationally efficient integration technique, based on Gauss-Hermite numerical integration, is also derived.
Bauer, Brad A; Warren, G Lee; Patel, Sandeep
2009-02-10
We discuss a new classical water force field that explicitly accounts for differences in polarizability between liquid and vapor phases. The TIP4P-QDP (4-point transferable intermolecular potential with charge dependent-polarizability) force field is a modification of the original TIP4P-FQ fluctuating charge water force field of Rick et al.(1) that self-consistently adjusts its atomic hardness parameters via a scaling function dependent on the M-site charge. The electronegativity (χ) parameters are also scaled in order to reproduce condensed-phase dipole moments of comparable magnitude to TIP4P-FQ. TIP4P-QDP is parameterized to reproduce experimental gas-phase and select condensed-phase properties. The TIP4P-QDP water model possesses a gas phase polarizability of 1.40 Å(3) and gas-phase dipole moment of 1.85 Debye, in excellent agreement with experiment and high-level ab initio predictions. The liquid density of TIP4P-QDP is 0.9954(±0.0002) g/cm(3) at 298 K and 1 atmosphere, and the enthalpy of vaporization is 10.55(±0.12) kcal/mol. Other condensed-phase properties such as the isobaric heat capacity, isothermal compressibility, and diffusion constant are also calculated within reasonable accuracy of experiment and consistent with predictions of other current state-of-the-art water force fields. The average molecular dipole moment of TIP4P-QDP in the condensed phase is 2.641(±0.001) Debye, approximately 0.02 Debye higher than TIP4P-FQ and within the range of values currently surmised for the bulk liquid. The dielectric constant, ε = 85.8 ± 1.0, is 10% higher than experiment. This is reasoned to be due to the increase in the condensed phase dipole moment over TIP4P-FQ, which estimates ε remarkably well. Radial distribution functions for TIP4P-QDP and TIP4P-FQ show similar features, with TIP4P-QDP showing slightly reduced peak heights and subtle shifts towards larger distance interactions. Since the greatest effects of the phase-dependent polarizability are
Incorporating direct marketing activity into latent attrition models
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 evolutionary processes into population viability models
Pierson, J.C.; Beissinger, S.R.; Bragg, J.G.; Coates, D.J.; Oostermeijer, J.G.B.; Sunnucks, P.; Schumaker, N.H.; Trotter, M.V.; Young, A.G.
2015-01-01
We examined how ecological and evolutionary (eco-evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco-evo PVA to offer powerful new approaches to understand
A dengue model incorporating saturation incidence and human migration
Gakkhar, S.; Mishra, A.
2015-03-01
In this paper, a non-linear model has been proposed to investigate the effects of human migration on dengue dynamics. Human migration has been considered between two patches having different dengue strains. Due to migration secondary infection is possible. Further, the secondary infection is considered in patch-2 only as strain-2 in patch-2 is considered to be more severe than that of strain-1 in patch-1. The saturation incidence rate has been considered to incorporate the behavioral changes towards epidemic in human population. The basic reproduction number has been computed. Four Equilibrium states have been found and analyzed. Increasing saturation rate decreases the threshold thereby enhancing the stability of disease-free state in both the patches. Control on migration may lead to change in infection level of patches.
Multiplicative earthquake likelihood models incorporating strain rates
Rhoades, D. A.; Christophersen, A.; Gerstenberger, M. C.
2017-01-01
SUMMARYWe examine the potential for strain-rate variables to improve long-term earthquake likelihood models. We derive a set of multiplicative hybrid earthquake likelihood models in which cell rates in a spatially uniform baseline model are scaled using combinations of covariates derived from earthquake catalogue data, fault data, and strain-rates for the New Zealand region. Three components of the strain rate estimated from GPS data over the period 1991-2011 are considered: the shear, rotational and dilatational strain rates. The hybrid model parameters are optimised for earthquakes of M 5 and greater over the period 1987-2006 and tested on earthquakes from the period 2012-2015, which is independent of the strain rate estimates. The shear strain rate is overall the most informative individual covariate, as indicated by Molchan error diagrams as well as multiplicative modelling. Most models including strain rates are significantly more informative than the best models excluding strain rates in both the fitting and testing period. A hybrid that combines the shear and dilatational strain rates with a smoothed seismicity covariate is the most informative model in the fitting period, and a simpler model without the dilatational strain rate is the most informative in the testing period. These results have implications for probabilistic seismic hazard analysis and can be used to improve the background model component of medium-term and short-term earthquake forecasting models.
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
Tantalum strength model incorporating temperature, strain rate and pressure
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.
Characteristic dynamics near two coalescing eigenvalues incorporating continuum threshold effects
Garmon, Savannah; Ordonez, Gonzalo
2017-06-01
It has been reported in the literature that the survival probability P(t) near an exceptional point where two eigenstates coalesce should generally exhibit an evolution P (t ) ˜t2e-Γ t, in which Γ is the decay rate of the coalesced eigenstate; this has been verified in a microwave billiard experiment [B. Dietz et al., Phys. Rev. E 75, 027201 (2007)]. However, the heuristic effective Hamiltonian that is usually employed to obtain this result ignores the possible influence of the continuum threshold on the dynamics. By contrast, in this work we employ an analytical approach starting from the microscopic Hamiltonian representing two simple models in order to show that the continuum threshold has a strong influence on the dynamics near exceptional points in a variety of circumstances. To report our results, we divide the exceptional points in Hermitian open quantum systems into two cases: at an EP2A two virtual bound states coalesce before forming a resonance, anti-resonance pair with complex conjugate eigenvalues, while at an EP2B two resonances coalesce before forming two different resonances. For the EP2B, which is the case studied in the microwave billiard experiment, we verify that the survival probability exhibits the previously reported modified exponential decay on intermediate time scales, but this is replaced with an inverse power law on very long time scales. Meanwhile, for the EP2A the influence from the continuum threshold is so strong that the evolution is non-exponential on all time scales and the heuristic approach fails completely. When the EP2A appears very near the threshold, we obtain the novel evolution P (t ) ˜1 -C1√{t } on intermediate time scales, while further away the parabolic decay (Zeno dynamics) on short time scales is enhanced.
Incorporating 3-dimensional models in online articles
Cevidanes, Lucia H. S.; Ruellasa, Antonio C. O.; Jomier, Julien; Nguyen, Tung; Pieper, Steve; Budin, Francois; Styner, Martin; Paniagua, Beatriz
2015-01-01
Introduction The aims of this article were to introduce the capability to view and interact with 3-dimensional (3D) surface models in online publications, and to describe how to prepare surface models for such online 3D visualizations. Methods Three-dimensional image analysis methods include image acquisition, construction of surface models, registration in a common coordinate system, visualization of overlays, and quantification of changes. Cone-beam computed tomography scans were acquired as volumetric images that can be visualized as 3D projected images or used to construct polygonal meshes or surfaces of specific anatomic structures of interest. The anatomic structures of interest in the scans can be labeled with color (3D volumetric label maps), and then the scans are registered in a common coordinate system using a target region as the reference. The registered 3D volumetric label maps can be saved in .obj, .ply, .stl, or .vtk file formats and used for overlays, quantification of differences in each of the 3 planes of space, or color-coded graphic displays of 3D surface distances. Results All registered 3D surface models in this study were saved in .vtk file format and loaded in the Elsevier 3D viewer. In this study, we describe possible ways to visualize the surface models constructed from cone-beam computed tomography images using 2D and 3D figures. The 3D surface models are available in the article’s online version for viewing and downloading using the reader’s software of choice. These 3D graphic displays are represented in the print version as 2D snapshots. Overlays and color-coded distance maps can be displayed using the reader’s software of choice, allowing graphic assessment of the location and direction of changes or morphologic differences relative to the structure of reference. The interpretation of 3D overlays and quantitative color-coded maps requires basic knowledge of 3D image analysis. Conclusions When submitting manuscripts, authors can
Incorporating POS Tagging into Language Modeling
Heeman, P A; Heeman, Peter A.; Allen, James F.
1997-01-01
Language models for speech recognition tend to concentrate solely on recognizing the words that were spoken. In this paper, we redefine the speech recognition problem so that its goal is to find both the best sequence of words and their syntactic role (part-of-speech) in the utterance. This is a necessary first step towards tightening the interaction between speech recognition and natural language understanding.
Incorporating Phaeocystis into a Southern Ocean ecosystem model
Wang, Shanlin; Moore, J. Keith
2011-01-01
Phaeocystis antarctica is an important phytoplankton species in the Southern Ocean. We incorporated P. antarctica into the biogeochemical elemental cycling ocean model to study Southern Ocean ecosystem dynamics and biogeochemistry. The optimum values of ecological parameters for Phaeocystis were sought through synthesizing laboratory and field observations, and the model output was evaluated with observed chlorophyll a, carbon biomass, and nutrient distributions. Several factors have been proposed to control Southern Ocean ecosystem structure, including light adaptation, iron uptake capability, and loss processes. Optimum simulation results were obtained when P. antarctica had a relatively high α (P-I curve initial slope) value and a higher half-saturation constant for iron uptake than other phytoplankton. Simulation results suggested that P. antarctica had a competitive advantage under low irradiance levels, especially in the Ross Sea and Weddell Sea. However, the distributions of P. antarctica and diatoms were also strongly influenced by iron availability. Although grazing rates had an influence on total biomass, our simulations did not show a strong influence of grazing pressure in the competition between P. antarctica and diatoms. However, limited observations and the relative simplicity of zooplankton in our model suggest further research is needed. Overall, P. antarctica contributed ˜13% of annual primary production and ˜19% of sinking carbon export in the Southern Ocean (>40°S) in our best case simulation. At higher latitudes (>60°S) P. antarctica accounts for ˜23% of annual primary production and ˜30% of sinking carbon export.
Incorporating Context Dependency of Species Interactions in Species Distribution Models.
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
Binny, Rachelle N; Plank, Michael J; James, Alex
2015-05-06
The ability of cells to undergo collective movement plays a fundamental role in tissue repair, development and cancer. Interactions occurring at the level of individual cells may lead to the development of spatial structure which will affect the dynamics of migrating cells at a population level. Models that try to predict population-level behaviour often take a mean-field approach, which assumes that individuals interact with one another in proportion to their average density and ignores the presence of any small-scale spatial structure. In this work, we develop a lattice-free individual-based model (IBM) that uses random walk theory to model the stochastic interactions occurring at the scale of individual migrating cells. We incorporate a mechanism for local directional bias such that an individual's direction of movement is dependent on the degree of cell crowding in its neighbourhood. As an alternative to the mean-field approach, we also employ spatial moment theory to develop a population-level model which accounts for spatial structure and predicts how these individual-level interactions propagate to the scale of the whole population. The IBM is used to derive an equation for dynamics of the second spatial moment (the average density of pairs of cells) which incorporates the neighbour-dependent directional bias, and we solve this numerically for a spatially homogeneous case.
Incorporating direct marketing activity into latent attrition models
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, th
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...... in the process as well as modeling dependences between attributes....
Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications
Eco-evolutionary population models are powerful new tools for exploring howevolutionary processes influence plant and animal population dynamics andvice-versa. The need to manage for climate change and other dynamicdisturbance regimes is creating a demand for the incorporation of...
Incorporating RTI in a Hybrid Model of Reading Disability
Spencer, Mercedes; Wagner, Richard K.; Schatschneider, Christopher; Quinn, Jamie M.; Lopez, Danielle; Petscher, Yaacov
2014-01-01
The present study seeks to evaluate a hybrid model of identification that incorporates response to instruction and intervention (RTI) as one of the key symptoms of reading disability. The 1-year stability of alternative operational definitions of reading disability was examined in a large-scale sample of students who were followed longitudinally…
"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 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.
Models for Dynamic Applications
DEFF Research Database (Denmark)
2011-01-01
be applied to formulate, analyse and solve these dynamic problems and how in the case of the fuel cell problem the model consists of coupledmeso and micro scale models. It is shown how data flows are handled between the models and how the solution is obtained within the modelling environment....
Airship dynamics modeling: A literature review
Li, Yuwen; Nahon, Meyer; Sharf, Inna
2011-04-01
The resurgence of airships has created a need for dynamics models and simulation capabilities adapted to these lighter-than-air vehicles. However, the modeling techniques for airship dynamics have lagged behind and are less systematic than those for fixed-wing aircraft. A state-of-the-art literature review is presented on airship dynamics modeling, aiming to provide a comprehensive description of the main problems in this area and a useful source of references for researchers and engineers interested in modern airship applications. The references are categorized according to the major topics in this area: aerodynamics, flight dynamics, incorporation of structural flexibility, incorporation of atmospheric turbulence, and effects of ballonets. Relevant analytical, numerical, and semi-empirical techniques are discussed, with a particular focus on how the main differences between lighter-than-air and heavier-than-air aircraft have been addressed in the modeling. Directions are suggested for future research on each of these topics.
Evans, Phillip G.; Dapino, Marcelo J.
2008-03-01
A general framework is developed to model the nonlinear magnetization and strain response of cubic magnetostrictive materials to 3-D dynamic magnetic fields and 3-D stresses. Dynamic eddy current losses and inertial stresses are modeled by coupling Maxwell's equations to Newton's second law through a nonlinear constitutive model. The constitutive model is derived from continuum thermodynamics and incorporates rate-dependent thermal effects. The framework is implemented in 1-D to describe a Tonpilz transducer in both dynamic actuation and sensing modes. The model is shown to qualitatively describe the effect of increase in magnetic hysteresis with increasing frequency, the shearing of the magnetization loops with increasing stress, and the decrease in the magnetostriction with increasing load stiffness.
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...
Incorporating RTI in a Hybrid Model of Reading Disability
2014-01-01
The present study seeks to evaluate a hybrid model of identification that incorporates response-to-intervention (RTI) as a one of the key symptoms of reading disability. The one-year stability of alternative operational definitions of reading disability was examined in a large scale sample of students who were followed longitudinally from first to second grade. The results confirmed previous findings of limited stability for single-criterion based operational definitions of reading disability...
Incorporating Linguistic Structure into Maximum Entropy Language Models
Institute of Scientific and Technical Information of China (English)
FANG GaoLin(方高林); GAO Wen(高文); WANG ZhaoQi(王兆其)
2003-01-01
In statistical language models, how to integrate diverse linguistic knowledge in a general framework for long-distance dependencies is a challenging issue. In this paper, an improved language model incorporating linguistic structure into maximum entropy framework is presented.The proposed model combines trigram with the structure knowledge of base phrase in which trigram is used to capture the local relation between words, while the structure knowledge of base phrase is considered to represent the long-distance relations between syntactical structures. The knowledge of syntax, semantics and vocabulary is integrated into the maximum entropy framework.Experimental results show that the proposed model improves by 24% for language model perplexity and increases about 3% for sign language recognition rate compared with the trigram model.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.
Methods improvements incorporated into the SAPHIRE ASP models
Energy Technology Data Exchange (ETDEWEB)
Sattison, M.B.; Blackman, H.S.; Novack, S.D. [Idaho National Engineering Lab., Idaho Falls, ID (United States)] [and others
1995-04-01
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.
3.5D dynamic PET image reconstruction incorporating kinetics-based clusters.
Lu, Lijun; Karakatsanis, Nicolas A; Tang, Jing; Chen, Wufan; Rahmim, Arman
2012-08-07
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 and
A novel fluence map optimization model incorporating leaf sequencing constraints.
Jin, Renchao; Min, Zhifang; Song, Enmin; Liu, Hong; Ye, Yinyu
2010-02-21
A novel fluence map optimization model incorporating leaf sequencing constraints is proposed to overcome the drawbacks of the current objective inside smoothing models. Instead of adding a smoothing item to the objective function, we add the total number of monitor unit (TNMU) requirement directly to the constraints which serves as an important factor to balance the fluence map optimization and leaf sequencing optimization process at the same time. Consequently, we formulate the fluence map optimization models for the trailing (left) leaf synchronized, leading (right) leaf synchronized and the interleaf motion constrained non-synchronized leaf sweeping schemes, respectively. In those schemes, the leaves are all swept unidirectionally from left to right. Each of those models is turned into a linear constrained quadratic programming model which can be solved effectively by the interior point method. Those new models are evaluated with two publicly available clinical treatment datasets including a head-neck case and a prostate case. As shown by the empirical results, our models perform much better in comparison with two recently emerged smoothing models (the total variance smoothing model and the quadratic smoothing model). For all three leaf sweeping schemes, our objective dose deviation functions increase much slower than those in the above two smoothing models with respect to the decreasing of the TNMU. While keeping plans in the similar conformity level, our new models gain much better performance on reducing TNMU.
Salinelli, Ernesto
2014-01-01
This book provides an introduction to the analysis of discrete dynamical systems. The content is presented by an unitary approach that blends the perspective of mathematical modeling together with the ones of several discipline as Mathematical Analysis, Linear Algebra, Numerical Analysis, Systems Theory and Probability. After a preliminary discussion of several models, the main tools for the study of linear and non-linear scalar dynamical systems are presented, paying particular attention to the stability analysis. Linear difference equations are studied in detail and an elementary introduction of Z and Discrete Fourier Transform is presented. A whole chapter is devoted to the study of bifurcations and chaotic dynamics. One-step vector-valued dynamical systems are the subject of three chapters, where the reader can find the applications to positive systems, Markov chains, networks and search engines. The book is addressed mainly to students in Mathematics, Engineering, Physics, Chemistry, Biology and Economic...
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.
Day-to-day route choice modeling incorporating inertial behavior
Essen, van M.A.; Rakha, H.; Vreeswijk, J.D.; Wismans, L.J.J.; Berkum, van E.C.
2015-01-01
Accurate route choice modeling is one of the most important aspects when predicting the effects of transport policy and dynamic traffic management. Moreover, the effectiveness of intervention measures to a large extent depends on travelers’ response to the changes these measures cause. As a compleme
Dynamic causal modelling revisited.
Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter
2017-02-17
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
The Dynamic Mundell-Fleming Model Reconsidered
金子, 邦彦; Kaneko, Kunihiko
2003-01-01
In this paper we reconsider the dynamic Mundell-Fleming model of Sarno and Taylor (2002) by incorporating one of the recent New Keynesian ingredients. In an extended framework, we reconfirm that their results on the effects of an expansionary fiscal policy are robust. However, we also show that their results on the effects of an expansionary monetary policy should be modified.
Advances in Inventory Management: Dynamic Models
C. Pinçe (Çerağ)
2010-01-01
textabstractIn this study, we develop and analyze models incorporating some of the dynamic aspects of inventory systems. In particular, we focus on two major themes to be analyzed separately: nonstationarity in demand rate and unfixed purchasing prices. In the first part of the study, we consider a
DEFF Research Database (Denmark)
Hedegaard, Karsten; Balyk, Olexandr
2013-01-01
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...... 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...
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 < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate-based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km(2) ). Estimates accounting for the area of functional habitats were significantly smaller (2-58% [SD 16]) than estimates based only on the total area occupied. An 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
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.
Directory of Open Access Journals (Sweden)
Sorin Dan ŞANDOR
2003-01-01
Full Text Available System Dynamics was introduced by Jay W. Forrester in the 1960s. Since then the methodology was adopted in many areas of natural or social sciences. This article tries to present briefly how this methodology works, both as Systems Thinking and as Modelling with Vensim computer software.
Dynamic modelling of windmills
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
An empirical dynamic model of windmills is set up based on analysis of measured Fourier spectra of the active electric power from a wind farm. The model is based on the assumption that eigenswings of the mechanical construction of the windmills excited by the phenomenon of vortex tower interaction...... will be transferred through the shaft to the electrical generator and result in disturbances of the active electric power supplied by the windmills. The results of the model are found to be in agreement with measurements in the frequency range of the model that is from 0.1 to 10 Hz....
A data-driven model for influenza transmission incorporating media effects
Mitchell, Lewis
2016-01-01
Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza, however quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of "big data" coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study we combine an online data set comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.
A data-driven model for influenza transmission incorporating media effects.
Mitchell, Lewis; Ross, Joshua V
2016-10-01
Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of 'big data' coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.
A data-driven model for influenza transmission incorporating media effects
Ross, Joshua V.
2016-01-01
Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of ‘big data’ coming from online social media and the like, large volumes of data on a population’s engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies. PMID:27853563
Murawski, Jens; Kleine, Eckhard
2017-04-01
Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.
Safety models incorporating graph theory based transit indicators.
Quintero, Liliana; Sayed, Tarek; Wahba, Mohamed M
2013-01-01
There is a considerable need for tools to enable the evaluation of the safety of transit networks at the planning stage. One interesting approach for the planning of public transportation systems is the study of networks. Network techniques involve the analysis of systems by viewing them as a graph composed of a set of vertices (nodes) and edges (links). Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements. Several indicators can be calculated including connectivity, coverage, directness and complexity, among others. The main objective of this study is to investigate the relationship between network-based transit indicators and safety. The study develops macro-level collision prediction models that explicitly incorporate transit physical and operational elements and transit network indicators as explanatory variables. Several macro-level (zonal) collision prediction models were developed using a generalized linear regression technique, assuming a negative binomial error structure. The models were grouped into four main themes: transit infrastructure, transit network topology, transit route design, and transit performance and operations. The safety models showed that collisions were significantly associated with transit network properties such as: connectivity, coverage, overlapping degree and the Local Index of Transit Availability. As well, the models showed a significant relationship between collisions and some transit physical and operational attributes such as the number of routes, frequency of routes, bus density, length of bus and 3+ priority lanes.
Incorporating inductances in tissue-scale models of cardiac electrophysiology
Rossi, Simone; Griffith, Boyce E.
2017-09-01
In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and we examine the effect of intracellular and extracellular inductances on the virtual electrode phenomenon.
An SIRS Epidemic Model Incorporating Media Coverage with Time Delay
Lin, Yiping; Dai, Yunxian
2014-01-01
An SIRS epidemic model incorporating media coverage with time delay is proposed. The positivity and boundedness are studied firstly. The locally asymptotical stability of the disease-free equilibrium and endemic equilibrium is studied in succession. And then, the conditions on which periodic orbits bifurcate are given. Furthermore, we show that the local Hopf bifurcation implies the global Hopf bifurcation after the second critical value of the delay. The obtained results show that the time delay in media coverage can not affect the stability of the disease-free equilibrium when the basic reproduction number R0 1, the stability of the endemic equilibrium will be affected by the time delay; there will be a family of periodic orbits bifurcating from the endemic equilibrium when the time delay increases through a critical value. Finally, some examples for numerical simulations are also included. PMID:24723967
Wang, Yuanyuan; Xie, Zhenghui; Jia, Binghao
2016-09-01
Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen (CN) interactions (CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 (BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production (GPP) and latent heat flux (LE) for the dry season, and improved the carbon (C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m-2 d-1, net ecosystem exchange by 1.96 g C m-2 d-1, LE by 5.0 W m-2, and soil moisture by 0.03 m3 m-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses (including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.
Wang, Xingwang; Huo, Zailin; Feng, Shaoyuan; Guo, Ping; Guan, Huade
2016-12-01
Estimating evapotranspiration from groundwater (ETg) is of importance to understanding water cycle and agricultural water management. Traditional ETg estimation was developed for regional steady condition and is difficult to be used for cropland where ETg changes with crop growth and irrigation schemes. In the present study, a new method estimating daily ETg during the crop growing season was developed. In this model, the effects of crop growth stage, climate condition, groundwater depth and soil moisture are considered. The method was tested with controlled lysimeter experiments of winter wheat including five controlled water table depths and four soil profiles of different textures. The simulated ETg is in good agreement with the measured data for four soil profiles and different depths to groundwater table. Coefficient of determination (R2) and coefficient of efficiency (NSE) are mostly larger than 0.85 and 0.70, respectively. This result suggests that the new method incorporating both soil texture and moisture dynamics can be used to estimate average daily groundwater evapotranspiration in cropland and contribute to quantifying the field water cycle.
Agent-Based Evacuation Model Incorporating Fire Scene and Building Geometry
Institute of Scientific and Technical Information of China (English)
TANG Fangqin; REN Aizhu
2008-01-01
A comprehensive description of the key factors affecting evacuations at fire scones is necessary for accurate simulations.An agent-based simulation model which incorporates the fire scene and the building geometry is developed using a fire dynamics simulator (FDS) based on the computational fluid dynamics and geographic information system (GIS) data to model the occupant response.The building entities are generated for FDS simulation while the spatial analysis on GIS data represents the occupant's knowledge of the building.The influence of the fire is based on a hazard assessment of the combustion products.The agent behavior and decisions are affected by environmental features and the fire field.A case study demonstrates that the evacuation model effectively simulates the coexistence and interactions of the major factors including occupants,building geometry,and fire disaster during the evacuation.The results can be used for the assessments of building designs regarding fire safety.
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
Dynamic wake meandering modeling
DEFF Research Database (Denmark)
Larsen, Gunner Chr.; Madsen Aagaard, Helge; Bingöl, Ferhat;
, 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......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...
Charpentier, Arthur; Durand, Marilou
2015-07-01
In this paper, we investigate questions arising in Parsons and Geist (Bull Seismol Soc Am 102:1-11, 2012). Pseudo causal models connecting magnitudes and waiting times are considered, through generalized regression. We do use conditional model (magnitude given previous waiting time, and conversely) as an extension to joint distribution model described in Nikoloulopoulos and Karlis (Environmetrics 19: 251-269, 2008). On the one hand, we fit a Pareto distribution for earthquake magnitudes, where the tail index is a function of waiting time following previous earthquake; on the other hand, waiting times are modeled using a Gamma or a Weibull distribution, where parameters are functions of the magnitude of the previous earthquake. We use those two models, alternatively, to generate the dynamics of earthquake occurrence, and to estimate the probability of occurrence of several earthquakes within a year or a decade.
A Constrained CA Model for Planning Simulation Incorporating Institutional Constraints
Institute of Scientific and Technical Information of China (English)
2010-01-01
In recent years,it is prevailing to simulate urban growth by means of cellular automata (CA in short) modeling,which is based on selforganizing theories and different from the system dynamic modeling.Since the urban system is definitely complex,the CA models applied in urban growth simulation should take into consideration not only the neighborhood influence,but also other factors influencing urban development.We bring forward the term of complex constrained CA (CC-CA in short) model,which integrates the constrained conditions of neighborhood,macro socio-economy,space and institution.Particularly,the constrained construction zoning,as one institutional constraint,is considered in the CC-CA modeling.In the paper,the conceptual CC-CA model is introduced together with the transition rules.Based on the CC-CA model for Beijing,we discuss the complex constraints to the urban development of,and we show how to set institutional constraints in planning scenario to control the urban growth pattern of Beijing.
Incorporation of fractional-order dynamics into an existing PI/PID DC motor control loop.
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.
Gupta, Ayush
2010-01-01
Researchers have argued against deficit-based explanations of students' troubles with mathematical sense-making, pointing instead to factors such as epistemology: students' beliefs about the nature of knowledge and learning can hinder them from activating and integrating productive knowledge they have. But such explanations run the risk of substituting an epistemological deficit for a concepts/skills deficit. Our analysis of an undergraduate engineering major avoids this "deficit trap" by incorporating multiple, context-dependent epistemological stances into his cognitive dynamics.
Effect of Long—Term Straw Incorporation on Soil Microbial Biomass and C and N Dynamics
Institute of Scientific and Technical Information of China (English)
SHENRENFANG; P.C.BROOKES; 等
1997-01-01
A study was performed on the long-term effect of straw incorporation on soil microbial biomass C contents,C and N dynamics in both Rothamsted and Woburn soils.The results showed that for both soils,the microbial biomass C contents were significantly different among all the treatments,and followed the sequence in treatments of straw chopped and incorporated into 10 cm(CI10)>straw burnt and incorporated into 10 cm(BI10)>staw chopped and incorporated into 20 cm(CI20)>straw burnt and incorporated into 20 cm(BI20).Laboratory incubation of soils showed that the cumulative CO2 evolution was closely related to the soil microbial biomass C content ,Carbon dioxide evolution rates(CO2-C,μg(g.d)-1)decreased rapidly in the first two weeks' incubation,then decreased more slowly,The initial K2SO4-extractable NH4-N and NO33-N contents were low and similar in all the treatments,and all increased gradually with the incubation time ,However,net N immobiliztion was oberved in chopped treatments for Rothamsted soils durig the first 4 weeks ,Nevertheless,more N mineralization occurred in Treatment CI10 than any other treatment at the end of incubation for both soils .The Woburn soils ,could more easily suffer from the leaching of nitrate because the soils were more pemeable and more N was mineralized during the incubation compared to the Rothamsted soils.
Structural dynamic modifications via models
Indian Academy of Sciences (India)
T K Kundra
2000-06-01
Structural dynamic modification techniques attempt to reduce dynamic design time and can be implemented beginning with spatial models of structures, dynamic test data or updated models. The models assumed in this discussion are mathematical models, namely mass, stiffness, and damping matrices of the equations of motion of a structure. These models are identified/extracted from dynamic test data viz. frequency response functions (FRFs). Alternatively these models could have been obtained by adjusting or updating the finite element model of the structure in the light of the test data. The methods of structural modification for getting desired dynamic characteristics by using modifiers namely mass, beams and tuned absorbers are discussed.
Digital terrain model generalization incorporating scale, semantic and cognitive constraints
Partsinevelos, Panagiotis; Papadogiorgaki, Maria
2014-05-01
Cartographic generalization is a well-known process accommodating spatial data compression, visualization and comprehension under various scales. In the last few years, there are several international attempts to construct tangible GIS systems, forming real 3D surfaces using a vast number of mechanical parts along a matrix formation (i.e., bars, pistons, vacuums). Usually, moving bars upon a structured grid push a stretching membrane resulting in a smooth visualization for a given surface. Most of these attempts suffer either in their cost, accuracy, resolution and/or speed. Under this perspective, the present study proposes a surface generalization process that incorporates intrinsic constrains of tangible GIS systems including robotic-motor movement and surface stretching limitations. The main objective is to provide optimized visualizations of 3D digital terrain models with minimum loss of information. That is, to minimize the number of pixels in a raster dataset used to define a DTM, while reserving the surface information. This neighborhood type of pixel relations adheres to the basics of Self Organizing Map (SOM) artificial neural networks, which are often used for information abstraction since they are indicative of intrinsic statistical features contained in the input patterns and provide concise and characteristic representations. Nevertheless, SOM remains more like a black box procedure not capable to cope with possible particularities and semantics of the application at hand. E.g. for coastal monitoring applications, the near - coast areas, surrounding mountains and lakes are more important than other features and generalization should be "biased"-stratified to fulfill this requirement. Moreover, according to the application objectives, we extend the SOM algorithm to incorporate special types of information generalization by differentiating the underlying strategy based on topologic information of the objects included in the application. The final
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism
Li, Zhen; Bian, Xin; Li, Xiantao; Karniadakis, George Em
2015-12-01
The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while the corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism
Energy Technology Data Exchange (ETDEWEB)
Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States); Li, Xiantao [Department of Mathematics, Pennsylvania State University, University Park, Pennsylvania 16802 (United States)
2015-12-28
The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while the corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism.
Li, Zhen; Bian, Xin; Li, Xiantao; Karniadakis, George Em
2015-12-28
The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while the corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.
Dynamical Modeling of Mars' Paleoclimate
Richardson, Mark I.
2004-01-01
This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.
Kock, B. E.
2008-12-01
The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.
Towards Disaggregate Dynamic Travel Forecasting Models
Institute of Scientific and Technical Information of China (English)
Moshe Ben-Akiva; Jon Bottom; Song Gao; Haris N. Koutsopoulos; Yang Wen
2007-01-01
The authors argue that travel forecasting models should be dynamic and disaggregate in their representation of demand, supply, and supply-demand interactions, and propose a framework for such models.The proposed framework consists of disaggregate activity-based representation of travel choices of individual motorists on the demand side integrated with disaggregate dynamic modeling of network performance,through vehicle-based traffic simulation models on the supply side. The demand model generates individual members of the population and assigns to them socioeconomic characteristics. The generated motorists maintain these characteristics when they are loaded on the network by the supply model. In an equilibrium setting, the framework lends itself to a fixed-point formulation to represent and resolve demand-supply interactions. The paper discusses some of the remaining development challenges and presents an example of an existing travel forecasting model system that incorporates many of the proposed elements.
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.
Incorporation of the Driver’s Personality Profile in an Agent Model
Directory of Open Access Journals (Sweden)
Mian Muhammad Mubasher
2015-12-01
Full Text Available Urban traffic flow is a complex system. Behavior of an individual driver can have butterfly effect which can become root cause of an emergent phenomenon such as congestion or accident. Interaction of drivers with each other and the surrounding environment forms the dynamics of traffic flow. Hence global effects of traffic flow depend upon the behavior of each individual driver. Due to several applications of driver models in serious games, urban traffic planning and simulations, study of a realistic driver model is important. Hhence cognitive models of a driver agent are required. In order to address this challenge concepts from cognitive science and psychology are employed to design a computational model of driver cognition which is capable of incorporating law abidance and social norms using big five personality profile.
Comparing different dynamic stall models
Energy Technology Data Exchange (ETDEWEB)
Holierhoek, J.G. [Unit Wind Energy, Energy research Centre of the Netherlands, ZG, Petten (Netherlands); De Vaal, J.B.; Van Zuijlen, A.H.; Bijl, H. [Aerospace Engineering, Delft University of Technology, Delft (Netherlands)
2012-07-16
The dynamic stall phenomenon and its importance for load calculations and aeroelastic simulations is well known. Different models exist to model the effect of dynamic stall; however, a systematic comparison is still lacking. To investigate if one is performing better than another, three models are used to simulate the Ohio State University measurements and a set of data from the National Aeronautics and Space Administration Ames experimental study of dynamic stall and compare results. These measurements were at conditions and for aerofoils that are typical for wind turbines, and the results are publicly available. The three selected dynamic stall models are the ONERA model, the Beddoes-Leishman model and the Snel model. The simulations show that there are still significant differences between measurements and models and that none of the models is significantly better in all cases than the other models. Especially in the deep stall regime, the accuracy of each of the dynamic stall models is limited.
A Biomimetic Model of the Outer Plexiform Layer by Incorporating Memristive Devices
Gelencser, Andras; Toumazou, Christofer; Roska, Tamas
2011-01-01
In this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices. The architecture of the proposed network is based on the organisation and functioning of the outer plexiform layer (OPL) in the vertebrate retina. We demonstrate that memristive devices are indeed a valuable building block for neuromorphic architectures, as their highly non-linear and adaptive response could be exploited for establishing ultra-dense networks with similar dynamics to their biological counterparts. We particularly show that hexagonal memristive grids can be employed for faithfully emulating the smoothing-effect occurring at the OPL for enhancing the dynamic range of the system. In addition, we employ a memristor-based thresholding scheme for detecting the edges of grayscale images, while the proposed system is also evaluated for its adaptation and fault tolerance capacity against different light or noise conditions as well as distinct device yields.
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.
Incorporating nucleosomes into thermodynamic models of transcription regulation.
Raveh-Sadka, Tali; Levo, Michal; Segal, Eran
2009-08-01
Transcriptional control is central to many cellular processes, and, consequently, much effort has been devoted to understanding its underlying mechanisms. The organization of nucleosomes along promoter regions is important for this process, since most transcription factors cannot bind nucleosomal sequences and thus compete with nucleosomes for DNA access. This competition is governed by the relative concentrations of nucleosomes and transcription factors and by their respective sequence binding preferences. However, despite its importance, a mechanistic understanding of the quantitative effects that the competition between nucleosomes and factors has on transcription is still missing. Here we use a thermodynamic framework based on fundamental principles of statistical mechanics to explore theoretically the effect that different nucleosome organizations along promoters have on the activation dynamics of promoters in response to varying concentrations of the regulating factors. We show that even simple landscapes of nucleosome organization reproduce experimental results regarding the effect of nucleosomes as general repressors and as generators of obligate binding cooperativity between factors. Our modeling framework also allows us to characterize the effects that various sequence elements of promoters have on the induction threshold and on the shape of the promoter activation curves. Finally, we show that using only sequence preferences for nucleosomes and transcription factors, our model can also predict expression behavior of real promoter sequences, thereby underscoring the importance of the interplay between nucleosomes and factors in determining expression kinetics.
DEFF Research Database (Denmark)
Keck, Rolf-Erik; de Mare, Martin Tobias; Churchfield, Matthew J.
2015-01-01
the model to simulate the build-up of turbulence over a row of turbines in a physically consistent manner. The performance of the modified model is validated against actuator line (AL) model results and field data from the Lillgrund offshore wind farm. Qualitatively, the modified DWM model is in fair......%, respectively, by including the proposed corrections for a row of eight turbines. Furthermore, it is found that the root-mean-square difference between the AL model and the modified DWM model in terms of wind speed and turbulence intensity does not increase over a row of turbines compared with the root...
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.
NexGen PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models
We examine how the integration of evolutionary and ecological processes in population dynamics – an emerging framework in ecology – could be incorporated into population viability analysis (PVA). Driven by parallel, complementary advances in population genomics and computational ...
Incorporating flood event analyses and catchment structures into model development
Oppel, Henning; Schumann, Andreas
2016-04-01
The space-time variability in catchment response results from several hydrological processes which differ in their relevance in an event-specific way. An approach to characterise this variance consists in comparisons between flood events in a catchment and between flood responses of several sub-basins in such an event. In analytical frameworks the impact of space and time variability of rainfall on runoff generation due to rainfall excess can be characterised. Moreover the effect of hillslope and channel network routing on runoff timing can be specified. Hence, a modelling approach is needed to specify the runoff generation and formation. Knowing the space-time variability of rainfall and the (spatial averaged) response of a catchment it seems worthwhile to develop new models based on event and catchment analyses. The consideration of spatial order and the distribution of catchment characteristics in their spatial variability and interaction with the space-time variability of rainfall provides additional knowledge about hydrological processes at the basin scale. For this purpose a new procedure to characterise the spatial heterogeneity of catchments characteristics in their succession along the flow distance (differentiated between river network and hillslopes) was developed. It was applied to study of flood responses at a set of nested catchments in a river basin in eastern Germany. In this study the highest observed rainfall-runoff events were analysed, beginning at the catchment outlet and moving upstream. With regard to the spatial heterogeneities of catchment characteristics, sub-basins were separated by new algorithms to attribute runoff-generation, hillslope and river network processes. With this procedure the cumulative runoff response at the outlet can be decomposed and individual runoff features can be assigned to individual aspects of the catchment. Through comparative analysis between the sub-catchments and the assigned effects on runoff dynamics new
Shangguan, Mingjia; Wang, Chong; Xia, Haiyun; Shentu, Guoliang; Dou, Xiankang; Zhang, Qiang; Pan, Jian-wei
2017-09-01
For the first time, to the best of our knowledge, a direct detection Brillouin optical time-domain reflectometry (BOTDR) is demonstrated for fast distributed dynamic strain sensing incorporating double-edge technique, time-division multiplexing technique and upconversion technique. In order to guarantee the robust stability of the system, the double-edge technique is implemented by using a convert single-channel FPI and a fiber-coupled upconversion single-photon detector, incorporating a time-division multiplexing method. The upconversion single-photon detector is adopted to upconvert the backscattering photons from 1548.1 nm to 863 nm, which is subsequently detected by a Silicon avalanche photodiode (Si-APD). In the experiment, dynamic strain disturbance up to 1.9 mε over 1.5 km of a polarization maintaining fiber is detected at a sampling rate of 30 Hz. An accuracy of ± 30 με and spatial resolution of 0.6 m are realized.
Modelling dynamic roughness during floods
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
Friston, K J; Harrison, L; Penny, W
2003-08-01
In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
Directory of Open Access Journals (Sweden)
Ray Huffaker
Full Text Available 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.
Models of microbiome evolution incorporating host and microbial selection.
Zeng, Qinglong; Wu, Steven; Sukumaran, Jeet; Rodrigo, Allen
2017-09-25
Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong
Mouzakis, Dionysios E; Papadopoulos, Triantafillos D; Polyzois, Gregory L; Griniari, Panagiota G
2010-11-01
The main objective of the current study was to investigate the dynamic mechanical properties of a room-temperature vulcanizing silicone incorporating different fractions of zinc oxide (ZnO) after indoor and outdoor photoaging. Forty-eight samples were produced by adding different amounts of ZnO into a commercial maxillofacial silicone (EPISIL-E). The samples were divided into 4 groups containing 0.0, 0.2, 0.5, and 1 wt% ZnO additive, respectively. Samples were exposed to sunlight (subgroup 2), ultraviolet (subgroup 3), and fluorescence (subgroup 4) aging, whereas nonaged samples comprised the control subgroup (subgroup 1). Dynamic mechanical analysis was used to determine the storage modulus (E'), loss modulus (E″), and damping capacity (tanδ). General linear statistic model was conducted to evaluate the effects of aging, testing frequency, and composition on the dynamic mechanical properties of the silicone with the ZnO additive. Post hoc analysis was performed using Tukey test. Statistical analysis revealed a significant impact of composition on tanδ (P < 0.05). Aging influenced E' and E″ (P < 0.01). The combination of aging and composition had a significant effect on all dynamic properties (P < 0.01).
Unger, J K; Kuehlein, G; Schroers, A; Gerlach, J C; Rossaint, R
2001-07-01
Commonly used materials incorporated into dynamic culture systems typically show the feature of adsorption of lipophilic xenobiotics. Yet, this phenomenon is strongly limiting the use of dynamic culture models and ex vivo organ perfusions in pharmacological and toxicological research. The aim of the study was to characterize different materials with respect to their capacity for drug adsorption and to find methods or materials to reduce the loss of substrate by adsorption in order to improve the use of dynamic in vitro systems. The adsorption of different xenobiotics (lidocaine, midazolam, lormetazepam, phenobarbital, testosterone, ethoxyresoroufine) to tubes used in dynamic in vitro systems (polyvinyl-chloride, silicone) were investigated and compared to a new material (silicone-caoutchouc-mixture). In addition, the role of protein deposition onto the tubing was studied and it was investigated whether it was possible to reach saturation of the inner tube surface by pre-loading it with the test compound. We found that silicone tubes provided the highest comfort with respect to handling and reusability, but they also demonstrated the highest capacity for substrate adsorption. Polyvinyl-chloride was the second best in handling but also demonstrated a high complexity in its adsorption behavior. The silicone-caoutchouc-mixture reached acceptable experimental results with respect to its handling and demonstrated a very low capacity for substrate adsorption.
Dynamics modeling and simulation of flexible airships
Li, Yuwen
The resurgence of airships has created a need for dynamics models and simulation capabilities of these lighter-than-air vehicles. The focus of this thesis is a theoretical framework that integrates the flight dynamics, structural dynamics, aerostatics and aerodynamics of flexible airships. The study begins with a dynamics model based on a rigid-body assumption. A comprehensive computation of aerodynamic effects is presented, where the aerodynamic forces and moments are categorized into various terms based on different physical effects. A series of prediction approaches for different aerodynamic effects are unified and applied to airships. The numerical results of aerodynamic derivatives and the simulated responses to control surface deflection inputs are verified by comparing to existing wind-tunnel and flight test data. With the validated aerodynamics and rigid-body modeling, the equations of motion of an elastic airship are derived by the Lagrangian formulation. The airship is modeled as a free-free Euler-Bernoulli beam and the bending deformations are represented by shape functions chosen as the free-free normal modes. In order to capture the coupling between the aerodynamic forces and the structural elasticity, local velocity on the deformed vehicle is used in the computation of aerodynamic forces. Finally, with the inertial, gravity, aerostatic and control forces incorporated, the dynamics model of a flexible airship is represented by a single set of nonlinear ordinary differential equations. The proposed model is implemented as a dynamics simulation program to analyze the dynamics characteristics of the Skyship-500 airship. Simulation results are presented to demonstrate the influence of structural deformation on the aerodynamic forces and the dynamics behavior of the airship. The nonlinear equations of motion are linearized numerically for the purpose of frequency domain analysis and for aeroelastic stability analysis. The results from the latter for the
Florian Ion Tiberiu Petrescu; Relly Victoria Virgil Petrescu
2016-01-01
Otto engine dynamics are similar in almost all common internal combustion engines. We can speak so about dynamics of engines: Lenoir, Otto, and Diesel. The dynamic presented model is simple and original. The first thing necessary in the calculation of Otto engine dynamics, is to determine the inertial mass reduced at the piston. One uses then the Lagrange equation. Kinetic energy conservation shows angular speed variation (from the shaft) with inertial masses. One uses and elastic constant of...
Sahbaee, Pooyan; Segars, W Paul; Marin, Daniele; Nelson, Rendon C; Samei, Ehsan
2017-06-01
Purpose To develop a method to incorporate the propagation of contrast material into computational anthropomorphic phantoms for estimation of organ dose at computed tomography (CT). Materials and Methods A patient-specific physiologically based pharmacokinetic (PBPK) model of the human cardiovascular system was incorporated into 58 extended cardiac-torso (XCAT) patient phantoms. The PBPK model comprised compartmental models of vessels and organs unique to each XCAT model. For typical injection protocols, the dynamics of the contrast material in the body were described according to a series of patient-specific iodine mass-balance differential equations, the solutions to which provided the contrast material concentration time curves for each compartment. Each organ was assigned to a corresponding time-varying iodinated contrast agent to create the contrast material-enhanced five-dimensional XCAT models, in which the fifth dimension represents the dynamics of contrast material. To validate the accuracy of the models, simulated aortic and hepatic contrast-enhancement results throughout the models were compared with previously published clinical data by using the percentage of discrepancy in the mean, time to 90% peak, peak value, and slope of enhancement in a paired t test at the 95% significance level. Results The PBPK model allowed effective prediction of the time-varying concentration curves of various contrast material administrations in each organ for different patient models. The contrast-enhancement results were in agreement with results of previously published clinical data, with mean percentage, time to 90% peak, peak value, and slope of less than 10% (P > .74), 4%, 7%, and 14% for uniphasic and 12% (P > .56), 4%, 12%, and 14% for biphasic injection protocols, respectively. The exception was hepatic enhancement results calculated for a uniphasic injection protocol for which the discrepancy was less than 25%. Conclusion A technique to model the propagation of
Incorporating animal behavior into seed dispersal models: implications for seed shadows.
Russo, Sabrina E; Portnoy, Stephen; Augspurger, Carol K
2006-12-01
Seed dispersal fundamentally influences plant population and community dynamics but is difficult to quantify directly. Consequently, models are frequently used to describe the seed shadow (the seed deposition pattern of a plant population). For vertebrate-dispersed plants, animal behavior is known to influence seed shadows but is poorly integrated in seed dispersal models. Here, we illustrate a modeling approach that incorporates animal behavior and develop a stochastic, spatially explicit simulation model that predicts the seed shadow for a primate-dispersed tree species (Virola calophylla, Myristicaceae) at the forest stand scale. The model was parameterized from field-collected data on fruit production and seed dispersal, behaviors and movement patterns of the key disperser, the spider monkey (Ateles paniscus), densities of dispersed and non-dispersed seeds, and direct estimates of seed dispersal distances. Our model demonstrated that the spatial scale of dispersal for this V. calophylla population was large, as spider monkeys routinely dispersed seeds >100 m, a commonly used threshold for long-distance dispersal. The simulated seed shadow was heterogeneous, with high spatial variance in seed density resulting largely from behaviors and movement patterns of spider monkeys that aggregated seeds (dispersal at their sleeping sites) and that scattered seeds (dispersal during diurnal foraging and resting). The single-distribution dispersal kernels frequently used to model dispersal substantially underestimated this variance and poorly fit the simulated seed-dispersal curve, primarily because of its multimodality, and a mixture distribution always fit the simulated dispersal curve better. Both seed shadow heterogeneity and dispersal curve multimodality arose directly from these different dispersal processes generated by spider monkeys. Compared to models that did not account for disperser behavior, our modeling approach improved prediction of the seed shadow of this V
Institute of Scientific and Technical Information of China (English)
伍慧玲
2012-01-01
研究一类具有离散时间、外界捕获、毒素作用的捕食-食饵系统,通过运用比较引理和构造恰当的Lyapunov函数,证明了系统的持久性和全局吸引性,最后,我们给出了捕食者、食饵种群绝灭的充分条件.%A discrete predator-prey model with harvesting and toxicity was studied.By using comparison theorem and constructing a suitable Lyapunov function,the permanence and global attractivity of the system were proved.Sufficient conditions for the extinction of the predator and prey were given.
Reyes, J. J.; Liu, M.; Tague, C.; Choate, J. S.; Evans, R. D.; Johnson, K. A.; Adam, J. C.
2013-12-01
Rangelands provide an opportunity to investigate the coupled feedbacks between human activities and natural ecosystems. These areas comprise at least one-third of the Earth's surface and provide ecological support for birds, insects, wildlife and agricultural animals including grazing lands for livestock. Capturing the interactions among water, carbon, and nitrogen cycles within the context of regional scale patterns of climate and management is important to understand interactions, responses, and feedbacks between rangeland systems and humans, as well as provide relevant information to stakeholders and policymakers. The overarching objective of this research is to understand the full consequences, intended and unintended, of human activities and climate over time in rangelands by incorporating dynamics related to rangeland management into an eco-hydrologic model that also incorporates biogeochemical and soil processes. Here we evaluate our model over ungrazed and grazed sites for different rangeland ecosystems. The Regional Hydro-ecologic Simulation System (RHESSys) is a process-based, watershed-scale model that couples water with carbon and nitrogen cycles. Climate, soil, vegetation, and management effects within the watershed are represented in a nested landscape hierarchy to account for heterogeneity and the lateral movement of water and nutrients. We incorporated a daily time-series of plant biomass loss from rangeland to represent grazing. The TRY Plant Trait Database was used to parameterize genera of shrubs and grasses in different rangeland types, such as tallgrass prairie, Intermountain West cold desert, and shortgrass steppe. In addition, other model parameters captured the reallocation of carbon and nutrients after grass defoliation. Initial simulations were conducted at the Curlew Valley site in northern Utah, a former International Geosphere-Biosphere Programme Desert Biome site. We found that grasses were most sensitive to model parameters affecting
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.
Model dynamics for quantum computing
Tabakin, Frank
2017-08-01
A model master equation suitable for quantum computing dynamics is presented. In an ideal quantum computer (QC), a system of qubits evolves in time unitarily and, by virtue of their entanglement, interfere quantum mechanically to solve otherwise intractable problems. In the real situation, a QC is subject to decoherence and attenuation effects due to interaction with an environment and with possible short-term random disturbances and gate deficiencies. The stability of a QC under such attacks is a key issue for the development of realistic devices. We assume that the influence of the environment can be incorporated by a master equation that includes unitary evolution with gates, supplemented by a Lindblad term. Lindblad operators of various types are explored; namely, steady, pulsed, gate friction, and measurement operators. In the master equation, we use the Lindblad term to describe short time intrusions by random Lindblad pulses. The phenomenological master equation is then extended to include a nonlinear Beretta term that describes the evolution of a closed system with increasing entropy. An external Bath environment is stipulated by a fixed temperature in two different ways. Here we explore the case of a simple one-qubit system in preparation for generalization to multi-qubit, qutrit and hybrid qubit-qutrit systems. This model master equation can be used to test the stability of memory and the efficacy of quantum gates. The properties of such hybrid master equations are explored, with emphasis on the role of thermal equilibrium and entropy constraints. Several significant properties of time-dependent qubit evolution are revealed by this simple study.
Energy Technology Data Exchange (ETDEWEB)
Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua; Alfonsi, Andrea; Askin Guler; Tunc Aldemir
2014-11-01
Passive system, structure and components (SSCs) will degrade over their operation life and this degradation may cause to reduction in the safety margins of a nuclear power plant. In traditional probabilistic risk assessment (PRA) using the event-tree/fault-tree methodology, passive SSC failure rates are generally based on generic plant failure data and the true state of a specific plant is not reflected realistically. To address aging effects of passive SSCs in the traditional PRA methodology [1] does consider physics based models that account for the operating conditions in the plant, however, [1] does not include effects of surveillance/inspection. This paper represents an overall methodology for the incorporation of aging modeling of passive components into the RAVEN/RELAP-7 environment which provides a framework for performing dynamic PRA. Dynamic PRA allows consideration of both epistemic and aleatory uncertainties (including those associated with maintenance activities) in a consistent phenomenological and probabilistic framework and is often needed when there is complex process/hardware/software/firmware/ human interaction [2]. Dynamic PRA has gained attention recently due to difficulties in the traditional PRA modeling of aging effects of passive components using physics based models and also in the modeling of digital instrumentation and control systems. RAVEN (Reactor Analysis and Virtual control Environment) [3] is a software package under development at the Idaho National Laboratory (INL) as an online control logic driver and post-processing tool. It is coupled to the plant transient code RELAP-7 (Reactor Excursion and Leak Analysis Program) also currently under development at INL [3], as well as RELAP 5 [4]. The overall methodology aims to: • Address multiple aging mechanisms involving large number of components in a computational feasible manner where sequencing of events is conditioned on the physical conditions predicted in a simulation
Institute of Scientific and Technical Information of China (English)
张香成; 徐赵东; 冉成崧; 朱俊涛
2013-01-01
磁流变阻尼器(MRD)是一种性能优越的半主动控制装置.首先推导了设置有MRD框架结构中MRD的位置矩阵,然后将框架结构简化为杆系模型,用MATLAB编制了加入MRD的框架结构的弹塑性动力时程分析程序,分别计算并对比了框架结构在未控和有控下各层的位移、加速度响应和各杆端塑性铰分布情况.结果表明,设置MRD的框架结构各层位移和加速度响应显著减小,其中位移的减震效果优于加速度的减震效果,同时杆件屈服数量相应减少.%Magneto-rheological damper (MRD) is an excellent semi-active control device. The location matrix of MRD in the frame structure incorporated with MRD was derived. Then a member model was selected as the mathematical model of the structure. An elastic-plastic dynamic response analysis of the structure incorporated with MRD was programmed by using MATLAB. The displacement and acceleration responses of the structure with and without MRD, as well as the distribution of plastic hinges of the member, were calculated and compared. Comparison results show that the displacement and the acceleration responses of each floor of the structure with MRD were reduced significantly, in which the vibration mitigation effect on displacement is superior to that on acceleration. At the same time, the number of plastic hinges is also reduced.
Alo, C. A.; Anagnostou, E. N.
2009-09-01
Recent projections of climate change over the Mediterranean region based on general circulation models (e.g. IPCC AR4 GCMs) and regional climate models (e.g. PRUDENCE RCMs) generally show strong warming and pronounced decrease in precipitation, especially in the summer. While the role of vegetation in modulating the regional climate is widely recognized, most, if not all, of these GCM and RCM climate change projections do not account for the response of the dynamic biosphere to potential climate changes. Here, we present preliminary results from ongoing 15-year simulations over the Mediterranean region with a regional climate model (RegCM3) asynchronously coupled to a dynamic vegetation model (CLM-DGVM). Three experiments are performed in order to explore the impact of vegetation feedback on simulated changes in mean climate, climate variability and extreme climatic events (i.e., flood-inducing storms, droughts, heat waves, and extreme winds). This includes 1) a present day climate run with dynamic vegetation, 2) a future climate run with dynamic vegetation, and 3) a future climate run with static vegetation (i.e. vegetation fixed at the present day state). RegCM3 and CLM-DGVM are both run at a horizontal grid spacing of 20 km over a region covering the Mediterranean basin and parts of Central Europe and Northern Africa. Results illustrate the importance of including vegetation feedback in predictions of climate change impacts on Mediterranean climate variability, extreme climatic events and storms.
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.
Incorporating Enterprise Risk Management in the Business Model Innovation Process
Yariv Taran; Harry Boer; Peter Lindgren
2013-01-01
Purpose: Relative to other types of innovations, little is known about business model innovation, let alone the process of managing the risks involved in that process. Using the emerging (enterprise) risk management literature, an approach is proposed through which risk management can be embedded in the business model innovation process. Design: The integrated business model innovation risk management model developed in this paper has been tested through an action research study in a Dani...
Shangguan, Mingjia; Xia, Haiyun; Qiu, Jiawei; Shentu, Guoliang; Dou, Xiankang; Zhang, Qiang; Pan, Jian-wei
2016-01-01
For the first time, a direct detection BOTDR is demonstrated for distributed dynamic strain sensing incorporating double-edge technique, time-division multiplexing technique and upconversion technique. The double edges are realized by using the transmission curve and reflection curve of an all-fiber Fabry-Perot interferometer (FPI). Benefiting from the low loss of the fiber at, the time-division multiplexing technique is performed to realize the double-edge technique by using only a single-channel FPI and only one piece of a detector. In order to detect the weak spontaneous Brillouin backscattering signal efficiently, a fiber-coupled upconversion detector is adopted to upconvert the backscattering signal at 1548.1 nm to 863 nm, which is detected by a Si-APD finally. In the experiment, dynamic strain disturbance up to 1.9m{\\epsilon} over 1.5 km of polarization maintaining fiber is detected at a sampling rate of 30 Hz. An accuracy of 30{\\mu}{\\epsilon} and spatial resolution of 0.6 m is realized.
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.
Seasonal variation in survival and reproduction can be a large source of prediction uncertainty in models used for conservation and management. A seasonally varying matrix population model is developed that incorporates temperature-driven differences in mortality and reproduction...
Launch Vehicle Dynamics Demonstrator Model
1963-01-01
Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov
Generative models of conformational dynamics.
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.
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies
Smith, Carrie E.; Cribbie, Robert A.
2013-01-01
When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
Incorporating Enterprise Risk Management in the Business Model Innovation Process
Directory of Open Access Journals (Sweden)
Yariv Taran
2013-12-01
Full Text Available Purpose: Relative to other types of innovations, little is known about business model innovation, let alone the process of managing the risks involved in that process. Using the emerging (enterprise risk management literature, an approach is proposed through which risk management can be embedded in the business model innovation process. Design: The integrated business model innovation risk management model developed in this paper has been tested through an action research study in a Danish company. Findings: The study supports our proposition that the implementation of risk management throughout the innovation process reduces the risks related to the uncertainty and complexity of developing and implementing a new business model. Originality: The study supports the proposition that the implementation of risk management throughout the innovation process reduces the risks related to the uncertainty and complexity of developing and implementing a new business model. The business model risk management model makes managers much more focused on identifying problematic issues and putting explicit plans and timetables into place for resolving/reducing risks, and assists companies in aligning the risk treatment choices made during the
Fractal Models of Earthquake Dynamics
Bhattacharya, Pathikrit; Kamal,; Samanta, Debashis
2009-01-01
Our understanding of earthquakes is based on the theory of plate tectonics. Earthquake dynamics is the study of the interactions of plates (solid disjoint parts of the lithosphere) which produce seismic activity. Over the last about fifty years many models have come up which try to simulate seismic activity by mimicking plate plate interactions. The validity of a given model is subject to the compliance of the synthetic seismic activity it produces to the well known empirical laws which describe the statistical features of observed seismic activity. Here we present a review of two such models of earthquake dynamics with main focus on a relatively new model namely The Two Fractal Overlap Model.
Sankaran, Shrikrishnan; Kiren, Mustafa Can; Jonkheijm, Pascal
2015-01-01
Supramolecular assemblies, formed through noncovalent interactions, has become particularly attractive to develop dynamic and responsive architectures to address living systems at the nanoscale. Cucurbit[8]uril (CB[8]), a pumpkin shaped macrocylic host molecule, has been successfully used to construct various self-assembled architectures for biomedical applications since it can simultaneously bind two aromatic guest molecules within its cavity. Such architectures can also be designed to respond to external stimuli. Integrating living organisms as an active component into such supramolecular architectures would add a new dimension to the capabilities of such systems. To achieve this, we have incorporated supramolecular functionality at the bacterial surface by genetically modifying a transmembrane protein to display a CB[8]-binding motif as part of a cystine-stabilized miniprotein. We were able to confirm that this supramolecular motif on the bacterial surface specifically binds CB[8] and forms multiple intercellular ternary complexes leading to aggregation of the bacterial solution. We performed various aggregation experiments to understand how CB[8] interacts with this bacterial strain and also demonstrate that it can be chemically reversed using a competitor. To confirm that this strain can be incorporated with a CB[8] based architecture, we show that the bacterial cells were able to adhere to CB[8] self-assembled monolayers (SAMs) on gold and still retain considerable motility for several hours, indicating that the system can potentially be used to develop supramolecular bacterial biomotors. The bacterial strain also has the potential to be combined with other CB[8] based architectures like nanoparticles, vesicles and hydrogels.
Modelling of Permanent Magnet Synchronous Motor Incorporating Core-loss
Directory of Open Access Journals (Sweden)
K. Suthamno
2012-08-01
Full Text Available This study proposes a dq-axis modelling of a Permanent Magnet Synchronous Motor (PMSM with copper-loss and core-loss taken into account. The proposed models can be applied to PMSM control and drive with loss minimization in simultaneous consideration. The study presents simulation results of direct drive of a PMSM under no-load and loaded conditions using the proposed models with MATLAB codes. Comparisons of the results are made among those obtained from using PSIM and SIMULINK software packages. The comparison results indicate very good agreement.
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
Markov modulated Poisson process models incorporating covariates for rainfall intensity.
Thayakaran, R; Ramesh, N I
2013-01-01
Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.
Building dynamic spatial environmental models
Karssenberg, D.J.
2003-01-01
An environmental model is a representation or imitation of complex natural phenomena that can be discerned by human cognitive processes. This thesis deals with the type of environmental models referred to as dynamic spatial environmental models. The word spatial refers to the geographic domain whi
Dynamical models of the Galaxy
Directory of Open Access Journals (Sweden)
McMillan P.J.
2012-02-01
Full Text Available I discuss the importance of dynamical models for exploiting survey data, focusing on the advantages of “torus” models. I summarize a number of applications of these models to the study of the Milky Way, including the determination of the peculiar Solar velocity and investigation of the Hyades moving group.
Incorporating concern for relative wealth into economic models
1995-01-01
This article develops a simple model that captures a concern for relative standing, or status. This concern is instrumental, in the sense that individuals do not get utility directly from their relative standing, but, rather, the concern is induced because their relative standing affects their consumption of standard commodities. The article investigates the consequences of a concern for relative wealth in models in which individuals are making labor/leisure decisions. The analysis shows how ...
DEFF Research Database (Denmark)
Knudsen, Torben
2011-01-01
The purpose with this deliverable 2.5 is to use fresh experimental data for validation and selection of a flow model to be used for control design in WP3-4. Initially the idea was to investigate the models developed in WP2. However, in the project it was agreed to include and focus on a additive...... model turns out not to be useful for prediction of the flow. Moreover, standard Box Jenkins model structures and multiple output auto regressive models proves to be superior as they can give useful predictions of the flow....
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
Zacharof, A I; Butler, A P
2004-01-01
A mathematical model simulating the hydrological and biochemical processes occurring in landfilled waste is presented and demonstrated. The model combines biochemical and hydrological models into an integrated representation of the landfill environment. Waste decomposition is modelled using traditional biochemical waste decomposition pathways combined with a simplified methodology for representing the rate of decomposition. Water flow through the waste is represented using a statistical velocity model capable of representing the effects of waste heterogeneity on leachate flow through the waste. Given the limitations in data capture from landfill sites, significant emphasis is placed on improving parameter identification and reducing parameter requirements. A sensitivity analysis is performed, highlighting the model's response to changes in input variables. A model test run is also presented, demonstrating the model capabilities. A parameter perturbation model sensitivity analysis was also performed. This has been able to show that although the model is sensitive to certain key parameters, its overall intuitive response provides a good basis for making reasonable predictions of the future state of the landfill system. Finally, due to the high uncertainty associated with landfill data, a tool for handling input data uncertainty is incorporated in the model's structure. It is concluded that the model can be used as a reasonable tool for modelling landfill processes and that further work should be undertaken to assess the model's performance.
The incorporation and validation of empirical crawling data into the buildingEXODUS model
Muhdi, Rani; Gwynne, Steve; Davis, Jerry
2009-01-01
The deterioration of environmental conditions can influence evacuee decisions and their subsequent behaviors. Simulating evacuee behaviors enhances the robustness of engineering procedural designs, improves the accuracy of egress models, and better evaluates the safety of evacuees. The purpose of this paper is to more accurately incorporate and validate evacuee crawling behavior into the buildingEXODUS egress model. Crawling data were incorporated into the model and tested for accurate repres...
Adams, Neil S.; Bollenbacher, Gary
1992-01-01
This report discusses the development and underlying mathematics of a rigid-body computer model of a proposed cryogenic on-orbit liquid depot storage, acquisition, and transfer spacecraft (COLD-SAT). This model, referred to in this report as the COLD-SAT dynamic model, consists of both a trajectory model and an attitudinal model. All disturbance forces and torques expected to be significant for the actual COLD-SAT spacecraft are modeled to the required degree of accuracy. Control and experimental thrusters are modeled, as well as fluid slosh. The model also computes microgravity disturbance accelerations at any specified point in the spacecraft. The model was developed by using the Boeing EASY5 dynamic analysis package and will run on Apollo, Cray, and other computing platforms.
Modelling toluene oxidation : Incorporation of mass transfer phenomena
Hoorn, J.A.A.; van Soolingen, J.; Versteeg, G. F.
2005-01-01
The kinetics of the oxidation of toluene have been studied in close interaction with the gas-liquid mass transfer occurring in the reactor. Kinetic parameters for a simple model have been estimated on basis of experimental observations performed under industrial conditions. The conclusions for the m
Modelling toluene oxidation : Incorporation of mass transfer phenomena
Hoorn, J.A.A.; van Soolingen, J.; Versteeg, G. F.
The kinetics of the oxidation of toluene have been studied in close interaction with the gas-liquid mass transfer occurring in the reactor. Kinetic parameters for a simple model have been estimated on basis of experimental observations performed under industrial conditions. The conclusions for the
Modelling toluene oxidation : Incorporation of mass transfer phenomena
Hoorn, J.A.A.; van Soolingen, J.; Versteeg, G. F.
2005-01-01
The kinetics of the oxidation of toluene have been studied in close interaction with the gas-liquid mass transfer occurring in the reactor. Kinetic parameters for a simple model have been estimated on basis of experimental observations performed under industrial conditions. The conclusions for the m
Incorporating Uncertainties in Satellite-Derived Chlorophyll into Model Forecasts
2012-10-01
radiances in the seven visible MODIS channels used in the estimation of the bio-optical products, such as chlorophyll, absorption and backscattering...grazers, nitrate, silicate, ammonium, and two detritus pools. Phytoplankton photosynthesis in the biochemical model is driven by Photosynthetically
Workforce scheduling: A new model incorporating human factors
Directory of Open Access Journals (Sweden)
Mohammed Othman
2012-12-01
Full Text Available Purpose: The majority of a company’s improvement comes when the right workers with the right skills, behaviors and capacities are deployed appropriately throughout a company. This paper considers a workforce scheduling model including human aspects such as skills, training, workers’ personalities, workers’ breaks and workers’ fatigue and recovery levels. This model helps to minimize the hiring, firing, training and overtime costs, minimize the number of fired workers with high performance, minimize the break time and minimize the average worker’s fatigue level.Design/methodology/approach: To achieve this objective, a multi objective mixed integer programming model is developed to determine the amount of hiring, firing, training and overtime for each worker type.Findings: The results indicate that the worker differences should be considered in workforce scheduling to generate realistic plans with minimum costs. This paper also investigates the effects of human fatigue and recovery on the performance of the production systems.Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the model such as the assumption of certainty of the demand in each period, and the linearity function of Fatigue accumulation and recovery curves. These assumptions can be relaxed in future work.Originality/value: In this research, a new model for integrating workers’ differences with workforce scheduling is proposed. To the authors' knowledge, it is the first time to study the effects of different important human factors such as human personality, skills and fatigue and recovery in the workforce scheduling process. This research shows that considering both technical and human factors together can reduce the costs in manufacturing systems and ensure the safety of the workers.
Incorporating Satellite Time-Series Data into Modeling
Gregg, Watson
2008-01-01
In situ time series observations have provided a multi-decadal view of long-term changes in ocean biology. These observations are sufficiently reliable to enable discernment of even relatively small changes, and provide continuous information on a host of variables. Their key drawback is their limited domain. Satellite observations from ocean color sensors do not suffer the drawback of domain, and simultaneously view the global oceans. This attribute lends credence to their use in global and regional model validation and data assimilation. We focus on these applications using the NASA Ocean Biogeochemical Model. The enhancement of the satellite data using data assimilation is featured and the limitation of tongterm satellite data sets is also discussed.
Aircraft conceptual design modelling incorporating reliability and maintainability predictions
Vaziry-Zanjany , Mohammad Ali (F)
1996-01-01
A computer assisted conceptual aircraft design program has been developed (CACAD). It has an optimisation capability, with extensive break-down in maintenance costs. CACAD's aim is to optimise the size, and configurations of turbofan-powered transport aircraft. A methodology was developed to enhance the reliability of current aircraft systems, and was applied to avionics systems. R&M models of thermal management were developed and linked with avionics failure rate and its ma...
Nonlinear Dynamic Analysis of Multi-component Mooring Lines Incorporating Line-seabed Interaction
Directory of Open Access Journals (Sweden)
V.J. Kurian
2013-07-01
Full Text Available In this study, a deterministic approach for the dynamic analysis of a multi-component mooring line was formulated. The floater motion responses were considered as the mooring line upper boundary conditions while the anchored point was considered as pinned. Lumped parameter approach was adopted for the mooring line modelling. The forces considered were the submerged weights of mooring/attachment, physical/added inertia, line tension, fluid/line relative drag forces and line/seabed reactive forces. The latter interactions were modelled assuming that the mooring line rested on an elastic dissipative foundation. An iterative procedure for the dynamic analysis was developed and results for various mooring lines partially lying on different soils were obtained and validated by conducting a comparative study against published results. Good agreement between numerical and published experimental results was achieved. The contribution of the soil characteristics of the seabed to the dynamic behaviour of mooring line was investigated for different types of soil and reported.
Berg, van den, Aad; Meester, R.; White, Damien
1997-01-01
Consider an ordinary Boolean model, that is, a homogeneous Poisson point process in Rd, where the points are all centres of random balls with i.i.d. radii. Now let these points move around according to i.i.d. stochastic processes. It is not hard to show that at each xed time t we again have a Boolean model with the original distribution. Hence if the original model is supercritical then, for any t, the probability of having an unbounded occupied component at time t equals 1. We show that unde...
Amphiphilic poly-N-vinylpyrrolidone nanocarriers with incorporated model proteins
Energy Technology Data Exchange (ETDEWEB)
Kuskov, A N [Department of Polymers, D I Mendeleyev University of Chemical Technology, 9 Miusskaya Square, Moscow 125047 (Russian Federation); Villemson, A L [Department of Chemistry, M V Lomonosov Moscow State University, 119992 Moscow (Russian Federation); Shtilman, M I [Department of Polymers, D I Mendeleyev University of Chemical Technology, 9 Miusskaya Square, Moscow 125047 (Russian Federation); Larionova, N I [Department of Chemistry, M V Lomonosov Moscow State University, 119992 Moscow (Russian Federation); Tsatsakis, A M [Medical School, University of Crete, Voutes, 71409 Heraklion, Crete (Greece); Tsikalas, I [Department of Chemistry and Foundation for Research and Technology-Hellas (FORTH), University of Crete, PO Box 2208, Heraklion 71003, Crete (Greece); Rizos, A K [Department of Chemistry and Foundation for Research and Technology-Hellas (FORTH), University of Crete, PO Box 2208, Heraklion 71003, Crete (Greece)
2007-05-23
New nanoscaled polymeric carriers have been prepared on the basis of different amphiphilic water-soluble derivatives of poly-N-vinylpyrrolidone (PVP). The polymer self-assembly and interaction with model proteins (Bowman-Birk soybean proteinase inhibitor (BBI) and its hydrophobized derivatives) were studied in aqueous media. The possibility of inclusion of both BBI and hydrophobized oleic acid derivatives of BBI in amphiphilic PVP aggregates was investigated. It was ascertained that polymeric particles of size 50-80 nm were formed in certain concentrations of amphiphilic PVP and poorly soluble dioleic acid derivatives of BBI. Such polymeric aggregates are capable of solubilization of dioleoyl BBI with a concomitant prevention of its inactivation at low pH values.
Amphiphilic poly-N-vinylpyrrolidone nanocarriers with incorporated model proteins
Kuskov, A. N.; Villemson, A. L.; Shtilman, M. I.; Larionova, N. I.; Tsatsakis, A. M.; Tsikalas, I.; Rizos, A. K.
2007-05-01
New nanoscaled polymeric carriers have been prepared on the basis of different amphiphilic water-soluble derivatives of poly-N-vinylpyrrolidone (PVP). The polymer self-assembly and interaction with model proteins (Bowman-Birk soybean proteinase inhibitor (BBI) and its hydrophobized derivatives) were studied in aqueous media. The possibility of inclusion of both BBI and hydrophobized oleic acid derivatives of BBI in amphiphilic PVP aggregates was investigated. It was ascertained that polymeric particles of size 50-80 nm were formed in certain concentrations of amphiphilic PVP and poorly soluble dioleic acid derivatives of BBI. Such polymeric aggregates are capable of solubilization of dioleoyl BBI with a concomitant prevention of its inactivation at low pH values.
Modelling group dynamic animal movement
DEFF Research Database (Denmark)
Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.
2014-01-01
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......, 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...... 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...
National Research Council Canada - National Science Library
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...
Dynamical model for Pion-Nucleon Bremsstrahlung
Mariano, A V
2000-01-01
A dynamical model based on effective Lagrangians is proposed to describe the bremsstrahlung reaction $ \\pi N \\to \\pi N \\gamma$ at low energies. The $\\Delta(1232)$ degrees of freedom are incorporated in a way consistent with both, electromagnetic gauge invariance and invariance under contact transformations. The model also includes the initial and final state rescattering of hadrons via a T-matrix with off-shell effects. The $\\pi N \\gamma$ differential cross sections are calculated using three different T-matrix models and the results are compared with the soft photon approximation, and with experimental data. The aim of this analysis is to test the off-shell behavior of the different T-matrices under consideration.
Tripathi, Jai Prakash; Abbas, Syed; Thakur, Manoj
2015-05-01
This paper describes a predator-prey model incorporating a prey refuge. The feeding rate of consumers (predators) per consumer (i.e. functional response) is considered to be of Beddington-DeAngelis type. The Beddington-DeAngelis functional response is similar to the Holling-type II functional response but contains an extra term describing mutual interference by predators. We investigate the role of prey refuge and degree of mutual interference among predators in the dynamics of system. The dynamics of the system is discussed mainly from the point of view of permanence and stability. We obtain conditions that affect the persistence of the system. Local and global asymptotic stability of various equilibrium solutions is explored to understand the dynamics of the model system. The global asymptotic stability of positive interior equilibrium solution is established using suitable Lyapunov functional. The dynamical behaviour of the delayed system is further analyzed through incorporating discrete type gestation delay of predator. It is found that Hopf bifurcation occurs when the delay parameter τ crosses some critical value. The analytical results found in the paper are illustrated with the help of numerical examples.
Gabora, Liane
2008-01-01
EVOC (for EVOlution of Culture) is a computer model of culture that enables us to investigate how various factors such as barriers to cultural diffusion, the presence and choice of leaders, or changes in the ratio of innovation to imitation affect the diversity and effectiveness of ideas. It consists of neural network based agents that invent ideas for actions, and imitate neighbors' actions. The model is based on a theory of culture according to which what evolves through culture is not memes or artifacts, but the internal models of the world that give rise to them, and they evolve not through a Darwinian process of competitive exclusion but a Lamarckian process involving exchange of innovation protocols. EVOC shows an increase in mean fitness of actions over time, and an increase and then decrease in the diversity of actions. Diversity of actions is positively correlated with population size and density, and with barriers between populations. Slowly eroding borders increase fitness without sacrificing diver...
Crowther, Michael J; Andersson, Therese M-L; Lambert, Paul C; Abrams, Keith R; Humphreys, Keith
2016-03-30
A now common goal in medical research is to investigate the inter-relationships between a repeatedly measured biomarker, measured with error, and the time to an event of interest. This form of question can be tackled with a joint longitudinal-survival model, with the most common approach combining a longitudinal mixed effects model with a proportional hazards survival model, where the models are linked through shared random effects. In this article, we look at incorporating delayed entry (left truncation), which has received relatively little attention. The extension to delayed entry requires a second set of numerical integration, beyond that required in a standard joint model. We therefore implement two sets of fully adaptive Gauss-Hermite quadrature with nested Gauss-Kronrod quadrature (to allow time-dependent association structures), conducted simultaneously, to evaluate the likelihood. We evaluate fully adaptive quadrature compared with previously proposed non-adaptive quadrature through a simulation study, showing substantial improvements, both in terms of minimising bias and reducing computation time. We further investigate, through simulation, the consequences of misspecifying the longitudinal trajectory and its impact on estimates of association. Our scenarios showed the current value association structure to be very robust, compared with the rate of change that we found to be highly sensitive showing that assuming a simpler trend when the truth is more complex can lead to substantial bias. With emphasis on flexible parametric approaches, we generalise previous models by proposing the use of polynomials or splines to capture the longitudinal trend and restricted cubic splines to model the baseline log hazard function. The methods are illustrated on a dataset of breast cancer patients, modelling mammographic density jointly with survival, where we show how to incorporate density measurements prior to the at-risk period, to make use of all the available
Swimmers’ Collective Dynamics Modelization
Ferré Porta, Guillem
2011-01-01
English: We describe a new model in order to study the properties of collections of self-propelled particles swimming in a two-dimensional fluid. Our model consist in two types of particles, the first interacting with each other with a soft potential and thus representing the fluid while the second type are self-propelled particles of biological nature capable of changing its orientation following the velocity field of the fluid. The results of the simulations show how a super-diffusive regim...
Model of THz Magnetization Dynamics
Bocklage, Lars
2016-01-01
Magnetization dynamics can be coherently controlled by THz laser excitation, which can be applied in ultrafast magnetization control and switching. Here, transient magnetization dynamics are calculated for excitation with THz magnetic field pulses. We use the ansatz of Smit and Beljers, to formulate dynamic properties of the magnetization via partial derivatives of the samples free energy density, and extend it to solve the Landau-Lifshitz-equation to obtain the THz transients of the magnetization. The model is used to determine the magnetization response to ultrafast multi- and single-cycle THz pulses. Control of the magnetization trajectory by utilizing the THz pulse shape and polarization is demonstrated. PMID:26956997
Modeling Internet Topology Dynamics
Haddadi, H.; Uhlig, S.; Moore, A.; Mortier, R.; Rio, M.
Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. While recent findings have illustrated the inaccuracies in maps inferred from BGP peering and traceroute measurements, exist
Vehicle dynamics modeling and simulation
Schramm, Dieter; Bardini, Roberto
2014-01-01
The authors examine in detail the fundamentals and mathematical descriptions of the dynamics of automobiles. In this context different levels of complexity will be presented, starting with basic single-track models up to complex three-dimensional multi-body models. A particular focus is on the process of establishing mathematical models on the basis of real cars and the validation of simulation results. The methods presented are explained in detail by means of selected application scenarios.
Indian Academy of Sciences (India)
Anirudh Guha; G Narayanan
2016-02-01
The objective of this paper is to study the influence of inverter dead-time on steady as well as dynamic operation of an open-loop induction motor drive fed from a voltage source inverter (VSI). Towards this goal, this paper presents a systematic derivation of a dynamic model for an inverter-fed induction motor, incorporating the effect of inverter dead-time, in the synchronously revolving dq reference frame. Simulation results based on this dynamic model bring out the impact of inverter dead-time on both the transient response and steady-state operation of the motor drive. For the purpose of steady-state analysis, the dynamic model of the motor drive is used to derive a steady-state model, which is found to be non-linear. The steady-state model shows that the impact of dead-time can be seen as an additional resistance in the stator circuit, whose value depends on the stator current. Towards precise evaluation of this dead-time equivalent resistance, an analytical expression is proposed for the same in terms of inverter dead-time, switching frequency, modulation index and load impedance. The notion of dead-time equivalent resistance is shown to simplify the solution of the non-linear steady-state model. The analytically evaluated steady-state solutions are validated through numerical simulations and experiments.
Dynamic Pathloss Model for Future Mobile Communication Networks
DEFF Research Database (Denmark)
Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee
2016-01-01
— Future mobile communication networks (MCNs) are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network...... that incorporates the environmental dynamics factor in the propagation model for intelligent and proactively iterative networks...
Dynamic Characteristics and Models
DEFF Research Database (Denmark)
Pedersen, Lars
2007-01-01
Vibration levels of flooring-systems are generally difficult to predict. Nevertheless an estimate may be needed for flooring-systems that are prone to vibrate to actions of humans in motion (e.g. grandstands, footbridges or long-span office floors). One reason for the difficulties...... and the paper therefore looks into this mechanism which is done by carrying out controlled modal identification tests on a test floor. The paper describes the experimental investigations and the basic principles adopted for modal identification. Since there is an interest in being able to model the scenario...
Energy Technology Data Exchange (ETDEWEB)
Pfeffer, A; Das, S; Lawless, D; Ng, B
2006-10-10
Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.
On the formulation of the dynamic mixed subgrid-scale model
Vreman, A.W.; Geurts, Bernardus J.; Kuerten, Johannes G.M.
1994-01-01
The dynamic mixed subgrid‐scale model of Zang et al. [Phys. Fluids A 5, 3186 (1993)] (DMM1) is modified with respect to the incorporation of the similarity model in order to remove a mathematical inconsistency. Compared to DMM1, the magnitude of the dynamic model coefficient of the modified model
Organic production in a dynamic CGE model
DEFF Research Database (Denmark)
Jacobsen, Lars Bo
2004-01-01
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...... to illustrate the working of our theory by constructing a long term forecast for the development of the Danish economy. Moreover we simulate the effect of the recent agreed 2003 reform of the common agricultural policy....
Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor
Reed, Sasha C.; Yang, Xiaojuan; Thornton, Peter E.
2015-01-01
Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO2 exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate–carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate–carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward.
Directory of Open Access Journals (Sweden)
Justin Douglas Yeakel
2016-01-01
Full Text Available Consumer foraging behaviors are dynamic, changing in response to prey availability, seasonality, competition, and even the consumer's physiological state. The isotopic composition of a consumer is a product of these factors as well as the isotopic `landscape' of its prey, i.e. the isotopic mixing space. Stable isotope mixing models are used to back-calculate the most likely proportional contribution of a set of prey to a consumer's diet based on their respective isotopic distributions, however they are disconnected from ecological process. Here we build a mechanistic framework that links the ecological and physiological processes of an individual consumer to the isotopic distribution that describes its diet, and ultimately to the isotopic composition of its own tissues, defined as its `isotopic niche’. By coupling these processes, we systematically investigate under what conditions the isotopic niche of a consumer changes as a function of both the geometric properties of its mixing space and foraging strategies that may be static or dynamic over time. Results of our derivations reveal general insight into the conditions impacting isotopic niche width as a function of consumer specialization on prey, as well as the consumer's ability to transition between diets over time. We show analytically that moderate specialization on isotopically unique prey can serve to maximize a consumer's isotopic niche width, while temporally dynamic diets will tend to result in peak isotopic variance during dietary transitions. We demonstrate the relevance of our theoretical findings by examining a marine system composed of nine invertebrate species commonly consumed by sea otters. In general, our analytical framework highlights the complex interplay of mixing space geometry and consumer dietary behavior in driving expansion and contraction of the isotopic niche. Because this approach is established on ecological mechanism, it is well-suited for enhancing the
Using Unlabeled Data to Improve Inductive Models by Incorporating Transductive Models
Directory of Open Access Journals (Sweden)
ShengJun Cheng
2014-02-01
Full Text Available This paper shows how to use labeled and unlabeled data to improve inductive models with the help of transductivemodels.We proposed a solution for the self-training scenario. Self- training is an effective semi-supervised wrapper method which can generalize any type of supervised inductive model to the semi-supervised settings. it iteratively refines a inductive model by bootstrap from unlabeled data. Standard self-training uses the classifier model(trained on labeled examples to label and select candidates from the unlabeled training set, which may be problematic since the initial classifier may not be able to provide highly confident predictions as labeled training data is always rare. As a result, it could always suffer from introducing too much wrongly labeled candidates to the labeled training set, which may severely degrades performance. To tackle this problem, we propose a novel self-training style algorithm which incorporate a graph-based transductive model in the self-labeling process. Unlike standard self-training, our algorithm utilizes labeled and unlabeled data as a whole to label and select unlabeled examples for training set augmentation. A robust transductive model based on graph markov random walk is proposed, which exploits manifold assumption to output reliable predictions on unlabeled data using noisy labeled examples. The proposed algorithm can greatly minimize the risk of performance degradation due to accumulated noise in the training set. Experiments show that the proposed algorithm can effectively utilize unlabeled data to improve classification performance.
Experimental Modeling of Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten Haack
2006-01-01
An engineering course, Simulation and Experimental Modeling, has been developed that is based on a method for direct estimation of physical parameters in dynamic systems. Compared with classical system identification, the method appears to be easier to understand, apply, and combine with physical...
Nonlinear Dynamic Model Explains The Solar Dynamic
Kuman, Maria
Nonlinear mathematical model in torus representation describes the solar dynamic. Its graphic presentation shows that without perturbing force the orbits of the planets would be circles; only perturbing force could elongate the circular orbits into ellipses. Since the Hubble telescope found that the planetary orbits of other stars in the Milky Way are also ellipses, powerful perturbing force must be present in our galaxy. Such perturbing force is the Sagittarius Dwarf Galaxy with its heavy Black Hole and leftover stars, which we see orbiting around the center of our galaxy. Since observations of NASA's SDO found that magnetic fields rule the solar activity, we can expect when the planets align and their magnetic moments sum up, the already perturbed stars to reverse their magnetic parity (represented graphically as periodic looping through the hole of the torus). We predict that planets aligned on both sides of the Sun, when their magnetic moments sum-up, would induce more flares in the turbulent equatorial zone, which would bulge. When planets align only on one side of the Sun, the strong magnetic gradient of their asymmetric pull would flip the magnetic poles of the Sun. The Sun would elongate pole-to-pole, emit some energy through the poles, and the solar activity would cease. Similar reshaping and emission was observed in stars called magnetars and experimentally observed in super-liquid fast-spinning Helium nanodroplets. We are certain that NASA's SDO will confirm our predictions.
Directory of Open Access Journals (Sweden)
Florian Ion Tiberiu Petrescu
2016-03-01
Full Text Available Otto engine dynamics are similar in almost all common internal combustion engines. We can speak so about dynamics of engines: Lenoir, Otto, and Diesel. The dynamic presented model is simple and original. The first thing necessary in the calculation of Otto engine dynamics, is to determine the inertial mass reduced at the piston. One uses then the Lagrange equation. Kinetic energy conservation shows angular speed variation (from the shaft with inertial masses. One uses and elastic constant of the crank shaft, k. Calculations should be made for an engine with a single cylinder. Finally it makes a dynamic analysis of the mechanism with discussion and conclusions. The ratio between the crank length r and the length of the connecting-rod l is noted with landa. When landa increases the mechanism dynamics is deteriorating. For a proper operation is necessary the reduction of the ratio landa, especially if we want to increase the engine speed. We can reduce the acceleration values by reducing the dimensions r and l.
Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Khaled, Bilal; Shyamsunder, Loukham; Rajan, Subramaniam; Blankenhorn, Gunther
2017-01-01
The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. In the damage model, a semi-coupled approach is employed where the overall damage in a particular coordinate direction is assumed to be a multiplicative combination of the damage in that direction resulting from the applied loads in various coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current
A new model for in situ nitrogen incorporation into 4H-SiC during epitaxy
Ferro, Gabriel; Chaussende, Didier
2017-02-01
Nitrogen doping of 4H-SiC during vapor phase epitaxy is still lacking of a general model explaining the apparently contradictory trends obtained by different teams. In this paper, the evolutions of nitrogen incorporation (on both polar Si and C faces) as a function of the main growth parameters (C/Si ratio, temperature, pressure and growth rate) are reviewed and explained using a model based on surface exchanges between the gas phase and the uppermost 4H-SiC atomic layers. In this model, N incorporation is driven mainly by the transient formation of C vacancies, due to H2 etching, at the surface or near the surface. It is shown that all the growth parameters are influencing the probability of C vacancies formation in a similar manner as they do for N incorporation. The surface exchange model proposes a new framework for explaining the experimental results even beyond the commonly accepted reactor type dependency.
Dynamics modeling and simulation of mechanism with joint clearance
Institute of Scientific and Technical Information of China (English)
BAI Zheng-feng; TIAN Hao; ZHAO Yang
2010-01-01
The existence of clearance in the joints of mechanisms system is inevitable.The movements of the real mechanism are deftection from the ideal mechanism due to the clearances and the motion accuracv is decreased.The effects of the hinge clearance on the crank and rocker mechanism system are studied.The svstem dynamics equation with clearance is presented.The contact dynamics model is established using the nonlinear equivalent spring-damp model and the friction effect is considered by using Coulomb friction model.Then the models are incorporated into ADAMS,and based on the model,large numbers numeric simulations are made.The regularity of contact forces in clearance are studied in detail.And the effects of clearance size.clearance friction on the mechanism dynamics characteristic are analyzed.The simulation resuhs Can predict the effects of clearance on the mechanism dynamics characteristic preferably.
Business model dynamics and innovation
DEFF Research Database (Denmark)
Cavalcante, Sergio Andre; Kesting, Peter; Ulhøi, John Parm
2011-01-01
Purpose – This paper aims to discuss the need to dynamize the existing conceptualization of business model, and proposes a new typology to distinguish different types of business model change. Design/methodology/approach – The paper integrates basic insights of innovation, business process...... and routine research into the concept of business model. The main focus of the paper is on strategic and terminological issues. Findings – The paper offers a new, process-based conceptualization of business model, which recognizes and integrates the role of individual agency. Based on this, it distinguishes...... and specifies four different types of business model change: business model creation, extension, revision, and termination. Each type of business model change is associated with specific challenges. Practical implications – The proposed typology can serve as a basis for developing a management tool to evaluate...
DYNAMIC TEACHING RATIO PEDAGOGIC MODEL
Directory of Open Access Journals (Sweden)
Chen Jiaying
2010-11-01
Full Text Available This paper outlines an innovative pedagogic model, Dynamic Teaching Ratio (DTR Pedagogic Model, for learning design and teaching strategy aimed at the postsecondary technical education. The model draws on the theory of differential learning, which is widely recognized as an important tool for engaging students and addressing the individual needs of all students. The DTR model caters to the different abilities, interest or learning needs of students and provides different learning approaches based on a student’s learning ability. The model aims to improve students’ academic performance through increasing the lecturer-to-student ratio in the classroom setting. An experimental case study on the model was conducted and the outcome was favourable. Hence, a large-scale implementation was carried out upon the successful trial run. The paper discusses the methodology of the model and its application through the case study and the large-scale implementation.
DYNAMIC MODELING OF METAMORPHIC MECHANISM
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
The concept of metamorphic mechanism is put forward according to the change of configurations from one state to another. Different configurations of metamorphic mechanism are described through the method of Huston lower body arrays. Kinematics analyses for metamorphic mechanism with generalized topological structure, including the velocity, angular velocity, acceleration and angular acceleration, are given. Dynamic equations for an arbitrary configuration, including close-loop constraints, are formed by using Kane's equations. For an arbitrary metamorphic mechanism, the transformation matrix of generalized speeds between configuration (*)and(*)+1 is obtained for the first time. Furthermore, configuration-complete dynamic modeling of metamorphic mechanism including all configurations is completely established.
Stochastic Model of Microtubule Dynamics
Hryniv, Ostap; Martínez Esteban, Antonio
2017-10-01
We introduce a continuous time stochastic process on strings made of two types of particle, whose dynamics mimics that of microtubules in a living cell. The long term behaviour of the system is described in terms of the velocity v of the string end. We show that v is an analytic function of its parameters and study its monotonicity properties. We give a complete characterisation of the phase diagram of the model and derive several criteria of the growth (v>0) and the shrinking (v<0) regimes of the dynamics.
Dynamical Modelling of Meteoroid Streams
Clark, David; Wiegert, P. A.
2012-10-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and
Yu, Tung Fai; Wilson, Adrian J
2014-05-01
In this paper we present an experimental method of parameterising the passive mechanical characteristics of the bicep and tricep muscles in vivo, by fitting the dynamics of a two muscle arm model incorporating anatomically meaningful and structurally identifiable modified Hill muscle models to measured elbow movements. Measurements of the passive flexion and extension of the elbow joint were obtained using 3D motion capture, from which the elbow angle trajectories were determined and used to obtain the spring constants and damping coefficients in the model through parameter estimation. Four healthy subjects were used in the experiments. Anatomical lengths and moment of inertia values of the subjects were determined by direct measurement and calculation. There was good reproducibility in the measured arm movement between trials, and similar joint angle trajectory characteristics were seen between subjects. Each subject had their own set of fitted parameter values determined and the results showed good agreement between measured and simulated data. The average fitted muscle parallel spring constant across all subjects was 143 N/m and the average fitted muscle parallel damping constant was 1.73 Ns/m. The passive movement method was proven to be successful, and can be applied to other joints in the human body, where muscles with similar actions are grouped together. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Dynamic Model of Mesoscale Eddies
Dubovikov, Mikhail S.
2003-04-01
Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV
Dynamic queuing transmission model for dynamic network loading
DEFF Research Database (Denmark)
Raovic, Nevena; Nielsen, Otto Anker; Prato, Carlo Giacomo
2017-01-01
This paper presents a new macroscopic multi-class dynamic network loading model called Dynamic Queuing Transmission Model (DQTM). The model utilizes ‘good’ properties of the Dynamic Queuing Model (DQM) and the Link Transmission Model (LTM) by offering a DQM consistent with the kinematic wave theory...... and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared...
Peng, Guanghan; He, Hongdi; Lu, Wei-Zhen
2016-01-01
In this paper, a new car-following model is proposed with the consideration of the incorporating timid and aggressive behaviors on single lane. The linear stability condition with the incorporating timid and aggressive behaviors term is obtained. Numerical simulation indicates that the new car-following model can estimate proper delay time of car motion and kinematic wave speed at jam density by considering the incorporating the timid and aggressive behaviors. The results also show that the aggressive behavior can improve traffic flow while the timid behavior deteriorates traffic stability, which means that the aggressive behavior is better than timid behavior since the aggressive driver makes rapid response to the variation of the velocity of the leading car. Snapshot of the velocities also shows that the new model can approach approximation to a wide moving jam.
Incorporation of the capillary hysteresis model HYSTR into the numerical code TOUGH
Energy Technology Data Exchange (ETDEWEB)
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.
Relating structure and dynamics in organisation models
Jonkers, C.M.; Treur, J.
To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems,
Bias associated with failing to incorporate dependence on event history in Markov models.
Bentley, Tanya G K; Kuntz, Karen M; Ringel, Jeanne S
2010-01-01
When using state-transition Markov models to simulate risk of recurrent events over time, incorporating dependence on higher numbers of prior episodes can increase model complexity, yet failing to capture this event history may bias model outcomes. This analysis assessed the tradeoffs between model bias and complexity when evaluating risks of recurrent events in Markov models. The authors developed a generic episode/relapse Markov cohort model, defining bias as the percentage change in events prevented with 2 hypothetical interventions (prevention and treatment) when incorporating 0 to 9 prior episodes in relapse risk versus a model with 10 such episodes. Magnitude and sign of bias were evaluated as a function of event and recovery risks, disease-specific mortality, and risk function. Bias was positive in the base case for a prevention strategy, indicating that failing to fully incorporate dependence on event history overestimated the prevention's predicted impact. For treatment, the bias was negative, indicating an underestimated benefit. Bias approached zero as the number of tracked prior episodes increased, and the average bias over 10 tracked episodes was greater with the exponential compared with linear functions of relapse risk and with treatment compared with prevention strategies. With linear and exponential risk functions, absolute bias reached 33% and 78%, respectively, in prevention and 52% and 85% in treatment. Failing to incorporate dependence on prior event history in subsequent relapse risk in Markov models can greatly affect model outcomes, overestimating the impact of prevention and treatment strategies by up to 85% and underestimating the impact in some treatment models by up to 20%. When at least 4 prior episodes are incorporated, bias does not exceed 26% in prevention or 11% in treatment.
Multifractal Model of Asset Returns versus real stock market dynamics
Oswiecimka, P; Drozdz, S; Górski, A Z; Rak, R
2006-01-01
There is more and more empirical evidence that multifractality constitutes another and perhaps the most significant financial stylized fact. A realistic model of the financial dynamics should therefore incorporate this effect. The most promising in this respect is the Multifractal Model of Asset Returns (MMAR) introduced by Mandelbrot in which multifractality is carried by time deformation. In our study we focus on the Lux extension to MMAR and empirical data from Warsaw Stock Exchange. We show that this model is able to reproduce relevant aspects of the real stock market dynamics.
Stirling Engine Dynamic System Modeling
Nakis, Christopher G.
2004-01-01
The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.
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...
Paynter, Stuart
2016-03-15
Conventional measures of causality (which compare risks between exposed and unexposed individuals) do not factor in the population-scale dynamics of infectious disease transmission. We used mathematical models of 2 childhood infections (respiratory syncytial virus and rotavirus) to illustrate this problem. These models incorporated 3 causal pathways whereby malnutrition could act to increase the incidence of severe infection: increasing the proportion of infected children who develop severe infection, increasing the children's susceptibility to infection, and increasing infectiousness. For risk factors that increased the proportion of infected children who developed severe infection, the population attributable fraction (PAF) calculated conventionally was the same as the PAF calculated directly from the models. However, for risk factors that increased transmission (by either increasing susceptibility to infection or increasing infectiousness), the PAF calculated directly from the models was much larger than that predicted by the conventional PAF calculation. The models also showed that even when conventional studies find no association between a risk factor and an outcome, risk factors that increase transmission can still have a large impact on disease burden. For a complete picture of infectious disease causality, transmission effects must be incorporated into causal models.
The direction of migration: a dynamic general equilibrium model.
Lee, K S
1984-11-01
A two-sector dynamic general equilibrium model is developed "to investigate the direction of migration in response to differing demographic and consumption demand behavior, as well as variations in production conditions." The model, which involves a rural sector and an urban sector, incorporates "returns to scale and the natural rate of sectoral population growth as important determinants of the direction of migration, in addition to price and income elasticities, and the sectoral technical change rate with which...previous studies dealt."
The Dynamics of the Uzawa- Lucas Model with Unskilled Labor
Institute of Scientific and Technical Information of China (English)
Ma Su-yan; Cai Dong-han
2004-01-01
The existence and uniqueness of the modified Uzawa-Lucas growth model which incorporates unskilled labor as a distinct factor from human capital are given and the dynamics of the model is presented. Furthermore, the varieties of the time allocation to the physical and human capital production along the optimal path and the affections of fertility and the natural growth rate of human capital on economic growth are discussed.
Wang, Jian-Xun; Xiao, Heng
2015-01-01
Simulations based on Reynolds-Averaged Navier--Stokes (RANS) models have been used to support high-consequence decisions related to turbulent flows. Apart from the deterministic model predictions, the decision makers are often equally concerned about the predictions confidence. Among the uncertainties in RANS simulations, the model-form uncertainty is an important or even a dominant source. Therefore, quantifying and reducing the model-form uncertainties in RANS simulations are of critical importance to make risk-informed decisions. Researchers in statistics communities have made efforts on this issue by considering numerical models as black boxes. However, this physics-neutral approach is not a most efficient use of data, and is not practical for most engineering problems. Recently, we proposed an open-box, Bayesian framework for quantifying and reducing model-form uncertainties in RANS simulations by incorporating observation data and physics-prior knowledge. It can incorporate the information from the vast...
Brisbin, Abra; Fridley, Brooke L
2013-08-01
Pathway topology and relationships between genes have the potential to provide information for modeling effects of mRNA gene expression on complex traits. For example, researchers may wish to incorporate the prior belief that "hub" genes (genes with many neighbors) are more likely to influence the trait. In this paper, we propose and compare six Bayesian pathway-based prior models to incorporate pathway topology information into association analyses. Including prior information regarding the relationships among genes in a pathway was effective in somewhat improving detection rates for genes associated with complex traits. Through an extensive set of simulations, we found that when hub (central) effects are expected, the diagonal degree model is preferred; when spoke (edge) effects are expected, the spatial power model is preferred. When there is no prior knowledge about the location of the effect genes in the pathway (e.g., hub versus spoke model), it is worthwhile to apply multiple models, as the model with the best DIC is not always the one with the best detection rate. We also applied the models to pharmacogenomic studies for the drugs gemcitabine and 6-mercaptopurine and found that the diagonal degree model identified an association between 6-mercaptopurine response and expression of the gene SLC28A3, which was not detectable using the model including no pathway information. These results demonstrate the value of incorporating pathway information into association analyses.
Absorptive capacity, technological innovation, and product life cycle: a system dynamics model
National Research Council Canada - National Science Library
Zou, Bo; Guo, Feng; Guo, Jinyu
2016-01-01
.... 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...
Dynamics Modeling of Heavy Special Driving Simulator
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Based on the dynamical characteristic parameters of the real vehicle, the modeling approach and procedure of dynamics of vehicles are expatiated. The layout of vehicle dynamics is proposed, and the sub-models of the diesel engine, drivetrain system and vehicle multi-body dynamics are introduced. Finally, the running characteristic data of the virtual and real vehicles are compared, which shows that the dynamics model is similar closely to the real vehicle system.
Goldstein, Harvey; Leckie, George; Charlton, Christopher; Tilling, Kate; Browne, William J
2017-01-01
Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subjects and methods A Bayesian model is developed that includes random effects for the mean growth function, an individual age-alignment random effect and random effects for the within-individual variance function. This model is applied to data on boys' heights from the Edinburgh longitudinal growth study and to repeated weight measurements of a sample of pregnant women in the Avon Longitudinal Study of Parents and Children cohort. Results The mean age at which the growth curves for individual boys are aligned is 11.4 years, corresponding to the mean 'take off' age for pubertal growth. The within-individual variance (standard deviation) is found to decrease from 0.24 cm(2) (0.50 cm) at 9 years for the 'average' boy to 0.07 cm(2) (0.25 cm) at 16 years. Change in weight during pregnancy can be characterised by regression splines with random effects that include a large woman-specific random effect for the within-individual variation, which is also correlated with overall weight and weight gain. Conclusions The proposed model provides a useful extension to existing approaches, allowing considerable flexibility in describing within- and between-individual differences in growth patterns.
Models of ungulate population dynamics
Directory of Open Access Journals (Sweden)
L. L. Eberhardt
1991-10-01
Full Text Available A useful theory for analyzing ungulate population dynamics is available in the form of equations based on the work of A. J. Lotka. Because the Leslie matrix model yields identical results and is widely known, it is convenient to label the resulting equations as the "Lotka-Leslie" model. The approach is useful for assessing population trends and attempting to predict the outcomes of various management actions. A broad list of applications to large mammals, and two examples specific to caribou are presented with a simple spreadsheet approach to calculations.
Chowdhury, Nadim; Azim, Zubair Al; Alam, Md Hasibul; Niaz, Iftikhar Ahmad; Khosru, Quazi D M
2014-01-01
We propose a physically based analytical compact model to calculate Eigen energies and Wave functions which incorporates penetration effect. The model is applicable for a quantum well structure that frequently appears in modern nano-scale devices. This model is equally applicable for both silicon and III-V devices. Unlike other models already available in the literature, our model can accurately predict all the eigen energies without the inclusion of any fitting parameters. The validity of our model has been checked with numerical simulations and the results show significantly better agreement compared to the available methods.
Dynamical model of brushite precipitation
Oliveira, Cristina; Georgieva, Petia; Rocha, Fernando; Ferreira, António; Feyo de Azevedo, Sebastião
2007-07-01
The objectives of this work are twofold. From academic point of view the aim is to build a dynamical macro model to fit the material balance and explain the main kinetic mechanisms that govern the transformation of the hydroxyapatite (HAP) into brushite and the growth of brushite, based on laboratory experiments and collected database. From practical point of view, the aim is to design a reliable process simulator that can be easily imbedded in industrial software for model driven monitoring, optimization and control purposes. Based upon a databank of laboratory measurements of the calcium concentration in solution (on-line) and the particle size distribution (off-line) a reliable dynamical model of the dual nature of brushite particle formation for a range of initial concentrations of the reagents was derived as a system of ordinary differential equations of time. The performance of the model is tested with respect to the predicted evolution of mass of calcium in solution and the average (in mass) particle size along time. Results obtained demonstrate a good agreement between the model time trajectories and the available experimental data for a number of different initial concentrations of reagents.
Antle, J.M.; Stoorvogel, J.J.
2006-01-01
Agricultural systems are complex and dynamic, being made up of interacting bio-physical and human sub-systems. Moreover, agricultural systems are remarkably diverse, both within geographic regions and across regions. Accordingly, this paper focuses on dynamics and heterogeneity in coupled, multi-dis
Computational fluid dynamics modelling in cardiovascular medicine.
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.
Liu, Helin; Silva, Elisabete A.; Wang, Qian
2016-07-01
This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.
Dynamic pricing models for electronic business
Indian Academy of Sciences (India)
Y Narahari; C V L Raju; K Ravikumar; Sourabh Shah
2005-04-01
Dynamic pricing is the dynamic adjustment of prices to consumers depending upon the value these customers attribute to a product or service. Today’s digital economy is ready for dynamic pricing; however recent research has shown that the prices will have to be adjusted in fairly sophisticated ways, based on sound mathematical models, to derive the beneﬁts of dynamic pricing. This article attempts to survey different models that have been used in dynamic pricing. We ﬁrst motivate dynamic pricing and present underlying concepts, with several examples, and explain conditions under which dynamic pricing is likely to succeed. We then bring out the role of models in computing dynamic prices. The models surveyed include inventory-based models, data-driven models, auctions, and machine learning. We present a detailed example of an e-business market to show the use of reinforcement learning in dynamic pricing.
A new experimental procedure for incorporation of model contaminants in polymer hosts
Papaspyrides, C.D.; Voultzatis, Y.; Pavlidou, S.; Tsenoglou, C.; Dole, P.; Feigenbaum, A.; Paseiro, P.; Pastorelli, S.; Cruz Garcia, C. de la; Hankemeier, T.; Aucejo, S.
2005-01-01
A new experimental procedure for incorporation of model contaminants in polymers was developed as part of a general scheme for testing the efficiency of functional barriers in food packaging. The aim was to progressively pollute polymers in a controlled fashion up to a high level in the range of 100
75 FR 56487 - Airworthiness Directives; Erickson Air-Crane Incorporated Model S-64F Helicopters
2010-09-16
... Federal Aviation Administration 14 CFR Part 39 RIN 2120-AA64 Airworthiness Directives; Erickson Air-Crane... rulemaking (NPRM). SUMMARY: This document proposes adopting a new airworthiness directive (AD) for Erickson Air-Crane Incorporated (Erickson Air-Crane) Model S- 64F helicopters. The AD would require, at...
A new experimental procedure for incorporation of model contaminants in polymer hosts
Papaspyrides, C.D.; Voultzatis, Y.; Pavlidou, S.; Tsenoglou, C.; Dole, P.; Feigenbaum, A.; Paseiro, P.; Pastorelli, S.; Cruz Garcia, C. de la; Hankemeier, T.; Aucejo, S.
2005-01-01
A new experimental procedure for incorporation of model contaminants in polymers was developed as part of a general scheme for testing the efficiency of functional barriers in food packaging. The aim was to progressively pollute polymers in a controlled fashion up to a high level in the range of 100
The Forced Choice Dilemma: A Model Incorporating Idiocentric/Allocentric Cultural Orientation
Jung, Jae Yup; McCormick, John; Gross, Miraca U. M.
2012-01-01
This study developed and tested a new model of the forced choice dilemma (i.e., the belief held by some intellectually gifted students that they must choose between academic achievement and peer acceptance) that incorporates individual-level cultural orientation variables (i.e., vertical allocentrism and vertical idiocentrism). A survey that had…
SPARC Groups: A Model for Incorporating Spiritual Psychoeducation into Group Work
Christmas, Christopher; Van Horn, Stacy M.
2012-01-01
The use of spirituality as a resource for clients within the counseling field is growing; however, the primary focus has been on individual therapy. The purpose of this article is to provide counseling practitioners, administrators, and researchers with an approach for incorporating spiritual psychoeducation into group work. The proposed model can…
Kok, de Jean-Luc; Titus, Milan; Wind, Herman G.
2000-01-01
Decision-support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not
Incorporation of composite defects from ultrasonic NDE into CAD and FE models
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.
Modelling of the Manifold Filling Dynamics
DEFF Research Database (Denmark)
Hendricks, Elbert; Chevalier, Alain Marie Roger; Jensen, Michael
1996-01-01
Mean Value Engine Models (MVEMs) are dynamic models which describe dynamic engine variable (or state) responses on time scales slightly longer than an engine event. This paper describes a new model of the intake manifold filling dynamics which is simple and easy to calibrate for use in engine con...
Sankaran, Shrikrishnan; Kiren, Mustafa Can; Jonkheijm, Pascal
2015-01-01
Supramolecular assemblies, formed through noncovalent interactions, has become particularly attractive to develop dynamic and responsive architectures to address living systems at the nanoscale. Cucurbit[8]uril (CB[8]), a pumpkin shaped macrocylic host molecule, has been successfully used to constru
Sankaran, S.; Kiren, Mustafa Can; Jonkheijm, Pascal
2015-01-01
Supramolecular assemblies, formed through noncovalent interactions, has become particularly attractive to develop dynamic and responsive architectures to address living systems at the nanoscale. Cucurbit[8]uril (CB[8]), a pumpkin shaped macrocylic host molecule, has been successfully used to
Incorporating sorption/desorption of organic pollutants into river water quality model
Institute of Scientific and Technical Information of China (English)
LOU Bao-feng; ZHU Li-zhong; YANG Kun
2004-01-01
Preliminary research was conducted about how to incorporate sorption/desorption of organic pollutants with suspended solids and sediments into single-chemical and one-dimensional water quality model of Jinghang Canal.Sedimentation-resuspension coefficient k3 was deduced; characteristics of organic pollutants, concentrations and components of suspended solids/sediments and hydrological and hydraulic conditions were integrated into k3 and further into river water quality model; impact of sorption/desorption of organic pollutants with suspended solids and sediments on prediction function of the model was discussed. Results demonstrated that this impact is pronounced for organic pollutants with relatively large Koc and Kow, especially when they are also conservative and foc of river suspended solids/sediments is high, and that incorporation of sorption/ desorption of organic pollutants into river water quality model can improve its prediction accuracy.
Multiscale modeling of pedestrian dynamics
Cristiani, Emiliano; Tosin, Andrea
2014-01-01
This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.
Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Van Leemput, Koen
2012-01-01
Many successful segmentation algorithms are based on Bayesian models in which prior anatomical knowledge is combined with the available image information. However, these methods typically have many free parameters that are estimated to obtain point estimates only, whereas a faithful Bayesian analysis would also consider all possible alternate values these parameters may take. In this paper, we propose to incorporate the uncertainty of the free parameters in Bayesian segmentation models more a...
Incorporating social role theory into topic models for social media content analysis
Zhao, Wayne Xin; Wang, Jinpeng; He, Yulan; Nie, Jian-Yun; Wen, Ji-Rong; Li, Xiaoming
2015-01-01
In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiate...
DYNAMICAL MODEL OF ELECTROMAGNETIC DRIVE
Directory of Open Access Journals (Sweden)
Trunev A. P.
2016-02-01
Full Text Available The article discusses the dynamic model of the rocket motor electromagnetic type, consisting of a source of electromagnetic waves of radio frequency band and a conical cavity in which electromagnetic waves are excited. The processes of excitation of electromagnetic oscillations in a cavity with conducting walls, as well as the waves of the YangMills field have been investigated. Multi-dimensional transient numerical model describing the processes of establishment of electromagnetic oscillations in a cavity with the conducting wall was created Separately, the case of standing waves in the cavity with conducting walls been tested. It is shown that the oscillation mode in the conducting resonator different from that in an ideal resonator, both in the steady and unsteady processes. The mechanism of formation of traction for the changes in the space-time metric, the contribution of particle currents, the Yang-Mills and electromagnetic field proposed. It is shown that the effect of the Yang-Mills field calls change the dielectric properties of vacuum, which leads to a change in capacitance of the resonator. Developed a dynamic model, which enables optimal traction on a significant number of parameters. It was found that the thrust increases in the Yang-Mills field parameters near the main resonance frequency. In the presence of thermal fluctuations and the Yang-Mills field as well the traction force changes sign, indicating the presence of various oscillation modes
Incorporating preferential flow into a 3D model of a forested headwater catchment
Glaser, Barbara; Jackisch, Conrad; Hopp, Luisa; Pfister, Laurent; Klaus, Julian
2016-04-01
Preferential flow plays an important role for water flow and solute transport. The inclusion of preferential flow, for example with dual porosity or dual permeability approaches, is a common feature in transport simulations at the plot scale. But at hillslope and catchment scales, incorporation of macropore and fracture flow into distributed hydrologic 3D models is rare, often due to limited data availability for model parameterisation. In this study, we incorporated preferential flow into an existing 3D integrated surface subsurface hydrologic model (HydroGeoSphere) of a headwater region (6 ha) of the forested Weierbach catchment in western Luxembourg. Our model philosophy was a strong link between measured data and the model setup. The model setup we used previously had been parameterised and validated based on various field data. But existing macropores and fractures had not been considered in this initial model setup. The multi-criteria validation revealed a good model performance but also suggested potential for further improvement by incorporating preferential flow as additional process. In order to pursue the data driven model philosophy for the implementation of preferential flow, we analysed the results of plot scale bromide sprinkling and infiltration experiments carried out in the vicinity of the Weierbach catchment. Three 1 sqm plots were sprinkled for one hour and excavated one day later for bromide depth profile sampling. We simulated these sprinkling experiments at the soil column scale, using the parameterisation of the base headwater model extended by a second permeability domain. Representing the bromide depth profiles was successful without changing this initial parameterisation. Moreover, to explain the variability between the three bromide depth profiles it was sufficient to adapt the dual permeability properties, indicating the spatial heterogeneity of preferential flow. Subsequently, we incorporated the dual permeability simulation in the
Eigenvalue dynamics for multimatrix models
de Mello Koch, Robert; Gossman, David; Nkumane, Lwazi; Tribelhorn, Laila
2017-07-01
By performing explicit computations of correlation functions, we find evidence that there is a sector of the two matrix model defined by the S U (2 ) sector of N =4 super Yang-Mills theory that can be reduced to eigenvalue dynamics. There is an interesting generalization of the usual Van der Monde determinant that plays a role. The observables we study are the Bogomol'nyi-Prasad-Sommerfield operators of the S U (2 ) sector and include traces of products of both matrices, which are genuine multimatrix observables. These operators are associated with supergravity solutions of string theory.
Eigenvalue Dynamics for Multimatrix Models
Koch, Robert de Mello; Nkumane, Lwazi; Tribelhorn, Laila
2016-01-01
By performing explicit computations of correlation functions, we find evidence that there is a sector of the two matrix model defined by the $SU(2)$ sector of ${\\cal N}=4$ super Yang-Mills theory, that can be reduced to eigenvalue dynamics. There is an interesting generalization of the usual Van der Monde determinant that plays a role. The observables we study are the BPS operators of the $SU(2)$ sector and include traces of products of both matrices, which are genuine multi matrix observables. These operators are associated to supergravity solutions of string theory.
Dislocation climb models from atomistic scheme to dislocation dynamics
Niu, Xiaohua; Luo, Tao; Lu, Jianfeng; Xiang, Yang
2017-02-01
We develop a mesoscopic dislocation dynamics model for vacancy-assisted dislocation climb by upscalings from a stochastic model on the atomistic scale. Our models incorporate microscopic mechanisms of (i) bulk diffusion of vacancies, (ii) vacancy exchange dynamics between bulk and dislocation core, (iii) vacancy pipe diffusion along the dislocation core, and (iv) vacancy attachment-detachment kinetics at jogs leading to the motion of jogs. Our mesoscopic model consists of the vacancy bulk diffusion equation and a dislocation climb velocity formula. The effects of these microscopic mechanisms are incorporated by a Robin boundary condition near the dislocations for the bulk diffusion equation and a new contribution in the dislocation climb velocity due to vacancy pipe diffusion driven by the stress variation along the dislocation. Our climb formulation is able to quantitatively describe the translation of prismatic loops at low temperatures when the bulk diffusion is negligible. Using this new formulation, we derive analytical formulas for the climb velocity of a straight edge dislocation and a prismatic circular loop. Our dislocation climb formulation can be implemented in dislocation dynamics simulations to incorporate all the above four microscopic mechanisms of dislocation climb.
Bayesian Estimation of Categorical Dynamic Factor Models
Zhang, Zhiyong; Nesselroade, John R.
2007-01-01
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
Emsellem, E; Bacon, R; Emsellem, Eric; Dejonghe, Herwig; Bacon, Roland
1998-01-01
We present new dynamical models of the S0 galaxy N3115, making use of the available published photometry and kinematics as well as of two-dimensional TIGER spectrography. We first examined the kinematics in the central 40 arcsec in the light of two integral f(E,J) models. Jeans equations were used to constrain the mass to light ratio, and the central dark mass whose existence was suggested by previous studies. The even part of the distribution function was then retrieved via the Hunter & Qian formalism. We thus confirmed that the velocity and dispersion profiles in the central region could be well fit with a two-integral model, given the presence of a central dark mass of ~10^9 Msun. However, no two integral model could fit the h_3 profile around a radius of 25 arcsec where the outer disc dominates the surface brightness distribution. Three integral analytical models were therefore built using a Quadratic Programming technique. These models showed that three integral components do indeed provide a reasona...
Sarakorn, Weerachai
2017-04-01
In this research, the finite element (FE) method incorporating quadrilateral elements for solving 2-D MT modeling was presented. The finite element software was developed, employing a paving algorithm to generate the unstructured quadrilateral mesh. The accuracy, efficiency, reliability, and flexibility of our FE forward modeling are presented, compared and discussed. The numerical results indicate that our FE codes using an unstructured quadrilateral mesh provide good accuracy when the local mesh refinement is applied around sites and in the area of interest, with superior results when compared to other FE methods. The reliability of the developed codes was also confirmed when comparing both analytical solutions and COMMEMI2D model. Furthermore, our developed FE codes incorporating an unstructured quadrilateral mesh showed useful and powerful features such as handling irregular and complex subregions and providing local refinement of the mesh for a 2-D domain as closely as unstructured triangular mesh but it requires less number of elements in a mesh.
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.
Energy Technology Data Exchange (ETDEWEB)
Cipiti, Benjamin B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-03-01
The Co-Decontamination (CoDCon) Demonstration project is designed to test the separation of a mixed U and Pu product from dissolved spent nuclear fuel. The primary purpose of the project is to quantify the accuracy and precision to which a U/Pu mass ratio can be achieved without removing a pure Pu product. The system includes an on-line monitoring system using spectroscopy to monitor the ratios throughout the process. A dynamic model of the CoDCon flowsheet and on-line monitoring system was developed in order to expand the range of scenarios that can be examined for process control and determine overall measurement uncertainty. The model development and initial results are presented here.
Characterizing and modeling citation dynamics
Eom, Young-Ho; 10.1371/journal.pone.0024926
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts...
Incorporating planned activities and events in a dynamic multi-day activity agenda generator
Nijland, L.; Arentze, T.; Timmermans, H.J.P.
2012-01-01
Daily agenda formation is influenced by formal commitments, satisfaction of needs surpassing some threshold and the desire to conduct particular activities in anticipation of socially and religiously driven events such as birthdays, Christmas, etc. As part of a research program to develop a dynamic
Evolving Responsibilities in Work Force Development: Incorporating the Dynamics of Change.
Flynn, Patricia M.
Changes in skill requirements, training needs, the industrial and occupational mix of employment, and the spatial location of jobs are 'natural' consequences of a dynamic economy. These changes, in turn, influence employers' hiring and staffing patterns, workers' career paths, and economic growth and development. However, the evolving nature of…
Dynamic modelling of household automobile transactions within a microsimulation framework
Energy Technology Data Exchange (ETDEWEB)
Mohammadian, A.
2002-07-01
This thesis presents a newly developed dynamic model of household automobile transactions within an integrated land-use transportation and environment (ILUTE) modeling system framework. It is a market-based decision-making tool for use by individuals who have to choose between adding new vehicles to a fleet, disposing of vehicles, trading one of the vehicles of a fleet, or do-nothing. Different approaches were used within the model, including an artificial neural network, hedonic price, regression, and vehicle class and vintage choices. The model can also predict the complex activity of individuals' behaviour to become active in the market. An estimation approach was used to incorporate the vehicle type choice model into the main dynamic transaction choice model.
Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A
2014-08-01
Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate
Incorporating Mobility in Growth Modeling for Multilevel and Longitudinal Item Response Data.
Choi, In-Hee; Wilson, Mark
2016-01-01
Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility.
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...
Directory of Open Access Journals (Sweden)
Anandakumari Chandrasekharan Sunil Sekhar
2016-05-01
Full Text Available Ultra-small gold nanoparticles incorporated in mesoporous silica thin films with accessible pore channels perpendicular to the substrate are prepared by a modified sol-gel method. The simple and easy spin coating technique is applied here to make homogeneous thin films. The surface characterization using FESEM shows crack-free films with a perpendicular pore arrangement. The applicability of these thin films as catalysts as well as a robust SERS active substrate for model catalysis study is tested. Compared to bare silica film our gold incorporated silica, GSM-23F gave an enhancement factor of 103 for RhB with a laser source 633 nm. The reduction reaction of p-nitrophenol with sodium borohydride from our thin films shows a decrease in peak intensity corresponding to –NO2 group as time proceeds, confirming the catalytic activity. Such model surfaces can potentially bridge the material gap between a real catalytic system and surface science studies.
Kok, de, JMM John; Titus, Milan; Wind, Herman G.
2000-01-01
Decision-support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the co...
Torsional dynamics of steerable needles: modeling and fluoroscopic guidance.
Swensen, John P; Lin, MingDe; Okamura, Allison M; Cowan, Noah J
2014-11-01
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 semitransparent 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.
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)
Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh
2017-03-10
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.
Incorporation of ICRP-116 eye model into ICRP reference polygonal surface phantoms
Energy Technology Data Exchange (ETDEWEB)
Nguyen, Thang Tat; Yeom, Yeon Soo; Han, Min Cheol; Wang, Zhao Jun; Kim, Han Sung; Kim, Chan Hyeong [Dept. of Nuclear Engineering, Hanyang University, Seoul (Korea, Republic of)
2015-04-15
The ICRP adopted a detailed stylized eye model developed by Behrens et al. for evaluation of lens dose coefficients released in ICRP publication 116. However, the dose coefficients were calculated with the stylized eye model modelled into the head of mathematical phantoms not the ICRP reference phantoms, which may cause inconsistency in lens dose assessment. In order to keep consistency in the lens dose assessment, the present study incorporates the ICRP-116 eye model into the currently developing polygonal-mesh-type ICRP reference phantoms which are being converted from the voxel-type ICRP reference phantoms. Then, lens dose values were calculated and compared with those calculated with the mathematical phantom to see how it affects lens doses. The present study incorporated the ICRP-116 eye model into the currently developing polygonal-mesh-type ICRP reference phantoms and showed significant dose differences when compared with ICRP-116 data calculated with the mathematical phantom. We believe that the ICRP reference phantoms including the detailed eye model provide more consistent assessment for eye lens dose.
Dittmer, Jens; Thøgersen, Lea; Underhaug, Jarl; Bertelsen, Kresten; Vosegaard, Thomas; Pedersen, Jan M; Schiøtt, Birgit; Tajkhorshid, Emad; Skrydstrup, Troels; Nielsen, Niels Chr
2009-05-14
Detailed insight into the interplay between antimicrobial peptides and biological membranes is fundamental to our understanding of the mechanism of bacterial ion channels and the action of these in biological host-defense systems. To explore this interplay, we have studied the incorporation, membrane-bound structure, and conformation of the antimicrobial peptide alamethicin in lipid bilayers using a combination of 1H liquid-state NMR spectroscopy and molecular dynamics (MD) simulations. On the basis of experimental NMR data, we evaluate simple in-plane and transmembrane incorporation models as well as pore formation for alamethicin in DMPC/DHPC (1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine/1,2-dihexanoyl-sn-glycero-3-phosphatidylcholine) bicelles. Peptide-lipid nuclear Overhauser effect (NOE) and paramagnetic relaxation enhancement (PRE) data support a transmembrane configuration of the peptide in the bilayers, but they also reveal that the system cannot be described by a single simple conformational model because there is a very high degree of dynamics and heterogeneity in the three-component system. To explore the origin of this heterogeneity and dynamics, we have compared the NOE and PRE data with MD simulations of an ensemble of alamethicin peptides in a DMPC bilayer. From all-atom MD simulations, the contacts between peptide, lipid, and water protons are quantified over a time interval up to 95 ns. The MD simulations provide a statistical base that reflects our NMR data and even can explain some initially surprising NMR results concerning specific interactions between alamethicin and the lipids.
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.
Christhilf, David M.; Pototzky, Anthony S.; Stevens, William L.
2010-01-01
The Simulink-based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) was modified to incorporate linear models representing aeroservoelastic characteristics of the SemiSpan SuperSonic Transport (S4T) wind-tunnel model. The S4T planform is for a Technology Concept Aircraft (TCA) design from the 1990s. The model has three control surfaces and is instrumented with accelerometers and strain gauges. Control laws developed for wind-tunnel testing for Ride Quality Enhancement, Gust Load Alleviation, and Flutter Suppression System functions were implemented in the simulation. The simulation models open- and closed-loop response to turbulence and to control excitation. It provides time histories for closed-loop stable conditions above the open-loop flutter boundary. The simulation is useful for assessing the potential impact of closed-loop control rate and position saturation. It also provides a means to assess fidelity of system identification procedures by providing time histories for a known plant model, with and without unmeasured turbulence as a disturbance. Sets of linear models representing different Mach number and dynamic pressure conditions were implemented as MATLAB Linear Time Invariant (LTI) objects. Configuration changes were implemented by selecting which LTI object to use in a Simulink template block. A limited comparison of simulation versus wind-tunnel results is shown.
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...
Prosthetics socket that incorporates an air splint system focusing on dynamic interface pressure.
Razak, Nasrul Anuar Abd; Osman, Noor Azuan Abu; Gholizadeh, Hossein; Ali, Sadeeq
2014-08-01
The interface pressure between the residual limb and prosthetic socket has a significant effect on an amputee's satisfaction and comfort. This paper presents the design and performance of a new prosthetic socket that uses an air splint system. The air splint prosthetic socket system was implemented by combining the air splint with a pressure sensor that the transhumeral user controls through the use of a microcontroller. The modular construction of the system developed allows the FSR pressure sensors that are placed inside the air splint socket to determine the required size and fitting for the socket used. Fifteen transhumeral amputees participated in the study. The subject's dynamic pressure on the socket that's applied while wearing the air splint systems was recorded using F-socket transducers and microcontroller analysis. The values collected by the F-socket sensor for the air splint prosthetic socket system were determined accordingly by comparing the dynamic pressure applied using statically socket. The pressure volume of the air splint fluctuated and was recorded at an average of 38 kPa (2.5) to 41 kPa (1.3) over three hours. The air splint socket might reduce the pressure within the interface of residual limb. This is particularly important during the daily life activities and may reduce the pain and discomfort at the residual limb in comparison to the static socket. The potential development of an auto-adjusted socket that uses an air splint system as the prosthetic socket will be of interest to researchers involved in rehabilitation engineering, prosthetics and orthotics.
Dynamical model for virus spread
Camelo-Neto, G
1995-01-01
The steady state properties of the mean density population of infected cells in a viral spread is simulated by a general forest fire like cellular automaton model with two distinct populations of cells ( permissive and resistant ones) and studied in the framework of the mean field approximation. Stochastic dynamical ingredients are introduced in this model to mimic cells regeneration (with probability {\\it p}) and to consider infection processes by other means than contiguity (with probability {\\it f}). Simulations are carried on a L \\times L square lattice considering the eight first neighbors. The mean density population of infected cells (D_i) is measured as function of the regeneration probability {\\it p}, and analyzed for small values of the ratio {\\it f/p } and for distinct degrees of the cell resistance. The results obtained by a mean field like approach recovers the simulations results. The role of the resistant parameter R (R \\geq 2) on the steady state properties is investigated and discussed in com...
Characterizing and modeling citation dynamics.
Directory of Open Access Journals (Sweden)
Young-Ho Eom
Full Text Available Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.
Relating structure and dynamics in organisation models
Jonkers, C.M.; Treur, J.
2008-01-01
To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems, on t
Modelling the dynamics of youth subcultures
Holme, P; Holme, Petter; Gronlund, Andreas
2005-01-01
What are the dynamics behind youth subcultures such as punk, hippie, or hip-hop cultures? How does the global dynamics of these subcultures relate to the individual's search for a personal identity? We propose a simple dynamical model to address these questions and find that only a few assumptions of the individual's behaviour are necessary to regenerate known features of youth culture.
A new dynamic null model for phylogenetic community structure.
Pigot, Alex L; Etienne, Rampal S
2015-02-01
Phylogenies are increasingly applied to identify the mechanisms structuring ecological communities but progress has been hindered by a reliance on statistical null models that ignore the historical process of community assembly. Here, we address this, and develop a dynamic null model of assembly by allopatric speciation, colonisation and local extinction. Incorporating these processes fundamentally alters the structure of communities expected due to chance, with speciation leading to phylogenetic overdispersion compared to a classical statistical null model assuming equal probabilities of community membership. Applying this method to bird and primate communities in South America we show that patterns of phylogenetic overdispersion - often attributed to negative biotic interactions - are instead consistent with a species neutral model of allopatric speciation, colonisation and local extinction. Our findings provide a new null expectation for phylogenetic community patterns and highlight the importance of explicitly accounting for the dynamic history of assembly when testing the mechanisms governing community structure.
Institute of Scientific and Technical Information of China (English)
Hong Li; Yihu Song; Qiang Zheng
2008-01-01
The dynamic rheological properties of a composite composed of solution-polymerized styrene butadiene rubber (SSBR) filled with starch/silica (SiO2) compound fillers were studied by means of temperature,frequency and strain sweeps,respectively,and the influence of the starch content in the compound fillers (SCCF) on the rheological behaviors was discussed.It is found from frequency sweeps that a maximum of loss tangent (tanδ) appears at 20 rad/s,which is independent of SCCF.G' of the composites decreases whereas tanδ and critical strain (γc) of Payne effect increase with increasing SCCF.The reasons for these are believed to be that both SiO2 and starch could form filler networks due to interaction of hydrogen bounding between them,and the interactions between SiO2 and SSBR are stronger than those between starch and SSBR.Moreover,increasing SCCF in the compound fillers is in favor of improving the stability of the filler networks.Furthermore,tanδ values at 0℃ and 60℃ representing the properties for the wet traction and the rolling resistance of SSBR composites respectively can be improved by partial replacing SiO2 with starch.However,the reinforcement effect of starch to SSBR is weaker than that of SiO2 due to starch agglomeration.
Mathews, David H.; Disney, Matthew D.; Childs, Jessica L.; Schroeder, Susan J.; Zuker, Michael; Turner, Douglas H.
2004-01-01
A dynamic programming algorithm for prediction of RNA secondary structure has been revised to accommodate folding constraints determined by chemical modification and to include free energy increments for coaxial stacking of helices when they are either adjacent or separated by a single mismatch. Furthermore, free energy parameters are revised to account for recent experimental results for terminal mismatches and hairpin, bulge, internal, and multibranch loops. To demonstrate the applicability of this method, in vivo modification was performed on 5S rRNA in both Escherichia coli and Candida albicans with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate, dimethyl sulfate, and kethoxal. The percentage of known base pairs in the predicted structure increased from 26.3% to 86.8% for the E. coli sequence by using modification constraints. For C. albicans, the accuracy remained 87.5% both with and without modification data. On average, for these sequences and a set of 14 sequences with known secondary structure and chemical modification data taken from the literature, accuracy improves from 67% to 76%. This enhancement primarily reflects improvement for three sequences that are predicted with <40% accuracy on the basis of energetics alone. For these sequences, inclusion of chemical modification constraints improves the average accuracy from 28% to 78%. For the 11 sequences with <6% pseudoknotted base pairs, structures predicted with constraints from chemical modification contain on average 84% of known canonical base pairs. PMID:15123812
Towards a functional model of mental disorders incorporating the laws of thermodynamics.
Murray, George C; McKenzie, Karen
2013-05-01
The current paper presents the hypothesis that the understanding of mental disorders can be advanced by incorporating the laws of thermodynamics, specifically relating to energy conservation and energy transfer. These ideas, along with the introduction of the notion that entropic activities are symptomatic of inefficient energy transfer or disorder, were used to propose a model of understanding mental ill health as resulting from the interaction of entropy, capacity and work (environmental demands). The model was applied to Attention Deficit Hyperactivity Disorder, and was shown to be compatible with current thinking about this condition, as well as emerging models of mental disorders as complex networks. A key implication of the proposed model is that it argues that all mental disorders require a systemic functional approach, with the advantage that it offers a number of routes into the assessment, formulation and treatment for mental health problems.
A predictive model of community assembly that incorporates intraspecific trait variation.
Laughlin, Daniel C; Joshi, Chaitanya; van Bodegom, Peter M; Bastow, Zachary A; Fulé, Peter Z
2012-11-01
Community assembly involves two antagonistic processes that select functional traits in opposite directions. Environmental filtering tends to increase the functional similarity of species within communities leading to trait convergence, whereas competition tends to limit the functional similarity of species within communities leading to trait divergence. Here, we introduce a new hierarchical Bayesian model that incorporates intraspecific trait variation into a predictive framework to unify classic coexistence theory and evolutionary biology with recent trait-based approaches. Model predictions exhibited a significant positive correlation (r = 0.66) with observed relative abundances along a 10 °C gradient in mean annual temperature. The model predicted the correct dominant species in half of the plots, and accurately reproduced species' temperature optimums. The framework is generalizable to any ecosystem as it can accommodate any species pool, any set of functional traits and multiple environmental gradients, and it eliminates some of the criticisms associated with recent trait-based community assembly models.
English, Sinéad; Bateman, Andrew W; Clutton-Brock, Tim H
2012-05-01
Lifetime records of changes in individual size or mass in wild animals are scarce and, as such, few studies have attempted to model variation in these traits across the lifespan or to assess the factors that affect them. However, quantifying lifetime growth is essential for understanding trade-offs between growth and other life history parameters, such as reproductive performance or survival. Here, we used model selection based on information theory to measure changes in body mass over the lifespan of wild meerkats, and compared the relative fits of several standard growth models (monomolecular, von Bertalanffy, Gompertz, logistic and Richards). We found that meerkats exhibit monomolecular growth, with the best model incorporating separate growth rates before and after nutritional independence, as well as effects of season and total rainfall in the previous nine months. Our study demonstrates how simple growth curves may be improved by considering life history and environmental factors, which may be particularly relevant when quantifying growth patterns in wild populations.
Delay driven spatiotemporal chaos in single species population dynamics models.
Jankovic, Masha; Petrovskii, Sergei; Banerjee, Malay
2016-08-01
Questions surrounding the prevalence of complex population dynamics form one of the central themes in ecology. Limit cycles and spatiotemporal chaos are examples that have been widely recognised theoretically, although their importance and applicability to natural populations remains debatable. The ecological processes underlying such dynamics are thought to be numerous, though there seems to be consent as to delayed density dependence being one of the main driving forces. Indeed, time delay is a common feature of many ecological systems and can significantly influence population dynamics. In general, time delays may arise from inter- and intra-specific trophic interactions or population structure, however in the context of single species populations they are linked to more intrinsic biological phenomena such as gestation or resource regeneration. In this paper, we consider theoretically the spatiotemporal dynamics of a single species population using two different mathematical formulations. Firstly, we revisit the diffusive logistic equation in which the per capita growth is a function of some specified delayed argument. We then modify the model by incorporating a spatial convolution which results in a biologically more viable integro-differential model. Using the combination of analytical and numerical techniques, we investigate the effect of time delay on pattern formation. In particular, we show that for sufficiently large values of time delay the system's dynamics are indicative to spatiotemporal chaos. The chaotic dynamics arising in the wake of a travelling population front can be preceded by either a plateau corresponding to dynamical stabilisation of the unstable equilibrium or by periodic oscillations.
Dynamic stall model for wind turbine airfoils
DEFF Research Database (Denmark)
Larsen, J.W.; Nielsen, S.R.K.; Krenk, Steen
2007-01-01
A model is presented for aerodynamic lift of wind turbine profiles under dynamic stall. The model combines memory delay effects under attached flow with reduced lift due to flow separation under dynamic stall conditions. The model is based on a backbone curve in the form of the static lift...... conditions, nonstationary effects are included by three mechanisms: a delay of the lift coefficient of fully attached flow via a second-order filter, a delay of the development of separation represented via a first-order filter, and a lift contribution due to leading edge separation also represented via...... during dynamic stall conditions. The proposed model is compared with five other dynamic stall models including, among others, the Beddoes-Leishman model and the ONERA model. It is demonstrated that the proposed model performs equally well or even better than more complicated models and that the included...
An immune based dynamic intrusion detection model
Institute of Scientific and Technical Information of China (English)
LI Tao
2005-01-01
With the dynamic description method for self and antigen, and the concept of dynamic immune tolerance for lymphocytes in network-security domain presented in this paper, a new immune based dynamic intrusion detection model (Idid) is proposed. In Idid, the dynamic models and the corresponding recursive equations of the lifecycle of mature lymphocytes, and the immune memory are built. Therefore, the problem of the dynamic description of self and nonself in computer immune systems is solved, and the defect of the low efficiency of mature lymphocyte generating in traditional computer immune systems is overcome. Simulations of this model are performed, and the comparison experiment results show that the proposed dynamic intrusion detection model has a better adaptability than the traditional methods.
Cher, D J; Miyamoto, J; Lenert, L A
1997-01-01
Most decision models published in the medical literature take a risk-neutral perspective. Under risk neutrality, the utility of a gamble is equivalent to its expected value and the marginal utility of living a given unit of time is the same regardless of when it occurs. Most patients, however, are not risk-neutral. Not only does risk aversion affect decision analyses when tradeoffs between short- and long-term survival are involved, it also affects the interpretation of time-tradeoff measures of health-state utility. The proportional time tradeoff under- or overestimates the disutility of an inferior health state, depending on whether the patient is risk-seeking or risk-averse (it is unbiased if the patient is risk-neutral). The authors review how risk attitude with respect to gambles for survival duration can be incorporated into decision models using the framework of risk-adjusted quality-adjusted life years (RA-QALYs). They present a simple extension of this framework that allows RA-QALYs to be calculated for Markov-process decision models. Using a previously published Markov-process model of surgical vs expectant treatment for benign prostatic hypertrophy (BPH), they show how attitude towards risk affects the expected number of QALYs calculated by the model. In this model, under risk neutrality, surgery was the preferred option. Under mild risk aversion, expectant treatment was the preferred option. Risk attitude is an important aspect of preferences that should be incorporated into decision models where one treatment option has upfront risks of morbidity or mortality.
Gao, X.-L.; Zhang, G. Y.
2016-07-01
A non-classical model for a Mindlin plate resting on an elastic foundation is developed in a general form using a modified couple stress theory, a surface elasticity theory and a two-parameter Winkler-Pasternak foundation model. It includes all five kinematic variables possible for a Mindlin plate. The equations of motion and the complete boundary conditions are obtained simultaneously through a variational formulation based on Hamilton's principle, and the microstructure, surface energy and foundation effects are treated in a unified manner. The newly developed model contains one material length-scale parameter to describe the microstructure effect, three surface elastic constants to account for the surface energy effect, and two foundation parameters to capture the foundation effect. The current non-classical plate model reduces to its classical elasticity-based counterpart when the microstructure, surface energy and foundation effects are all suppressed. In addition, the new model includes the Mindlin plate models considering the microstructure dependence or the surface energy effect or the foundation influence alone as special cases, recovers the Kirchhoff plate model incorporating the microstructure, surface energy and foundation effects, and degenerates to the Timoshenko beam model including the microstructure effect. To illustrate the new Mindlin plate model, the static bending and free vibration problems of a simply supported rectangular plate are analytically solved by directly applying the general formulae derived.
Extension of the QUASAR river water quality model to incorporate dead-zone mixing
Directory of Open Access Journals (Sweden)
M. J. Lees
1998-01-01
Full Text Available A modification to the well-known water quality model 'Quality Simulation Along River Systems' (QUASAR is presented, extending its utility to real-time forecasting applications such as the management and control of pollution incidents. Two aggregated dead-zone (ADZ parameters, namely time delay and dispersive fraction, are incorporated into the existing model formulation, extending the current continuously stirred tank reactor based model processes to account for advective and active mixing volume dispersive processes. The resulting river water quality model combines the strengths of the QUASAR model, which has proven non-conservative pollutant modelling capabilities, with the accurate advection and dispersion characterisation of the ADZ model. A discrete-time mathematical representation of the governing equations is developed that enables efficient system identification methods of parameter estimation to be utilised. The enhanced water quality model and associated methods of parameter estimation are validated using data from tracer experiments conducted on the River Mimram. The revised model produces accurate predictions of observed concentration-time curves for conservative substances.
Extension of the QUASAR river water quality model to incorporate dead-zone mixing
Lees, M. J.; Camacho, L.; Whitehead, P.
A modification to the well-known water quality model "Quality Simulation Along River Systems" (QUASAR) is presented, extending its utility to real-time forecasting applications such as the management and control of pollution incidents. Two aggregated dead-zone (ADZ) parameters, namely time delay and dispersive fraction, are incorporated into the existing model formulation, extending the current continuously stirred tank reactor based model processes to account for advective and active mixing volume dispersive processes. The resulting river water quality model combines the strengths of the QUASAR model, which has proven non-conservative pollutant modelling capabilities, with the accurate advection and dispersion characterisation of the ADZ model. A discrete-time mathematical representation of the governing equations is developed that enables efficient system identification methods of parameter estimation to be utilised. The enhanced water quality model and associated methods of parameter estimation are validated using data from tracer experiments conducted on the River Mimram. The revised model produces accurate predictions of observed concentration-time curves for conservative substances.
Modelling Opinion Dynamics: Theoretical analysis and continuous approximation
Pinasco, Juan Pablo; Balenzuela, Pablo
2016-01-01
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. In this case, the agreement is reached because the new arguments are incorporated. In this paper we deal with a simple model of opinion formation with such persuasion dynamics, and we find the exact analytical solutions for both, long and short range interactions. A novel theoretical approach has been used in order to solve the master equations of the model with non-local kernels. Simulation results demonstrate an excellent agreement with results obtained by the theoretical estimation.
Non-Newtonian fluid model incorporated into elastohydrodynamic lubrication of rectangular contacts
Jacobson, B. O.; Hamrock, B. J.
1984-01-01
A procedure is outlined for the numerical solution of the complete elastohydrodynamic lubrication of rectangular contacts incorporating a non-Newtonian fluid model. The approach uses a Newtonian model as long as the shear stress is less than a limiting shear stress. If the shear stress exceeds the limiting value, the shear stress is set equal to the limiting value. The numerical solution requires the coupled solution of the pressure, film shape, and fluid rheology equations from the inlet to the outlet. Isothermal and no-side-leakage assumptions were imposed in the analysis. The influence of dimensionless speed, load, materials, and sliding velocity and limiting-shear-strength proportionality constant on dimensionless minimum film thickness was investigated. Fourteen cases were used in obtaining the minimum-film-thickness equation for an elastohydrodynamically lubricated rectangular contact incorporating a non-Newtonian fluid model. Computer plots are also presented that indicate in detail pressure distribution, film shape, shear stress at the surfaces, and flow throughout the conjunction.
Miller, Tom E X; Williams, Jennifer L; Jongejans, Eelke; Brys, Rein; Jacquemyn, Hans
2012-07-22
Understanding the selective forces that shape reproductive strategies is a central goal of evolutionary ecology. Selection on the timing of reproduction is well studied in semelparous organisms because the cost of reproduction (death) can be easily incorporated into demographic models. Iteroparous organisms also exhibit delayed reproduction and experience reproductive costs, although these are not necessarily lethal. How non-lethal costs shape iteroparous life histories remains unresolved. We analysed long-term demographic data for the iteroparous orchid Orchis purpurea from two habitat types (light and shade). In both the habitats, flowering plants had lower growth rates and this cost was greater for smaller plants. We detected an additional growth cost of fruit production in the light habitat. We incorporated these non-lethal costs into integral projection models to identify the flowering size that maximizes fitness. In both habitats, observed flowering sizes were well predicted by the models. We also estimated optimal parameters for size-dependent flowering effort, but found a strong mismatch with the observed flower production. Our study highlights the role of context-dependent non-lethal reproductive costs as selective forces in the evolution of iteroparous life histories, and provides a novel and broadly applicable approach to studying the evolutionary demography of iteroparous organisms.
Workflow-Based Dynamic Enterprise Modeling
Institute of Scientific and Technical Information of China (English)
黄双喜; 范玉顺; 罗海滨; 林慧萍
2002-01-01
Traditional systems for enterprise modeling and business process control are often static and cannot adapt to the changing environment. This paper presents a workflow-based method to dynamically execute the enterprise model. This method gives an explicit representation of the business process logic and the relationships between the elements involved in the process. An execution-oriented integrated enterprise modeling system is proposed in combination with other enterprise views. The enterprise model can be established and executed dynamically in the actual environment due to the dynamic properties of the workflow model.
Dynamical model of the kinesin protein motor
Nesterov, Alexander I; Ramírez, Mónica F
2016-01-01
We model and simulate the stepping dynamics of the kinesin motor including electric and mechanical forces, environmental noise, and the complicated potentials produced by tracking and neighboring protofilaments. Our dynamical model supports the hand-over-hand mechanism of the kinesin stepping. Our theoretical predictions and numerical simulations include the off-axis displacements of the kinesin heads while the steps are performed. The results obtained are in a good agreement with recent experiments on the kinesin dynamics.
A simplified model of software project dynamics
Ruiz Carreira, Mercedes; Ramos Román, Isabel; Toro Bonilla, Miguel
2001-01-01
The simulation of a dynamic model for software development projects (hereinafter SDPs) helps to investigate the impact of a technological change, of different management policies, and of maturity level of organisations over the whole project. In the beginning of the 1990s, with the appearance of the dynamic model for SDPs by Abdel-Hamid and Madnick [Software Project Dynamics: An Integrated Approach, Prentice-Hall, Englewood Cliffs, NJ, 1991], a significant advance took place in the field of p...
Explicit models for dynamic software
Bosloper, Ivor; Siljee, Johanneke; Nijhuis, Jos; Nord, R; Medvidovic, N; Krikhaar, R; Khrhaar, R; Stafford, J; Bosch, J
2006-01-01
A key aspect in creating autonomous dynamic software systems is the possibility of reasoning about properties of runtime variability and dynamic behavior, e.g. when and how to reconfigure the system. Currently these properties are often not made explicit in the software architecture. We argue that
Explicit models for dynamic software
Bosloper, Ivor; Siljee, Johanneke; Nijhuis, Jos; Nord, R; Medvidovic, N; Krikhaar, R; Khrhaar, R; Stafford, J; Bosch, J
2006-01-01
A key aspect in creating autonomous dynamic software systems is the possibility of reasoning about properties of runtime variability and dynamic behavior, e.g. when and how to reconfigure the system. Currently these properties are often not made explicit in the software architecture. We argue that h
Evolutionary Models of Super-Earths and Mini-Neptunes Incorporating Cooling and Mass Loss
Howe, Alex R
2015-01-01
We construct models of the structural evolution of super-Earth- and mini-Neptune-type exoplanets with hydrogen-helium envelopes, incorporating radiative cooling and XUV-driven mass loss. We conduct a parameter study of these models, focusing on initial mass, radius, and envelope mass fractions, as well as orbital distance, metallicity, and the specific prescription for mass loss. From these calculations, we investigate how the observed masses and radii of exoplanets today relate to the distribution of their initial conditions. Orbital distance and initial envelope mass fraction are the most important factors determining planetary evolution, particular radius evolution. Initial mass also becomes important below a "turnoff mass," which varies with orbital distance, with mass-radius curves being approximately flat for higher masses. Initial radius is the least important parameter we study, with very little difference between the hot start and cold start limits after an age of 100 Myr. Model sets with no mass los...
Institute of Scientific and Technical Information of China (English)
Niranjan P.Bidargaddi; Madlhu Chetty; Joarder Kamruzzaman
2008-01-01
Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forwardand backward variables, we propose a fuzzy Baum-Welch parameter estimation al-gorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.
Barnett, Tony; Fournié, Guillaume; Gupta, Sunetra; Seeley, Janet
2015-01-01
Incorporation of 'social' variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection - a highly social process in human populations - may be considered with little reference to the social. The French sociologist Émile Durkheim proposed that the scientific study of society required identification and study of 'social currents'. Such 'currents' are what we might today describe as 'emergent properties', specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to represent complex social and economic processes bearing on infectious disease transmission.
Bush, Alex; Mokany, Karel; Catullo, Renee; Hoffmann, Ary; Kellermann, Vanessa; Sgrò, Carla; McEvey, Shane; Ferrier, Simon
2016-12-01
Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change. © 2016 John Wiley & Sons Ltd/CNRS.
Directory of Open Access Journals (Sweden)
Alexander Andrason
2015-12-01
Full Text Available The present paper demonstrates that insights from the affordances perspective can contribute to developing a more comprehensive model of grammaticalization. The authors argue that the grammaticalization process is afforded differently depending on the values of three contributing parameters: the factor (schematized as a qualitative-quantitative map or a wave of a gram, environment (understood as the structure of the stream along which the gram travels, and actor (narrowed to certain cognitive-epistemological capacities of the users, in particular to the fact of being a native speaker. By relating grammaticalization to these three parameters and by connecting it to the theory of optimization, the proposed model offers a better approximation to realistic cases of grammaticalization: The actor and environment are overtly incorporated into the model and divergences from canonical grammaticalization paths are both tolerated and explicable.
Murphy, Kelly E.
2012-01-13
Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.
Comparative dynamics in a health investment model.
Eisenring, C
1999-10-01
The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.
Dynamic Heat Transfer Model of Refrigerated Foodstuff
DEFF Research Database (Denmark)
Cai, Junping; Risum, Jørgen; Thybo, Claus
2006-01-01
their temperature relation. This paper discusses the dynamic heat transfer model of foodstuff inside the display cabinet, one-dimensional dynamic model is developed, and the Explicit Finite Difference Method is applied, to handle the unsteady heat transfer problem with phase change, as well as time varying boundary...
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...
Chakraborty, Kunal; Das, Kunal; Kar, Tapan Kumar
2013-01-01
In this paper, we propose a prey-predator system with stage structure for predator. The proposed system incorporates cannibalism for predator populations in a competitive environment. The combined fishing effort is considered as control used to harvest the populations. The steady states of the system are determined and the dynamical behavior of the system is discussed. Local stability of the system is analyzed and sufficient conditions are derived for the global stability of the system at the positive equilibrium point. The existence of the Hopf bifurcation phenomenon is examined at the positive equilibrium point of the proposed system. We consider harvesting effort as a control parameter and subsequently, characterize the optimal control parameter in order to formulate the optimal control problem under the dynamic framework towards optimal utilization of the resource. Moreover, the optimal system is solved numerically to investigate the sustainability of the ecosystem using an iterative method with a Runge-Kutta fourth-order scheme. Simulation results show that the optimal control scheme can achieve sustainable ecosystem. Results are analyzed with the help of graphical illustrations.
The Challenges to Coupling Dynamic Geospatial Models
Energy Technology Data Exchange (ETDEWEB)
Goldstein, N
2006-06-23
Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.
A Direct Method for Incorporating Experimental Data into Multiscale Coarse-Grained Models.
Dannenhoffer-Lafage, Thomas; White, Andrew D; Voth, Gregory A
2016-05-10
To extract meaningful data from molecular simulations, it is necessary to incorporate new experimental observations as they become available. Recently, a new method was developed for incorporating experimental observations into molecular simulations, called experiment directed simulation (EDS), which utilizes a maximum entropy argument to bias an existing model to agree with experimental observations while changing the original model by a minimal amount. However, there is no discussion in the literature of whether or not the minimal bias systematically and generally improves the model by creating agreement with the experiment. In this work, we show that the relative entropy of the biased system with respect to an ideal target is always reduced by the application of a minimal bias, such as the one utilized by EDS. Using all-atom simulations that have been biased with EDS, one can then easily and rapidly improve a bottom-up multiscale coarse-grained (MS-CG) model without the need for a time-consuming reparametrization of the underlying atomistic force field. Furthermore, the improvement given by the many-body interactions introduced by the EDS bias can be maintained after being projected down to effective two-body MS-CG interactions. The result of this analysis is a new paradigm in coarse-grained modeling and simulation in which the "bottom-up" and "top-down" approaches are combined within a single, rigorous formalism based on statistical mechanics. The utility of building the resulting EDS-MS-CG models is demonstrated on two molecular systems: liquid methanol and ethylene carbonate.
Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling.
Ye, Hao; Beamish, Richard J; Glaser, Sarah M; Grant, Sue C H; Hsieh, Chih-Hao; Richards, Laura J; Schnute, Jon T; Sugihara, George
2015-03-31
It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.
Hydration dynamics near a model protein surface
Energy Technology Data Exchange (ETDEWEB)
Russo, Daniela; Hura, Greg; Head-Gordon, Teresa
2003-09-01
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.
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)
Dynamic Factor Models for the Volatility Surface
DEFF Research Database (Denmark)
van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van
The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...... features for representing the surface and its dynamics: a general dynamic factor model, restricted factor models designed to capture the key features of the surface along the moneyness and maturity dimensions, and in-between spline-based methods. Key findings are that: (i) the restricted and spline......-based models are both rejected against the general dynamic factor model, (ii) the factors driving the surface are highly persistent, (iii) for the restricted models option Delta is preferred over the more often used strike relative to spot price as measure for moneyness....
Comprehensive Survey on Dynamic Graph Models
Directory of Open Access Journals (Sweden)
Aya Zaki
2016-02-01
Full Text Available Most of the critical real-world networks are con-tinuously changing and evolving with time. Motivated by the growing importance and widespread impact of this type of networks, the dynamic nature of these networks have gained a lot of attention. Because of their intrinsic and special characteristics, these networks are best represented by dynamic graph models. To cope with their evolving nature, the representation model must keep the historical information of the network along with its temporal time. Storing such amount of data, poses many problems from the perspective of dynamic graph data management. This survey provides an in-depth overview on dynamic graph related problems. Novel categorization and classification of the state of the art dynamic graph models are also presented in a systematic and comprehensive way. Finally, we discuss dynamic graph processing including the output representation of its algorithms.
Incorporating uncertainty of management costs in sensitivity analyses of matrix population models.
Salomon, Yacov; McCarthy, Michael A; Taylor, Peter; Wintle, Brendan A
2013-02-01
The importance of accounting for economic costs when making environmental-management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population-management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost-efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on
Multicomponent aerosol dynamics model UHMA: model development and validation
Directory of Open Access Journals (Sweden)
H. Korhonen
2004-01-01
Full Text Available A size-segregated aerosol dynamics model UHMA (University of Helsinki Multicomponent Aerosol model was developed for studies of multicomponent tropospheric aerosol particles. The model includes major aerosol microphysical processes in the atmosphere with a focus on new particle formation and growth; thus it incorporates particle coagulation and multicomponent condensation, applying a revised treatment of condensation flux onto free molecular regime particles and the activation of nanosized clusters by organic vapours (Nano-Köhler theory, as well as recent parameterizations for binary H2SO4-H2O and ternary H2SO4-NH3-H2O homogeneous nucleation and dry deposition. The representation of particle size distribution can be chosen from three sectional methods: the hybrid method, the moving center method, and the retracking method in which moving sections are retracked to a fixed grid after a certain time interval. All these methods can treat particle emissions and atmospheric transport consistently, and are therefore suitable for use in large scale atmospheric models. In a test simulation against an accurate high resolution solution, all the methods showed reasonable treatment of new particle formation with 20 size sections although the hybrid and the retracking methods suffered from artificial widening of the distribution. The moving center approach, on the other hand, showed extra dents in the particle size distribution and failed to predict the onset of detectable particle formation. In a separate test simulation of an observed nucleation event, the model captured the key qualitative behaviour of the system well. Furthermore, its prediction of the organic volume fraction in newly formed particles, suggesting values as high as 0.5 for 3–4 nm particles and approximately 0.8 for 10 nm particles, agrees with recent indirect composition measurements.
Multicomponent aerosol dynamics model UHMA: model development and validation
Directory of Open Access Journals (Sweden)
H. Korhonen
2004-01-01
Full Text Available A size-segregated aerosol dynamics model UHMA (University of Helsinki Multicomponent Aerosol model was developed for studies of multicomponent tropospheric aerosol particles. The model includes major aerosol microphysical processes in the atmosphere with a focus on new particle formation and growth; thus it incorporates particle coagulation and multicomponent condensation, applying a revised treatment of condensation flux onto free molecular regime particles and the activation of nanosized clusters by organic vapours (Nano-Köhler theory, as well as recent parameterizations for binary H_{2}SO_{4}–H_{2}O and ternary H_{2}SO_{4}–NH_{3}-H_{2}O homogeneous nucleation and dry deposition. The representation of particle size distribution can be chosen from three sectional methods: the hybrid method, the moving center method, and the retracking method in which moving sections are retracked to a fixed grid after a certain time interval. All these methods can treat particle emissions and transport consistently, and are therefore suitable for use in large scale atmospheric models. In a test simulation against an accurate high resolution solution, all the methods showed reasonable treatment of new particle formation with 20 size sections although the hybrid and the retracking methods suffered from artificial widening of the distribution. The moving center approach, on the other hand, showed extra dents in the particle size distribution and failed to predict the onset of detectable particle formation. In a separate test simulation of an observed nucleation event, the model captured the key qualitative behaviour of the system well. Furthermore, its prediction of the organic volume fraction in newly formed particles, suggesting values as high as 0.5 for 3–4 nm particles and approximately 0.8 for 10 nm particles, agrees with recent indirect composition measurements.
Multicomponent aerosol dynamics model UHMA: model development and validation
Korhonen, H.; Lehtinen, K. E. J.; Kulmala, M.
2004-05-01
A size-segregated aerosol dynamics model UHMA (University of Helsinki Multicomponent Aerosol model) was developed for studies of multicomponent tropospheric aerosol particles. The model includes major aerosol microphysical processes in the atmosphere with a focus on new particle formation and growth; thus it incorporates particle coagulation and multicomponent condensation, applying a revised treatment of condensation flux onto free molecular regime particles and the activation of nanosized clusters by organic vapours (Nano-Köhler theory), as well as recent parameterizations for binary H2SO4-H2O and ternary H2SO4-NH3-H2O homogeneous nucleation and dry deposition. The representation of particle size distribution can be chosen from three sectional methods: the hybrid method, the moving center method, and the retracking method in which moving sections are retracked to a fixed grid after a certain time interval. All these methods can treat particle emissions and atmospheric transport consistently, and are therefore suitable for use in large scale atmospheric models. In a test simulation against an accurate high resolution solution, all the methods showed reasonable treatment of new particle formation with 20 size sections although the hybrid and the retracking methods suffered from artificial widening of the distribution. The moving center approach, on the other hand, showed extra dents in the particle size distribution and failed to predict the onset of detectable particle formation. In a separate test simulation of an observed nucleation event, the model captured the key qualitative behaviour of the system well. Furthermore, its prediction of the organic volume fraction in newly formed particles, suggesting values as high as 0.5 for 3-4 nm particles and approximately 0.8 for 10 nm particles, agrees with recent indirect composition measurements.
Hirsch, Philipp Emanuel; Thorlacius, Magnus; Brodin, Tomas; Burkhardt-Holm, Patricia
2017-01-01
Animal personalities are an important factor that affects the dispersal of animals. In the context of aquatic species, dispersal modeling needs to consider that most freshwater ecosystems are highly fragmented by barriers reducing longitudinal connectivity. Previous research has incorporated such barriers into dispersal models under the neutral assumption that all migrating animals attempt to ascend at all times. Modeling dispersal of animals that do not perform trophic or reproductive migrations will be more realistic if it includes assumptions of which individuals attempt to overcome a barrier. We aimed to introduce personality into predictive modeling of whether a nonmigratory invasive freshwater fish (the round goby, Neogobius melanostomus) will disperse across an in-stream barrier. To that end, we experimentally assayed the personalities of 259 individuals from invasion fronts and established round goby populations. Based on the population differences in boldness, asociability, and activity, we defined a priori thresholds with bolder, more asocial, and more active individuals having a higher likelihood of ascent. We then combined the personality thresholds with swimming speed data from the literature and in situ measurements of flow velocities in the barrier. The resulting binary logistic regression model revealed probabilities of crossing a barrier which depended not only on water flow and fish swimming speed but also on animal personalities. We conclude that risk assessment through predictive dispersal modeling across fragmented landscapes can be advanced by including personality traits as parameters. The inclusion of behavior into modeling the spread of invasive species can help to improve the accuracy of risk assessments.
A constitutive mechanical model for gas hydrate bearing sediments incorporating inelastic mechanisms
Sánchez, Marcelo
2016-11-30
Gas hydrate bearing sediments (HBS) are natural soils formed in permafrost and sub-marine settings where the temperature and pressure conditions are such that gas hydrates are stable. If these conditions shift from the hydrate stability zone, hydrates dissociate and move from the solid to the gas phase. Hydrate dissociation is accompanied by significant changes in sediment structure and strongly affects its mechanical behavior (e.g., sediment stiffenss, strength and dilatancy). The mechanical behavior of HBS is very complex and its modeling poses great challenges. This paper presents a new geomechanical model for hydrate bearing sediments. The model incorporates the concept of partition stress, plus a number of inelastic mechanisms proposed to capture the complex behavior of this type of soil. This constitutive model is especially well suited to simulate the behavior of HBS upon dissociation. The model was applied and validated against experimental data from triaxial and oedometric tests conducted on manufactured and natural specimens involving different hydrate saturation, hydrate morphology, and confinement conditions. Particular attention was paid to model the HBS behavior during hydrate dissociation under loading. The model performance was highly satisfactory in all the cases studied. It managed to properly capture the main features of HBS mechanical behavior and it also assisted to interpret the behavior of this type of sediment under different loading and hydrate conditions.
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.
Directory of Open Access Journals (Sweden)
Min Chen
2011-04-01
Full Text Available Genome-wide association studies (GWAS examine a large number of markers across the genome to identify associations between genetic variants and disease. Most published studies examine only single markers, which may be less informative than considering multiple markers and multiple genes jointly because genes may interact with each other to affect disease risk. Much knowledge has been accumulated in the literature on biological pathways and interactions. It is conceivable that appropriate incorporation of such prior knowledge may improve the likelihood of making genuine discoveries. Although a number of methods have been developed recently to prioritize genes using prior biological knowledge, such as pathways, most methods treat genes in a specific pathway as an exchangeable set without considering the topological structure of a pathway. However, how genes are related with each other in a pathway may be very informative to identify association signals. To make use of the connectivity information among genes in a pathway in GWAS analysis, we propose a Markov Random Field (MRF model to incorporate pathway topology for association analysis. We show that the conditional distribution of our MRF model takes on a simple logistic regression form, and we propose an iterated conditional modes algorithm as well as a decision theoretic approach for statistical inference of each gene's association with disease. Simulation studies show that our proposed framework is more effective to identify genes associated with disease than a single gene-based method. We also illustrate the usefulness of our approach through its applications to a real data example.
Institute of Scientific and Technical Information of China (English)
Qiuying Li; Haifeng Li; Minyan Lu
2015-01-01
Testing-effort (TE) and imperfect debugging (ID) in the reliability modeling process may further improve the fitting and pre-diction results of software reliability growth models (SRGMs). For describing the S-shaped varying trend of TE increasing rate more accurately, first, two S-shaped testing-effort functions (TEFs), i.e., delayed S-shaped TEF (DS-TEF) and inflected S-shaped TEF (IS-TEF), are proposed. Then these two TEFs are incorporated into various types (exponential-type, delayed S-shaped and in-flected S-shaped) of non-homogeneous Poisson process (NHPP) SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as wel as ID. Final y these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the fitting and prediction power of these new SRGMs. The experimental results show that: (i) the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs; (i ) incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs; (i i) the inflected S-shaped NHPP SRGM con-sidering both IS-TEF and ID yields the most accurate fitting and prediction results than the other comparison NHPP SRGMs.
Modelling the dynamics of turbulent floods
Mei, Z; Li, Z; Li, Zhenquan
1999-01-01
Consider the dynamics of turbulent flow in rivers, estuaries and floods. Based on the widely used k-epsilon model for turbulence, we use the techniques of centre manifold theory to derive dynamical models for the evolution of the water depth and of vertically averaged flow velocity and turbulent parameters. This new model for the shallow water dynamics of turbulent flow: resolves the vertical structure of the flow and the turbulence; includes interaction between turbulence and long waves; and gives a rational alternative to classical models for turbulent environmental flows.
Dynamic optimization model for allocating medical resources in epidemic controlling
Directory of Open Access Journals (Sweden)
Ming Liu
2013-03-01
Full Text Available Purpose: The model proposed in this paper addresses a dynamic optimization model for allocating medical resources in epidemic controlling.Design/methodology/approach: In this work, a three-level and dynamic linear programming model for allocating medical resources based on epidemic diffusion model is proposed. The epidemic diffusion model is used to construct the forecasting mechanism for dynamic demand of medical resources. Heuristic algorithm coupled with MTLAB mathematical programming solver is adopted to solve the model. A numerical example is presented for testing the model’s practical applicability.Findings: The main contribution of the present study is that a discrete time-space network model to study the medical resources allocation problem when an epidemic outbreak is formulated. It takes consideration of the time evolution and dynamic nature of the demand, which is different from most existing researches on medical resources allocation.Practical implications: In our model, the medicine logistics operation problem has been decomposed into several mutually correlated sub-problems, and then be solved systematically in the same decision scheme. Thus, the result will be much more suitable for real operations.Originality/value: In our model, the rationale that the medical resources allocated in early periods will take effect in subduing the spread of the epidemic spread and thus impact the demand in later periods has been for the first time incorporated. A win-win emergency rescue effect is achieved by the integrated and dynamic optimization model. The total rescue cost is controlled effectively, and meanwhile, inventory level in each urban health departments is restored and raised gradually.
Flapping Wing Flight Dynamic Modeling
2011-08-22
von Karman, T. and Burgers, J. M., Gerneral Aerodynamic Theory - Perfect Fluids , Vol. II, Julius Springer , Berlin, 1935. [24] Pesavento, U. and Wang...L., Methods of Analytical Dynamics , McGraw-Hill Book Company, New York, 1970. [34] Deng, X., Schenato, L., Wu, W. C., and Sastry, S. S., Flapping...Micro air vehicle- motivated computational biomechanics in bio ights: aerodynamics, ight dynamics and maneuvering stability, Acta Mechanica
A spatial model for conflict incorporating within- and between-actor effects
Knipl, Diána; Davies, Toby; Baudains, Peter
2017-10-01
The application of ecological models to human conflict scenarios has given rise to a number of models which describe antagonistic relationships between adversaries. Recent work demonstrates that the spatial disaggregation of such models is not only well-motivated but also gives rise to interesting dynamic behaviour, particularly with respect to the spatial distribution of resources. One feature which is largely absent from previous models, however, is the ability of an adversary to coordinate activity across its various locations. Most immediately, this corresponds to the notion of 'support' - the reallocation of resources from one site to another according to need - which plays an important role in real-world conflict. In this paper, we generalise a spatially-disaggregated form of the classic Richardson model of conflict escalation by adding a cross-location interaction term for the within-adversary dynamics at each location. We explore the model analytically, giving conditions for the stability of the balanced equilibrium state. We then also carry out a number of numerical simulations which correspond to stylised real-world conflict scenarios. Potential further applications of the model, and its implications for policy, are then discussed.
Structural Modeling and Molecular Dynamics Simulation of the Actin Filament
Energy Technology Data Exchange (ETDEWEB)
Splettstoesser, Thomas [University of Heidelberg; Holmes, Kenneth [Max Planck Institute, Heidelberg, Germany; Noe, Frank [DFG Research Center Matheon, FU Berlin, Germany; Smith, Jeremy C [ORNL
2011-01-01
Actin is a major structural protein of the eukaryotic cytoskeleton and enables cell motility. Here, we present a model of the actin filament (F-actin) that not only incorporates the global structure of the recently published model by Oda et al. but also conserves internal stereochemistry. A comparison is made using molecular dynamics simulation of the model with other recent F-actin models. A number of structural determents such as the protomer propeller angle, the number of hydrogen bonds, and the structural variation among the protomers are analyzed. The MD comparison is found to reflect the evolution in quality of actin models over the last 6 years. In addition, simulations of the model are carried out in states with both ADP or ATP bound and local hydrogen-bonding differences characterized.
Iglesias, Juan Eugenio; Sabuncu, Mert Rory; Van Leemput, Koen
2012-01-01
Many successful segmentation algorithms are based on Bayesian models in which prior anatomical knowledge is combined with the available image information. However, these methods typically have many free parameters that are estimated to obtain point estimates only, whereas a faithful Bayesian analysis would also consider all possible alternate values these parameters may take. In this paper, we propose to incorporate the uncertainty of the free parameters in Bayesian segmentation models more accurately by using Monte Carlo sampling. We demonstrate our technique by sampling atlas warps in a recent method for hippocampal subfield segmentation, and show a significant improvement in an Alzheimer's disease classification task. As an additional benefit, the method also yields informative "error bars" on the segmentation results for each of the individual sub-structures.
DEFF Research Database (Denmark)
Iglesias, J. E.; Sabuncu, M. R.; Van Leemput, Koen
2012-01-01
in a recent method for hippocampal subfield segmentation, and show a significant improvement in an Alzheimer’s disease classification task. As an additional benefit, the method also yields informative “error bars” on the segmentation results for each of the individual sub-structures.......Many successful segmentation algorithms are based on Bayesian models in which prior anatomical knowledge is combined with the available image information. However, these methods typically have many free parameters that are estimated to obtain point estimates only, whereas a faithful Bayesian...... analysis would also consider all possible alternate values these parameters may take. In this paper, we propose to incorporate the uncertainty of the free parameters in Bayesian segmentation models more accurately by using Monte Carlo sampling. We demonstrate our technique by sampling atlas warps...
Energy Technology Data Exchange (ETDEWEB)
Shouri, P.V.; Sreejith, P.S. [Division of Mechanical Engineering, School of Engineering, Cochin University of Science and Technology (CUSAT), Cochin 682 022, Kerala (India)
2008-06-15
In the present scenario of energy demand overtaking energy supply, top priority is given for energy conservation programs and policies. As a result, most existing systems are redesigned or modified with a view for improving energy efficiency. Often these modifications can have an impact on process system configuration, thereby affecting process system reliability. The paper presents a model for valuation of process systems incorporating reliability that can be used to determine the change in process system value resulting from system modification. The model also determines the break even system availability and presents an algorithm for allocation of component reliabilities of the modified system based on the break even system availability. The developed equations are applied to a steam power plant to study the effect of various operating parameters on system value. (author)
Lu, Xuesong; Zhang, Su; Yang, Wei; Chen, Yazhu
2010-11-01
Non-rigid registration of ultrasound images takes an important role in image-guided radiotherapy and surgery. Intensity-based method is popular in non-rigid registration, but it is sensitive to intensity variations and has problems with matching small structure features for the existence of speckles in ultrasound images. In this paper, we develop a new algorithm integrating the intensity and feature of ultrasound images. Both global shape information and local keypoint information extracted by scale invariant feature transform (SIFT) are incorporated into intensity similarity measure as the body force of viscous fluid model in a Bayesian framework. Experiments were performed on synthetic and clinical ultrasound images of breast and kidney. It is shown that shape and keypoint information significantly improves fluid model for non-rigid registration, especially for alignment of small structure features in accuracy.
Lateral thinking, from the Hopfield model to cortical dynamics.
Akrami, Athena; Russo, Eleonora; Treves, Alessandro
2012-01-24
Self-organizing attractor networks may comprise the building blocks for cortical dynamics, providing the basic operations of categorization, including analog-to-digital conversion, association and auto-association, which are then expressed as components of distinct cognitive functions depending on the contents of the neural codes in each region. To assess the viability of this scenario, we first review how a local cortical patch may be modeled as an attractor network, in which memory representations are not artificially stored as prescribed binary patterns of activity as in the Hopfield model, but self-organize as continuously graded patterns induced by afferent input. Recordings in macaques indicate that such cortical attractor networks may express retrieval dynamics over cognitively plausible rapid time scales, shorter than those dominated by neuronal fatigue. A cortical network encompassing many local attractor networks, and incorporating a realistic description of adaptation dynamics, may be captured by a Potts model. This network model has the capacity to engage long-range associations into sustained iterative attractor dynamics at a cortical scale, in what may be regarded as a mathematical model of spontaneous lateral thought. This article is part of a Special Issue entitled: Neural Coding.
A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition
Directory of Open Access Journals (Sweden)
Brian C. J. Moore
2016-12-01
Full Text Available This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.
A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition.
Moore, Brian C J; Glasberg, Brian R; Varathanathan, Ajanth; Schlittenlacher, Josef
2016-01-01
This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.
Sacks, Michael S
2003-04-01
Structural constitutive models integrate information on tissue composition and structure, avoiding ambiguities in material characterization. However, critical structural information (such as fiber orientation) must be modeled using assumed statistical distributions, with the distribution parameters estimated from fits to the mechanical test data. Thus, full realization of structural approaches continues to be limited without direct quantitative structural information for direct implementation or to validate model predictions. In the present study, fiber orientation information obtained using small angle light scattering (SALS) was directly incorporated into a structural constitutive model based on work by Lanir (J. Biomech., v. 16, pp. 1-12, 1983). Demonstration of the model was performed using existing biaxial mechanical and fiber orientation data for native bovine pericardium (Sacks and Chuong, ABME, v.26, pp. 892-902, 1998). The structural constitutive model accurately predicted the complete measured biaxial mechanical response. An important aspect of this approach is that only a single equibiaxial test to determine the effective fiber stress-strain response and the SALS-derived fiber orientation distribution were required to determine the complete planar biaxial mechanical response. Changes in collagen fiber crimp under equibiaxial strain suggest that, at the meso-scale, fiber deformations follow the global tissue strains. This result supports the assumption of affine strain to estimate the fiber strains. However, future evaluations will have to be performed for tissue subjected to a wider range of strain to more fully validate the current approach.
An agent-based model of stock markets incorporating momentum investors
Wei, J. R.; Huang, J. P.; Hui, P. M.
2013-06-01
It has been widely accepted that there exist investors who adopt momentum strategies in real stock markets. Understanding the momentum behavior is of both academic and practical importance. For this purpose, we propose and study a simple agent-based model of trading incorporating momentum investors and random investors. The random investors trade randomly all the time. The momentum investors could be idle, buying or selling, and they decide on their action by implementing an action threshold that assesses the most recent price movement. The model is able to reproduce some of the stylized facts observed in real markets, including the fat-tails in returns, weak long-term correlation and scaling behavior in the kurtosis of returns. An analytic treatment of the model relates the model parameters to several quantities that can be extracted from real data sets. To illustrate how the model can be applied, we show that real market data can be used to constrain the model parameters, which in turn provide information on the behavior of momentum investors in different markets.
Jahn, Beate; Theurl, Engelbert; Siebert, Uwe; Pfeiffer, Karl-Peter
2010-01-01
In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example.
Development of a solid propellant viscoelastic dynamic model
Hufferd, W. L.; Fitzgerald, J. E.
1976-01-01
The results of a one year study to develop a dynamic response model for the Space Shuttle Solid Rocket Motor (SRM) propellant are presented. An extensive literature survey was conducted, from which it was concluded that the only significant variables affecting the dynamic response of the SRM propellant are temperature and frequency. Based on this study, and experimental data on propellants related to the SRM propellant, a dynamic constitutive model was developed in the form of a simple power law with temperature incorporated in the form of a modified power law. A computer program was generated which performs a least-squares curve-fit of laboratory data to determine the model parameters and it calculates dynamic moduli at any desired temperature and frequency. Additional studies investigated dynamic scaling laws and the extent of coupling between the SRM propellant and motor cases. It was found, in agreement with other investigations, that the propellant provides all of the mass and damping characteristics whereas the case provides all of the stiffness.
Incorporating prediction models in the SelfLet framework: a plugin approach
Calcavecchia, Nicolo' Maria
2010-01-01
A complex pervasive system is typically composed of many cooperating \\emph{nodes}, running on machines with different capabilities, and pervasively distributed across the environment. These systems pose several new challenges such as the need for the nodes to manage autonomously and dynamically in order to adapt to changes detected in the environment. To address the above issue, a number of autonomic frameworks has been proposed. These usually offer either predefined self-management policies or programmatic mechanisms for creating new policies at design time. From a more theoretical perspective, some works propose the adoption of prediction models as a way to anticipate the evolution of the system and to make timely decisions. In this context, our aim is to experiment with the integration of prediction models within a specific autonomic framework in order to assess the feasibility of such integration in a setting where the characteristics of dynamicity, decentralization, and cooperation among nodes are import...
Modeling Mitochondrial Bioenergetics with Integrated Volume Dynamics
Bazil, Jason N.; Buzzard, Gregery T.; Ann E Rundell
2010-01-01
Author Summary Mathematically modeling biological systems challenges our current understanding of the physical and biochemical events contributing to the observed dynamics. It requires careful consideration of hypothesized mechanisms, model development assumptions and details regarding the experimental conditions. We have adopted a modeling approach to translate these factors that explicitly considers the thermodynamic constraints, biochemical states and reaction mechanisms during model devel...
Dynamical CP violation in composite Higgs models
Hashimoto, S.; Inagaki, Tomohiro; Muta, Taizo
1993-01-01
The dynamical origin of the CP violation in electroweak theory is investigated in composite Higgs models. The mechanism of the spontaneous CP violation proposed in other context by Dashen is adopted to construct simple models of the dynamical CP violation. Within the models the size of the neutron electric dipole moment is estimated and the constraint on the $\\varepsilon$-parameter in K-meson decays is discussed.
Comprehensive Gravity and Dynamics Model Determination of Binary Asteroid Systems
Fahnestock, Eugene G.
2009-09-01
I present the development of additional tools within the framework of JPL's in-house Mirage / Orbit Determination Program (ODP) software to allow the determination of a comprehensive gravity and dynamics model for any binary asteroid system potentially visited by a spacecraft rendezvous mission. This involves a concurrent global solution for the gravity fields of both components, sufficient parametric description of their fully-coupled translational and rotational dynamics, the spacecraft state, and all other relevant force model parameters. This estimation process primarily uses spacecraft radio tracking data (range and Doppler measurements), supplemented by in-situ imaging observations data types. A solution for the gravity field (gravity analysis) and a simultaneous solution for the spacecraft motion and other system properties has been performed before using the ODP for solitary irregular small solar system bodies (e.g. Eros, visited by the NEAR mission), but never for any closely gravitationally bound pair of irregular small solar system bodies. I am expanding NASA's tool set to allow the latter, in preparation for potential future spacecraft rendezvous missions. This is nontrivial, because of the need to incorporate propagation of the binary system's fully-coupled rigid-body dynamical model either along with the spacecraft state within Mirage/ODP or "offline", followed by interpolating an appropriate "binary dynamics ephemeris” representation. Further, this model optionally incorporates formulations for body gravity fields not previously used in this context, and it can be computationally very expensive. However, successfully performing this model determination at a binary asteroid yields valuable science results concerning internal mass distributions and structures of the components and insight into the system's formation and evolution. In this poster I present my current progress in the development of this capability and results for the quality of science
Schumann, Andreas; Oppel, Henning
2017-04-01
To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark
Ryves, David B.; Battarbee, Richard W.; Fritz, Sherilyn C.
2009-01-01
Taphonomic issues pose fundamental challenges for Quaternary scientists to recover environmental signals from biological proxies and make accurate inferences of past environments. The problem of microfossil preservation, specifically diatom dissolution, remains an important, but often overlooked, source of error in both qualitative and quantitative reconstructions of key variables from fossil samples, especially those using relative abundance data. A first step to tackling this complex issue is establishing an objective method of assessing preservation (here, diatom dissolution) that can be applied by different analysts and incorporated into routine counting strategies. Here, we establish a methodology for assessment of diatom dissolution under standard light microscopy (LM) illustrated with morphological criteria for a range of major diatom valve shapes. Dissolution data can be applied to numerical models (transfer functions) from contemporary samples, and to fossil material to aid interpretation of stratigraphic profiles and taphonomic pathways of individual taxa. Using a surface sediment diatom-salinity training set from the Northern Great Plains (NGP) as an example, we explore a variety of approaches to include dissolution data in salinity inference models indirectly and directly. Results show that dissolution data can improve models, with apparent dissolution-adjusted error (RMSE) up to 15% lower than their unadjusted counterparts. Internal validation suggests improvements are more modest, with bootstrapped prediction errors (RMSEP) up to 10% lower. When tested on a short core from Devils Lake, North Dakota, which has a historical record of salinity, dissolution-adjusted models infer higher values compared to unadjusted models during peak salinity of the 1930s-1940s Dust Bowl but nonetheless significantly underestimate peak values. Site-specific factors at Devils Lake associated with effects of lake level change on taphonomy (preservation and re
Very Large System Dynamics Models - Lessons Learned
Energy Technology Data Exchange (ETDEWEB)
Jacob J. Jacobson; Leonard Malczynski
2008-10-01
This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.
Directory of Open Access Journals (Sweden)
Puntani Pongsumpun
2014-01-01
Full Text Available The respiratory disease caused by the Influenza A Virus is occurring worldwide. The transmission for new strain of the H1N1 Influenza A virus is studied by formulating a SEIQR (susceptible, exposed, infected, quarantine, and recovered model to describe its spread. In the present model, we have assumed that a fraction of the infected population will die from the disease. This changes the mathematical equations governing the transmission. The effect of repetitive contact is also included in the model. Analysis of the model by using standard dynamical modeling method is given. Conditions for the stability of equilibrium state are given. Numerical solutions are presented for different values of parameters. It is found that increasing the amount of repetitive contacts leads to a decrease in the peak numbers of exposed and infectious humans. A stability analysis shows that the solutions are robust.
Comparing models of Red Knot population dynamics
McGowan, Conor
2015-01-01
Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.
A Stochastic Cobweb Dynamical Model
Directory of Open Access Journals (Sweden)
Serena Brianzoni
2008-01-01
_,__0__1, and the forward predictor with probability (1−, so that the expected price at time is a random variable and consequently the dynamics describing the price evolution in time is governed by a stochastic dynamical system. The dynamical system becomes a Markov process when the memory rate vanishes. In particular, we study the Markov chain in the cases of discrete and continuous time. Using a mixture of analytical tools and numerical methods, we show that, when prices take discrete values, the corresponding Markov chain is asymptotically stable. In the case with continuous prices and nonnecessarily zero memory rate, numerical evidence of bounded price oscillations is shown. The role of the memory rate is studied through numerical experiments, this study confirms the stabilizing effects of the presence of resistant memory.
Overall challenges in incorporating micro-mechanical models into materials design process
Bennoura, M.; Aboutajeddine, A.
2016-10-01
Using materials in engineering design has historically been handled using the paradigm of selecting appropriate materials from the finite set of available material databases. Recent trends, however, have moved toward the tailoring of materials that meet the overall system performance requirements, based on a process called material design. An important building block of this process is micromechanical models that relate microstructure to proprieties. Unfortunately, these models remain short and include a lot of uncertainties from assumptions and idealizations, which, unavoidably, impacts material design strategy. In this work, candidate methods to deal with micromechanical models uncertainties and their drawbacks in material design are investigated. Robust design methods for quantifying uncertainty and managing or mitigating its impact on design performances are reviewed first. These methods include principles for classifying uncertainty, mathematical techniques for evaluating its level degree, and design methods for performing and generating design alternatives, that are relatively insensitive to sources of uncertainty and flexible for admitting design changes or variations. The last section of this paper addresses the limits of the existing approaches from material modelling perspective and identifies the research opportunities to overcome the impediment of incorporating micromechanical models in material design process.
Incorporating experimental design and error into coalescent/mutation models of population history.
Knudsen, Bjarne; Miyamoto, Michael M
2007-08-01
Coalescent theory provides a powerful framework for estimating the evolutionary, demographic, and genetic parameters of a population from a small sample of individuals. Current coalescent models have largely focused on population genetic factors (e.g., mutation, population growth, and migration) rather than on the effects of experimental design and error. This study develops a new coalescent/mutation model that accounts for unobserved polymorphisms due to missing data, sequence errors, and multiple reads for diploid individuals. The importance of accommodating these effects of experimental design and error is illustrated with evolutionary simulations and a real data set from a population of the California sea hare. In particular, a failure to account for sequence errors can lead to overestimated mutation rates, inflated coalescent times, and inappropriate conclusions about the population. This current model can now serve as a starting point for the development of newer models with additional experimental and population genetic factors. It is currently implemented as a maximum-likelihood method, but this model may also serve as the basis for the development of Bayesian approaches that incorporate experimental design and error.
Lei, Y.; Zhang, B. W.; Bai, B. F.; Zhao, T. S.
2015-12-01
In a typical all-vanadium redox flow battery (VRFB), the ion exchange membrane is directly exposed in the bulk electrolyte. Consequently, the Donnan effect occurs at the membrane/electrolyte (M/E) interfaces, which is critical for modeling of ion transport through the membrane and the prediction of cell performance. However, unrealistic assumptions in previous VRFB models, such as electroneutrality and discontinuities of ionic potential and ion concentrations at the M/E interfaces, lead to simulated results inconsistent with the theoretical analysis of ion adsorption in the membrane. To address this issue, this work proposes a continuous-Donnan effect-model using the Poisson equation coupled with the Nernst-Planck equation to describe variable distributions at the M/E interfaces. A one-dimensional transient VRFB model incorporating the Donnan effect is developed. It is demonstrated that the present model enables (i) a more realistic simulation of continuous distributions of ion concentrations and ionic potential throughout the membrane and (ii) a more comprehensive estimation for the effect of the fixed charge concentration on species crossover across the membrane and cell performance.
Howard, A. M.; Bernardes, S.; Nibbelink, N.; Biondi, L.; Presotto, A.; Fragaszy, D. M.; Madden, M.
2012-07-01
Movement patterns of bearded capuchin monkeys (Cebus (Sapajus) libidinosus) in northeastern Brazil are likely impacted by environmental features such as elevation, vegetation density, or vegetation type. Habitat preferences of these monkeys provide insights regarding the impact of environmental features on species ecology and the degree to which they incorporate these features in movement decisions. In order to evaluate environmental features influencing movement patterns and predict areas suitable for movement, we employed a maximum entropy modelling approach, using observation points along capuchin monkey daily routes as species presence points. We combined these presence points with spatial data on important environmental features from remotely sensed data on land cover and topography. A spectral mixing analysis procedure was used to generate fraction images that represent green vegetation, shade and soil of the study area. A Landsat Thematic Mapper scene of the area of study was geometrically and atmospherically corrected and used as input in a Minimum Noise Fraction (MNF) procedure and a linear spectral unmixing approach was used to generate the fraction images. These fraction images and elevation were the environmental layer inputs for our logistic MaxEnt model of capuchin movement. Our models' predictive power (test AUC) was 0.775. Areas of high elevation (>450 m) showed low probabilities of presence, and percent green vegetation was the greatest overall contributor to model AUC. This work has implications for predicting daily movement patterns of capuchins in our field site, as suitability values from our model may relate to habitat preference and facility of movement.
Moreno-Amat, Elena; Rubiales, Juan Manuel; Morales-Molino, César; García-Amorena, Ignacio
2017-08-01
The increasing development of species distribution models (SDMs) using palaeodata has created new prospects to address questions of evolution, ecology and biogeography from wider perspectives. Palaeobotanical data provide information on the past distribution of taxa at a given time and place and its incorporation on modelling has contributed to advancing the SDM field. This has allowed, for example, to calibrate models under past climate conditions or to validate projected models calibrated on current species distributions. However, these data also bear certain shortcomings when used in SDMs that may hinder the resulting ecological outcomes and eventually lead to misleading conclusions. Palaeodata may not be equivalent to present data, but instead frequently exhibit limitations and biases regarding species representation, taxonomy and chronological control, and their inclusion in SDMs should be carefully assessed. The limitations of palaeobotanical data applied to SDM studies are infrequently discussed and often neglected in the modelling literature; thus, we argue for the more careful selection and control of these data. We encourage authors to use palaeobotanical data in their SDMs studies and for doing so, we propose some recommendations to improve the robustness, reliability and significance of palaeo-SDM analyses.
Yamamoto, Takashi; Watanuki, Yutaka; Hazen, Elliott L; Nishizawa, Bungo; Sasaki, Hiroko; Takahashi, Akinori
2015-12-01
Habitat use is often examined at a species or population level, but patterns likely differ within a species, as a function of the sex, breeding colony, and current breeding status of individuals. Hence, within-species differences should be considered in habitat models when analyzing and predicting species distributions, such as predicted responses to expected climate change scenarios. Also, species' distribution data obtained by different methods (vessel-survey and individual tracking) are often analyzed separately rather than integrated to improve predictions. Here, we eventually fit generalized additive models for Streaked Shearwaters Calonectris leuconelas using tracking data from two different breeding colonies in the Northwestern Pacific and visual observer data collected during a research cruise off the coast of western Japan. The tracking-based models showed differences among patterns of relative density distribution as a function of life history category (colony, sex, and breeding conditions). The integrated tracking-based and vessel-based bird count model incorporated ecological states rather than predicting a single surface for the entire species. This study highlights both the importance of including ecological and life history data and integrating multiple data types (tag-based tracking and vessel count) when examining species-environment relationships, ultimately advancing the capabilities of species distribution models.
Modeling the Dynamics of an Information System
Directory of Open Access Journals (Sweden)
Jacek Unold
2003-11-01
Full Text Available The article concentrates on the nature of a social subsystem of an information system. It analyzes the nature of information processes of collectivity within an IS and introduces a model of IS dynamics. The model is based on the assumption that a social subsystem of an information system works as a nonlinear dynamic system. The model of IS dynamics is verified on the indexes of the stock market. It arises from the basic assumption of the technical analysis of the markets, that is, the index chart reflects the play of demand and supply, which in turn represents the crowd sentiment on the market.
Structural Dynamics Model of a Cartesian Robot
1985-10-01
34 D FILE COPY AD-A198 053 *.CC Technical Report 1009 Structural Dynamics Model of a Cartesian Robot "DTIC SELEC T E 0 Alfonso Garcia Reynoso MIT...COVERED Structural Dynamics Model of a Cartesian Robot technical report G. PERFORMING ORG. REPORT NUM9ER 7. AUTHO0R(@) S. CONTRACT On GRANT NUMSER...8217 %S S Structural Dynamics Model of a Cartesian Robot by Alfonso Garcia Reynoso BSME Instituto Tecnol6gico de Veracruz (1967) MSME Instituto Tecnol6gico
Equivalent dynamic model of DEMES rotary joint
Zhao, Jianwen; Wang, Shu; Xing, Zhiguang; McCoul, David; Niu, Junyang; Huang, Bo; Liu, Liwu; Leng, Jinsong
2016-07-01
The dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by a small voltage-induced strain of the dielectric elastomer (DE), so it is a suitable candidate to make a rotary joint for a soft robot. Dynamic analysis is necessary for some applications, but the dynamic response of DEMESs is difficult to model because of the complicated morphology and viscoelasticity of the DE film. In this paper, a method composed of theoretical analysis and experimental measurement is presented to model the dynamic response of a DEMES rotary joint under an alternating voltage. Based on measurements of equivalent driving force and damping of the DEMES, the model can be derived. Some experiments were carried out to validate the equivalent dynamic model. The maximum angle error between model and experiment is greater than ten degrees, but it is acceptable to predict angular velocity of the DEMES, therefore, it can be applied in feedforward-feedback compound control.
Modeling microbial growth and dynamics.
Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M
2015-11-01
Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.
Modeling dynamics of HIV infected cells using stochastic cellular automaton
Precharattana, Monamorn; Triampo, Wannapong
2014-08-01
Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.
A modified social force model for crowd dynamics
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.
Perching Dynamics and Development of a Simple Model
Puopolo, Michael; Jacob, Jamey; Reynolds, Ryan
2013-11-01
Aerodynamicists with a vision for bird-like aircraft have been forced to develop new ways of modeling extremely agile flight systems, and in recent years there has been a growing variety of creative approaches that incorporate computer methods, empirical data, and unsteady flow theory. However, there remains a lack of simple and easily transferable models that can be used to predict and control motion of a fixed-wing, perching aircraft in the low Reynolds number flow regime. The authors have developed a simple dynamic model for a perching vehicle with a common fixed wing configuration that uses only input of the system design parameters, in addition to other relevant widely available information, and does not rely on wind tunnel measurements, CFD analysis or other rigorous forms of system identification. The resulting model is presented with a comparison of model simulations to flight data from a perching UAV.
Scaling of musculoskeletal models from static and dynamic trials
DEFF Research Database (Denmark)
Lund, Morten Enemark; Andersen, Michael Skipper; de Zee, Mark
2015-01-01
Subject-specific scaling of cadaver-based musculoskeletal models is important for accurate musculoskeletal analysis within multiple areas such as ergonomics, orthopaedics and occupational health. We present two procedures to scale ‘generic’ musculoskeletal models to match segment lengths and joint...... parameters to a specific subject and compare the results to a simpler approach based on linear, segment-wise scaling. By incorporating data from functional and standing reference trials, the new scaling approaches reduce the model sensitivity to assumed model marker positions. For validation, we applied all...... three scaling methods to an inverse dynamics-based musculoskeletal model and compared predicted knee joint contact forces to those measured with an instrumented prosthesis during gait. Additionally, a Monte Carlo study was used to investigate the sensitivity of the knee joint contact force to random...
Continuum neural dynamics models for visual object identification
Singh, Vijay; Tchernookov, Martin; Nemenman, Ilya
2013-03-01
Visual object identification has remained one of the most challenging problems even after decades of research. Most of the current models of the visual cortex represent neurons as discrete elements in a largely feedforward network arrangement. They are generally very specific in the objects they can identify. We develop a continuum model of recurrent, nonlinear neural dynamics in the primary visual cortex, incorporating connectivity patterns and other experimentally observed features of the cortex. The model has an interesting correspondence to the Landau-DeGennes theory of a nematic liquid crystal in two dimensions. We use collective spatiotemporal excitations of the model cortex as a signal for segmentation of contiguous objects from the background clutter. The model is capable of suppressing clutter in images and filling in occluded elements of object contours, resulting in high-precision, high-recall identification of large objects from cluttered scenes. This research has been partially supported by the ARO grant No. 60704-NS-II.
Human insulin dynamics in women: a physiologically based model.
Weiss, Michael; Tura, Andrea; Kautzky-Willer, Alexandra; Pacini, Giovanni; D'Argenio, David Z
2016-02-01
Currently available models of insulin dynamics are mostly based on the classical compartmental structure and, thus, their physiological utility is limited. In this work, we describe the development of a physiologically based model and its application to data from 154 patients who underwent an insulin-modified intravenous glucose tolerance test (IM-IVGTT). To determine the time profile of endogenous insulin delivery without using C-peptide data and to evaluate the transcapillary transport of insulin, the hepatosplanchnic, renal, and peripheral beds were incorporated into the circulatory model as separate subsystems. Physiologically reasonable population mean estimates were obtained for all estimated model parameters, including plasma volume, interstitial volume of the peripheral circulation (mainly skeletal muscle), uptake clearance into the interstitial space, hepatic and renal clearance, as well as total insulin delivery into plasma. The results indicate that, at a population level, the proposed physiologically based model provides a useful description of insulin disposition, which allows for the assessment of muscle insulin uptake.
Energy Technology Data Exchange (ETDEWEB)
Tucker, Susan L., E-mail: sltucker@mdanderson.org [Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li Minghuan [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Xu Ting; Gomez, Daniel [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yuan Xianglin [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China); Yu Jinming [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Liu Zhensheng; Yin Ming; Guan Xiaoxiang; Wang Lie; Wei Qingyi [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Vinogradskiy, Yevgeniy [University of Colorado School of Medicine, Aurora, Colorado (United States); Martel, Mary [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)
2013-01-01
Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.
Incorporation of caffeine into a quantitative model of fatigue and sleep.
Puckeridge, M; Fulcher, B D; Phillips, A J K; Robinson, P A
2011-03-21
A recent physiologically based model of human sleep is extended to incorporate the effects of caffeine on sleep-wake timing and fatigue. The model includes the sleep-active neurons of the hypothalamic ventrolateral preoptic area (VLPO), the wake-active monoaminergic brainstem populations (MA), their interactions with cholinergic/orexinergic (ACh/Orx) input to MA, and circadian and homeostatic drives. We model two effects of caffeine on the brain due to competitive antagonism of adenosine (Ad): (i) a reduction in the homeostatic drive and (ii) an increase in cholinergic activity. By comparing the model output to experimental data, constraints are determined on the parameters that describe the action of caffeine on the brain. In accord with experiment, the ranges of these parameters imply significant variability in caffeine sensitivity between individuals, with caffeine's effectiveness in reducing fatigue being highly dependent on an individual's tolerance, and past caffeine and sleep history. Although there are wide individual differences in caffeine sensitivity and thus in parameter values, once the model is calibrated for an individual it can be used to make quantitative predictions for that individual. A number of applications of the model are examined, using exemplar parameter values, including: (i) quantitative estimation of the sleep loss and the delay to sleep onset after taking caffeine for various doses and times; (ii) an analysis of the system's stable states showing that the wake state during sleep deprivation is stabilized after taking caffeine; and (iii) comparing model output successfully to experimental values of subjective fatigue reported in a total sleep deprivation study examining the reduction of fatigue with caffeine. This model provides a framework for quantitatively assessing optimal strategies for using caffeine, on an individual basis, to maintain performance during sleep deprivation.
Directory of Open Access Journals (Sweden)
Stefan Fürtinger
2014-11-01
Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number
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...
Matthews, S.; Lovell, M.; Davies, S. J.; Pritchard, T.; Sirju, C.; Abdelkarim, A.
2012-12-01
Heterolithic or 'shaly' sandstone reservoirs constitute a significant proportion of hydrocarbon resources. Petroacoustic models (a combination of petrophysics and rock physics) enhance the ability to extract reservoir properties from seismic data, providing a connection between seismic and fine-scale rock properties. By incorporating sedimentological observations these models can be better constrained and improved. Petroacoustic modelling is complicated by the unpredictable effects of clay minerals and clay-sized particles on geophysical properties. Such effects are responsible for erroneous results when models developed for "clean" reservoirs - such as Gassmann's equation (Gassmann, 1951) - are applied to heterolithic sandstone reservoirs. Gassmann's equation is arguably the most popular petroacoustic modelling technique in the hydrocarbon industry and is used to model elastic effects of changing reservoir fluid saturations. Successful implementation of Gassmann's equation requires well-constrained drained rock frame properties, which in heterolithic sandstones are heavily influenced by reservoir sedimentology, particularly clay distribution. The prevalent approach to categorising clay distribution is based on the Thomas - Stieber model (Thomas & Stieber, 1975), this approach is inconsistent with current understanding of 'shaly sand' sedimentology and omits properties such as sorting and grain size. The novel approach presented here demonstrates that characterising reservoir sedimentology constitutes an important modelling phase. As well as incorporating sedimentological constraints, this novel approach also aims to improve drained frame moduli estimates through more careful consideration of Gassmann's model assumptions and limitations. A key assumption of Gassmann's equation is a pore space in total communication with movable fluids. This assumption is often violated by conventional applications in heterolithic sandstone reservoirs where effective porosity, which
Phone Routing using the Dynamic Memory Model
DEFF Research Database (Denmark)
Bendtsen, Claus Nicolaj; Krink, Thiemo
2002-01-01
In earlier studies a genetic algorithm (GA) extended with the dynamic memory model has shown remarkable performance on real-world-like problems. In this paper we experiment with routing in communication networks and show that the dynamic memory GA performs remarkable well compared to ant colony o...
System Dynamics Modelling for a Balanced Scorecard
DEFF Research Database (Denmark)
Nielsen, Steen; Nielsen, Erland Hejn
2008-01-01
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/methodology...
Nonlinear dynamic phenomena in the beer model
DEFF Research Database (Denmark)
Mosekilde, Erik; Laugesen, Jakob Lund
2007-01-01
The production-distribution system or "beer game" is one of the most well-known system dynamics models. Notorious for the complex dynamics it produces, the beer game has been used for nearly five decades to illustrate how structure generates behavior and to explore human decision making. Here we...
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....
A Dynamic Pore-Scale Model of Imbibition
DEFF Research Database (Denmark)
Mogensen, Kristian; Stenby, Erling Halfdan
1998-01-01
could not incorporate long-range correlations among pore and throat sizes in our network, but were limited to small-range correlations. Consequently, the gradual suppression of snap-off occurs within one order of magnitude of the capillary number. At capillary numbers around l0- to l0-, snap-off has......We present a dynamic pore-scale network model of imbibition, capable of calculating residual oil saturation for any given capillary number, viscosity ratio, contact angle and aspect ratio. Our goal is not to predict the outcome of core floods, but rather to perform a sensitivity analysis...
Energy Technology Data Exchange (ETDEWEB)
Huang, Lei; Fang, Hongwei; Xu, Xingya; He, Guojian; Zhang, Xuesong; Reible, Danny
2017-08-01
Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Several software reliability growth models (SRGM) have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity: simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate (FRR) is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.
Khan, T.; Agnan, Y.; Obrist, D.; Selin, N. E.; Urban, N. R.; Wu, S.; Perlinger, J. A.
2015-12-01
Inadequate representation of process-based mechanisms of exchange behavior of elemental mercury (Hg0) and decoupled treatment of deposition and emission are two major limitations of parameterizations of atmosphere-surface exchange flux commonly incorporated into chemical transport models (CTMs). Of nineteen CTMs for Hg0 exchange we reviewed (ten global, nine regional), eight global and seven regional models have decoupled treatment of Hg0 deposition and emission, two global models include no parameterization to account for emission, and the remaining two regional models include coupled deposition and emission parameterizations (i.e., net atmosphere-surface exchange). The performance of atmosphere-surface exchange parameterizations in CTMs depends on parameterization uncertainty (in terms of both accuracy and precision) and feasibility of implementation. We provide a comparison of the performance of three available parameterizations of net atmosphere-surface exchange. To evaluate parameterization accuracy, we compare predicted exchange fluxes to field measurements conducted over a variety of surfaces compiled in a recently developed global database of terrestrial Hg0 surface-atmosphere exchange flux measurements. To assess precision, we estimate the sensitivity of predicted fluxes to the imprecision in parameter input values, and compare this sensitivity to that derived from analysis of the global Hg0 flux database. Feasibility of implementation is evaluated according to the availability of input parameters, computational requirements, and the adequacy of uncertainty representation. Based on this assessment, we provide suggestions for improved treatment of Hg0 net exchange processes in CTMs.
A new dynamics model for traffic flow
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
As a study method of traffic flow, dynamics models were developedand applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using car-following theory and the usual connection method of micro-macro variables, which can overcome some ubiquitous problems in the existing models. Numerical results show that the new model can very well simulate traffic flow conditions, such as congestion, evacuation of congestion, stop-and-go phenomena and phantom jam.
Dynamic Metabolic Modeling of Denitrifying Bacterial Growth: The Cybernetic Approach
Energy Technology Data Exchange (ETDEWEB)
Song, Hyun-Seob; Liu, Chongxuan
2015-06-29
Denitrification is a multistage reduction process converting nitrate ultimately to nitrogen gas, carried out mostly by facultative bacteria. Modeling of the denitrification process is challenging due to the complex metabolic regulation that modulates sequential formation and consumption of a series of nitrogen oxide intermediates, which serve as the final electron acceptors for denitrifying bacteria. In this work, we examined the effectiveness and accuracy of the cybernetic modeling framework in simulating the growth dynamics of denitrifying bacteria in comparison with kinetic models. In four different case studies using the literature data, we successfully simulated diauxic and triauxic growth patterns observed in anoxic and aerobic conditions, only by tuning two or three parameters. In order to understand the regulatory structure of the cybernetic model, we systematically analyzed the effect of cybernetic control variables on simulation accuracy. The results showed that the consideration of both enzyme synthesis and activity control through u- and v-variables is necessary and relevant and that uvariables are of greater importance in comparison to v-variables. In contrast, simple kinetic models were unable to accurately capture dynamic metabolic shifts across alternative electron acceptors, unless an inhibition term was additionally incorporated. Therefore, the denitrification process represents a reasonable example highlighting the criticality of considering dynamic regulation for successful metabolic modeling.
Taylor, Andrew T; Papeş, Monica; Long, James M
2017-09-06
Fluvial fishes face increased imperilment from anthropogenic activities, but the specific factors contributing most to range declines are often poorly understood. For example, the shoal bass (Micropterus cataractae) is a fluvial-specialist species experiencing continual range loss, yet how perceived threats have contributed to range loss is largely unknown. We employed species distribution models (SDMs) to disentangle which factors are contributing most to shoal bass range loss by estimating a potential distribution based on natural abiotic factors and by estimating a series of current, occupied distributions that also incorporated variables characterizing land cover, non-native species, and fragmentation intensity (no fragmentation, dams only, and dams and large impoundments). Model construction allowed for interspecific relationships between non-native congeners and shoal bass to vary across fragmentation intensities. Results from the potential distribution model estimated shoal bass presence throughout much of their native basin, whereas models of current occupied distribution illustrated increased range loss as fragmentation intensified. Response curves from current occupied models indicated a potential interaction between fragmentation intensity and the relationship between shoal bass and non-native congeners, wherein non-natives may be favored at the highest fragmentation intensity. Response curves also suggested that free-flowing fragment lengths of > 100 km were necessary to support shoal bass presence. Model evaluation, including an independent validation, suggested models had favorable predictive and discriminative abilities. Similar approaches that use readily-available, diverse geospatial datasets may deliver insights into the biology and conservation needs of other fluvial species facing similar threats. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Horwitz, James; Zeng, Wen
2008-10-01
As new methods of describing multiple fluid species and other advances enhance the capability of global magnetospheric models to simulate the dynamics of multiple ion species, they also allow more accurate incorporation of ionospheric plasma outflows as source populations into these large scale models. Here, we shall describe the distilled results of numerous physics-based simulations of ionospheric plasma outflows influenced by auroral driving agents in terms of compact analytic expressions in terms of precipitation electron energy flux levels, characteristic energy levels of the precipitating electrons, the peak spectral wave densities for low-frequency electrostatic waves which transversely heat ionospheric ions, and solar zenith angle. The simulations are conducted with the UT Arlington Dynamic Fluid Kinetic (DyFK) ionospheric plasma transport code. We present these analytic expressions for ionospheric origin O^+ and H^+ densities, temperatures and field-aligned flow velocities at the 3 RE altitude inner boundaries of typical magnetospheric models.
Dutta, Rituraj; Kumar, A.
2017-10-01
Dielectric relaxation dynamics and AC conductivity scaling of a metal-organic framework (MOF-5) based poly (vinylidene fluoride-co-hexafluoropropylene) (PVdf-HFP) incorporated with 1-Butyl-3-methylimidazolium hexafluorophosphate have been studied over a frequency range of 40 Hz–5 MHz and in the temperature range of 300 K–380 K. High values of dielectric permittivity (~{{\\varepsilon }\\prime} ) having strong dispersion are obtained at low frequency because of interfacial polarization. The real part of the dielectric modulus spectra (M‧) shows no prominent peak, whereas the imaginary part (M″) shows certain peaks, with a reduction in relaxation time (τ) that can be attributed to a non-Debye relaxation mechanism. The spectra also depict both concentration- and temperature-independent scaling behavior. The power law dependent variation of AC conductivity follows the jump relaxation model and reveals activated ion hopping over diffusion barriers. The value of the frequency exponent is observed to decrease with increasing concentration of ionic liquid, indicating the forward hopping of ions in the relaxation process. The AC conductivity scaling curves at different temperatures also depict the temperature-independent relaxation dynamics.
MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS
Institute of Scientific and Technical Information of China (English)
CHAHINE Georges L.; HSIAO Chao-Tsung
2012-01-01
Controlling mierobubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge,which can be achieved only through a combination of experimental and numerical/analytical techniques.The present communication presents a multi-physics approach to study the dynamics combining viscousinviseid effects,liquid and structure dynamics,and multi bubble interaction.While complex numerical tools are developed and used,the study aims at identifying the key parameters influencing the dynamics,which need to be included in simpler models.
Computational fluid dynamics modeling in yarn engineering
CSIR Research Space (South Africa)
Patanaik, A
2011-07-01
Full Text Available This chapter deals with the application of computational fluid dynamics (CFD) modeling in reducing yarn hairiness during the ring spinning process and thereby “engineering” yarn with desired properties. Hairiness significantly affects the appearance...
Molecular dynamics model of dimethyl ether
Energy Technology Data Exchange (ETDEWEB)
Lin, B.; Halley, W.J. [Univ. of Minnesota, Minneapolis, MN (United States)
1995-11-02
We report a molecular dynamics model of the monomeric liquid dimethyl ether. The united atom approach is used to treat CH{sub 3} groups as point source centers. Partial charges are derived from the experimental dipole moment. Harmonic force constants are used for intramolecular interactions, and their values are so chosen that the model`s fundamental frequencies agree with experimental results. Because we are interested in solvation properties, the model contains flexible molecules, allowing molecular distortion and internal dynamical quantities. We report radial distribution functions and the static structure factors as well as some dynamical quantities such as the dynamical structure factor, infrared absorption, and Raman scattering spectra. Calculated results agree reasonably well with experimental and other simulation results. 25 refs., 8 figs., 1 tab.
Stochastic population dynamic models as probability networks
M.E. and D.C. Lee. Borsuk
2009-01-01
The dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and...
System Identification by Dynamic Factor Models
C. Heij (Christiaan); W. Scherrer; M. Destler
1996-01-01
textabstractThis paper concerns the modelling of stochastic processes by means of dynamic factor models. In such models the observed process is decomposed into a structured part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so
Damping mechanisms and models in structural dynamics
DEFF Research Database (Denmark)
Krenk, Steen
2002-01-01
Several aspects of damping models for dynamic analysis of structures are investigated. First the causality condition for structural response is used to identify rules for the use of complex-valued frequency dependent material models, illustrated by the shortcomings of the elastic hysteretic model...
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Probabilistic Modeling in Dynamic Information Retrieval
Sloan, M. C.
2016-01-01
Dynamic modeling is used to design systems that are adaptive to their changing environment and is currently poorly understood in information retrieval systems. Common elements in the information retrieval methodology, such as documents, relevance, users and tasks, are dynamic entities that may evolve over the course of several interactions, which is increasingly captured in search log datasets. Conventional frameworks and models in information retrieval treat these elements as static, or only...
Identification and Modelling of Linear Dynamic Systems
Directory of Open Access Journals (Sweden)
Stanislav Kocur
2006-01-01
Full Text Available System identification and modelling are very important parts of system control theory. System control is only as good as good is created model of system. So this article deals with identification and modelling problems. There are simple classification and evolution of identification methods, and then the modelling problem is described. Rest of paper is devoted to two most known and used models of linear dynamic systems.
Energy Technology Data Exchange (ETDEWEB)
Candy, J V; Chambers, D H; Breitfeller, E F; Guidry, B L; Verbeke, J M; Axelrod, M A; Sale, K E; Meyer, A M
2010-03-02
The detection of radioactive contraband is a critical problem is maintaining national security for any country. Photon emissions from threat materials challenge both detection and measurement technologies especially when concealed by various types of shielding complicating the transport physics significantly. This problem becomes especially important when ships are intercepted by U.S. Coast Guard harbor patrols searching for contraband. The development of a sequential model-based processor that captures both the underlying transport physics of gamma-ray emissions including Compton scattering and the measurement of photon energies offers a physics-based approach to attack this challenging problem. The inclusion of a basic radionuclide representation of absorbed/scattered photons at a given energy along with interarrival times is used to extract the physics information available from the noisy measurements portable radiation detection systems used to interdict contraband. It is shown that this physics representation can incorporated scattering physics leading to an 'extended' model-based structure that can be used to develop an effective sequential detection technique. The resulting model-based processor is shown to perform quite well based on data obtained from a controlled experiment.
Grady, Matthew W.; Beretvas, S. Natasha
2010-01-01
Multiple membership random effects models (MMREMs) have been developed for use in situations where individuals are members of multiple higher level organizational units. Despite their availability and the frequency with which multiple membership structures are encountered, no studies have extended the MMREM approach to hierarchical growth curve…
Modeling Illicit Drug Use Dynamics and Its Optimal Control Analysis
Directory of Open Access Journals (Sweden)
Steady Mushayabasa
2015-01-01
Full Text Available The global burden of death and disability attributable to illicit drug use, remains a significant threat to public health for both developed and developing nations. This paper presents a new mathematical modeling framework to investigate the effects of illicit drug use in the community. In our model the transmission process is captured as a social “contact” process between the susceptible individuals and illicit drug users. We conduct both epidemic and endemic analysis, with a focus on the threshold dynamics characterized by the basic reproduction number. Using our model, we present illustrative numerical results with a case study in Cape Town, Gauteng, Mpumalanga and Durban communities of South Africa. In addition, the basic model is extended to incorporate time dependent intervention strategies.
Dynamical model for spindown of solar-type stars
Sood, Aditi; Hollerbach, Rainer
2016-01-01
Since their formation, stars slow down their rotation rates by the removal of angular momentum from their surfaces, e.g. via stellar winds. Despite the complexity of the processes involved, a traditional model, where the removal of angular momentum loss by magnetic fields is prescribed, has provided a useful framework to understand observational relations between stellar rotation and age and magnetic field strength. Here, a spindown model is proposed where loss of angular momentum by magnetic fields is evolved dynamically, instead of being kinematically prescribed. To this end, we evolve the stellar rotation and magnetic field simultaneously over stellar evolution time by extending our previous work on a dynamo model which incorporates the nonlinear feedback mechanisms on rotation and magnetic fields. Our extended model reproduces key observations and explains the presence of the two branches of (fast and slow rotating) stars which have different relations between rotation rate $\\Omega$ vs. time (age), magnet...
A stochastic model of human gait dynamics
Ashkenazy, Yosef; M. Hausdorff, Jeffrey; Ch. Ivanov, Plamen; Eugene Stanley, H.
2002-12-01
We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood-including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.
Integration of Dynamic Models in Range Operations
Bardina, Jorge; Thirumalainambi, Rajkumar
2004-01-01
This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.
Long-term dynamics simulation: Modeling requirements
Energy Technology Data Exchange (ETDEWEB)
Morched, A.S.; Kar, P.K.; Rogers, G.J.; Morison, G.K. (Ontario Hydro, Toronto, ON (Canada))
1989-12-01
This report details the required performance and modelling capabilities of a computer program intended for the study of the long term dynamics of power systems. Following a general introduction which outlines the need for long term dynamic studies, the modelling requirements for the conduct of such studies is discussed in detail. Particular emphasis is placed on models for system elements not normally modelled in power system stability programs, which will have a significant impact in the long term time frame of minutes to hours following the initiating disturbance. The report concludes with a discussion of the special computational and programming requirements for a long term stability program. 43 refs., 36 figs.
Energy Technology Data Exchange (ETDEWEB)
Ma, Jie; Wang, Bo [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhao, Shunli [Research Institute, Baoshan Iron & Steel Co., Ltd, Shanghai 201900 (China); Wu, Guangxin [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhang, Jieyu, E-mail: zjy6162@staff.shu.edu.cn [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Yang, Zhiliang [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China)
2016-05-25
We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.
A land use regression model incorporating data on industrial point source pollution
Institute of Scientific and Technical Information of China (English)
Li Chen; Yuming Wang; Peiwu Li; Yaqin Ji; Shaofei Kong; Zhiyong Li; Zhipeng Bai
2012-01-01
Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and polcy support.We created land use regression (LUR) models for SO2,NO2 and PM10for Tianjin,China.Traffic volumes,road networks,land use data,population density,meteorological conditions,physical conditions and satellite-derived greenness,brightness and wetness were used for predicting SO2,NO2 and PM10 concentrations.We incorporated data on industrial point sources to improve LUR model performance.In order to consider the impact of different sources,we calculated the PSIndex,LSIndex and area of different land use types (agricultural land,industrial land,commercial land,residential land,green space and water area) within different buffer radii (1 to 20 km).This method makes up for the lack of consideration of source impact based on the LUR model.Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO2 and NO2.R2 values of the multiple linear regression equations for SO2,NO2 and PM10 were 0.78,0.89 and 0.84,respectively,and the RMSE values were 0.32,0.18 and 0.21,respectively.Model predictions at validation monitoring sites went well with predictions generally within 15％ of measured values.Compared to the relationship between dependent variables and simple variables (such as traffic variables or meteorological condition variables),the relationship between dependent variables and integrated variables was more consistent with a linear relationship.Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.
A land use regression model incorporating data on industrial point source pollution.
Chen, Li; Wang, Yuming; Li, Peiwu; Ji, Yaqin; Kong, Shaofei; Li, Zhiyong; Bai, Zhipeng
2012-01-01
Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression (LUR) models for SO2, NO2 and PM10 for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SO2, NO2 and PM10 concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types (agricultural land, industrial land, commercial land, residential land, green space and water area) within different buffer radii (1 to 20 km). This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO2 and NO2. R2 values of the multiple linear regression equations for SO2, NO2 and PM10 were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables (such as traffic variables or meteorological condition variables), the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.
Directory of Open Access Journals (Sweden)
Reinhard Koch
2010-09-01
Full Text Available For broadcasting purposes mixed reality, the combination of real and virtual scene content, has become ubiquitous nowadays. Mixed Reality recording still requires expensive studio setups and is often limited to simple color keying. We present a system for Mixed Reality applications which uses depth keying and provides threedimensional mixing of real and artificial content. It features enhanced realism through automatic shadow computation which we consider a core issue to obtain realism and a convincing visual perception, besides the correct alignment of the two modalities and correct occlusion handling. Furthermore we present a possibility to support placement of virtual content in the scene. Core feature of our system is the incorporation of a time-of-flight (TOF-camera device. This device delivers real-time depth images of the environment at a reasonable resolution and quality. This camera is used to build a static environment model and it also allows correct handling of mutual occlusions between real and virtual content, shadow computation and enhanced content planning. The presented system is inexpensive, compact, mobile, flexible and provides convenient calibration procedures. Chroma-keying is replaced by depth-keying which is efficiently performed on the graphics processing unit (GPU by the usage of an environment model and the current ToF-camera image. Automatic extraction and tracking of dynamic scene content is herewith performed and this information is used for planning and alignment of virtual content. An additional sustainable feature is that depth maps of the mixed content are available in real-time, which makes the approach suitable for future 3DTV productions. The presented paper gives an overview of the whole system approach including camera calibration, environment model generation, real-time keying and mixing of virtual and real content, shadowing for virtual content and dynamic object tracking for content planning.
Bias in diet determination: incorporating traditional methods in Bayesian mixing models.
Franco-Trecu, Valentina; Drago, Massimiliano; Riet-Sapriza, Federico G; Parnell, Andrew; Frau, Rosina; Inchausti, Pablo
2013-01-01
There are not "universal methods" to determine diet composition of predators. Most traditional methods are biased because of their reliance on differential digestibility and the recovery of hard items. By relying on assimilated food, stable isotope and Bayesian mixing models (SIMMs) resolve many biases of traditional methods. SIMMs can incorporate prior information (i.e. proportional diet composition) that may improve the precision in the estimated dietary composition. However few studies have assessed the performance of traditional methods and SIMMs with and without informative priors to study the predators' diets. Here we compare the diet compositions of the South American fur seal and sea lions obtained by scats analysis and by SIMMs-UP (uninformative priors) and assess whether informative priors (SIMMs-IP) from the scat analysis improved the estimated diet composition compared to SIMMs-UP. According to the SIMM-UP, while pelagic species dominated the fur seal's diet the sea lion's did not have a clear dominance of any prey. In contrast, SIMM-IP's diets compositions were dominated by the same preys as in scat analyses. When prior information influenced SIMMs' estimates, incorporating informative priors improved the precision in the estimated diet composition at the risk of inducing biases in the estimates. If preys isotopic data allow discriminating preys' contributions to diets, informative priors should lead to more precise but unbiased estimated diet composition. Just as estimates of diet composition obtained from traditional methods are critically interpreted because of their biases, care must be exercised when interpreting diet composition obtained by SIMMs-IP. The best approach to obtain a near-complete view of predators' diet composition should involve the simultaneous consideration of different sources of partial evidence (traditional methods, SIMM-UP and SIMM-IP) in the light of natural history of the predator species so as to reliably ascertain and
Uncertainty and Sensitivity in Surface Dynamics Modeling
Kettner, Albert J.; Syvitski, James P. M.
2016-05-01
Papers for this special issue on 'Uncertainty and Sensitivity in Surface Dynamics Modeling' heralds from papers submitted after the 2014 annual meeting of the Community Surface Dynamics Modeling System or CSDMS. CSDMS facilitates a diverse community of experts (now in 68 countries) that collectively investigate the Earth's surface-the dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere, by promoting, developing, supporting and disseminating integrated open source software modules. By organizing more than 1500 researchers, CSDMS has the privilege of identifying community strengths and weaknesses in the practice of software development. We recognize, for example, that progress has been slow on identifying and quantifying uncertainty and sensitivity in numerical modeling of earth's surface dynamics. This special issue is meant to raise awareness for these important subjects and highlight state-of-the-art progress.
The future dynamic world model
Karr, Thomas J.
2014-10-01
Defense and security forces exploit sensor data by means of a model of the world. They use a world model to geolocate sensor data, fuse it with other data, navigate platforms, recognize features and feature changes, etc. However, their need for situational awareness today exceeds the capabilities of their current world model for defense operations, despite the great advances of sensing technology in recent decades. I review emerging technologies that may enable a great improvement in the spatial and spectral coverage, the timeliness, and the functional insight of their world model.
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 stiffness model of spherical parallel robots
Cammarata, Alessandro; Caliò, Ivo; D`Urso, Domenico; Greco, Annalisa; Lacagnina, Michele; Fichera, Gabriele
2016-12-01
A novel approach to study the elastodynamics of Spherical Parallel Robots is described through an exact dynamic model. Timoshenko arches are used to simulate flexible curved links while the base and mobile platforms are modelled as rigid bodies. Spatial joints are inherently included into the model without Lagrangian multipliers. At first, the equivalent dynamic stiffness matrix of each leg, made up of curved links joined by spatial joints, is derived; then these matrices are assembled to obtain the Global Dynamic Stiffness Matrix of the robot at a given pose. Actuator stiffness is also included into the model to verify its influence on vibrations and modes. The latter are found by applying the Wittrick-Williams algorithm. Finally, numerical simulations and direct comparison to commercial FE results are used to validate the proposed model.
Haptics-based dynamic implicit solid modeling.
Hua, Jing; Qin, Hong
2004-01-01
This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
2015-01-01
Nanofibers were prepared from polycaprolactone, polylactide and polyvinyl alcohol using NanospiderTM technology. Polyethylene glycols with molecular weights of 2 000, 6 000, 10 000 and 20 000 g/mol, which can be used to moderate the release profile of incorporated pharmacologically active compounds, served as model molecules. They were terminated by aromatic isocyanate and incorporated into the nanofibers. The release of these molecules into an aqueous environment was investigated. The influe...
Computational fluid dynamics modeling for emergency preparedness and response
Energy Technology Data Exchange (ETDEWEB)
Lee, R.L.; Albritton, J.R.; Ermak, D.L.; Kim, J.
1995-02-01
Computational fluid dynamics (CFD) has (CFD) has played an increasing in the improvement of atmospheric dispersion modeling. This is because many dispersion models are now driven by meteorological fields generated from CFD models or, in numerical weather prediction`s terminology, prognostic models. Whereas most dispersion models typically involve one or a few scalar, uncoupled equations, the prognostic equations are a set of highly-couple equations whose solution requires a significant level of computational power. Recent advances in computer hardware and software have enabled modestly-priced, high performance, workstations to exhibit the equivalent computation power of some mainframes. Thus desktop-class machines that were limited to performing dispersion calculations driven by diagnostic wind fields may now be used to calculate complex flows using prognostic CFD models. The Release and Advisory Capability (ARAC) program at Lawrence Livermore National Laboratory (LLNL) has, for the past several years, taken advantage of the improvements in hardware technology to develop a national emergency response capability based on executing diagnostic models on workstations. Diagnostic models that provide wind fields are, in general, simple to implement, robust and require minimal time for execution. Because these models typically contain little physics beyond mass-conservation, their performance is extremely sensitive to the quantity and quality of input meteorological data and, in spite of their utility, can be applied with confidence to only modestly complex flows. We are now embarking on a development program to incorporate prognostic models to generate, in real-time, the meteorological fields for the dispersion models. In contrast to diagnostic models, prognostic models are physically-based and are capable of incorporating many physical processes to treat highly complex flow scenarios.
Ma, Songyun; Scheider, Ingo; Bargmann, Swantje
2016-09-01
An anisotropic constitutive model is proposed in the framework of finite deformation to capture several damage mechanisms occurring in the microstructure of dental enamel, a hierarchical bio-composite. It provides the basis for a homogenization approach for an efficient multiscale (in this case: multiple hierarchy levels) investigation of the deformation and damage behavior. The influence of tension-compression asymmetry and fiber-matrix interaction on the nonlinear deformation behavior of dental enamel is studied by 3D micromechanical simulations under different loading conditions and fiber lengths. The complex deformation behavior and the characteristics and interaction of three damage mechanisms in the damage process of enamel are well captured. The proposed constitutive model incorporating anisotropic damage is applied to the first hierarchical level of dental enamel and validated by experimental results. The effect of the fiber orientation on the damage behavior and compressive strength is studied by comparing micro-pillar experiments of dental enamel at the first hierarchical level in multiple directions of fiber orientation. A very good agreement between computational and experimental results is found for the damage evolution process of dental enamel.
Wildes, Jennifer E.; Marcus, Marsha D.
2013-01-01
There is increasing recognition of the limitations of current approaches to psychiatric classification. Nowhere is this more apparent than in the eating disorders (EDs). Several alternative methods of classifying EDs have been proposed, which can be divided into two major groups: 1) those that have classified individuals on the basis of disordered eating symptoms; and, 2) those that have classified individuals on the basis of comorbid psychopathology and associated features. Several reviews have addressed symptom-based approaches to ED classification, but we are aware of no paper that has critically examined comorbidity-based systems. Thus, in this paper, we review models of classifying EDs that incorporate information about comorbid psychopathology and associated features. Early approaches are described first, followed by more recent scholarly contributions to comorbidity-based ED classification. Importantly, several areas of overlap among the classification schemes are identified that may have implications for future research. In particular, we note similarities between early models and newer studies in the salience of impulsivity, compulsivity, distress, and inhibition versus risk taking. Finally, we close with directions for future work, with an emphasis on neurobiologically-informed research to elucidate basic behavioral and neuropsychological correlates of comorbidity-based ED classes, as well as implications for treatment. PMID:23416343
Wang, Zi Shuai; Sha, Wei E. I.; Choy, Wallace C. H.
2016-12-01
Modeling the charge-generation process is highly important to understand device physics and optimize power conversion efficiency of bulk-heterojunction organic solar cells (OSCs). Free carriers are generated by both ultrafast exciton delocalization and slow exciton diffusion and dissociation at the heterojunction interface. In this work, we developed a systematic numerical simulation to describe the charge-generation process by a modified drift-diffusion model. The transport, recombination, and collection of free carriers are incorporated to fully capture the device response. The theoretical results match well with the state-of-the-art high-performance organic solar cells. It is demonstrated that the increase of exciton delocalization ratio reduces the energy loss in the exciton diffusion-dissociation process, and thus, significantly improves the device efficiency, especially for the short-circuit current. By changing the exciton delocalization ratio, OSC performances are comprehensively investigated under the conditions of short-circuit and open-circuit. Particularly, bulk recombination dependent fill factor saturation is unveiled and understood. As a fundamental electrical analysis of the delocalization mechanism, our work is important to understand and optimize the high-performance OSCs.
Incorporating social contact data in spatio-temporal models for infectious disease spread
Meyer, Sebastian
2015-01-01
Routine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases - possibly stratified by region and/or age group. A well-established approach to the statistical analysis of such surveillance data are endemic-epidemic time-series models. The temporal dependence inherent to communicable diseases is thereby taken into account by an observation-driven formulation conditioning on past counts. Additional spatial dynamics in areal-level counts are largely driven by human travel and can be captured by power-law weights based on the order of adjacency. However, social contacts are highly assortative also with respect to age. For example, characteristic pathways of directly transmitted pathogens are linked to childcare facilities, schools and nursing homes. We therefore investigate how a spatio-temporal endemic-epidemic model can be extended to take social contact data into account. The approach is illustrated in a case study on norovirus gastroenteritis in Berlin, 201...
Model Reduction of Nonlinear Fire Dynamics Models
Lattimer, Alan Martin
2016-01-01
Due to the complexity, multi-scale, and multi-physics nature of the mathematical models for fires, current numerical models require too much computational effort to be useful in design and real-time decision making, especially when dealing with fires over large domains. To reduce the computational time while retaining the complexity of the domain and physics, our research has focused on several reduced-order modeling techniques. Our contributions are improving wildland fire reduced-order mod...
2015-12-01
women with a diagnosis of breast cancer from 2003 to 2012 and enrolled in a larger study on MD were evaluated. Operative and pathology reports were...AD______________ AWARD NUMBER: W81XWH-11-1-0545 TITLE: Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast ...Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources 5a. CONTRACT
Contribution to a dynamic wind turbine model validation from a wind farm islanding experiment
DEFF Research Database (Denmark)
Pedersen, Jørgen Kaas; Pedersen, Knud Ole Helgesen; Poulsen, Niels Kjølstad;
2003-01-01
and possible discrepancies are explained. The work with the wind turbine model validation relates to the dynamic stability investigations on incorporation of large amount of wind power in the Danish power grid, where the dynamic wind turbine model is applied.......Measurements from an islanding experiment on the Rejsby Hede wind farm, Denmark, are used for the validation of the dynamic model of grid-connected, stall-controlled wind turbines equipped with induction generators. The simulated results are found to be in good agreement with the measurements...
A Modeling Framework to Incorporate Effects of Infrastructure in Sociohydrological Systems
Muneepeerakul, R.
2014-12-01
In studying coupled natural-human systems, most modeling efforts focus on humans and the natural resources. In reality, however, humans rarely interact with these resources directly; the relationships between humans and resources are mediated by infrastructures. In sociohydrological systems, these include, for example, dams and irrigation canals. These infrastructures have important characteristics such as threshold behavior and a separate entity/organization tasked with maintaining them. These characteristics influence social dynamics within the system, which in turn determines the state of infrastructure and water usage, thereby exerting feedbacks onto the hydrological processes. Infrastructure is thus a necessary ingredient for modeling co-evolution of human and water in sociohydrological systems. A conceptual framework to address this gap has been proposed by Anderies, Janssen, and Ostrom (2004). Here we develop a model to operationalize the framework and report some preliminary results. Simple in its setup, the model highlights the structure of the social dilemmas and how it affects the system's sustainability. The model also offers a platform to explore how the system's sustainability may respond to external shocks from globalization and global climate change.
Institute of Scientific and Technical Information of China (English)
Zhixiang ZHOU
2009-01-01
On the basis of a comprehensive literature review and data analysis of global influenza surveillance,a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. Internal dynamic resonance; variations of meteorological elements (solar radiation,precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating strains prove to be the critical explanatory thctors of the seasonality and weekly activity of influenza. In all climate regions,influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza could be deemed as the consequence of the dynamic resonance and interactions of determinants. Early interventions (such as opportune vaccination,prompt social distancing,and maintaining incidence well below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons,more outdoor activities,and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree,the study reveals the mechanism of inlluenza seasonality,demonstrating a potential for influenza activity projection. The concept and algorithm can be explored
Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje
2017-09-01
Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
Andre, B. J.; Rajaram, H.; Silverstein, J.
2010-12-01
diffusion model at the scale of a single rock is developed incorporating the proposed kinetic rate expressions. Simulations of initiation, washout and AMD flows are discussed to gain a better understanding of the role of porosity, effective diffusivity and reactive surface area in generating AMD. Simulations indicate that flow boundary conditions control generation of acid rock drainage as porosity increases.
Online Learning of Industrial Manipulators' Dynamics Models
DEFF Research Database (Denmark)
Polydoros, Athanasios
2017-01-01
The robotics industry has introduced light-weight compliant manipulators to increase the safety during human-robot interaction. This characteristic is achieved by replacing the stiff actuators of the traditional robots with compliant ones which creates challenges in the analytical derivation...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated. In this thesis, is presented, a novel online machine learning approach which is able to model both inverse and forward dynamics models of industrial manipulators...
A stochastic evolutionary model for survival dynamics
Fenner, Trevor; Loizou, George
2014-01-01
The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in different contexts. Here we propose a generative model to capture the essential dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. In our model, the only implicit assumption made is that the longer an actor has been in the system, the more likely it is to have failed. We derive a power-law distribution for the process and provide preliminary empirical evidence for the validity of the model from two well-known survival analysis data sets.
Cellular automata modeling of pedestrian's crossing dynamics
Institute of Scientific and Technical Information of China (English)
张晋; 王慧; 李平
2004-01-01
Cellular automata modeling techniques and the characteristics of mixed traffic flow were used to derive the 2-dimensional model presented here for simulation of pedestrian's crossing dynamics.A conception of "stop point" is introduced to deal with traffic obstacles and resolve conflicts among pedestrians or between pedestrians and the other vehicles on the crosswalk.The model can be easily extended,is very efficient for simulation of pedestrian's crossing dynamics,can be integrated into traffic simulation software,and has been proved feasible by simulation experiments.
Dynamical modelling of coordinated multiple robot systems
Hayati, Samad
1987-01-01
The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.
Stochastic transition model for pedestrian dynamics
Schultz, Michael
2012-01-01
The proposed stochastic model for pedestrian dynamics is based on existing approaches using cellular automata, combined with substantial extensions, to compensate the deficiencies resulting of the discrete grid structure. This agent motion model is extended by both a grid-based path planning and mid-range agent interaction component. The stochastic model proves its capabilities for a quantitative reproduction of the characteristic shape of the common fundamental diagram of pedestrian dynamics. Moreover, effects of self-organizing behavior are successfully reproduced. The stochastic cellular automata approach is found to be adequate with respect to uncertainties in human motion patterns, a feature previously held by artificial noise terms alone.
Quantum Dynamics of the HMF Model
Plestid, Ryan; Mahon, Perry; O'Dell, Duncan
2016-01-01
We study the dynamics of the quantized Hamiltonian Mean Field (HMF) model assuming a gas of bosons in the large N limit. We characterize the full set of stationary states, and study the dynamics of the model numerically focussing on competition between classical and quantum effects. We make contact with the existing literature on the HMF model as a classical system, and stress universal features which can be inferred in the semi-classical limit.In particular we show that the characteristic ch...
Dynamical effects of overparametrization in nonlinear models
Aguirre, Luis Antonio; Billings, S. A.
1995-01-01
This paper is concemed with dynamical reconstruction for nonlinear systems. The effects of the driving function and of the complexity of a given representation on the bifurcation patter are investigated. It is shown that the use of different driving functions to excite the system may yield models with different bifurcation patterns. The complexity of the reconstructions considered is quantified by the embedding dimension and the number of estimated parameters. In this respect it appears that models which reproduce the original bifurcation behaviour are of limited complexity and that excessively complex models tend to induce ghost bifurcations and spurious dynamical regimes. Moreover, some results suggest that the effects of overparametrization on the global dynamical behaviour of a nonlinear model may be more deleterious than the presence of moderate noise levels. In order to precisely quantify the complexity of the reconstructions, global polynomials are used although the results are believed to apply to a much wider class of representations including neural networks.
Dynamic optimization deterministic and stochastic models
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.
MODELS FOR NETWORK DYNAMICS - A MARKOVIAN FRAMEWORK
LEENDERS, RTAJ
1995-01-01
A question not very often addressed in social network analysis relates to network dynamics and focuses on how networks arise and change. It alludes to the idea that ties do not arise or vanish randomly, but (partly) as a consequence of human behavior and preferences. Statistical models for modeling
Dynamic modeling of the INAPRO aquaponic system
Karimanzira, Divas; Keesman, Karel J.; Kloas, Werner; Baganz, Daniela; Rauschenbach, Thomas
2016-01-01
The use of modeling techniques to analyze aquaponics systems is demonstrated with an example of dynamic modeling for the production of Nile tilapia (Oreochromis niloticus) and tomatoes (Solanum lycopersicon) using the innovative double recirculating aquaponic system ASTAF-PRO. For the management and
Dynamic spatial panels : models, methods, and inferences
Elhorst, J. Paul
This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent
A Discrete Dynamical Model of Signed Partitions
Directory of Open Access Journals (Sweden)
G. Chiaselotti
2013-01-01
Full Text Available We use a discrete dynamical model with three evolution rules in order to analyze the structure of a partially ordered set of signed integer partitions whose main properties are actually not known. This model is related to the study of some extremal combinatorial sum problems.
A system dynamics model for communications networks
Awcock, A. J.; King, T. E. G.
1985-09-01
An abstract model of a communications network in system dynamics terminology is developed as implementation of this model by a FORTRAN program package developed at RSRE is discussed. The result of this work is a high-level simulation package in which the performance of adaptive routing algorithms and other network controls may be assessed for a network of arbitrary topology.
Concept-Oriented Modeling of Dynamic Behavior
Breedveld, P.C.; Borutzky, Wolfgang
2011-01-01
This chapter introduces the reader to the concept-oriented approach to modeling that clearly separates ideal concepts from the physical components of a system when modeling its dynamic behavior for a specific problem context. This is done from a port-based point of view for which the domain-independ
Dynamic Decision Making for Graphical Models Applied to Oil Exploration
Martinelli, Gabriele; Hauge, Ragnar
2012-01-01
We present a framework for sequential decision making in problems described by graphical models. The setting is given by dependent discrete random variables with associated costs or revenues. In our examples, the dependent variables are the potential outcomes (oil, gas or dry) when drilling a petroleum well. The goal is to develop an optimal selection strategy that incorporates a chosen utility function within an approximated dynamic programming scheme. We propose and compare different approximations, from simple heuristics to more complex iterative schemes, and we discuss their computational properties. We apply our strategies to oil exploration over multiple prospects modeled by a directed acyclic graph, and to a reservoir drilling decision problem modeled by a Markov random field. The results show that the suggested strategies clearly improve the simpler intuitive constructions, and this is useful when selecting exploration policies.
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.
A dynamical model for the Utricularia trap
Llorens, Coraline; Argentina, Médéric; Bouret, Yann; Marmottant, Philippe; Vincent, Olivier
2012-01-01
We propose a model that captures the dynamics of a carnivorous plant, Utricularia inflata. This plant possesses tiny traps for capturing small aquatic animals. Glands pump water out of the trap, yielding a negative pressure difference between the plant and its surroundings. The trap door is set into a meta-stable state and opens quickly as an extra pressure is generated by the displacement of a potential prey. As the door opens, the pressure difference sucks the animal into the trap. We write an ODE model that captures all the physics at play. We show that the dynamics of the plant is quite similar to neuronal dynamics and we analyse the effect of a white noise on the dynamics of the trap. PMID:22859569
Adaptation dynamics of the quasispecies model
Indian Academy of Sciences (India)
Kavita Jain
2008-08-01
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen’s model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a quasispecies which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.
Adaptation dynamics of the quasispecies model
Jain, Kavita
2009-02-01
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.
Replicator-dynamics models of sexual conflict.
Kimura, Mariko; Ihara, Yasuo
2009-09-07
Evolutionary conflict between the sexes has been studied in various taxa and in various contexts. When the sexes are in conflict over mating rates, natural selection favors both males that induce higher mating rates and females that are more successful at resisting mating attempts. Such sexual conflict may result in an escalating coevolutionary arms race between males and females. In this article, we develop simple replicator-dynamics models of sexual conflict in order to investigate its evolutionary dynamics. Two specific models of the dependence of a female's fitness on her number of matings are considered: in model 1, female fitness decreases linearly with increasing number of matings and in model 2, there is an optimal number of matings that maximizes female fitness. For each of these models, we obtain the conditions for a coevolutionary process to establish costly male and female traits and examine under what circumstances polymorphism is maintained at equilibrium. Then we discuss how assumptions in previous models of sexual conflict are translated to fit to our model framework and compare our results with those of the previous studies. The simplicity of our models allows us to consider sexual conflict in various contexts within a single framework. In addition, we find that our model 2 shows more complicated evolutionary dynamics than model 1. In particular, the population exhibits bistability, where the evolutionary outcome depends on the initial state, only in model 2.
Jung, Jae Yup
2013-01-01
This study tested a newly developed model of the cognitive decision-making processes of senior high school students related to university entry. The model incorporated variables derived from motivation theory (i.e. expectancy-value theory and the theory of reasoned action), literature on cultural orientation and occupational considerations. A…
Taatgen, Niels A.; de Weerd, Harmen; Reitter, David; Ritter, Frank
2016-01-01
We present a Swift re-implementation of the ACT-R cognitive architecture, which can be used to quickly build iOS Apps that incorporate an ACT-R model as a core feature. We discuss how this implementation can be used in an example model, and explore the breadth of possibilities by presenting six Apps
Jung, Jae Yup
2013-01-01
This study tested a newly developed model of the cognitive decision-making processes of senior high school students related to university entry. The model incorporated variables derived from motivation theory (i.e. expectancy-value theory and the theory of reasoned action), literature on cultural orientation and occupational considerations. A…
Directory of Open Access Journals (Sweden)
Wen-Jeng Huang
2016-02-01
Full Text Available We develop a folding boundary element model in a medium containing a fault and elastic layers to show that anticlines growing over slipping reverse faults can be significantly amplified by mechanical layering buckling under horizontal shortening. Previous studies suggested that folds over blind reverse faults grow primarily during deformation increments associated with slips on the fault during and immediately after earthquakes. Under this assumption, the potential for earthquakes on blind faults can be determined directly from fold geometry because the amount of slip on the fault can be estimated directly from the fold geometry using the solution for a dislocation in an elastic half-space. Studies that assume folds grown solely by slip on a fault may therefore significantly overestimate fault slip. Our boundary element technique demonstrates that the fold amplitude produced in a medium containing a fault and elastic layers with free slip and subjected to layer-parallel shortening can grow to more than twice the fold amplitude produced in homogeneous media without mechanical layering under the same amount of shortening. In addition, the fold wavelengths produced by the combined fault slip and buckling mechanisms may be narrower than folds produced by fault slip in an elastic half space by a factor of two. We also show that subsurface fold geometry of the Kettleman Hills Anticline in Central California inferred from seismic reflection image is consistent with a model that incorporates layer buckling over a dipping, blind reverse fault and the coseismic uplift pattern produced during a 1985 earthquake centered over the anticline forelimb is predicted by the model.
Cosmological model with dynamical curvature
Stichel, Peter C
2016-01-01
We generalize the recently introduced relativistic Lagrangian darkon fluid model (EPJ C (2015) 75:9) by starting with a self-gravitating geodesic fluid whose energy-momentum tensor is dust-like with a nontrivial energy flow. The corresponding covariant propagation and constraint equations are considered in a shear-free nonrelativistic limit whose analytic solutions determine the 1st-order relativistic correction to the spatial curvature. This leads to a cosmological model where the accelerated expansion of the Universe is driven by a time-dependent spatial curvature without the need for introducing any kind of dark energy. We derive the differential equation to be satisfied by the area distance for this model.
Stevens, Andrew W.; Gelfenbaum, Guy; Elias, Edwin; Jones, Craig
2008-01-01
lab with Sedflume, an apparatus for measuring sediment erosion-parameters. In this report, we present results of the characterization of fine-grained sediment erodibility within Capitol Lake. The erodibility data were incorporated into the previously developed hydrodynamic and sediment transport model. Model simulations using the measured erodibility parameters were conducted to provide more robust estimates of the overall magnitudes and spatial patterns of sediment transport resulting from restoration of the Deschutes Estuary.
A diagnostic model incorporating P50 sensory gating and neuropsychological tests for schizophrenia.
Directory of Open Access Journals (Sweden)
Jia-Chi Shan
Full Text Available OBJECTIVES: Endophenotypes in schizophrenia research is a contemporary approach to studying this heterogeneous mental illness, and several candidate neurophysiological markers (e.g. P50 sensory gating and neuropsychological tests (e.g. Continuous Performance Test (CPT and Wisconsin Card Sorting Test (WCST have been proposed. However, the clinical utility of a single marker appears to be limited. In the present study, we aimed to construct a diagnostic model incorporating P50 sensory gating with other neuropsychological tests in order to improve the clinical utility. METHODS: We recruited clinically stable outpatients meeting DSM-IV criteria of schizophrenia and age- and gender-matched healthy controls. Participants underwent P50 sensory gating experimental sessions and batteries of neuropsychological tests, including CPT, WCST and Wechsler Adult Intelligence Scale Third Edition (WAIS-III. RESULTS: A total of 106 schizophrenia patients and 74 healthy controls were enrolled. Compared with healthy controls, the patient group had significantly a larger S2 amplitude, and thus poorer P50 gating ratio (gating ratio = S2/S1. In addition, schizophrenia patients had a poorer performance on neuropsychological tests. We then developed a diagnostic model by using multivariable logistic regression analysis to differentiate patients from healthy controls. The final model included the following covariates: abnormal P50 gating (defined as P50 gating ratio >0.4, three subscales derived from the WAIS-III (Arithmetic, Block Design, and Performance IQ, sensitivity index from CPT and smoking status. This model had an adequate accuracy (concordant percentage = 90.4%; c-statistic = 0.904; Hosmer-Lemeshow Goodness-of-Fit Test, p = 0.64>0.05. CONCLUSION: To the best of our knowledge, this is the largest study to date using P50 sensory gating in subjects of Chinese ethnicity and the first to use P50 sensory gating along with other neuropsychological tests
Modeling hybrid perovskites by molecular dynamics.
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Modeling hybrid perovskites by molecular dynamics
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Dispersive models describing mosquitoes’ population dynamics
Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.
2016-08-01
The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.
Induction generator models in dynamic simulation tools
DEFF Research Database (Denmark)
Knudsen, Hans; Akhmatov, Vladislav
1999-01-01
. It is found to be possible to include a transient model in dynamic stability tools and, then, obtain correct results also in dynamic tools. The representation of the rotating system influences on the voltage recovery shape which is an important observation in case of windmills, where a heavy mill is connected......For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained...
Ellison, Donald; Conway, Bruce; Englander, Jacob
2015-01-01
A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.
Dynamics of the supermarket model
MacPhee, I M; Vachkovskaia, M
2010-01-01
We consider the long term behaviour of a Markov chain \\xi(t) on \\Z^N based on the N station supermarket model. Different routing policies for the supermarket model give different Markov chains. We show that for a general class of local routing policies, "join the least weighted queue" (JLW), the N one-dimensional components \\xi_i(t) can be partitioned into disjoint clusters C_k. Within each cluster C_k the "speed" of each component \\xi_j converges to a constant V_k and under certain conditions \\xi is recurrent in shape on each cluster. To establish these results we have assembled methods from two distinct areas of mathematics, semi-martingale techniques used for showing stability of Markov chains together with the theory of optimal flows in networks. As corollaries to our main result we obtain the stability classification of the supermarket model under any JLW policy and can explicitly compute the C_k and V_k for any instance of the model and specific JLW policy.
Renormalized dynamics of the Dean-Kawasaki model
Bidhoodi, Neeta; Das, Shankar P.
2015-07-01
We study the model of a supercooled liquid for which the equation of motion for the coarse-grained density ρ (x ,t ) is the nonlinear diffusion equation originally proposed by Dean and Kawasaki, respectively, for Brownian and Newtonian dynamics of fluid particles. Using a Martin-Siggia-Rose (MSR) field theory we study the renormalization of the dynamics in a self-consistent form in terms of the so-called self-energy matrix Σ . The appropriate model for the renormalized dynamics involves an extended set of field variables {ρ ,θ } , linked through a nonlinear constraint. The latter incorporates, in a nonperturbative manner, the effects of an infinite number of density nonlinearities in the dynamics. We show that the contributing element of Σ which renormalizes the bare diffusion constant D0 to DR is same as that proposed by Kawasaki and Miyazima [Z. Phys. B Condens. Matter 103, 423 (1997), 10.1007/s002570050396]. DR sharply decreases with increasing density. We consider the likelihood of a ergodic-nonergodic (ENE) transition in the model beyond a critical point. The transition is characterized by the long-time limit of the density correlation freezing at a nonzero value. From our analysis we identify an element of Σ which arises from the above-mentioned nonlinear constraint and is key to the viability of the ENE transition. If this self-energy would be zero, then the model supports a sharp ENE transition with DR=0 as predicted by Kawasaki and Miyazima. With the full model having nonzero value for this self-energy, the density autocorrelation function decays to zero in the long-time limit. Hence the ENE transition is not supported in the model.
Renormalized dynamics of the Dean-Kawasaki model.
Bidhoodi, Neeta; Das, Shankar P
2015-07-01
We study the model of a supercooled liquid for which the equation of motion for the coarse-grained density ρ(x,t) is the nonlinear diffusion equation originally proposed by Dean and Kawasaki, respectively, for Brownian and Newtonian dynamics of fluid particles. Using a Martin-Siggia-Rose (MSR) field theory we study the renormalization of the dynamics in a self-consistent form in terms of the so-called self-energy matrix Σ. The appropriate model for the renormalized dynamics involves an extended set of field variables {ρ,θ}, linked through a nonlinear constraint. The latter incorporates, in a nonperturbative manner, the effects of an infinite number of density nonlinearities in the dynamics. We show that the contributing element of Σ which renormalizes the bare diffusion constant D(0) to D(R) is same as that proposed by Kawasaki and Miyazima [Z. Phys. B Condens. Matter 103, 423 (1997)]. D(R) sharply decreases with increasing density. We consider the likelihood of a ergodic-nonergodic (ENE) transition in the model beyond a critical point. The transition is characterized by the long-time limit of the density correlation freezing at a nonzero value. From our analysis we identify an element of Σ which arises from the above-mentioned nonlinear constraint and is key to the viability of the ENE transition. If this self-energy would be zero, then the model supports a sharp ENE transition with D(R)=0 as predicted by Kawasaki and Miyazima. With the full model having nonzero value for this self-energy, the density autocorrelation function decays to zero in the long-time limit. Hence the ENE transition is not supported in the model.
Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness.
Zhang, Jing; Chu, Haitao; Hong, Hwanhee; Virnig, Beth A; Carlin, Bradley P
2015-07-28
Network meta-analysis expands the scope of a conventional pairwise meta-analysis to simultaneously compare multiple treatments, synthesizing both direct and indirect information and thus strengthening inference. Since most of trials only compare two treatments, a typical data set in a network meta-analysis managed as a trial-by-treatment matrix is extremely sparse, like an incomplete block structure with significant missing data. Zhang et al. proposed an arm-based method accounting for correlations among different treatments within the same trial and assuming that absent arms are missing at random. However, in randomized controlled trials, nonignorable missingness or missingness not at random may occur due to deliberate choices of treatments at the design stage. In addition, those undertaking a network meta-analysis may selectively choose treatments to include in the analysis, which may also lead to missingness not at random. In this paper, we extend our previous work to incorporate missingness not at random using selection models. The proposed method is then applied to two network meta-analyses and evaluated through extensive simulation studies. We also provide comprehensive comparisons of a commonly used contrast-based method and the arm-based method via simulations in a technical appendix under missing completely at random and missing at random.
Energy Technology Data Exchange (ETDEWEB)
Galan, S.F. [Dpto. de Inteligencia Artificial, E.T.S.I. Informatica (UNED), Juan del Rosal, 16, 28040 Madrid (Spain)]. E-mail: seve@dia.uned.es; Mosleh, A. [2100A Marie Mount Hall, Materials and Nuclear Engineering Department, University of Maryland, College Park, MD 20742 (United States)]. E-mail: mosleh@umd.edu; Izquierdo, J.M. [Area de Modelado y Simulacion, Consejo de Seguridad Nuclear, Justo Dorado, 11, 28040 Madrid (Spain)]. E-mail: jmir@csn.es
2007-08-15
The {omega}-factor approach is a method that explicitly incorporates organizational factors into Probabilistic safety assessment of nuclear power plants. Bayesian networks (BNs) are the underlying formalism used in this approach. They have a structural part formed by a graph whose nodes represent organizational variables, and a parametric part that consists of conditional probabilities, each of them quantifying organizational influences between one variable and its parents in the graph. The aim of this paper is twofold. First, we discuss some important limitations of current procedures in the {omega}-factor approach for either assessing conditional probabilities from experts or estimating them from data. We illustrate the discussion with an example that uses data from Licensee Events Reports of nuclear power plants for the estimation task. Second, we introduce significant improvements in the way BNs for the {omega}-factor approach can be constructed, so that parameter acquisition becomes easier and more intuitive. The improvements are based on the use of noisy-OR gates as model of multicausal interaction between each BN node and its parents.
Sikorska, Emilia; Sobolewski, Dariusz; Kwiatkowska, Anna
2012-04-01
In this study, arginine vasopressin analogues modified with proline derivatives - indoline-2-carboxylic acid (Ica), (2S,4R)-4-(naphthalene-2-ylmethyl)pyrrolidine-2-carboxylic acid (Nmp), (2S,4S)-4-aminopyroglutamic acid (APy) and (2R,4S)-4-aminopyroglutamic acid, (Apy) - were examined using NMR spectroscopy and molecular modelling methods. The results have shown that Ica is involved in the formation of the cis peptide bond. Moreover, it reduces to a great extent the conformational flexibility of the peptide. In turn, incorporation of (2S,4R)-Nmp stabilizes the backbone conformation, which is heavily influenced by the pyrrolidine ring. However, the aromatic part of the Nmp side chain exhibits a high degree of conformational freedom. With analogues IV and V, introduction of the 4-aminopyroglumatic acid reduces locally conformational space of the peptides, but it also results in weaker interactions with the dodecylphosphocholine/sodium dodecyl sulphate micelle. Admittedly, both analogues are adsorbed on the micelle's surface but they do not penetrate into its core. With analogue V, the interactions between the peptide and the micelle seem to be so weak that conformational equilibrium is established between different bound states.
Directory of Open Access Journals (Sweden)
Adriana Z. Mazurek
2012-01-01
Full Text Available Floating dust-originated solid particles at air-water interfaces will interact with one another and disturb the smoothness of such a composite surface affecting its dilational elasticity. To quantify the effect, surface pressure (Π versus film area (A isotherm, and stress-relaxation (Π-time measurements were performed for monoparticulate layers of the model hydrophobic material (of μm-diameter and differentiated hydrophobicity corresponding to the water contact angles (CA ranging from 60 to 140° deposited at surfaces of surfactant-containing original seawater and were studied with a Langmuir trough system. The composite surface dilational modulus predicted from the theoretical approach, in which natural dust load signatures (particle number flux, daily deposition rate, and diameter spectra originated from in situ field studies performed along Baltic Sea near-shore line stations, agreed well with the direct experimentally derived data. The presence of seawater surfactants affected wettability of the solid material which was evaluated with different CA techniques applicable to powdered samples. Surface energetics of the particle-subphase interactions was expressed in terms of the particle removal energy, contact cross-sectional areas, collapse energies, and so forth. The hydrophobic particles incorporation at a sea surface film structure increased the elasticity modulus by a factor K (1.29–1.58. The particle-covered seawater revealed a viscoelastic behavior with the characteristic relaxation times ranging from 2.6 to 68.5 sec.
Intermittent rainfall in dynamic multimedia fate modeling.
Hertwich, E G
2001-03-01
It has been shown that steady-state multimedia models (level III fugacity models) lead to a substantial underestimate of air concentrations for chemicals with a low Henry's law constant (H multimedia models are used to estimate the spatial range or inhalation exposure. A dynamic model of pollutant fate is developed for conditions of intermittent rainfall to calculate the time profile of pollutant concentrations in different environmental compartments. The model utilizes a new, mathematically efficient approach to dynamic multimedia fate modeling that is based on the convolution of solutions to the initial conditions problem. For the first time, this approach is applied to intermittent conditions. The investigation indicates that the time-averaged pollutant concentrations under intermittent rainfall can be approximated by the appropriately weighted average of steady-state concentrations under conditions with and without rainfall.
Dynamic exponents for potts model cluster algorithms
Coddington, Paul D.; Baillie, Clive F.
We have studied the Swendsen-Wang and Wolff cluster update algorithms for the Ising model in 2, 3 and 4 dimensions. The data indicate simple relations between the specific heat and the Wolff autocorrelations, and between the magnetization and the Swendsen-Wang autocorrelations. This implies that the dynamic critical exponents are related to the static exponents of the Ising model. We also investigate the possibility of similar relationships for the Q-state Potts model.
The dynamic model of enterprise revenue management
Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.
2017-01-01
The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.
Feature Extraction for Structural Dynamics Model Validation
Energy Technology Data Exchange (ETDEWEB)
Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield
2016-01-13
As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.
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.
A Dynamic Model for Energy Structure Analysis
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Energy structure is a complicated system concerning economic development, natural resources, technological innovation, ecological balance, social progress and many other elements. It is not easy to explain clearly the developmental mechanism of an energy system and the mutual relations between the energy system and its related environments by the traditional methods. It is necessary to develop a suitable dynamic model, which can reflect the dynamic characteristics and the mutual relations of the energy system and its related environments. In this paper, the historical development of China's energy structure was analyzed. A new quantitative analysis model was developed based on system dynamics principles through analysis of energy resources, and the production and consumption of energy in China and comparison with the world. Finally, this model was used to predict China's future energy structures under different conditions.
Dynamic Model Identification for Industrial Robots
Directory of Open Access Journals (Sweden)
Ngoc Dung Vuong
2009-12-01
Full Text Available In this paper, a systematic procedure for identifying the dynamics of industrialrobots is presented. Since joint friction can be highly nonlinearwith time varyingcharacteristics in the low speed region,a simple and yet effective scheme has been used toidentify the boundary velocity that separates this “dynamic” friction region from its staticregion. The robot’s dynamic model is then identified in this static region, where thenonlinnear friction model is reduced to the linear-in-parameter form. To overcome thedrawbacks of the least squares estimator, which does not take in any constraints, anonlinear optimization problem is formulated to guarantee the physical feasibility of theidentified parameters. The proposed procedure has been demonstrated on the first fourlinks of the Mitsubishi PA10 manipulator, an improved dynamic model was obtained andthe the effectiveness of the proposed identification procedure is demonstrated.
Dynamic Model for Life History of Scyphozoa.
Directory of Open Access Journals (Sweden)
Congbo Xie
Full Text Available A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish.
Clarke; Bell; Hobbs; George
1999-07-01
/ This paper synthesizes results of research into the impact that major faults have on dryland salinity and the development of revegetation treatments in the wheatbelt of Western Australia. Currently, landscape planning does not routinely incorporate geology, but this research shows that faults can have a dramatic impact on land and stream salinization and on the effectiveness of revegetation treatments, and evidence exists that other geological features can have a similar influence. This research shows that faults can be identified from airborne magnetic data, they can be assigned a characteristic hydraulic conductivity based on simple borehole tests, and four other geological features that are expected to affect land and stream salinity could be identified in airborne geophysical data. A geological theme map could then be created to which characteristic hydraulic conductivities could be assigned for use in computer groundwater models to improve prediction of the effectiveness of revegetation treatments and thus enhance the landscape planning process. The work highlights the difficulties of using standard sampling and statistical techniques to investigate regional phenomena and presents an integrated approach combining small-scale sampling with broad-scale observations to provide input into a modeling exercise. It is suggested that such approaches are vital if landscape- and regional-scale processes are to be understood and managed. The way in which the problem is perceived (holistically or piecemeal) affects the way treatments are designed and their effectiveness: past approaches have failed to integrate the various scales and processes involved. Effective solutions require an integrated holistic response.KEY WORDS: Dryland salinity; Geology; Landscape; Revegetation integrationhttp://link.springer-ny.com/link/service/journals/00267/bibs/24n1p99.html
Modeling Of Ballistic Missile Dynamics
Directory of Open Access Journals (Sweden)
Salih Mahmoud Attiya
2013-05-01
Full Text Available Aerodynamic modeling of ballistic missile in pitch plane is performed and the open-loop transfer function related to the jet deflector angle as input and pitch rate, normal acceleration as output has been derived with certain acceptable assumptions. For typical values of ballistic missile parameters such as mass, velocity, altitude, moment of inertia, thrust, moment and lift coefficient show that, the step time response and frequency response of the missile is unstable. The steady state gain, damping ratio and undraped natural frequency depend on the missile parameters. To stabilize the missile a lead compensator must be added to the forward loop.
Dynamic modeling of solar dynamic components and systems
Hochstein, John I.; Korakianitis, T.
1992-09-01
The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.
Dynamic species distribution models from categorical survey data.
Mieszkowska, Nova; Milligan, Gregg; Burrows, Michael T; Freckleton, Rob; Spencer, Matthew
2013-11-01
1. Species distribution models are static models for the distribution of a species, based on Hutchinson's niche concept. They make probabilistic predictions about the distribution of a species, but do not have a temporal interpretation. In contrast, density-structured models based on categorical abundance data make it possible to incorporate population dynamics into species distribution modelling. 2. Using dynamic species distribution models, temporal aspects of a species' distribution can be investigated, including the predictability of future abundance categories and the expected persistence times of local populations, and how these may respond to environmental or anthropogenic drivers. 3. We built density-structured models for two intertidal marine invertebrates, the Lusitanian trochid gastropods Phorcus lineatus and Gibbula umbilicalis, based on 9 years of field data from around the United Kingdom. Abundances were recorded on a categorical scale, and stochastic models for year-to-year changes in abundance category were constructed with winter mean sea surface temperature (SST) and wave fetch (a measure of the exposure of a shore) as explanatory variables. 4. Both species were more likely to be present at sites with high SST, but differed in their responses to wave fetch. Phorcus lineatus had more predictable future abundance and longer expected persistence times than G. umbilicalis. This is consistent with the longer lifespan of P. lineatus. 5. Where data from multiple time points are available, dynamic species distribution models of the kind described here have many applications in population and conservation biology. These include allowing for changes over time when combining historical and contemporary data, and predicting how climate change might alter future abundance conditional on current distributions.
Sensitivity studies for incorporating the direct effect of sulfate aerosols into climate models
Miller, Mary Rawlings Lamberton
2000-09-01
Aerosols have been identified as a major element of the climate system known to scatter and absorb solar and infrared radiation, but the development of procedures for representing them is still rudimentary. This study addresses the need to improve the treatment of sulfate aerosols in climate models by investigating how sensitive radiative particles are to varying specific sulfate aerosol properties. The degree to which sulfate particles absorb or scatter radiation, termed the direct effect, varies with the size distribution of particles, the aerosol mass density, the aerosol refractive indices, the relative humidity and the concentration of the aerosol. This study develops 504 case studies of altering sulfate aerosol chemistry, size distributions, refractive indices and densities at various ambient relative humidity conditions. Ammonium sulfate and sulfuric acid aerosols are studied with seven distinct size distributions at a given mode radius with three corresponding standard deviations implemented from field measurements. These test cases are evaluated for increasing relative humidity. As the relative humidity increases, the complex index of refraction and the mode radius for each distribution correspondingly change. Mie theory is employed to obtain the radiative properties for each case study. The case studies are then incorporated into a box model, the National Center of Atmospheric Research's (NCAR) column radiation model (CRM), and NCAR's community climate model version 3 (CCM3) to determine how sensitive the radiative properties and potential climatic effects are to altering sulfate properties. This study found the spatial variability of the sulfate aerosol leads to regional areas of intense aerosol forcing (W/m2). These areas are particularly sensitive to altering sulfate properties. Changes in the sulfate lognormal distribution standard deviation can lead to substantial regional differences in the annual aerosol forcing greater than 2 W/m 2. Changes in the
Dynamical properties of the Rabi model
Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin
2017-02-01
We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation.
Dynamical Model of Weak Pion Production Reactions
Sato, T; Lee, T S H
2003-01-01
The dynamical model of pion electroproduction has been extended to investigate the weak pion production reactions. The predicted cross sections of neutrino-induced pion production reactions are in good agreement with the existing data. We show that the renormalized(dressed) axial N-$\\Delta$ form factor contains large dynamical pion cloud effects and this renormalization effects are crucial in getting agreement with the data. We conclude that the N-$\\Delta$ transitions predicted by the constituent quark model are consistent with the existing neutrino induced pion production data in the $\\Delta$ region.
Research on nonlinear stochastic dynamical price model
Energy Technology Data Exchange (ETDEWEB)
Li Jiaorui [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); School of Statistics, Xi' an University of Finance and Economics, Xi' an 710061 (China)], E-mail: jiaoruili@mail.nwpu.edu.cn; Xu Wei; Xie Wenxian; Ren Zhengzheng [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2008-09-15
In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies.
Energy Technology Data Exchange (ETDEWEB)
Nelson, Tammie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Center for Nonlinear Studies (CNLS) and Center for Integrated Nanotechnologies (CINT), Theoretical Division; Fernandez-Alberti, Sebastian [Univ. Nacional de Quilmes, Buenos Aires (Argentina); Chernyak, Vladimir [Wayne State Univ., Detroit, MI (United States). Dept. of Chemistry; Roitberg, Adrian E. [Univ. of Florida, Gainesville, FL (United States). Depts. of Physics and Chemistry. Quantum Theory Project; Tretiak, Sergei [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Center for Nonlinear Studies (CNLS) and Center for Integrated Nanotechnologies (CINT), Theoretical Division
2011-01-10
Nonadiabatic dynamics generally defines the entire evolution of electronic excitations in optically active molecular materials. It is commonly associated with a number of fundamental and complex processes such as intraband relaxation, energy transfer, and light harvesting influenced by the spatial evolution of excitations and transformation of photoexcitation energy into electrical energy via charge separation (e.g., charge injection at interfaces). To treat ultrafast excited-state dynamics and exciton/charge transport we have developed a nonadiabatic excited-state molecular dynamics (NA-ESMD) framework incorporating quantum transitions. Our calculations rely on the use of the Collective Electronic Oscillator (CEO) package accounting for many-body effects and actual potential energy surfaces of the excited states combined with Tully’s fewest switches algorithm for surface hopping for probing nonadiabatic processes. This method is applied to model the photoinduced dynamics of distyrylbenzene (a small oligomer of polyphenylene vinylene, PPV). Our analysis shows intricate details of photoinduced vibronic relaxation and identifies specific slow and fast nuclear motions that are strongly coupled to the electronic degrees of freedom, namely, torsion and bond length alternation, respectively. Nonadiabatic relaxation of the highly excited mA{sub g} state is predicted to occur on a femtosecond time scale at room temperature and on a picosecond time scale at low temperature.
Dynamic model for the popularity of websites
Lee, Chang-Yong; Kim, Seungwhan
2002-03-01
In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.
Modelling environmental dynamics. Advances in goematic solutions
Energy Technology Data Exchange (ETDEWEB)
Paegelow, Martin [Toulouse-2 Univ., 31 (France). GEODE UMR 5602 CNRS; Camacho Olmedo, Maria Teresa (eds.) [Granada Univ (Spain). Dpto. de Analisis Geografico Regional y Geografia Fisica
2008-07-01
Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management. The first chapter introduces terminology and provides an overview of methodological modelling approaches which may be applied to environmental and complex dynamics. Based on this introduction this book illustrates various models applied to a large variety of themes: deforestation in tropical regions, fire risk, natural reforestation in European mountains, agriculture, biodiversity, urbanism, climate change and land management for decision support, etc. These case studies, provided by a large international spectrum of researchers and presented in a uniform structure, focus particularly on methods and model validation so that this book is not only aimed at researchers and graduates but also at professionals. (orig.)
Modeling emotional dynamics : currency versus field.
Energy Technology Data Exchange (ETDEWEB)
Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago
2008-08-01
Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.
Modeling dynamic functional connectivity using a wishart mixture model
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2017-01-01
.e. the window length. In this work we use the Wishart Mixture Model (WMM) as a probabilistic model for dFC based on variational inference. The framework admits arbitrary window lengths and number of dynamic components and includes the static one-component model as a special case. We exploit that the WMM...
Al-Jabr, Ahmad Ali
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.
Modeling the dynamics of dissent
Lee, Eun; Lee, Sang Hoon
2016-01-01
We investigate opinion formation against authority in an authoritarian society composed of agents with different levels of authority. We explore a (symbolically) "right" opinion, held by lower-ranking, obedient, less authoritative people, spreading in an environment of a "wrong" opinion held by authoritative leaders. The mental picture would be that of a corrupt society where the ruled people revolts against authority, but it could be argued to hold in more general situations. In our model, agents can change their opinion depending on the relative authority to their neighbors and their own confidence level. In addition, with a certain probability, agents can override the authority to take the right opinion of a neighbor. Based on analytic derivation and numerical simulations, we observe that both the network structure and heterogeneity in authority, and their correlation significantly affect the possibility of the right opinion to spread in the population. In particular, the right opinion is suppressed when t...
Induction generator models in dynamic simulation tools
DEFF Research Database (Denmark)
Knudsen, Hans; Akhmatov, Vladislav
1999-01-01
For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained. It is fo......For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained....... It is found to be possible to include a transient model in dynamic stability tools and, then, obtain correct results also in dynamic tools. The representation of the rotating system influences on the voltage recovery shape which is an important observation in case of windmills, where a heavy mill is connected...
Dissipative particle dynamics model for colloid transport in porous media
Energy Technology Data Exchange (ETDEWEB)
Pan, W.; Tartakovsky, A. M.
2013-08-01
We present that the transport of colloidal particles in porous media can be effectively modeled with a new formulation of dissipative particle dynamics, which augments standard DPD with non-central dissipative shear forces between particles while preserving angular momentum. Our previous studies have demonstrated that the new formulation is able to capture accurately the drag forces as well as the drag torques on colloidal particles that result from the hydrodynamic retardation effect. In the present work, we use the new formulation to study the contact efficiency in colloid filtration in saturated porous media. Note that the present model include all transport mechanisms simultaneously, including gravitational sedimentation, interception and Brownian diffusion. Our results of contact efficiency show a good agreement with the predictions of the correlation equation proposed by Tufenkji and EliMelech, which also incorporate all transport mechanisms simultaneously without the additivity assumption.
Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*
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
Knowledge Map: Mathematical Model and Dynamic Behaviors
Institute of Scientific and Technical Information of China (English)
Hai Zhuge; Xiang-Feng Luo
2005-01-01
Knowledge representation and reasoning is a key issue of the Knowledge Grid. This paper proposes a Knowledge Map (KM) model for representing and reasoning causal knowledge as an overlay in the Knowledge Grid. It extends Fuzzy Cognitive Maps (FCMs) to represent and reason not only simple cause-effect relations, but also time-delay causal relations, conditional probabilistic causal relations and sequential relations. The mathematical model and dynamic behaviors of KM are presented. Experiments show that, under certain conditions, the dynamic behaviors of KM can translate between different states. Knowing this condition, experts can control or modify the constructed KM while its dynamic behaviors do not accord with their expectation. Simulations and applications show that KM is more powerful and natural than FCM in emulating real world.
Dynamic landscape models of coevolutionary games
Richter, Hendrik
2016-01-01
Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling procedure is carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use either birth-death (BD) or death-birth (DB) strategy updating. With the main focus on using dynamic fitness landscapes as an alternative tool for analyzing coevolutionary games, landscape measures such as modality, ruggedness and information content are computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the network of interaction are calculated numerically. Relations are established between landscape properties expressed by landscape measures and quantifiers of coevolutionary game dynamics such as fixation probabilities, fixation times and network properties
Hidden Symmetry of a Fluid Dynamical Model
Neves, C
2001-01-01
A connection between solutions of the relativistic d-brane system in (d+1) dimensions with the solutions of a Galileo invariant fluid in d-dimensions is by now well established. However, the physical nature of the light-cone gauge description of a relativistic membrane changes after the reduction to the fluid dynamical model since the gauge symmetry is lost. In this work we argue that the original gauge symmetry present in a relativistic d-brane system can be recovered after the reduction process to a d-dimensional fluid model. To this end we propose, without introducing Wess-Zumino fields, a gauge invariant theory of isentropic fluid dynamics and show that this symmetry corresponds to the invariance under local translation of the velocity potential in the fluid dynamics picture. We show that different but equivalent choices of the sympletic sector lead to distinct representations of the embedded gauge algebra.
Dynamics models of soil organic carbon
Institute of Scientific and Technical Information of China (English)
YANGLi-xia; PANJian-jun
2003-01-01
As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.
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.
Human Muscle Fatigue Model in Dynamic Motions
Ma, Ruina; Bennis, Fouad; Ma, Liang
2012-01-01
Human muscle fatigue is considered to be one of the main reasons for Musculoskeletal Disorder (MSD). Recent models have been introduced to define muscle fatigue for static postures. However, the main drawbacks of these models are that the dynamic effect of the human and the external load are not taken into account. In this paper, each human joint is assumed to be controlled by two muscle groups to generate motions such as push/pull. The joint torques are computed using Lagrange's formulation to evaluate the dynamic factors of the muscle fatigue model. An experiment is defined to validate this assumption and the result for one person confirms its feasibility. The evaluation of this model can predict the fatigue and MSD risk in industry production quickly.
System and mathematical modeling of quadrotor dynamics
Goodman, Jacob M.; Kim, Jinho; Gadsden, S. Andrew; Wilkerson, Stephen A.
2015-05-01
Unmanned aerial systems (UAS) are becoming increasingly visible in our daily lives; and range in operation from search and rescue, monitoring hazardous environments, and to the delivery of goods. One of the most popular UAS are based on a quad-rotor design. These are typically small devices that rely on four propellers for lift and movement. Quad-rotors are inherently unstable, and rely on advanced control methodologies to keep them operating safely and behaving in a predictable and desirable manner. The control of these devices can be enhanced and improved by making use of an accurate dynamic model. In this paper, we examine a simple quadrotor model, and note some of the additional dynamic considerations that were left out. We then compare simulation results of the simple model with that of another comprehensive model.
Contact force models for multibody dynamics
Flores, Paulo
2016-01-01
This book analyzes several compliant contact force models within the context of multibody dynamics, while also revisiting the main issues associated with fundamental contact mechanics. In particular, it presents various contact force models, from linear to nonlinear, from purely elastic to dissipative, and describes their parameters. Addressing the different numerical methods and algorithms for contact problems in multibody systems, the book describes the gross motion of multibody systems by using a two-dimensional formulation based on the absolute coordinates and employs different contact models to represent contact-impact events. Results for selected planar multibody mechanical systems are presented and utilized to discuss the main assumptions and procedures adopted throughout this work. The material provided here indicates that the prediction of the dynamic behavior of mechanical systems involving contact-impact strongly depends on the choice of contact force model. In short, the book provides a comprehens...
Record Dynamics in the Parking Lot Model
DEFF Research Database (Denmark)
Sibani, Paolo; Boettcher, Stefan
2016-01-01
We study the aging dynamics in the parking lot model of granular relaxation with extensive numerical simulations. Our results reveal the log-Poisson statistics in the progression of intermittent events that lead to ever slower increases in the density. Defining clusters as domains of parked cars...
Modeling the Hydrogen Bond within Molecular Dynamics
Lykos, Peter
2004-01-01
The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.