Molenaar, Peter C M
2017-02-16
Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.
Thermal dynamic modeling study
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.
1972-01-01
Some thermal dynamic requirements associated with the space shuttle vehicle are reviewed. Pertinent scaling laws are discussed and recommendations are offered regarding the need for conducting reduced-scale dynamic tests of major components at elevated temperatures. Items considered are the development and interpretation of thermal dynamic structural scaling laws, the identification of major related problem areas and a presentation of viable model fabrication, instrumentation, and test procedures.
ERIC Educational Resources Information Center
Walsh, Jim; McGehee, Richard
2013-01-01
A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…
ERIC Educational Resources Information Center
Walsh, Jim; McGehee, Richard
2013-01-01
A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…
Paixão, Crysttian Arantes; da Costa, Antonio Tavares
2013-06-01
This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.
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.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Rokni Lamooki, Gholam Reza; Shirazi, Amir H.; Mani, Ali R.
2015-05-01
Thyroid's main chemical reactions are employed to develop a mathematical model. The presented model is based on differential equations where their dynamics reflects many aspects of thyroid's behavior. Our main focus here is the well known, but not well understood, phenomenon so called as Wolff-Chaikoff effect. It is shown that the inhibitory effect of intake iodide on the rate of one single enzyme causes a similar effect as Wolff-Chaikoff. Besides this issue, the presented model is capable of revealing other complex phenomena of thyroid hormones homeostasis.
NASA Astrophysics Data System (ADS)
West, Bruce J.
The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.
Mesoscale ocean dynamics modeling
mHolm, D.; Alber, M.; Bayly, B.; Camassa, R.; Choi, W.; Cockburn, B.; Jones, D.; Lifschitz, A.; Margolin, L.; Marsden, L.; Nadiga, B.; Poje, A.; Smolarkiewicz, P.; Levermore, D.
1996-05-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The ocean is a very complex nonlinear system that exhibits turbulence on essentially all scales, multiple equilibria, and significant intrinsic variability. Modeling the ocean`s dynamics at mesoscales is of fundamental importance for long-time-scale climate predictions. A major goal of this project has been to coordinate, strengthen, and focus the efforts of applied mathematicians, computer scientists, computational physicists and engineers (at LANL and a consortium of Universities) in a joint effort addressing the issues in mesoscale ocean dynamics. The project combines expertise in the core competencies of high performance computing and theory of complex systems in a new way that has great potential for improving ocean models now running on the Connection Machines CM-200 and CM-5 and on the Cray T3D.
NASA Technical Reports Server (NTRS)
Glaese, John R.; Tobbe, Patrick A.
1986-01-01
The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.
Relativistic dynamical collapse model
NASA Astrophysics Data System (ADS)
Pearle, Philip
2015-05-01
A model is discussed where all operators are constructed from a quantum scalar field whose energy spectrum takes on all real values. The Schrödinger picture wave function depends upon space and time coordinates for each particle, as well as an inexorably increasing evolution parameter s which labels a foliation of spacelike hypersurfaces. The model is constructed to be manifestly Lorentz invariant in the interaction picture. Free particle states and interactions are discussed in this framework. Then, the formalism of the continuous spontaneous localization (CSL) theory of dynamical collapse is applied. The collapse-generating operator is chosen to be the particle number space-time density. Unlike previous relativistically invariant models, the vacuum state is not excited. The collapse dynamics depends upon two parameters, a parameter Λ which represents the collapse rate/volume and a scale factor ℓ. A common example of collapse dynamics, involving a clump of matter in a superposition of two locations, is analyzed. The collapse rate is shown to be identical to that of nonrelativistic CSL when the GRW-CSL choice of ℓ=a =1 0-5 cm , is made, along with Λ =λ /a3 (GRW-CSL choice λ =1 0-16s-1). The collapse rate is also satisfactory with the choice ℓ as the size of the Universe, with Λ =λ /ℓa2. Because the collapse narrows wave functions in space and time, it increases a particle's momentum and energy, altering its mass. It is shown that, with ℓ=a , the change of mass of a nucleon is unacceptably large but, when ℓ is the size of the Universe, the change of mass over the age of the Universe is acceptably small.
Launch Vehicle Dynamics Demonstrator Model
NASA Technical Reports Server (NTRS)
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.
SSME structural dynamic model development
NASA Technical Reports Server (NTRS)
Foley, M. J.; Tilley, D. M.; Welch, C. T.
1983-01-01
A mathematical model of the Space Shuttle Main Engine (SSME) as a complete assembly, with detailed emphasis on LOX and High Fuel Turbopumps is developed. The advantages of both complete engine dynamics, and high fidelity modeling are incorporated. Development of this model, some results, and projected applications are discussed.
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.
Dynamic Modeling of ALS Systems
NASA Technical Reports Server (NTRS)
Jones, Harry
2002-01-01
The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.
NASA Technical Reports Server (NTRS)
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.
Aircraft Dynamic Modeling in Turbulence
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Cunninham, Kevin
2012-01-01
A method for accurately identifying aircraft dynamic models in turbulence was developed and demonstrated. The method uses orthogonal optimized multisine excitation inputs and an analytic method for enhancing signal-to-noise ratio for dynamic modeling in turbulence. A turbulence metric was developed to accurately characterize the turbulence level using flight measurements. The modeling technique was demonstrated in simulation, then applied to a subscale twin-engine jet transport aircraft in flight. Comparisons of modeling results obtained in turbulent air to results obtained in smooth air were used to demonstrate the effectiveness of the approach.
Model describes subsea control dynamics
Not Available
1988-02-01
A mathematical model of the hydraulic control systems for subsea completions and their umbilicals has been developed and applied successfully to Jabiru and Challis field production projects in the Timor Sea. The model overcomes the limitations of conventional linear steady state models and yields for the hydraulic system an accurate description of its dynamic response, including the valve shut-in times and the pressure transients. Results of numerical simulations based on the model are in good agreement with measurements of the dynamic response of the tree valves and umbilicals made during land testing.
ERIC Educational Resources Information Center
Journal of Science and Mathematics Education in Southeast Asia, 1981
1981-01-01
Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)
Modeling Molecular Dynamics from Simulations
Hinrichs, Nina Singhal
2009-01-28
Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical and life sciences. For example, many diseases are caused by protein aggregation or misfolding. One approach to studying these systems is to use physically-based computational simulations to model the interactions and movement of the molecules. While molecular simulations are computationally expensive, it is now possible to simulate many independent molecular dynamics trajectories in a parallel fashion by using super- or distributed- computing methods such as Folding@Home or Blue Gene. The analysis of these large, high-dimensional data sets presents new computational challenges. In this seminar, I will discuss a novel approach to analyzing large ensembles of molecular dynamics trajectories to generate a compact model of the dynamics. This model groups conformations into discrete states and describes the dynamics as Markovian, or history-independent, transitions between the states. I will discuss why the Markovian state model (MSM) is suitable for macromolecular dynamics, and how it can be used to answer many interesting and relevant questions about the molecular system. I will also discuss many of the computational and statistical challenges in building such a model, such as how to appropriately cluster conformations, determine the statistical reliability, and efficiently design new simulations.
Flapping Wing Flight Dynamic Modeling
2011-08-22
against those of Theodorsen [16], Garrick [17], Loewy [18], Issacs [19, 20], Greenberg [21], Wagner [22], and von Karman [23] as well as experimental...kinematics and this data was used to generate the nal equations of motion (added to the nonlinear equations already derived from the Newton -Euler...wings). The ight dynamic model is a six-degree-of-freedom set of dynamic equations ( Newton -Euler scheme) with translation described in the inertial
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
Structural dynamics system model reduction
NASA Technical Reports Server (NTRS)
Chen, J. C.; Rose, T. L.; Wada, B. K.
1987-01-01
Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.
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.
Dynamical models and Galaxy surveys
NASA Astrophysics Data System (ADS)
Binney, James; Sanders, Jason L.
2014-01-01
Equilibrium dynamical models are essential tools for extracting science from surveys of our Galaxy. We show how models can be tested with data from a survey before the survey's selection function has been determined. We illustrate the application of this method by presenting some results for the RAVE survey. We extend our published analytic distribution functions to include chemistry and fit the chosen functional form to a combination of the Geneva-Copenhagen survey (GCS) and a sample of G-dwarfs observed at z ~ 1.75 kpc by the SEGUE survey. By including solid dynamics we are able to predict the contribution that the thick disc/halo stars surveyed by SEGUE should make to the GCS survey. We show that the measured [Fe/H] distribution from the GCS includes many fewer stars at [Fe/H] < -0.6 than are predicted. The problem is more likely to lie in discordant abundance scales than with incorrect dynamics.
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. PMID:24446358
The dynamics of coastal models
Hearn, Clifford J.
2008-01-01
Coastal basins are defined as estuaries, lagoons, and embayments. This book deals with the science of coastal basins using simple models, many of which are presented in either analytical form or Microsoft Excel or MATLAB. The book introduces simple hydrodynamics and its applications, from the use of simple box and one-dimensional models to flow over coral reefs. The book also emphasizes models as a scientific tool in our understanding of coasts, and introduces the value of the most modern flexible mesh combined wave-current models. Examples from shallow basins around the world illustrate the wonders of the scientific method and the power of simple dynamics. This book is ideal for use as an advanced textbook for graduate students and as an introduction to the topic for researchers, especially those from other fields of science needing a basic understanding of the basic ideas of the dynamics of coastal basins.
Observability in dynamic evolutionary models.
López, I; Gámez, M; Carreño, R
2004-02-01
In the paper observability problems are considered in basic dynamic evolutionary models for sexual and asexual populations. Observability means that from the (partial) knowledge of certain phenotypic characteristics the whole evolutionary process can be uniquely recovered. Sufficient conditions are given to guarantee observability for both sexual and asexual populations near an evolutionarily stable state.
Predictive models of battle dynamics
NASA Astrophysics Data System (ADS)
Jelinek, Jan
2001-09-01
The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.
Stochastic Model of Microtubule Dynamics
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
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
Dynamic Model of Mesoscale Eddies
NASA Astrophysics Data System (ADS)
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
On whole Abelian model dynamics
Chauca, J.; Doria, R.
2012-09-24
Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.
Modeling wildfire incident complexity dynamics.
Thompson, Matthew P
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.
Dynamical modelling of meteoroid streams
NASA Astrophysics Data System (ADS)
Clark, D. L.; Wiegert, P. A.
2014-07-01
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 significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, 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 weights 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. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.
NASA Astrophysics Data System (ADS)
Subbareddy, Pramod; Candler, Graham
2009-11-01
Hybrid RANS/LES methods are being increasingly used for turbulent flow simulations in complex geometries. Spalart's detached eddy simulation (DES) model is one of the more popular ones. We are interested in examining the behavior of the Spalart-Allmaras (S-A) Detached Eddy Simulation (DES) model in its ``LES mode.'' The role of the near-wall functions present in the equations is analyzed and an explicit analogy between the S-A and a one-equation LES model based on the sub-grid kinetic energy is presented. A dynamic version of the S-A DES model is proposed based on this connection. Validation studies and results from DES and LES applications will be presented and the effect of the proposed modification will be discussed.
Modeling Catastrophic Barrier Island Dynamics
NASA Astrophysics Data System (ADS)
Whitley, J. W.; McNamara, D.
2012-12-01
Barrier islands, thin strips of sand lying parallel to the mainland coastline, along the U.S. Atlantic and Gulf Coasts appear to have maintained their form for thousands of years in the face of rising sea level. The mechanisms that allow barrier islands to remain robust are transport of sediment from the ocean side of barriers to the top and backside during storms, termed island overwash, and the growth and alongshore propagation of tidal deltas near barrier island inlets. Dynamically these processes provide the necessary feedbacks to maintain a barrier island in an attractor that withstands rising sea level within a phase space of barrier island geometrical characteristics. Current barrier island configurations along the Atlantic and Gulf coasts exist among a wide range of storm climate and underlying geologic conditions and therefore the environment that forces overwash and tidal delta dynamics varies considerably. It has been suggested that barrier islands in certain locations such as those between Avon and Buxton (losing 76% of island width since 1852) and Chandeleur islands (losing 85% of its surface area since 2005) along the Atlantic and Gulf coasts, respectively, may be subject to a catastrophic shift in barrier island attractor states - more numerous inlets cutting barriers in some locations and the complete disappearance of barrier islands in other locations. In contrast to common models for barrier islands that neglect storm dynamics and often only consider cross-shore response, we use an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of barrier islands to a wide range of environmental forcing. Results will be presented that show how barrier island attractor states are altered with variations in the rate of sea level rise, storminess, and underlying geology. We will
Modeling Wildfire Incident Complexity Dynamics
Thompson, Matthew P.
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014
Data modeling of network dynamics
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad
2004-01-01
This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.
Mathematical Modeling of Wildfire Dynamics
NASA Astrophysics Data System (ADS)
Del Bene, Kevin; Drew, Donald
2012-11-01
Wildfires have been a long-standing problem in today's society. In this paper, we derive and solve a fluid dynamics model to study a specific type of wildfire, namely, a two dimensional flow around a rising plume above a concentrated heat source, modeling a fire line. This flow assumes a narrow plume of hot gas rising and entraining the surrounding air. The surrounding air is assumed to have constant density and is irrotational far from the fire line. The flow outside the plume is described by a Biot-Savart integral with jump conditions across the position of the plume. The plume model describes the unsteady evolution of the mass, momentum, energy, and vorticity inside the plume, with sources derived to model mixing in the style of Morton, et al. 1956]. The fire is then modeled using a conservation derivation, allowing the fire to propagate, coupling back to the plume model. The results show that this model is capable of capturing the complex interaction of the plume with the surrounding air and fuel layer. Funded by NSF GRFP.
Modeling the Dynamics of Snags.
Morrison, Michael L; Raphael, Martin G
1993-05-01
Many wildlife species required standing dead trees (i.e., snags) as part of their habitat. Therefore, the ability to predict future density, distribution, and condition of snags can assist resource managers in making land-use decisions. Here we present methods for modeling the dynamics of snags using data from a 10-yr study on the rates of decay, falling, and recruitment of snags on burned and unburned plots in the Sierra Nevada, California. Snags (all species) in advanced stages of decay usually fell within 5 yr, and snags created by fire decayed rapidly and fell quicker (within 10 yr) than those on unburned plots. Pine (Pinus spp.) snags decayed more rapidly than fir (Abies spp.). Although there was an overall net increase in snag density on unburned plots, most of this increase was in the smaller (>13-38 cm diameter at breast height [dbh]) size classes; there was a net decrease in the larger (>38 cm dbh) snags preferred by many birds for nesting and feeding. Overall, snags remained standing the longest that were larger in diameter, shorter in height, less decayed, fir rather than pine, and lacking tops. A Leslie matrix model of snag dynamics predicted changes in snag decay and density only when adjusted for the specific environmental factors(s) causing initial tree mortality. Many snags are created by episodic events, such as fire, disease, drought, and insects. Models of snag dynamics must include the species and condition of trees becoming snags, as well as the factor(s) causing the tree to die. Forest managers must consider this episodic creation of snags when developing snag-management guidelines, and when planning tree-salvage programs based on short-term inventories.
Opinion dynamics model with weighted influence: Exit probability and dynamics
NASA Astrophysics Data System (ADS)
Biswas, Soham; Sinha, Suman; Sen, Parongama
2013-08-01
We introduce a stochastic model of binary opinion dynamics in which the opinions are determined by the size of the neighboring domains. The exit probability here shows a step function behavior, indicating the existence of a separatrix distinguishing two different regions of basin of attraction. This behavior, in one dimension, is in contrast to other well known opinion dynamics models where no such behavior has been observed so far. The coarsening study of the model also yields novel exponent values. A lower value of persistence exponent is obtained in the present model, which involves stochastic dynamics, when compared to that in a similar type of model with deterministic dynamics. This apparently counterintuitive result is justified using further analysis. Based on these results, it is concluded that the proposed model belongs to a unique dynamical class.
Eigenvalue dynamics for multimatrix models
NASA Astrophysics Data System (ADS)
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.
Bayesian Estimation of Categorical Dynamic Factor Models
ERIC Educational Resources Information Center
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…
Bayesian Estimation of Categorical Dynamic Factor Models
ERIC Educational Resources Information Center
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…
Characterizing and modeling citation dynamics.
Eom, Young-Ho; Fortunato, Santo
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 for the presence of citation bursts as well.
Characterizing and Modeling Citation Dynamics
Eom, Young-Ho; Fortunato, Santo
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 for the presence of citation bursts as well. PMID:21966387
Dynamical model for competing opinions
NASA Astrophysics Data System (ADS)
Souza, S. R.; Gonçalves, S.
2012-05-01
We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.
Dynamical modeling of tidal streams
Bovy, Jo
2014-11-01
I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
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.
Dynamical model of surrogate reactions
Aritomo, Y.; Chiba, S.; Nishio, K.
2011-08-15
A new dynamical model is developed to describe the whole process of surrogate reactions: Transfer of several nucleons at an initial stage, thermal equilibration of residues leading to washing out of shell effects, and decay of populated compound nuclei are treated in a unified framework. Multidimensional Langevin equations are employed to describe time evolution of collective coordinates with a time-dependent potential energy surface corresponding to different stages of surrogate reactions. The new model is capable of calculating spin distributions of the compound nuclei, one of the most important quantities in the surrogate technique. Furthermore, various observables of surrogate reactions can be calculated, for example, energy and angular distribution of ejectile and mass distributions of fission fragments. These features are important to assess validity of the proposed model itself, to understand mechanisms of the surrogate reactions, and to determine unknown parameters of the model. It is found that spin distributions of compound nuclei produced in {sup 18}O+{sup 238}U{yields}{sup 16}O+{sup 240}*U and {sup 18}O+{sup 236}U{yields}{sup 16}O+{sup 238}*U reactions are equivalent and much less than 10({h_bar}/2{pi}) and therefore satisfy conditions proposed by Chiba and Iwamoto [Phys. Rev. C 81, 044604 (2010)] if they are used as a pair in the surrogate ratio method.
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
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.
Modeling sandhill crane population dynamics
Johnson, D.H.
1979-01-01
The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.
SSME structural dynamic model development
NASA Technical Reports Server (NTRS)
Foley, Michael J.
1989-01-01
The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.
Opinion dynamics model based on quantum formalism
Artawan, I. Nengah; Trisnawati, N. L. P.
2016-03-11
Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.
Model dynamics for quantum computing
NASA Astrophysics Data System (ADS)
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.
Preliminary shuttle structural dynamics modeling design study
NASA Technical Reports Server (NTRS)
1972-01-01
The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.
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.
The Challenges to Coupling Dynamic Geospatial Models
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.
Hydration dynamics near a model protein surface
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.
Addressing Dynamic Issues of Program Model Checking
NASA Technical Reports Server (NTRS)
Lerda, Flavio; Visser, Willem
2001-01-01
Model checking real programs has recently become an active research area. Programs however exhibit two characteristics that make model checking difficult: the complexity of their state and the dynamic nature of many programs. Here we address both these issues within the context of the Java PathFinder (JPF) model checker. Firstly, we will show how the state of a Java program can be encoded efficiently and how this encoding can be exploited to improve model checking. Next we show how to use symmetry reductions to alleviate some of the problems introduced by the dynamic nature of Java programs. Lastly, we show how distributed model checking of a dynamic program can be achieved, and furthermore, how dynamic partitions of the state space can improve model checking. We support all our findings with results from applying these techniques within the JPF model checker.
Connecting micro dynamics and population distributions in system dynamics models.
Fallah-Fini, Saeideh; Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa
2013-01-01
Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model.
Connecting micro dynamics and population distributions in system dynamics models
Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa
2014-01-01
Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842
Stirling Convertor System Dynamic Model Developed
NASA Technical Reports Server (NTRS)
Lewandowski, Edward J.; Regan, Timothy F.
2005-01-01
Free-piston Stirling convertors are being developed for potential use on NASA exploration missions. In support of this effort, the NASA Glenn Research Center has developed the Stirling convertor System Dynamic Model (SDM). The SDM models the Stirling cycle thermodynamics; heat flow; gas, mechanical, and mounting dynamics; the linear alternator; and the controller. The SDM s scope extends from the thermal energy input to thermal, mechanical, and electrical energy output, allowing one to study complex system interactions among subsystems. Thermal, mechanical, fluid, magnetic, and electrical subsystems can be studied in one model. The SDM is a nonlinear time-domain model containing sub-cycle dynamics, which simulates transient and dynamic phenomena that other models cannot. The entire range of convertor operation is modeled, from startup to full-power conditions.
Chaotic dynamics in a simple dynamical green ocean plankton model
NASA Astrophysics Data System (ADS)
Cropp, Roger; Moroz, Irene M.; Norbury, John
2014-11-01
The exchange of important greenhouse gases between the ocean and atmosphere is influenced by the dynamics of near-surface plankton ecosystems. Marine plankton ecosystems are modified by climate change creating a feedback mechanism that could have significant implications for predicting future climates. The collapse or extinction of a plankton population may push the climate system across a tipping point. Dynamic green ocean models (DGOMs) are currently being developed for inclusion into climate models to predict the future state of the climate. The appropriate complexity of the DGOMs used to represent plankton processes is an ongoing issue, with models tending to become more complex, with more complicated dynamics, and an increasing propensity for chaos. We consider a relatively simple (four-population) DGOM of phytoplankton, zooplankton, bacteria and zooflagellates where the interacting plankton populations are connected by a single limiting nutrient. Chaotic solutions are possible in this 4-dimensional model for plankton population dynamics, as well as in a reduced 3-dimensional model, as we vary two of the key mortality parameters. Our results show that chaos is robust to the variation of parameters as well as to the presence of environmental noise, where the attractor of the more complex system is more robust than the attractor of its simplified equivalent. We find robust chaotic dynamics in low trophic order ecological models, suggesting that chaotic dynamics might be ubiquitous in the more complex models, but this is rarely observed in DGOM simulations. The physical equations of DGOMs are well understood and are constrained by conservation principles, but the ecological equations are not well understood, and generally have no explicitly conserved quantities. This work, in the context of the paucity of the empirical and theoretical bases upon which DGOMs are constructed, raises the interesting question of whether DGOMs better represent reality if they include
Very Large System Dynamics Models - Lessons Learned
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.
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.
Human systems dynamics: Toward a computational model
NASA Astrophysics Data System (ADS)
Eoyang, Glenda H.
2012-09-01
A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.
Dynamics Modelling of Biolistic Gene Guns
Zhang, M.; Tao, W.; Pianetta, P.A.
2009-06-04
The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model for improving and manipulating performance of the biolistic gene gun.
Differential equation models for sharp threshold dynamics.
Schramm, Harrison C; Dimitrov, Nedialko B
2014-01-01
We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations.
Equivalent dynamic model of DEMES rotary joint
NASA Astrophysics Data System (ADS)
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.
Markov state models of biomolecular conformational dynamics
Chodera, John D.; Noé, Frank
2014-01-01
It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges. PMID:24836551
Dynamic coupling of three hydrodynamic models
NASA Astrophysics Data System (ADS)
Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.
2008-12-01
The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The
Dynamic Modeling, Chaos, and Cognitive Development.
ERIC Educational Resources Information Center
Howe, Mark L.; Rabinowitz, F. Michael
1994-01-01
Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…
Dynamic Modeling, Chaos, and Cognitive Development.
ERIC Educational Resources Information Center
Howe, Mark L.; Rabinowitz, F. Michael
1994-01-01
Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…
Biomolecular dynamics of DNA: statistical mechanics and dynamical models
NASA Astrophysics Data System (ADS)
Peyrard, M.; Dauxois, T.; Hoyet, H.; Willis, C. R.
1993-09-01
There is a growing feeling that biomolecular structure is not sufficient to determine biological activity which is also governed by large amplitude dynamics of the molecules. The transcription of DNA or its thermal denaturation are typical examples. Traditional approaches use Ising models to describe the denaturation transition of DNA. They have to introduce phenomenological “cooperativity factors” to explain the rather sharp “melting” of this quasi one-dimensional system. We present models which describe the full dynamics of the melting. Using molecular dynamics simulations and statistical analysis, we discuss the mechanism of the denaturation, including precursor effects that can be related to large amplitude localized nonlinear excitations of the molecule in which discreteness effects play a large role. We also show the microscopic origin of the cooperativity factors.
Two-Stage Reduction Of Dynamical Models
NASA Technical Reports Server (NTRS)
Lee, Allan Y.; Tsuha, Walter S.
1993-01-01
No longer necessary to solve eigenvalue problems of high order. Component-mode projection-and-assembly model-reduction (COMPARE) method provides approximation of dynamics of vibrations of complicated, multiple flexible bodies by use of mathematical models of reduced order. Incorporates component-mode synthesis (CMS) method and enhanced projection-and-assembly (EP&A) method, described in "Enhanced Method of Reduction of Dynamical Models" (NPO-18402), providing for somewhat simplified two-stage process in which order of applicable mathematical models reduced. Reduced-order models used to design algorithms of control systems to suppress vibrations or otherwise control structure.
MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*
CHAHINE, Georges L.; HSIAO, Chao-Tsung
2012-01-01
Controlling microbubble 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 viscous- in-viscid 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. PMID:22833696
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan C.; Nemenman, Ilya
2015-01-01
Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508
Automated adaptive inference of phenomenological dynamical models
NASA Astrophysics Data System (ADS)
Daniels, Bryan C.; Nemenman, Ilya
2015-08-01
Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.
Constructing minimal models for complex system dynamics
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László
2015-05-01
One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.
Airship dynamics modeling: A literature review
NASA Astrophysics Data System (ADS)
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.
Model Verification of Mixed Dynamic Systems
NASA Technical Reports Server (NTRS)
Evensen, D. A.; Chrostowski, J. D.; Hasselman, T. K.
1982-01-01
MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.
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...
A dynamical model of color confinement
NASA Astrophysics Data System (ADS)
Loh, S.; Biró, T. S.; Mosel, U.; Thoma, M. H.
1996-02-01
A dynamical model of confinement based on a transport theoretical description of the Friedberg-Lee model is extended to explicit color degrees of freedom. The string tension is reproduced by an adiabatic string formation from the nucleon ground state. Color isovector oscillation modes of a qq¯-system are investigated for a wide range of relative qq¯-momenta and the dynamical impact of color confinement on the quark motion is shown.
Approximate dynamic model of a turbojet engine
NASA Technical Reports Server (NTRS)
Artemov, O. A.
1978-01-01
An approximate dynamic nonlinear model of a turbojet engine is elaborated on as a tool in studying the aircraft control loop, with the turbojet engine treated as an actuating component. Approximate relationships linking the basic engine parameters and shaft speed are derived to simplify the problem, and to aid in constructing an approximate nonlinear dynamic model of turbojet engine performance useful for predicting aircraft motion.
Single timepoint models of dynamic systems
Sachs, K.; Itani, S.; Fitzgerald, J.; Schoeberl, B.; Nolan, G. P.; Tomlin, C. J.
2013-01-01
Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We encounter an unexpected problem not previously described in elucidating connectivity structure from dynamic systems, show how this confounds structure learning of the system and discuss possible approaches to overcome the confounding effect. Finally, we test our hypotheses on an accurate dynamic model of the IGF signalling pathway. We use two structure-learning methods at four time points to contrast the performance and robustness of those methods in terms of recovering correct connectivity. PMID:24511382
Swarm Intelligence for Urban Dynamics Modelling
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.
2009-04-16
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Swarm Intelligence for Urban Dynamics Modelling
NASA Astrophysics Data System (ADS)
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.
2009-04-01
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Discrete model for DNA-promoter dynamics
NASA Astrophysics Data System (ADS)
Salerno, Mario
1991-10-01
We introduce a discrete model for DNA that takes into account the information about specific base sequences along the double helix. We use this model to study nonlinear wave dynamics of the T7A1 DNA promoter. As results we show the existence in the promoter of a dynamically active region in which static solitons acquire finite velocities, which contrasts with regions where solitons simply remain static. Furthermore, when they pass through this region moving solitons are accelerated, decelerated, or reflected, depending on their initial velocities. The possibility that these dynamical effects play a role in the mechanism of genetic activation is suggested.
Model systems for single molecule polymer dynamics
Latinwo, Folarin
2012-01-01
Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980
Understanding and Modeling Teams As Dynamical Systems
Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.
2017-01-01
By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231
Model systems for single molecule polymer dynamics.
Latinwo, Folarin; Schroeder, Charles M
2011-01-01
Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of "ideal" and "real" chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force-extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer-monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of "real" polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena.
Glassy dynamics of kinetically constrained models
NASA Astrophysics Data System (ADS)
Ritort, F.; Sollich, P.
2003-06-01
We review the use of kinetically constrained models (KCMs) for the study of dynamics in glassy systems. The characteristic feature of KCMs is that they have trivial, often non-interacting, equilibrium behaviour but interesting slow dynamics due to restrictions on the allowed transitions between configurations. The basic question which KCMs ask is therefore how much glassy physics can be understood without an underlying 'equilibrium glass transition'. After a brief review of glassy phenomenology, we describe the main model classes, which include spin-facilitated (Ising) models, constrained lattice gases, models inspired by cellular structures such as soap froths, models obtained via mappings from interacting systems without constraints, and finally related models such as urn, oscillator, tiling and needle models. We then describe the broad range of techniques that have been applied to KCMs, including exact solutions, adiabatic approximations, projection and mode-coupling techniques, diagrammatic approaches and mappings to quantum systems or effective models. Finally, we give a survey of the known results for the dynamics of KCMs both in and out of equilibrium, including topics such as relaxation time divergences and dynamical transitions, nonlinear relaxation, ageing and effective temperatures, cooperativity and dynamical heterogeneities, and finally non-equilibrium stationary states generated by external driving. We conclude with a discussion of open questions and possibilities for future work.
Battery electrochemical nonlinear/dynamic SPICE model
Glass, M.C.
1996-12-31
An Integrated Battery Model has been produced which accurately represents DC nonlinear battery behavior together with transient dynamics. The NiH{sub 2} battery model begins with a given continuous-function electrochemical math model. The math model for the battery consists of the sum of two electrochemical process DC currents, which are a function of the battery terminal voltage. This paper describes procedures for realizing a voltage-source SPICE model which implements the electrochemical equations using behavioral sources. The model merges the essentially DC non-linear behavior of the electrochemical model, together with the empirical AC dynamic terminal impedance from measured data. Thus the model integrates the short-term linear impedance behavior, with the long-term nonlinear DC resistance behavior. The long-duration non-Faradaic capacitive behavior of the battery is represented by a time constant. Outputs of the model include battery voltage/current, state-of-charge, and charge-current efficiency.
A stochastic model of human gait dynamics
NASA Astrophysics Data System (ADS)
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
NASA Technical Reports Server (NTRS)
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.
Multi-scale modelling and dynamics
NASA Astrophysics Data System (ADS)
Müller-Plathe, Florian
Moving from a fine-grained particle model to one of lower resolution leads, with few exceptions, to an acceleration of molecular mobility, higher diffusion coefficient, lower viscosities and more. On top of that, the level of acceleration is often different for different dynamical processes as well as for different state points. While the reasons are often understood, the fact that coarse-graining almost necessarily introduces unpredictable acceleration of the molecular dynamics severely limits its usefulness as a predictive tool. There are several attempts under way to remedy these shortcoming of coarse-grained models. On the one hand, we follow bottom-up approaches. They attempt already when the coarse-graining scheme is conceived to estimate their impact on the dynamics. This is done by excess-entropy scaling. On the other hand, we also pursue a top-down development. Here we start with a very coarse-grained model (dissipative particle dynamics) which in its native form produces qualitatively wrong polymer dynamics, as its molecules cannot entangle. This model is modified by additional temporary bonds, so-called slip springs, to repair this defect. As a result, polymer melts and solutions described by the slip-spring DPD model show correct dynamical behaviour. Read more: ``Excess entropy scaling for the segmental and global dynamics of polyethylene melts'', E. Voyiatzis, F. Müller-Plathe, and M.C. Böhm, Phys. Chem. Chem. Phys. 16, 24301-24311 (2014). [DOI: 10.1039/C4CP03559C] ``Recovering the Reptation Dynamics of Polymer Melts in Dissipative Particle Dynamics Simulations via Slip-Springs'', M. Langeloth, Y. Masubuchi, M. C. Böhm, and F. Müller-Plathe, J. Chem. Phys. 138, 104907 (2013). [DOI: 10.1063/1.4794156].
Dynamic landscape models of coevolutionary games.
Richter, Hendrik
2017-02-24
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. The main focus is on using dynamic fitness landscapes as a mathematical model of coevolutionary game dynamics. Hence, an alternative tool for analyzing coevolutionary games becomes available, and landscape measures such as modality, ruggedness and information content can be computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the interaction networks 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.
Uncertainty and Sensitivity in Surface Dynamics Modeling
NASA Astrophysics Data System (ADS)
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.
Energy Balance Models and Planetary Dynamics
NASA Technical Reports Server (NTRS)
Domagal-Goldman, Shawn
2012-01-01
We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.
Dynamic stiffness model of spherical parallel robots
NASA Astrophysics Data System (ADS)
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.
Dynamic centrifugal compressor model for system simulation
NASA Astrophysics Data System (ADS)
Jiang, Wei; Khan, Jamil; Dougal, Roger A.
A dynamic model of a centrifugal compressor capable of system simulation in the virtual test bed (VTB) computational environment is presented. The model is based on first principles, i.e. the dynamic performance including the losses is determined from the compressor geometry and not from the experimentally determined characteristic performance curves. In this study, the compressor losses, such as incidence and friction losses, etc., are mathematically modeled for developing compressor characteristics. For easy implementation in the VTB platform, the non-linear governing equations are discretized in resistive companion (RC) form. The developed simulation model can be applied to virtually any centrifugal compressor. By interfacing with a composite system, such as a Brayton cycle gas turbine, or a fuel cell, the compressor dynamic performance can be evaluated. The surge line for the compressor can also be determined from the simulation results. Furthermore, the model presented here provides a valuable tool for evaluating the system performance as a function of various operating parameters.
Modeling cell shape and dynamics on micropatterns
Albert, Philipp J.; Schwarz, Ulrich S.
2016-01-01
ABSTRACT Adhesive micropatterns have become a standard tool to study cells under defined conditions. Applications range from controlling the differentiation and fate of single cells to guiding the collective migration of cell sheets. In long-term experiments, single cell normalization is challenged by cell division. For all of these setups, mathematical models predicting cell shape and dynamics can guide pattern design. Here we review recent advances in predicting and explaining cell shape, traction forces and dynamics on micropatterns. Starting with contour models as the simplest approach to explain concave cell shapes, we move on to network and continuum descriptions as examples for static models. To describe dynamic processes, cellular Potts, vertex and phase field models can be used. Different types of model are appropriate to address different biological questions and together, they provide a versatile tool box to predict cell behavior on micropatterns. PMID:26838278
Integrated dynamics modeling for supercavitating vehicle systems
NASA Astrophysics Data System (ADS)
Kim, Seonhong; Kim, Nakwan
2015-06-01
We have performed integrated dynamics modeling for a supercavitating vehicle. A 6-DOF equation of motion was constructed by defining the forces and moments acting on the supercavitating body surface that contacted water. The wetted area was obtained by calculating the cavity size and axis. Cavity dynamics were determined to obtain the cavity profile for calculating the wetted area. Subsequently, the forces and moments acting on each wetted part-the cavitator, fins, and vehicle body-were obtained by physical modeling. The planing force-the interaction force between the vehicle transom and cavity wall-was calculated using the apparent mass of the immersed vehicle transom. We integrated each model and constructed an equation of motion for the supercavitating system. We performed numerical simulations using the integrated dynamics model to analyze the characteristics of the supercavitating system and validate the modeling completeness. Our research enables the design of high-quality controllers and optimal supercavitating systems.
Stirling Engine Dynamic System Modeling
NASA Technical Reports Server (NTRS)
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.
Stirling Engine Dynamic System Modeling
NASA Technical Reports Server (NTRS)
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.
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
Dynamics modeling and simulation of flexible airships
NASA Astrophysics Data System (ADS)
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
Component testing for dynamic model verification
NASA Technical Reports Server (NTRS)
Hasselman, T. K.; Chrostowski, J. D.
1984-01-01
Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.
Modeling Dynamic Regulatory Processes in Stroke.
McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.; Lancaster, Mary J.; Shankaran, Harish; Vartanian, Keri B.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.
2012-10-11
The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to develop dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.
Dynamical modeling of laser ablation processes
Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.
1995-09-01
Several physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume; plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms; gas dynamic, hydrodynamic, and collisional descriptions of plume transport; and molecular dynamics models of the interaction of plume particles with the deposition substrate. The complexity of the phenomena involved in the laser ablation process is matched by the diversity of the modeling task, which combines materials science, atomic physics, and plasma physics.
Dynamical modelling of coordinated multiple robot systems
NASA Technical Reports Server (NTRS)
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.
Dynamics Simulation Model for Space Tethers
NASA Technical Reports Server (NTRS)
Levin, E. M.; Pearson, J.; Oldson, J. C.
2006-01-01
This document describes the development of an accurate model for the dynamics of the Momentum Exchange Electrodynamic Reboost (MXER) system. The MXER is a rotating tether about 100-km long in elliptical Earth orbit designed to catch payloads in low Earth orbit and throw them to geosynchronous orbit or to Earth escape. To ensure successful rendezvous between the MXER tip catcher and a payload, a high-fidelity model of the system dynamics is required. The model developed here quantifies the major environmental perturbations, and can predict the MXER tip position to within meters over one orbit.
A stochastic evolutionary model for survival dynamics
NASA Astrophysics Data System (ADS)
Fenner, Trevor; Levene, Mark; Loizou, George
2014-09-01
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.
Dynamical effects of overparametrization in nonlinear models
NASA Astrophysics Data System (ADS)
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.
A system dynamics model for communications networks
NASA Astrophysics Data System (ADS)
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.
Magnetospheric dynamics from a low-dimensional nonlinear dynamics model
NASA Astrophysics Data System (ADS)
Doxas, I.; Horton, W.
1999-05-01
A physics based model for the coupled solar WIND-Magnetosphere-Ionosphere system (WINDMI) is described. The model is based on truncated descriptions of the collisionless microscopic energy transfer processes occurring in the quasineutral layer, and includes a thermal flux limit neglected in the Magnetohydrodynamic (MHD) closure of the moment equations. All dynamically relevant parameters of the model can be computed analytically. The system is both Kirchhoffian and Hamiltonian, ensuring that the power input from the solar wind is divided into physically realizable energy sub-components, a property not shared by data-based filters. The model provides a consistent mathematical formalism in which different models of the solar wind driver, ionospheric dissipation, global field configuration, and substorm trigger mechanism can be inserted, and the coupling between the different parts of the system investigated.
Adaptation dynamics of the quasispecies model
NASA Astrophysics Data System (ADS)
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.
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
Automated dynamic analytical model improvement
NASA Technical Reports Server (NTRS)
Berman, A.
1981-01-01
A method is developed and illustrated which finds minimum changes in analytical mass and stiffness matrices to make them consistent with a set of measured normal modes and natural frequencies. The corrected model is an improved base for studies of physical changes, changes in boundary conditions, and for prediction of forced responses. Features of the method are: efficient procedures not requiring solutions of the eigenproblem; the model may have more degrees of freedom than the test data; modal displacements at all the analytical degrees of freedom are obtained; the frequency dependence of the coordinate transformations are properly treated.
Session 6: Dynamic Modeling and Systems Analysis
NASA Technical Reports Server (NTRS)
Csank, Jeffrey; Chapman, Jeffryes; May, Ryan
2013-01-01
These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators
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
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
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.
Dynamical Modeling of Surface Tension
NASA Technical Reports Server (NTRS)
Brackbill, Jeremiah U.; Kothe, Douglas B.
1996-01-01
In a recent review it is said that free-surface flows 'represent some of the difficult remaining challenges in computational fluid dynamics'. There has been progress with the development of new approaches to treating interfaces, such as the level-set method and the improvement of older methods such as the VOF method. A common theme of many of the new developments has been the regularization of discontinuities at the interface. One example of this approach is the continuum surface force (CSF) formulation for surface tension, which replaces the surface stress given by Laplace's equation by an equivalent volume force. Here, we describe how CSF formulation might be made more useful. Specifically, we consider a derivation of the CSF equations from a minimization of surface energy as outlined by Jacqmin (1996). This reformulation suggests that if one eliminates the computation of curvature in terms of a unit normal vector, parasitic currents may be eliminated. For this reformulation to work, it is necessary that transition region thickness be controlled. Various means for this, in addition to the one discussed by Jacqmin (1996), are discussed.
Modelling Martian surface channel dynamics
NASA Astrophysics Data System (ADS)
Coulthard, T. J.; Skinner, C.; Kim, J.; Schumann, G.; Neal, J. C.; Bates, P. D.
2014-12-01
Extensive and large surface channel features found at Athabasca and Kasei have previously been attributed to the erosional power of flowing water with palaeoflood discharges being estimated from the surface channel dimensions. However, in order for these channels to be alluvial there are several basic questions to be answered. Are water flows under Martian conditions capable of eroding the amounts of sediment required to leave these channels? Are our present estimates of palaeoflood discharge of correct magnitude to carry out this erosion? And are the channels a product of one or many flood events? Here, we use a numerical model (CAESAR-Lisflood) that links a two-dimensional hydrodynamic flow scheme to a sediment transport model to simulate fluvial morphodynamics in the Athabasca and Kasei regions. CAESAR-Lisflood has been successfully applied to simulating flooding, erosion and deposition on Earth in a number of locations, and allows the development of channels, bars, braids and other fluvial features to be modelled. The numerical scheme of the model was adapted to Martian conditions by adjusting gravity, drag co-efficient, roughness and grainsize terms. Preliminary findings indicate that fluvial erosion and deposition is capable of creating mega channel features found at these sites and that existing palaeflood estimates are commensurate with channel forming discharges for these features.
Predicting dynamic topography from mantle circulation models
NASA Astrophysics Data System (ADS)
Webb, Peter; Davies, J. Huw
2013-04-01
Dynamic topography is anomalous vertical motions of Earth's surface associated with viscous flow in the mantle. Deformable boundaries, such as the surface, CMB and phase transition boundaries, within a fluid (Earth's mantle) are deflected by viscous flow. Denser than average, sinking mantle creates inward deflections of Earth's surface. Equally, upwelling flow creates bulges in the surface; large plumes are commonly thought to produce superswells, such as the anomalously high elevation of Southern Africa. Dynamic topography appears to operate on a number of length scales. Mantle density anomalies estimated from seismic tomography indicate long wavelength dynamic topography at present day of around 2 km amplitude (e.g. Conrand & Husson, 2009) whilst continental scale studies suggest vertical motions of a few hundred metres. Furthermore, time scales must be an important factor to consider when assessing dynamic topography. Stable, dense lower mantle 'piles' may contribute to dynamic surface topography; as they appear stable over reasonably long time scales, long wavelength dynamic topography may be a fairly constant feature over the recent geological past. Shorter wavelength, smaller amplitude dynamic topography may be due to more transient features of mantle convection. Studies on a continental scale reveal shorter term changes in dynamic topography of the order of a few hundred metres (e.g. Roberts & White, 2010; Heine et al., 2010). Understanding dynamic topography is complicated by the fact it is difficult to observe as the signal is often masked by isostatic effects. We use forward mantle convection models with 300 million years of recent plate motion history as the surface boundary condition to generate a present day distribution of density anomalies associated with subducted lithosphere. From the modelled temperature and density fields we calculate the normal stress at or near the surface of the model. As the models generally have a free slip surface where no
Modeling the Dynamics of Compromised Networks
Soper, B; Merl, D M
2011-09-12
Accurate predictive models of compromised networks would contribute greatly to improving the effectiveness and efficiency of the detection and control of network attacks. Compartmental epidemiological models have been applied to modeling attack vectors such as viruses and worms. We extend the application of these models to capture a wider class of dynamics applicable to cyber security. By making basic assumptions regarding network topology we use multi-group epidemiological models and reaction rate kinetics to model the stochastic evolution of a compromised network. The Gillespie Algorithm is used to run simulations under a worst case scenario in which the intruder follows the basic connection rates of network traffic as a method of obfuscation.
Alternative models for cyclic lemming dynamics.
Wang, Hao; Kuang, Yang
2007-01-01
Many natural population growths and interactions are affected by seasonal changes, suggesting that these natural population dynamics should be modeled by nonautonomous differential equations instead of autonomous differential equations. Through a series of carefully derived models of the well documented high-amplitude, large-period fluctuations of lemming populations, we argue that when appropriately formulated, autonomous differential equations may capture much of the desirable rich dynamics, such as the existence of a periodic solution with period and amplitude close to that of approximately periodic solutions produced by the more natural but mathematically daunt ing nonautonomous models. We start this series of models from the Barrow model, a well formulated model for the dynamics of food-lemming interaction at Point Barrow (Alaska, USA) with sufficient experimental data. Our work suggests that an autonomous system can indeed be a good approximation to the moss-lemming dynamics at Point Barrow. This, together with our bifurcation analysis, indicates that neither seasonal factors (expressed by time dependent moss growth rate and lemming death rate in the Barrow model) nor the moss growth rate and lemming death rate are the main culprits of the observed multi-year lemming cycles. We suspect that the main culprits may include high lemming predation rate, high lemming birth rate, and low lemming self-limitation rate.
Nonlinear Dynamic Models in Advanced Life Support
NASA Technical Reports Server (NTRS)
Jones, Harry
2002-01-01
To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.
Continuous Time Dynamic Topic Models
2008-06-20
called topics, can be used to explain the observed collection. LDA is a probabilistic extension of latent semantic indexing (LSI) [5] and probabilistic... latent semantic indexing (pLSI) [11]. Owing to its formal generative semantics, LDA has been extended and applied to authorship [19], email [15...Steyvers. Probabilistic topic models. In Latent Semantic Analysis: A Road to Meaning. 2006. [9] T. L. Griffiths and M. Steyvers. Finding scientific
Feature Extraction for Structural Dynamics Model Validation
Farrar, Charles; Nishio, Mayuko; Hemez, Francois; Stull, Chris; Park, Gyuhae; Cornwell, Phil; Figueiredo, Eloi; Luscher, D. J.; Worden, Keith
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.
Information Dynamics in Networks: Models and Algorithms
2016-09-13
the economics and computer science communities . Such a model of externality is motivated by several factors: • The physical effect of the number of...Information Dynamics in Networks: Models and Algorithms In this project, we investigated how network structure interplays with higher level processes in...online social networks. We investigated the appropriateness of existing mathematical models for explaining the structure of retweet cascades on
Dynamic river basin water quality model
Yearsley, J.
1991-09-01
RBM10 is a river basin model for simulating the dynamics of an aquatic ecosystem which has freely-flowing river reaches, river-run reservoirs, and vertically stratified reservoirs. An Eulerian viewpoint is adopted for solving the conservation equations for temperature, dissolved oxygen, nutrients, phytoplankton, bacteria and conservative constituents. The report describes the model development and the computer program which implements the mathematical model.
Modelling and control of HIV dynamics.
Landi, Alberto; Mazzoldi, Alberto; Andreoni, Chiara; Bianchi, Matteo; Cavallini, Andrea; Laurino, Marco; Ricotti, Leonardo; Iuliano, Rodolfo; Matteoli, Barbara; Ceccherini-Nelli, Luca
2008-02-01
Various models of HIV infection and evolution have been considered in the literature. This paper considers a variant of the Wodarz and Nowak mathematical model, adding "aggressiveness" as a new state variable in order to quantify the strength of the virus and its response to drugs. Although the model proposed is relatively simple, simulation results suggest that it may be useful in predicting the impact of the effectiveness of therapy on HIV dynamics.
The dynamic model of enterprise revenue management
NASA Astrophysics Data System (ADS)
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.
Dynamic exponents for potts model cluster algorithms
NASA Astrophysics Data System (ADS)
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.
Dynamic Model for Life History of Scyphozoa.
Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming
2015-01-01
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.
Dynamic Model for Life History of Scyphozoa
Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming
2015-01-01
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. PMID:26114642
A dynamic conceptual model of care planning.
Elf, Marie; Poutilova, Maria; Ohrn, Kerstin
2007-12-01
This article presents a conceptual model of the care planning process developed to identify the hypothetical links between structural, process and outcome factors important to the quality of the process. Based on existing literature, it was hypothesized that a thorough assessment of patients' health needs is an important prerequisite when making a rigorous diagnosis and preparing plans for various care interventions. Other important variables that are assumed to influence the quality of the process are the care culture and professional knowledge. The conceptual model was developed as a system dynamics causal loop diagram as a first essential step towards a computed model. System dynamics offers the potential to describe processes in a nonlinear, dynamic way and is suitable for exploring, comprehending, learning and communicating complex ideas about care processes.
Dynamic Smagorinsky model on anisotropic grids
NASA Technical Reports Server (NTRS)
Scotti, A.; Meneveau, C.; Fatica, M.
1996-01-01
Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.
Dynamic reliability models with conditional proportional hazards.
Hollander, M; Peña, E A
1995-01-01
A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a 'jump' from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution function of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.
Record Dynamics and the Parking Lot Model for granular dynamics
NASA Astrophysics Data System (ADS)
Sibani, Paolo; Boettcher, Stefan
Also known for its application to granular compaction (E. Ben-Naim et al., Physica D, 1998), the Parking Lot Model (PLM) describes the random parking of identical cars in a strip with no marked bays. In the thermally activated version considered, cars can be removed at an energy cost and, in thermal equilibrium, their average density increases as temperature decreases. However, equilibration at high density becomes exceedingly slow and the system enters an aging regime induced by a kinematic constraint, the fact that parked cars may not overlap. As parking an extra car reduces the available free space,the next parking event is even harder to achieve. Records in the number of parked cars mark the salient features of the dynamics and are shown to be well described by the log-Poisson statistics known from other glassy systems with record dynamics. Clusters of cars whose positions must be rearranged to make the next insertion possible have a length scale which grows logarithmically with age, while their life-time grows exponentially with size. The implications for a recent cluster model of colloidal dynamics,(S. Boettcher and P. Sibani, J. Phys.: Cond. Matter, 2011 N. Becker et al., J. Phys.: Cond. Matter, 2014) are discussed. Support rom the Villum Foundation is gratefully acknowledged.
Dynamic modeling of solar dynamic components and systems
NASA Astrophysics Data System (ADS)
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 Modeling of Solar Dynamic Components and Systems
NASA Technical Reports Server (NTRS)
Hochstein, John I.; Korakianitis, T.
1992-01-01
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 models of Fabry-Perot interferometers.
Redding, David; Regehr, Martin; Sievers, Lisa
2002-05-20
Long-baseline, high-finesse Fabry-Perot interferometers can be used to make distance measurements that are precise enough to detect gravity waves. This level of sensitivity is achieved in part when the interferometer mirrors are isolated dynamically, with pendulum mounts and high-bandwidth cavity length control servos to reduce the effects of seismic noise. We present dynamical models of the cavity fields and signals of Fabry-Perot interferometers for use in the design and evaluation of length control systems for gravity-wave detectors. Models are described and compared with experimental data.
Dynamical properties of the Rabi model
NASA Astrophysics Data System (ADS)
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.
Robot arm dynamic model reduction for control
NASA Technical Reports Server (NTRS)
Bejczy, A. K.; Lee, S.
1983-01-01
General methods are described by which the mathematical complexities of explicit and exact state equations of robot arms can be reduced to a simplified and compact state equation representation without introducing significant errors into the robot arm dynamic model. The model reduction methods are based on homogeneous coordinates and on the Langrangian algorithm for robot arm dynamics, and utilize matrix, vector and numeric analysis techniques. The derivation of differential vector representation of centripetal and Coriolis forces which has not yet been established in the literature is presented.
Quantum model for the price dynamics
NASA Astrophysics Data System (ADS)
Choustova, Olga
2008-10-01
We apply methods of quantum mechanics to mathematical modelling of price dynamics in a financial market. We propose to describe behavioral financial factors (e.g., expectations of traders) by using the pilot wave (Bohmian) model of quantum mechanics. Our model is a quantum-like model of the financial market, cf. with works of W. Segal, I.E. Segal, E. Haven. In this paper we study the problem of smoothness of price-trajectories in the Bohmian financial model. We show that even the smooth evolution of the financial pilot wave [psi](t,x) (representing expectations of traders) can induce jumps of prices of shares.
An integrated model of Plasmodium falciparum dynamics.
McKenzie, F Ellis; Bossert, William H
2005-02-07
The within-host and between-host dynamics of malaria are linked in myriad ways, but most obviously by gametocytes, the parasite blood forms transmissible from human to mosquito. Gametocyte dynamics depend on those of non-transmissible blood forms, which stimulate immune responses, impeding transmission as well as within-host parasite densities. These dynamics can, in turn, influence antigenic diversity and recombination between genetically distinct parasites. Here, we embed a differential-equation model of parasite-immune system interactions within each of the individual humans represented in a discrete-event model of Plasmodium falciparum transmission, and examine the effects of human population turnover, parasite antigenic diversity, recombination, and gametocyte production on the dynamics of malaria. Our results indicate that the local persistence of P. falciparum increases with turnover in the human population and antigenic diversity in the parasite, particularly in combination, and that antigenic diversity arising from meiotic recombination in the parasite has complex differential effects on the persistence of founder and progeny genotypes. We also find that reductions in the duration of individual human infectivity to mosquitoes, even if universal, produce population-level effects only if near-absolute, and that, in competition, the persistence and prevalence of parasite genotypes with gametocyte production concordant with data exceed those of genotypes with higher gametocyte production. This new, integrated approach provides a framework for investigating relationships between pathogen dynamics within an individual host and pathogen dynamics within interacting host and vector populations.
Particle dynamics modeling methods for colloid suspensions
NASA Astrophysics Data System (ADS)
Bolintineanu, Dan S.; Grest, Gary S.; Lechman, Jeremy B.; Pierce, Flint; Plimpton, Steven J.; Schunk, P. Randall
2014-09-01
We present a review and critique of several methods for the simulation of the dynamics of colloidal suspensions at the mesoscale. We focus particularly on simulation techniques for hydrodynamic interactions, including implicit solvents (Fast Lubrication Dynamics, an approximation to Stokesian Dynamics) and explicit/particle-based solvents (Multi-Particle Collision Dynamics and Dissipative Particle Dynamics). Several variants of each method are compared quantitatively for the canonical system of monodisperse hard spheres, with a particular focus on diffusion characteristics, as well as shear rheology and microstructure. In all cases, we attempt to match the relevant properties of a well-characterized solvent, which turns out to be challenging for the explicit solvent models. Reasonable quantitative agreement is observed among all methods, but overall the Fast Lubrication Dynamics technique shows the best accuracy and performance. We also devote significant discussion to the extension of these methods to more complex situations of interest in industrial applications, including models for non-Newtonian solvent rheology, non-spherical particles, drying and curing of solvent and flows in complex geometries. This work identifies research challenges and motivates future efforts to develop techniques for quantitative, predictive simulations of industrially relevant colloidal suspension processes.
Modeling emotional dynamics : currency versus field.
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.
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.
Dynamic model for the popularity of websites
NASA Astrophysics Data System (ADS)
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.
BDI-modelling of complex intracellular dynamics.
Jonker, C M; Snoep, J L; Treur, J; Westerhoff, H V; Wijngaards, W C A
2008-03-07
A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.
ODE models for oncolytic virus dynamics
Komarova, Natalia L.; Wodarz, Dominik
2010-01-01
Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remain uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the “fast spread” models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the “slow spread” models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers. PMID:20085772
Dynamic causal modelling of distributed electromagnetic responses
Daunizeau, Jean; Kiebel, Stefan J.; Friston, Karl J.
2009-01-01
In this note, we describe a variant of dynamic causal modelling for evoked responses as measured with electroencephalography or magnetoencephalography (EEG and MEG). We depart from equivalent current dipole formulations of DCM, and extend it to provide spatiotemporal source estimates that are spatially distributed. The spatial model is based upon neural-field equations that model neuronal activity on the cortical manifold. We approximate this description of electrocortical activity with a set of local standing-waves that are coupled though their temporal dynamics. The ensuing distributed DCM models source as a mixture of overlapping patches on the cortical mesh. Time-varying activity in this mixture, caused by activity in other sources and exogenous inputs, is propagated through appropriate lead-field or gain-matrices to generate observed sensor data. This spatial model has three key advantages. First, it is more appropriate than equivalent current dipole models, when real source activity is distributed locally within a cortical area. Second, the spatial degrees of freedom of the model can be specified and therefore optimised using model selection. Finally, the model is linear in the spatial parameters, which finesses model inversion. Here, we describe the distributed spatial model and present a comparative evaluation with conventional equivalent current dipole (ECD) models of auditory processing, as measured with EEG. PMID:19398015
Computational and dynamic models in neuroimaging
Friston, Karl J.; Dolan, Raymond J.
2010-01-01
This article reviews the substantial impact computational neuroscience has had on neuroimaging over the past years. It builds on the distinction between models of the brain as a computational machine and computational models of neuronal dynamics per se; i.e., models of brain function and biophysics. Both sorts of model borrow heavily from computational neuroscience, and both have enriched the analysis of neuroimaging data and the type of questions we address. To illustrate the role of functional models in imaging neuroscience, we focus on optimal control and decision (game) theory; the models used here provide a mechanistic account of neuronal computations and the latent (mental) states represent by the brain. In terms of biophysical modelling, we focus on dynamic causal modelling, with a special emphasis on recent advances in neural-mass models for hemodynamic and electrophysiological time series. Each example emphasises the role of generative models, which embed our hypotheses or questions, and the importance of model comparison (i.e., hypothesis testing). We will refer to this theme, when trying to contextualise recent trends in relation to each other. PMID:20036335
Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.
Onorante, Luca; Raftery, Adrian E
2016-01-01
Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.
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
A Novel Virus-Patch Dynamic Model
Yang, Lu-Xing; Yang, Xiaofan
2015-01-01
The distributed patch dissemination strategies are a promising alternative to the conventional centralized patch dissemination strategies. This paper aims to establish a theoretical framework for evaluating the effectiveness of distributed patch dissemination mechanism. Assuming that the Internet offers P2P service for every pair of nodes on the network, a dynamic model capturing both the virus propagation mechanism and the distributed patch dissemination mechanism is proposed. This model takes into account the infected removable storage media and hence captures the interaction of patches with viruses better than the original SIPS model. Surprisingly, the proposed model exhibits much simpler dynamic properties than the original SIPS model. Specifically, our model admits only two potential (viral) equilibria and undergoes a fold bifurcation. The global stabilities of the two equilibria are determined. Consequently, the dynamical properties of the proposed model are fully understood. Furthermore, it is found that reducing the probability per unit time of disconnecting a node from the Internet benefits the containment of electronic viruses. PMID:26368556
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.
Hidden process models for animal population dynamics.
Newman, K B; Buckland, S T; Lindley, S T; Thomas, L; Fernández, C
2006-02-01
Hidden process models are a conceptually useful and practical way to simultaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation, and movement. Observations of the population can be modeled as functions of true abundance with realistic probability distributions to describe observation or estimation error. Computer-intensive procedures, such as sequential Monte Carlo methods or Markov chain Monte Carlo, condition on the observed data to yield estimates of both the underlying true population abundances and the unknown population dynamics parameters. Formulation and fitting of a hidden process model are demonstrated for Sacramento River winter-run chinook salmon (Oncorhynchus tshawytsha).
Solvable model for polymorphic dynamics of biofilaments.
Mohrbach, Hervé; Kulić, Igor M
2012-03-01
We investigate an analytically tractable toy model for thermally induced polymorphic dynamics of cooperatively rearranging biofilaments-like microtubules. The proposed four-block model, which can be seen as a coarse-grained approximation of the full polymorphic tube model, permits a complete analytical treatment of all thermodynamic properties including correlation functions and angular Fourier mode distributions. Due to its mathematical tractability the model straightforwardly leads to some physical insights in recently discussed phenomena like the "length dependent persistence length." We show that a polymorphic filament can disguise itself as a classical worm-like chain on small and on large scales and yet display distinct anomalous tell-tale features indicating an inner switching dynamics on intermediate length scales.
Polarizable protein model for Dissipative Particle Dynamics
NASA Astrophysics Data System (ADS)
Peter, Emanuel; Lykov, Kirill; Pivkin, Igor
2015-11-01
In this talk, we present a novel polarizable protein model for the Dissipative Particle Dynamics (DPD) simulation technique, a coarse-grained particle-based method widely used in modeling of fluid systems at the mesoscale. We employ long-range electrostatics and Drude oscillators in combination with a newly developed polarizable water model. The protein in our model is resembled by a polarizable backbone and a simplified representation of the sidechains. We define the model parameters using the experimental structures of 2 proteins: TrpZip2 and TrpCage. We validate the model on folding of five other proteins and demonstrate that it successfully predicts folding of these proteins into their native conformations. As a perspective of this model, we will give a short outlook on simulations of protein aggregation in the bulk and near a model membrane, a relevant process in several Amyloid diseases, e.g. Alzheimer's and Diabetes II.
Modeling the Hydrogen Bond within Molecular Dynamics
ERIC Educational Resources Information Center
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.
DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING
The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...
A Flight Dynamic Model of Aircraft Spinning
1990-06-01
Australia, Library Australian Airlines, Library Qantas Airways Limited Hawker de Havilland Aust. Pty Ltd, Victoria, Library Hawker de Havilland Aust. Pty...3. MARTIN, C.A. ; Modelling Aircraft Dynamics. ARL-AERO-TECH- MEMO-400 July 1988 4. HULTBERG, R.S. ; Rotary Balance Data and Analysis for the
Modeling of tower relief dynamics: Part 2
Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )
1993-11-01
Dynamic simulations of individual towers or systems of distillations columns overcome limitations of steady-state models by rigorously determining dynamic responses. These will lead to a realistic quantification of relief header and flare system load and identify the design-setting relief scenario. Determination of distillation tower relief loads based on steady-state simulations or recognized methods of approximation can lead to over designing relief systems by large margins. This can result in unnecessary capital expenditure for relief headers and flare systems that can significantly alter the economics of a proposed project. Such overly conservative requirements may even cause potentially attractive projects to be unnecessarily canceled. In addition, approximate methods or analyses based on steady-state simulations sometimes do not identify the design-setting relief mode. Part 1 introduced the PRV and tower dynamic models. Different strategies were shown that can simplify these models. These strategies include tower segmentation, tray lumping and component lumping. Two case studies illustrate the advantages of dynamic models. The two studies are a depentanizer tower relief study and a delthanizer tower relief study.
Model Of Neural Network With Creative Dynamics
NASA Technical Reports Server (NTRS)
Zak, Michail; Barhen, Jacob
1993-01-01
Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.
Modeling the Hydrogen Bond within Molecular Dynamics
ERIC Educational Resources Information Center
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.
Model Of Neural Network With Creative Dynamics
NASA Technical Reports Server (NTRS)
Zak, Michail; Barhen, Jacob
1993-01-01
Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.
DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING
The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...
Modeling the population dynamics of Pacific yew.
Richard T. Busing; Thomas A. Spies
1995-01-01
A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-growth forest stands. Diameter growth at breast height ranged from 0 to 3 centimeters per decade...
Modeling of Reactor Kinetics and Dynamics
Matthew Johnson; Scott Lucas; Pavel Tsvetkov
2010-09-01
In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.
Constitutive Laws for Dynamic Modelling of Soils,
1980-01-01
AD-AO 733 DAMES AND MDORE LONDON (ENGLAND) F/ S/I3 CONSTITUTIVE LAWS FOR DYNAMIC MODELLING OF SOILS.(U) JAN 80 J MART1 P A CUNOALL F61708-79--087...shear history progresses. This is the type of approach followed in the endochronic models used by Bazant and co-workers ( Bazant and Krizeck, 1976...this improved model to soils (1978). Mean- while, Bazant and his co-workers have continued using the older model for 1describing concrete ( Bazant and
The quantum Rabi model: solution and dynamics
NASA Astrophysics Data System (ADS)
Xie, Qiongtao; Zhong, Honghua; Batchelor, Murray T.; Lee, Chaohong
2017-03-01
This article presents a review of recent developments on various aspects of the quantum Rabi model. Particular emphasis is given on the exact analytic solution obtained in terms of confluent Heun functions. The analytic solutions for various generalisations of the quantum Rabi model are also discussed. Results are also reviewed on the level statistics and the dynamics of the quantum Rabi model. The article concludes with an introductory overview of several experimental realisations of the quantum Rabi model. An outlook towards future developments is also given.
Developmental Stages in Dynamic Plant Growth Models
NASA Astrophysics Data System (ADS)
Maclean, Heather; Dochain, Denis; Waters, Geoff; Stasiak, Michael; Dixon, Mike; Van Der Straeten, Dominique
2011-09-01
During the growth of red beet plants in a closed environment plant growth chamber, a change in metabolism was observed (decreasing photosynthetic quotient) which was not predicted by a previously developed simple dynamic model of photosynthesis and respiration reactions. The incorporation of developmental stages into the model allowed for the representation of this change in metabolism without adding unnecessary complexity. Developmental stages were implemented by dividing the model into two successive sub-models with independent yields. The transition between the phases was detected based on online measurements. Results showed an accurate prediction of carbon dioxide and oxygen fluxes.
Dynamic model of the Earth's upper atmosphere
NASA Technical Reports Server (NTRS)
Slowey, J. W.
1984-01-01
An initial modification to the MSF/J70 Thermospheric Model, in which the variations due to sudden geomagnetic disturbances upon the Earth's upper atmospheric density structure were modeled is presented. This dynamic model of the geomagnetic variation included is an improved version of one which SAO developed from the analysis of the ESRO 4 mass spectrometer data that was incorporated in the Jacchia 1977 model. The variation with geomagnetic local time as well as with geomagnetic latitude are included, and also the effects due to disturbance of the temperature profiles in the region of energy deposition.
Population mixture model for nonlinear telomere dynamics
NASA Astrophysics Data System (ADS)
Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl
2008-12-01
Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.
Modeling joint friction in structural dynamics.
Segalman, Daniel Joseph
2005-05-01
The presence of mechanical joints--typified by the lap joint--in otherwise linear structures has been accommodated in structural dynamics via ad hoc methods for a century. The methods range from tuning linear models to approximate non-linear behavior in restricted load ranges to various methods which introduce joint dissipation in a post-processing stage. Other methods, employing constitutive models for the joints are being developed and their routine use is on the horizon.
Modeling of dynamical processes in laser ablation
Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.
1995-12-31
Various physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed-laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume, plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms, hydrodynamic and collisional descriptions of plume transport, and molecular dynamics models of the interaction of plume particles with the deposition substrate.
Modelling Subduction Dynamics: The South American Salsa
NASA Astrophysics Data System (ADS)
Hale, A. J.; Shephard, G.; Müller, D.; Liu, L.; Gurnis, M.
2009-12-01
Plate kinematic and seismic tomography models imply a gradual overriding of the Phoenix and Farallon slabs by the westward movement of the South American plate. This westward translation over the subducted slabs, and the currently subducting Nazca Plate, is expected to generate a dynamic surface topography effect, leading to time-progressive vertical motions and tilting of sedimentary basins and their hinterlands. We have set up a workflow to model these processes including ground-truthing with geological and geophysical data. A combination of geodynamic modelling software, CitcomS, GPlates (gplates.org) software and the Generic Mapping Tools (GMT) facilitates the modelling and visualisation of linked plate kinematics and mantle convection processes. The CitcomS software also allows us to alternatively use forward models, backward models, or combined forward and adjoint models. Forward models are driven by an imposed plate kinematic model and assumed initial subdution structure, whereas backwards models use mantle tomography as an input and run the model backwards by reversing the gravity field. Similarly, adjoint models use tomography as input, but iterate backwards and forwards in time to reach convergence upon present-day mantle structures. Model outputs include time-dependent mantle temperature, viscosity, and surface dynamic topography. Forward model results show that slab evolution under South America are strongly driven by the age of the subducting lithosphere. Hence, we can simulate flat-slab subduction and in regions close to the Chile triple junction we see a slab window developing, detaching older slab material from more recently subducted material. However, the forward model relies on an accurate description of the initial slab geometry at 140Ma to generate the initial slab pull. Forward and adjoint model results both suggest an alternative mechanism for major Miocene changes in paleo-Amazon river drainage. An eastward-sweeping negative dynamic
Sepsis progression and outcome: a dynamical model
Zuev, Sergey M; Kingsmore, Stephen F; Gessler, Damian DG
2006-01-01
Background Sepsis (bloodstream infection) is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions. Results We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC), a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system. Conclusion The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates. PMID:16480490
Feature extraction for structural dynamics model validation
Hemez, Francois; Farrar, Charles; Park, Gyuhae; Nishio, Mayuko; Worden, Keith; Takeda, Nobuo
2010-11-08
This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.
Data driven Langevin modeling of biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Rzepiela, Andrzej J.; Hegger, Rainer; Stock, Gerhard
2013-05-01
Based on a given time series, the data-driven Langevin equation proposed by Hegger and Stock [J. Chem. Phys. 130, 034106 (2009), 10.1063/1.3058436] aims to construct a low-dimensional dynamical model of the system. Adopting various simple model problems of biomolecular dynamics, this work presents a systematic study of the theoretical virtues and limitations as well as of the practical applicability and performance of the method. As the method requires only local information, the input data need not to be Boltzmann weighted in order to warrant that the Langevin model yields correct Boltzmann-distributed results. Moreover, a delay embedding of the state vector allows for the treatment of memory effects. The robustness of the modeling with respect to wrongly chosen model parameters or low sampling is discussed, as well as the treatment of inertial effects. Given sufficiently sampled input data, the Langevin modeling is shown to successfully recover the correct statistics (such as the probability distribution) and the dynamics (such as the position autocorrelation function) of all considered problems.
Nonsmooth dynamics in spiking neuron models
NASA Astrophysics Data System (ADS)
Coombes, S.; Thul, R.; Wedgwood, K. C. A.
2012-11-01
Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage
Direct modeling for computational fluid dynamics
NASA Astrophysics Data System (ADS)
Xu, Kun
2015-06-01
All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct
Dynamic occupancy models for explicit colonization processes
Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday
2016-01-01
The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.
NASA Astrophysics Data System (ADS)
Davtyan, Aram; Voth, Gregory A.; Andersen, Hans C.
2016-12-01
We recently developed a dynamic force matching technique for converting a coarse-grained (CG) model of a molecular system, with a CG potential energy function, into a dynamic CG model with realistic dynamics [A. Davtyan et al., J. Chem. Phys. 142, 154104 (2015)]. This is done by supplementing the model with additional degrees of freedom, called "fictitious particles." In that paper, we tested the method on CG models in which each molecule is coarse-grained into one CG point particle, with very satisfactory results. When the method was applied to a CG model of methanol that has two CG point particles per molecule, the results were encouraging but clearly required improvement. In this paper, we introduce a new type (called type-3) of fictitious particle that exerts forces on the center of mass of two CG sites. A CG model constructed using type-3 fictitious particles (as well as type-2 particles previously used) gives a much more satisfactory dynamic model for liquid methanol. In particular, we were able to construct a CG model that has the same self-diffusion coefficient and the same rotational relaxation time as an all-atom model of liquid methanol. Type-3 particles and generalizations of it are likely to be useful in converting more complicated CG models into dynamic CG models.
Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models
The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...
Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models
The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...
Indonesia’s Electricity Demand Dynamic Modelling
NASA Astrophysics Data System (ADS)
Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.
2017-06-01
Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.
Continuum modeling of cooperative traffic flow dynamics
NASA Astrophysics Data System (ADS)
Ngoduy, D.; Hoogendoorn, S. P.; Liu, R.
2009-07-01
This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.
Dynamic modeling and simulation of planetary rovers
NASA Technical Reports Server (NTRS)
Lindemann, Randel A.
1992-01-01
This paper documents a preliminary study into the dynamic modeling and computer simulation of wheeled surface vehicles. The research centered on the feasibility of using commercially available multibody dynamics codes running on engineering workstations to perform the analysis. The results indicated that physically representative vehicle mechanics can be modeled and simulated in state-of-the-art Computer Aided Engineering environments, but at excessive cost in modeling and computation time. The results lead to the recommendation for the development of an efficient rover mobility-specific software system. This system would be used for vehicle design and simulation in planetary environments; controls prototyping, design, and testing; as well as local navigation simulation and expectation planning.
Understanding Terrorist Organizations with a Dynamic Model
NASA Astrophysics Data System (ADS)
Gutfraind, Alexander
Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization’s membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.
Dynamical modelling of galactic disc outskirts
NASA Astrophysics Data System (ADS)
Athanassoula, E.
2017-03-01
I review briefly some dynamical models of structures in the outer parts of disc galaxies, including models of polar rings, tidal tails and bridges. I then discuss the density distribution in the outer parts of discs. For this, I compare observations to results of a model in which the disc galaxy is in fact the remnant of a major merger, and find good agreement. This comparison includes radial profiles of the projected surface density and of stellar age, as well as time evolution of the break radius and of the inner and outer disc scale lengths. I also compare the radial projected surface density profiles of dynamically motivated mono-age populations and find that, compared to older populations, younger ones have flatter density profiles in the inner region and steeper in the outer one. The break radius, however, does not vary with stellar age, again in good agreement with observations.
Building Markov state models with solvent dynamics.
Gu, Chen; Chang, Huang-Wei; Maibaum, Lutz; Pande, Vijay S; Carlsson, Gunnar E; Guibas, Leonidas J
2013-01-01
Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses.
Building Markov state models with solvent dynamics
2013-01-01
Background Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. Methods We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. Results We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. Conclusions In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses. PMID:23368418
Next Generation Carbon-Nitrogen Dynamics Model
NASA Astrophysics Data System (ADS)
Xu, C.; Fisher, R. A.; Vrugt, J. A.; Wullschleger, S. D.; McDowell, N. G.
2012-12-01
Nitrogen is a key regulator of vegetation dynamics, soil carbon release, and terrestrial carbon cycles. Thus, to assess energy impacts on the global carbon cycle and future climates, it is critical that we have a mechanism-based and data-calibrated nitrogen model that simulates nitrogen limitation upon both above and belowground carbon dynamics. In this study, we developed a next generation nitrogen-carbon dynamic model within the NCAR Community Earth System Model (CESM). This next generation nitrogen-carbon dynamic model utilized 1) a mechanistic model of nitrogen limitation on photosynthesis with nitrogen trade-offs among light absorption, electron transport, carboxylation, respiration and storage; 2) an optimal leaf nitrogen model that links soil nitrogen availability and leaf nitrogen content; and 3) an ecosystem demography (ED) model that simulates the growth and light competition of tree cohorts and is currently coupled to CLM. Our three test cases with changes in CO2 concentration, growing temperature and radiation demonstrate the model's ability to predict the impact of altered environmental conditions on nitrogen allocations. Currently, we are testing the model against different datasets including soil fertilization and Free Air CO2 enrichment (FACE) experiments across different forest types. We expect that our calibrated model will considerably improve our understanding and predictability of vegetation-climate interactions.itrogen allocation model evaluations. The figure shows the scatter plots of predicted and measured Vc,max and Jmax scaled to 25 oC (i.e.,Vc,max25 and Jmax25) at elevated CO2 (570 ppm, test case one), reduced radiation in canopy (0.1-0.9 of the radiation at the top of canopy, test case two) and reduced growing temperature (15oC, test case three). The model is first calibrated using control data under ambient CO2 (370 ppm), radiation at the top of the canopy (621 μmol photon/m2/s), the normal growing temperature (30oC). The fitted model
Global dynamic modeling of a transmission system
NASA Technical Reports Server (NTRS)
Choy, F. K.; Qian, W.
1993-01-01
The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.
Learning generative models of molecular dynamics
2012-01-01
We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L1 reg-ularization is used to ensure sparse models and thus reduce the risk of over-fitting the data. The topology of the resulting model reveals important couplings between different parts of the protein, thus aiding in the analysis of molecular motions. The generative nature of the model makes it well-suited to making predictions about the global effects of local structural changes (e.g., the binding of an allosteric regulator). Additionally, the model can be used to sample new conformations. The second algorithm learns a time-varying graphical model where the topology and parameters change smoothly along the trajectory, revealing the conformational sub-states. The last algorithm learns a Markov Chain over undirected graphical models which can be used to study and simulate kinetics. We demonstrate our algorithms on multiple molecular dynamics trajectories. PMID:22369071
Learning generative models of molecular dynamics.
Razavian, Narges Sharif; Kamisetty, Hetunandan; Langmead, Christopher J
2012-01-01
We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L1 regularization is used to ensure sparse models and thus reduce the risk of over-fitting the data. The topology of the resulting model reveals important couplings between different parts of the protein, thus aiding in the analysis of molecular motions. The generative nature of the model makes it well-suited to making predictions about the global effects of local structural changes (e.g., the binding of an allosteric regulator). Additionally, the model can be used to sample new conformations. The second algorithm learns a time-varying graphical model where the topology and parameters change smoothly along the trajectory, revealing the conformational sub-states. The last algorithm learns a Markov Chain over undirected graphical models which can be used to study and simulate kinetics. We demonstrate our algorithms on multiple molecular dynamics trajectories.
Global Langevin model of multidimensional biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard
2016-11-01
Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.
Dynamic Modeling of Meandering Alluvial Channels
NASA Astrophysics Data System (ADS)
Lan, Yongqiang
1990-01-01
The migration of meandering alluvial channels is investigated theoretically, numerically, and experimentally. An equation for the rate of bank erosion is derived from a two-dimensional continuity equation for sediment transport linked with the depth-averaged dynamic flow equations. A simple one-dimensional theoretical analysis of meander migration leads to a relationship between the migration rate and the relative channel curvature and sediment properties. The simple model appropriately simulates the pattern and rate of meander expansion and migrations of the White River, Indiana and the East Nishnabotna River, Iowa. Application of the one-dimensional model to sine -generated alluvial channels indicates that meander migration reaches its maximum when the relative radius of curvature reaches about 4.8, or when the sinuosity of meander approaches 1.3. A two-dimensional numerical model, DYNAMIC, which predicts both lateral and longitudinal migration of alluvial channels is then developed, based on a system of quasi -steady depth-averaged flow dynamic equations, a sediment continuity equation, and a bank erosion equation. A linear analysis of the two-dimensional model leads to a convolutional relation between the rate of meander migration and flow and sediment properties. In the two-dimensional numerical analysis, a numerical algorithm called FLOWSOL is developed to solve the flow dynamic equations. The flow algorithm is then linked to the sediment continuity equation and bank erosion equation to simulate bed deformation and bank erosion. The developed two-dimensional model is applied to calculate the velocity profiles in Rozovskii's experiments and the bed deformation and shear stress in Hooke's experiments. Good agreement is obtained between the calculated and measured velocities, shear stresses and bed profiles in all experiments. Small scaled meandering rivers are developed successfully on a floodplain with or without cohesive materials (about 3%) in a wide
Overview of the GRC Stirling Convertor System Dynamic Model
NASA Technical Reports Server (NTRS)
Lewandowski, Edward J.; Regan, Timothy F.
2004-01-01
A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.
A computational model for dynamic vision
NASA Technical Reports Server (NTRS)
Moezzi, Saied; Weymouth, Terry E.
1990-01-01
This paper describes a novel computational model for dynamic vision which promises to be both powerful and robust. Furthermore the paradigm is ideal for an active vision system where camera vergence changes dynamically. Its basis is the retinotopically indexed object-centered encoding of the early visual information. Specifically, the relative distances of objects to a set of referents is encoded in image registered maps. To illustrate the efficacy of the method, it is applied to the problem of dynamic stereo vision. Integration of depth information over multiple frames obtained by a moving robot generally requires precise information about the relative camera position from frame to frame. Usually, this information can only be approximated. The method facilitates the integration of depth information without direct use or knowledge of camera motion.
Polarizable water model for Dissipative Particle Dynamics
NASA Astrophysics Data System (ADS)
Pivkin, Igor; Peter, Emanuel
2015-11-01
Dissipative Particle Dynamics (DPD) is an efficient particle-based method for modeling mesoscopic behavior of fluid systems. DPD forces conserve the momentum resulting in a correct description of hydrodynamic interactions. Polarizability has been introduced into some coarse-grained particle-based simulation methods; however it has not been done with DPD before. We developed a new polarizable coarse-grained water model for DPD, which employs long-range electrostatics and Drude oscillators. In this talk, we will present the model and its applications in simulations of membrane systems, where polarization effects play an essential role.
Informations in Models of Evolutionary Dynamics
NASA Astrophysics Data System (ADS)
Rivoire, Olivier
2016-03-01
Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.
Structural system identification: Structural dynamics model validation
Red-Horse, J.R.
1997-04-01
Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.
Dynamic Modeling of an Evapotranspiration Cap
Jacob J. Jacobson; Steven Piet; Rafael Soto; Gerald Sehlke; Harold Heydt; John Visser
2005-10-01
The U.S. Department of Energy is scheduled to design and install hundreds of landfill caps/barriers over the next several decades and these caps will have a design life expectancy of up to 1,000 years. Other landfill caps with 30 year design lifetimes are reaching the end of their original design life; the changes to these caps need to be understood to provide a basis for lifetime extension. Defining the attributes that make a successful cap (one that isolates the waste from the environment) is crucial to these efforts. Because cap systems such as landfill caps are dynamic in nature, it is impossible to understand, monitor, and update lifetime predictions without understanding the dynamics of cap degradation, which is most often due to multiple interdependent factors rather than isolated independent events. In an attempt to understand the dynamics of cap degradation, a computer model using system dynamics is being developed to capture the complex behavior of an evapotranspiration cap. The specific objectives of this project are to capture the dynamic, nonlinear feedback loop structures underlying an evapotranspiration cap and, through computer simulation, gain a better understanding of long-term behavior, influencing factors, and, ultimately, long-term cap performance.
Activated Dynamics in Dense Model Nanocomposites
NASA Astrophysics Data System (ADS)
Xie, Shijie; Schweizer, Kenneth
The nonlinear Langevin equation approach is applied to investigate the ensemble-averaged activated dynamics of small molecule liquids (or disconnected segments in a polymer melt) in dense nanocomposites under model isobaric conditions where the spherical nanoparticles are dynamically fixed. Fully thermalized and quenched-replica integral equation theory methods are employed to investigate the influence on matrix dynamics of the equilibrium and nonequilibrium nanocomposite structure, respectively. In equilibrium, the miscibility window can be narrow due to depletion and bridging attraction induced phase separation which limits the study of activated dynamics to regimes where the barriers are relatively low. In contrast, by using replica integral equation theory, macroscopic demixing is suppressed, and the addition of nanoparticles can induce much slower activated matrix dynamics which can be studied over a wide range of pure liquid alpha relaxation times, interfacial attraction strengths and ranges, particle sizes and loadings, and mixture microstructures. Numerical results for the mean activated relaxation time, transient localization length, matrix elasticity and kinetic vitrification in the nanocomposite will be presented.
Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model
NASA Astrophysics Data System (ADS)
Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin
2016-04-01
Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343
Dynamic Alignment Models for Neural Coding
Kollmorgen, Sepp; Hahnloser, Richard H. R.
2014-01-01
Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448
Reduced Dynamic Models in Epithelial Transport
Hernández, Julio A.
2013-01-01
Most models developed to represent transport across epithelia assume that the cell interior constitutes a homogeneous compartment, characterized by a single concentration value of the transported species. This conception differs significantly from the current view, in which the cellular compartment is regarded as a highly crowded media of marked structural heterogeneity. Can the finding of relatively simple dynamic properties of transport processes in epithelia be compatible with this complex structural conception of the cell interior? The purpose of this work is to contribute with one simple theoretical approach to answer this question. For this, the techniques of model reduction are utilized to obtain a two-state reduced model from more complex linear models of transcellular transport with a larger number of intermediate states. In these complex models, each state corresponds to the solute concentration in an intermediate intracellular compartment. In addition, the numerical studies reveal that it is possible to approximate a general two-state model under conditions where strict reduction of the complex models cannot be performed. These results contribute with arguments to reconcile the current conception of the cell interior as a highly complex medium with the finding of relatively simple dynamic properties of transport across epithelial cells. PMID:23533397
Bioinactivation: Software for modelling dynamic microbial inactivation.
Garre, Alberto; Fernández, Pablo S; Lindqvist, Roland; Egea, Jose A
2017-03-01
This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC). The calculations are based on inactivation models common in academia and industry (Bigelow, Peleg, Mafart and Geeraerd). Bioinactivation SE supplies a user-friendly interface to selected functions of Bioinactivation core, namely the model fitting of non-isothermal experiments and the generation of prediction intervals. The capabilities of bioinactivation are presented in this paper through a case study, modelling the non-isothermal inactivation of Bacillus sporothermodurans. This study has provided a full characterization of the response of the bacteria to dynamic temperature conditions, including confidence intervals for the model parameters and a prediction interval of the survivor curve. We conclude that the MCMC algorithm produces a better characterization of the biological uncertainty and variability than non-linear regression. The bioinactivation software can be relevant to the food and pharmaceutical industry, as well as to regulatory agencies, as part of a (quantitative) microbial risk assessment.
Composite model for DNA torsion dynamics.
Cadoni, Mariano; De Leo, Roberto; Gaeta, Giuseppe
2007-02-01
DNA torsion dynamics is essential in the transcription process; a simple model for it, in reasonable agreement with experimental observations, has been proposed by Yakushevich (Y) and developed by several authors; in this, the nucleotides (the DNA subunits made of a sugar-phosphate group and the attached nitrogen base) are described by a single degree of freedom. In this paper we propose and investigate, both analytically and numerically, a "composite" version of the Y model, in which the sugar-phosphate group and the base are described by separate degrees of freedom. The model proposed here contains as a particular case the Y model and shares with it many features and results, but represents an improvement from both the conceptual and the phenomenological point of view. It provides a more realistic description of DNA and possibly a justification for the use of models which consider the DNA chain as uniform. It shows that the existence of solitons is a generic feature of the underlying nonlinear dynamics and is to a large extent independent of the detailed modeling of DNA. The model we consider supports solitonic solutions, qualitatively and quantitatively very similar to the Y solitons, in a fully realistic range of all the physical parameters characterizing the DNA.
Modeling of intensified high dynamic star tracker.
Yan, Jinyun; Jiang, Jie; Zhang, Guangjun
2017-01-23
An intensified high dynamic star tracker (IHDST) is a photoelectric instrument and stably outputs three-axis attitude for a spacecraft at very high angular velocity. The IHDST uses an image intensifier to multiply the incident starlight. Thus, high sensitivity of the star detection is achieved under short exposure time such that extremely high dynamic performance is achieved. The IHDST differs from a traditional star tracker in terms of the imaging process. Therefore, we establish a quantum transfer model of IHDST based on stochastic process theory. By this model, the probability distribution of the output quantum number is obtained accurately. Then, we introduce two-dimensional Lorentz functions to describe the spatial spreading process of the IHDST. Considering the interaction of these two processes, a complete star imaging model of IHDST is provided. Using this model, the centroiding accuracy of the IHDST is analyzed in detail. Accordingly, a working parameter optimizing strategy is developed for high centroiding accuracy and improved dynamic performance. Finally, the laboratory tests and the night sky experiment support the conclusions.
Dynamical Causal Modeling from a Quantum Dynamical Perspective
Demiralp, Emre; Demiralp, Metin
2010-09-30
Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, this limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at Tx ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (Tm ~ 900K), and the crossover temperature ismore » roughly twice of the glass-transition temperature (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less
NASA Astrophysics Data System (ADS)
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multicomponent metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamical aspects of a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulations with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (self diffusion coefficient, self relaxation time, and shear viscosity) bordered at Tx˜1300 K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs well above the melting point of the system (Tm˜900 K) in the equilibrium liquid state; and the crossover temperature Tx is roughly twice of the glass-transition temperature of the system (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a nonparametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter α2 and the four-point correlation function χ4.
Dynamic material modeling in hot forging
El-Gizawy, A.S. )
1992-03-01
A dynamic material model that characterized flow behavior in the workpiece under forging conditions was required to optimize the process and produce defect-free product at minimum cost. Constitutive equations describe the relationship between stress, strain rate, and temperature under forging conditions. Using aluminum alloy 7050, numerous deformation experiments were conducted to fully characterize constitutive equation variables. A thorough description of the experimental arrangement was provided. Flow data and efficiency data were assembled into a three-dimensional plot of temperature vs. strain rate vs. deformation efficiency to produce an efficiency map. The efficiency map provided the information required for optimization of forging process design. The results of dynamic modeling of the material were used in simulating the isothermal forging of a particular part. Recommendations concerning optimum preform design and processing conditions were reported.
The dynamic radiation environment assimilation model (DREAM)
Reeves, Geoffrey D; Koller, Josef; Tokar, Robert L; Chen, Yue; Henderson, Michael G; Friedel, Reiner H
2010-01-01
The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate results than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.
Dynamic plasmapause model based on THEMIS measurements
NASA Astrophysics Data System (ADS)
Liu, W.; Liu, X.
2015-12-01
We will present a dynamic plasmapause location model established based on five years of THEMIS measurements from 2009 to 2013. In total, 5878 plasmapause crossing events are identified, sufficiently covering all 24 Magnetic Local Time (MLT) sectors. Based on this plasmapause crossing database, we investigate the correlations between plasmapause locations with solar wind parameters and geomagnetic indices. Input parameters for the best fits are obtained for different MLT sectors and finally we choose five input parameters to build a plasmapause location model, including five-minute-averaged SYM-H, AL and AU indices as well as hourly-averaged AE and Kp indices. An out-of-sample comparison on the evolution of the plasmapause is shown during April 2001 magnetic storm, demonstrating good agreement between model results and observations. Two major advantages are achieved by this model. First, this model provides plasmapause locations at 24 MLT sectors, still providing good consistency with observations. Second, this model is able to reproduce dynamic variations of plasmapause in the time scale as short as five minutes.
Molecular dynamics modelling of solidification in metals
Boercker, D.B.; Belak, J.; Glosli, J.
1997-12-31
Molecular dynamics modeling is used to study the solidification of metals at high pressure and temperature. Constant pressure MD is applied to a simulation cell initially filled with both solid and molten metal. The solid/liquid interface is tracked as a function of time, and the data are used to estimate growth rates of crystallites at high pressure and temperature in Ta and Mg.
Modeling the dynamical systems on experimental data
NASA Astrophysics Data System (ADS)
Janson, Natalie B.; Anishchenko, Vadim S.
1996-06-01
An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog's heart, a human's heart and a blood circulation system of a white rat. Sampled one-dimensional realizations of these systems were taken as the initial data. Correlation dimensions were calculated to evaluate the embedding dimensions of the systems' attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation.
Dynamic analysis of a parasite population model
NASA Astrophysics Data System (ADS)
Sibona, G. J.; Condat, C. A.
2002-03-01
We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.
Dynamical model of birdsong maintenance and control
NASA Astrophysics Data System (ADS)
Abarbanel, Henry D. I.; Talathi, Sachin S.; Mindlin, Gabriel; Rabinovich, Misha; Gibb, Leif
2004-11-01
The neuroethology of song learning, production, and maintenance in songbirds presents interesting similarities to human speech. We have developed a biophysical model of the manner in which song could be maintained in adult songbirds. This model may inform us about the human counterpart to these processes. In songbirds, signals generated in nucleus High Vocal center (HVc) follow a direct route along a premotor pathway to the robust nucleus of the archistriatum (RA) as well as an indirect route to RA through the anterior forebrain pathway (AFP): the neurons of RA are innervated from both sources. HVc expresses very sparse bursts of spikes having interspike intervals of about 2ms . The expressions of these bursts arrive at the RA with a time difference ΔT≈50±10ms between the two pathways. The observed combination of AMPA and NMDA receptors at RA projection neurons suggests that long-term potentiation and long-term depression can both be induced by spike timing plasticity through the pairing of the HVc and AFP signals. We present a dynamical model that stabilizes this synaptic plasticity through a feedback from the RA to the AFP using known connections. The stabilization occurs dynamically and is absent when the RA→AFP connection is removed. This requires a dynamical selection of ΔT . The model does this, and ΔT lies within the observed range. Our model represents an illustration of a functional consequence of activity-dependent plasticity directly connected with neuroethological observations. Within the model the parameters of the AFP, and thus the magnitude of ΔT , can also be tuned to an unstable regime. This means that destabilization might be induced by neuromodulation of the AFP.
Dynamic Factor Analysis Models with Time-Varying Parameters
ERIC Educational Resources Information Center
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian
2011-01-01
Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…
Dynamic Factor Analysis Models with Time-Varying Parameters
ERIC Educational Resources Information Center
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian
2011-01-01
Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…
DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT
Privon, G. C.; Evans, A. S.; Barnes, J. E.; Hibbard, J. E.; Yun, M. S.; Mazzarella, J. M.; Armus, L.; Surace, J.
2013-07-10
We present dynamical models of four interacting systems: NGC 5257/8, The Mice, the Antennae, and NGC 2623. The parameter space of the encounters are constrained using the Identikit model-matching and visualization tool. Identikit utilizes hybrid N-body and test particle simulations to enable rapid exploration of the parameter space of galaxy mergers. The Identikit-derived matches of these systems are reproduced with self-consistent collisionless simulations which show very similar results. The models generally reproduce the observed morphology and H I kinematics of the tidal tails in these systems with reasonable properties inferred for the progenitor galaxies. The models presented here are the first to appear in the literature for NGC 5257/8 and NGC 2623, and The Mice and the Antennae are compared with previously published models. Based on the assumed mass model and our derived initial conditions, the models indicate that the four systems are currently being viewed 175-260 Myr after first passage and cover a wide range of merger stages. In some instances there are mismatches between the models and the data (e.g., in the length of a tail); these are likely due to our adoption of a single mass model for all galaxies. Despite the use of a single mass model, these results demonstrate the utility of Identikit in constraining the parameter space for galaxy mergers when applied to real data.
Simple models for biomembrane structure and dynamics
NASA Astrophysics Data System (ADS)
Brown, Frank L. H.
2007-07-01
Simulation of biomembranes over length and time scales relevant to cellular biology is not currently feasible with molecular dynamics including full atomic detail. Barring an unforeseen revolution in the computer industry, this situation will not change for many decades. We present two coarse grained simulation models for biomembranes that treat water implicitly (i.e. no water molecules appear in our simulations. The hydrophobic effect, hydrodynamics and related properties are approximately included without simulation of solvent). These models enable the study of systems and phenomena previously intractable to simulation. The influence of membrane bound proteins on lipid ordering and the diffusion of membrane bound proteins is discussed.
Cytoskeleton Dynamics: A Continuum Cooperative Hydrolysis Model
NASA Astrophysics Data System (ADS)
Xu, Jian-Wei; Cheng, Bo; Feng, Yu-Yu; Wang, Zi-Qing; Wang, Guo-Dong
2015-05-01
Cytoskeleton is a network of filamentous proteins, such as actin filaments and microtubules. We propose a continuum cooperative hydrolysis model which possesses exactly analytical solution to describe the dynamics of filament. The results show that the cooperativity leads to non negative-exponential distribution of T (ATP or GTP) subunits. As an application, we investigate the treadmilling phenomenon using our model. It is shown that the cooperativity remarkably affects the length of filament. Supported by Chinese Universities Scientific Fund under Grant No. 2014YB029 and National Natural Science Foundation of China under Grant No. 11205123
Population Model with a Dynamic Food Supply
NASA Astrophysics Data System (ADS)
Dickman, Ronald; da Silva Nascimento, Jonas
2009-09-01
We propose a simple population model including the food supply as a dynamic variable. In the model, survival of an organism depends on a certain minimum rate of food consumption; a higher rate of consumption is required for reproduction. We investigate the stationary behavior under steady food input, and the transient behavior of growth and decay when food is present initially but is not replenished. Under a periodic food supply, the system exhibits period-doubling bifurcations and chaos in certain ranges of the reproduction rate. Bifurcations and chaos are favored by a slow reproduction rate and a long period of food-supply oscillation.
Approaches for modeling magnetic nanoparticle dynamics
Reeves, Daniel B; Weaver, John B
2014-01-01
Magnetic nanoparticles are useful biological probes as well as therapeutic agents. There have been several approaches used to model nanoparticle magnetization dynamics for both Brownian as well as Néel rotation. The magnetizations are often of interest and can be compared with experimental results. Here we summarize these approaches including the Stoner-Wohlfarth approach, and stochastic approaches including thermal fluctuations. Non-equilibrium related temperature effects can be described by a distribution function approach (Fokker-Planck equation) or a stochastic differential equation (Langevin equation). Approximate models in several regimes can be derived from these general approaches to simplify implementation. PMID:25271360
Dynamical α -cluster model of 16O
NASA Astrophysics Data System (ADS)
Halcrow, C. J.; King, C.; Manton, N. S.
2017-03-01
We calculate the low-lying spectrum of the 16O nucleus using an α -cluster model which includes the important tetrahedral and square configurations. Our approach is motivated by the dynamics of α -particle scattering in the Skyrme model. We are able to replicate the large energy splitting that is observed between states of identical spin but opposite parities. We also provide a novel interpretation of the first excited state of 16O and make predictions for the energies of 6- states that have yet to be observed experimentally.
Modeling the dynamics of bivalent histone modifications.
Ku, Wai Lim; Girvan, Michelle; Yuan, Guo-Cheng; Sorrentino, Francesco; Ott, Edward
2013-01-01
Epigenetic modifications to histones may promote either activation or repression of the transcription of nearby genes. Recent experimental studies show that the promoters of many lineage-control genes in stem cells have "bivalent domains" in which the nucleosomes contain both active (H3K4me3) and repressive (H3K27me3) marks. It is generally agreed that bivalent domains play an important role in stem cell differentiation, but the underlying mechanisms remain unclear. Here we formulate a mathematical model to investigate the dynamic properties of histone modification patterns. We then illustrate that our modeling framework can be used to capture key features of experimentally observed combinatorial chromatin states.
A dynamical model for bark beetle outbreaks.
Křivan, Vlastimil; Lewis, Mark; Bentz, Barbara J; Bewick, Sharon; Lenhart, Suzanne M; Liebhold, Andrew
2016-10-21
Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees are highly nonlinear, due to complex aggregation behaviors exhibited by beetles attacking trees. Models have a role to play in helping unravel the effects of variable tree resistance and beetle aggregation on bark beetle outbreaks. In this article we develop a new mathematical model for bark beetle outbreaks using an analogy with epidemiological models. Because the model operates on several distinct time scales, singular perturbation methods are used to simplify the model. The result is a dynamical system that tracks populations of uninfested and infested trees. A limiting case of the model is a discontinuous function of state variables, leading to solutions in the Filippov sense. The model assumes an extensive seed-bank so that tree recruitment is possible even if trees go extinct. Two scenarios are considered for immigration of new beetles. The first is a single tree stand with beetles immigrating from outside while the second considers two forest stands with beetle dispersal between them. For the seed-bank driven recruitment rate, when beetle immigration is low, the forest stand recovers to a beetle-free state. At high beetle immigration rates beetle populations approach an endemic equilibrium state. At intermediate immigration rates, the model predicts bistability as the forest can be in either of the two equilibrium states: a healthy forest, or a forest with an endemic beetle population. The model bistability leads to hysteresis. Interactions between two stands show how a less resistant stand of trees may provide an initial toe-hold for the invasion, which later leads to a regional beetle outbreak in the
Dynamic stall simulation including turbulence modeling
Allet, A.; Halle, S.; Paraschivoiu, I.
1995-09-01
The objective of this study is to investigate the two-dimensional unsteady flow around an airfoil undergoing a Darrieus motion in dynamic stall conditions. For this purpose, a numerical solver based on the solution of the Reynolds-averaged Navier-Stokes equations expressed in a streamfunction-vorticity formulation in a non-inertial frame of reference was developed. The governing equations are solved by the streamline upwind Petrov-Galerkin finite element method (FEM). Temporal discretization is achieved by second-order-accurate finite differences. The resulting global matrix system is linearized by the Newton method and solved by the generalized minimum residual method (GMRES) with an incomplete triangular factorization preconditioning (ILU). Turbulence effects are introduced in the solver by an eddy viscosity model. The investigation centers on an evaluation of the possibilities of several turbulence models, including the algebraic Cebeci-Smith model (CSM) and the nonequilibrium Johnson-King model (JKM). In an effort to predict dynamic stall features on rotating airfoils, first the authors present some testing results concerning the performance of both turbulence models for the flat plate case. Then, computed flow structure together with aerodynamic coefficients for a NACA 0015 airfoil in Darrieus motion under stall conditions are presented.
Directed network discovery with dynamic network modelling.
Anzellotti, Stefano; Kliemann, Dorit; Jacoby, Nir; Saxe, Rebecca
2017-05-01
Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face. Copyright © 2017 Elsevier Ltd. All rights reserved.
Restoration of the Potosi Dynamic Model 2010
Adushita, Yasmin; Leetaru, Hannes
2014-09-30
In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate
A Multiscale Model for Virus Capsid Dynamics
Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei
2010-01-01
Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. PMID:20224756
Dynamical models of happiness with fractional order
NASA Astrophysics Data System (ADS)
Song, Lei; Xu, Shiyun; Yang, Jianying
2010-03-01
This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.
Transition matrix model for evolutionary game dynamics
NASA Astrophysics Data System (ADS)
Ermentrout, G. Bard; Griffin, Christopher; Belmonte, Andrew
2016-03-01
We study an evolutionary game model based on a transition matrix approach, in which the total change in the proportion of a population playing a given strategy is summed directly over contributions from all other strategies. This general approach combines aspects of the traditional replicator model, such as preserving unpopulated strategies, with mutation-type dynamics, which allow for nonzero switching to unpopulated strategies, in terms of a single transition function. Under certain conditions, this model yields an endemic population playing non-Nash-equilibrium strategies. In addition, a Hopf bifurcation with a limit cycle may occur in the generalized rock-scissors-paper game, unlike the replicator equation. Nonetheless, many of the Folk Theorem results are shown to hold for this model.
AFDM: An Advanced Fluid-Dynamics Model
Bohl, W.R.; Parker, F.R. ); Wilhelm, D. . Inst. fuer Neutronenphysik und Reaktortechnik); Berthier, J. ); Goutagny, L. . Inst. de Protection et de Surete Nucleaire); Ninokata,
1990-09-01
AFDM, or the Advanced Fluid-Dynamics Model, is a computer code that investigates new approaches simulating the multiphase-flow fluid-dynamics aspects of severe accidents in fast reactors. The AFDM formalism starts with differential equations similar to those in the SIMMER-II code. These equations are modified to treat three velocity fields and supplemented with a variety of new models. The AFDM code has 12 topologies describing what material contacts are possible depending on the presence or absence of a given material in a computational cell, on the dominant liquid, and on the continuous phase. Single-phase, bubbly, churn-turbulent, cellular, and dispersed flow regimes are permitted for the pool situations modeled. Virtual mass terms are included for vapor in liquid-continuous flow. Interfacial areas between the continuous and discontinuous phases are convected to allow some tracking of phenomenological histories. Interfacial areas are also modified by models of nucleation, dynamic forces, turbulence, flashing, coalescence, and mass transfer. Heat transfer is generally treated using engineering correlations. Liquid-vapor phase transitions are handled with the nonequilibrium, heat-transfer-limited model, whereas melting and freezing processes are based on equilibrium considerations. Convection is treated using a fractional-step method of time integration, including a semi-implicit pressure iteration. A higher-order differencing option is provided to control numerical diffusion. The Los Alamos SESAME equation-of-state has been implemented using densities and temperatures as the independent variables. AFDM programming has vectorized all computational loops consistent with the objective of producing an exportable code. 24 refs., 4 figs.
An efficient model of drillstring dynamics
NASA Astrophysics Data System (ADS)
Butlin, T.; Langley, R. S.
2015-11-01
High amplitude vibration regimes can cause significant damage to oilwell drillstrings: torsional stick-slip oscillation, forward whirl and backward whirl are each associated with different kinds of damage. There is a need for models of drillstring dynamics that can predict this variety of phenomena that are: efficient enough to carry out parametric studies; simple enough to provide insight into the underlying physics, and which retain sufficient detail to correlate to real drillstrings. The modelling strategy presented in this paper attempts to balance these requirements. It includes the dynamics of the full length of the drillstring over a wide bandwidth but assumes that the main nonlinear effects are due to spatially localised regions of strong nonlinearity, for example at the drillbit cutting interface and at stabilisers where the borehole wall clearance is smallest. The equations of motion can be formed in terms of this reduced set of degrees of freedom, coupled to the nonlinear contact laws and solved by time-domain integration. Two implementations of this approach are presented, using (1) digital filters and (2) a finite element model to describe the linear dynamics. Choosing a sampling period that is less than the group delay between nonlinear degrees of freedom results in a decoupled set of equations that can be solved very efficiently. Several cases are presented which demonstrate a variety of phenomena, including stick-slip oscillation; forward whirl and backward whirl. Parametric studies are shown which reveal the conditions which lead to high amplitude vibration regimes, and an analytic regime boundary is derived for torsional stick-slip oscillation. The digital filter and finite element models are shown to be in good agreement and are similarly computationally efficient. The digital filter approach has the advantage of more intuitive interpretation, while the finite element model is more readily implemented using existing software packages.
Dynamic geometry, brain function modeling, and consciousness.
Roy, Sisir; Llinás, Rodolfo
2008-01-01
Pellionisz and Llinás proposed, years ago, a geometric interpretation towards understanding brain function. This interpretation assumes that the relation between the brain and the external world is determined by the ability of the central nervous system (CNS) to construct an internal model of the external world using an interactive geometrical relationship between sensory and motor expression. This approach opened new vistas not only in brain research but also in understanding the foundations of geometry itself. The approach named tensor network theory is sufficiently rich to allow specific computational modeling and addressed the issue of prediction, based on Taylor series expansion properties of the system, at the neuronal level, as a basic property of brain function. It was actually proposed that the evolutionary realm is the backbone for the development of an internal functional space that, while being purely representational, can interact successfully with the totally different world of the so-called "external reality". Now if the internal space or functional space is endowed with stochastic metric tensor properties, then there will be a dynamic correspondence between events in the external world and their specification in the internal space. We shall call this dynamic geometry since the minimal time resolution of the brain (10-15 ms), associated with 40 Hz oscillations of neurons and their network dynamics, is considered to be responsible for recognizing external events and generating the concept of simultaneity. The stochastic metric tensor in dynamic geometry can be written as five-dimensional space-time where the fifth dimension is a probability space as well as a metric space. This extra dimension is considered an imbedded degree of freedom. It is worth noticing that the above-mentioned 40 Hz oscillation is present both in awake and dream states where the central difference is the inability of phase resetting in the latter. This framework of dynamic
A range extender hybrid electric vehicle dynamic model
Powell, B.K.; Pilutti, T.E.
1994-12-31
This paper describes a dynamic model possessing the key system components of a Range Extender Hybrid Electric Vehicle. The model is suitable for dynamic analysis, control law synthesis, and prototype simulation.
Dynamic Modeling of the SMAP Rotating Flexible Antenna
NASA Technical Reports Server (NTRS)
Nayeri, Reza D.
2012-01-01
Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications
Dynamic Modeling of the SMAP Rotating Flexible Antenna
NASA Technical Reports Server (NTRS)
Nayeri, Reza D.
2012-01-01
Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.
Ogbunugafor, C Brandon; Robinson, Sean P
2016-01-01
Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.
Spatial epidemic network models with viral dynamics
NASA Astrophysics Data System (ADS)
Tuckwell, Henry C.; Toubiana, Laurent; Vibert, Jean-Francois
1998-02-01
A mathematical model is presented for the spread of viral diseases within human or other populations in which both the dynamics of viral growth within individuals and the interactions between individuals are taken into account. We thus bridge the classical macroscopic approach to the growth and population dynamics of disease at the microscopic level. Each member, i, of the population of n individuals is represented by a vector function of time whose components are antibody numbers ai(t), and the virion level vi(t). These quantities evolve according to 2n differential equations, which are coupled via a transmission matrix B with elements βij, i,j=1,...,n, such that βijvi is the expected rate of transmission of infectious particles from individual i to individual j. We study nearest-neighbor interaction and transmission which declines exponentially with distance between the individuals. Results are shown to be related to those of classical macroscopic (SIR) models. We find threshold effects in the occurrence of epidemics as the parameters of the viral and antibody dynamics change. The distribution of the final size of an epidemic is estimated, for various initial patterns of infection, at various values of the parameter which describes the mobility of the population. We also determine the final size in the cases of extreme clustering and dispersion of infected individuals.
Comet Gas and Dust Dynamics Modeling
NASA Technical Reports Server (NTRS)
Von Allmen, Paul A.; Lee, Seungwon
2010-01-01
This software models the gas and dust dynamics of comet coma (the head region of a comet) in order to support the Microwave Instrument for Rosetta Orbiter (MIRO) project. MIRO will study the evolution of the comet 67P/Churyumov-Gerasimenko's coma system. The instrument will measure surface temperature, gas-production rates and relative abundances, and velocity and excitation temperatures of each species along with their spatial temporal variability. This software will use these measurements to improve the understanding of coma dynamics. The modeling tool solves the equation of motion of a dust particle, the energy balance equation of the dust particle, the continuity equation for the dust and gas flow, and the dust and gas mixture energy equation. By solving these equations numerically, the software calculates the temperature and velocity of gas and dust as a function of time for a given initial gas and dust production rate, and a dust characteristic parameter that measures the ability of a dust particle to adjust its velocity to the local gas velocity. The software is written in a modular manner, thereby allowing the addition of more dynamics equations as needed. All of the numerical algorithms are added in-house and no third-party libraries are used.
Dynamic Stabilization of Atmospheric Single Column Models.
NASA Astrophysics Data System (ADS)
Bergman, John W.; Sardeshmukh, Prashant D.
2004-03-01
Single column models (SCMs) provide an economical framework for assessing the sensitivity of atmospheric temperature and humidity to natural and imposed perturbations, and also for developing improved representations of diabatic processes in weather and climate models. Their economy is achieved at the expense of ignoring interactions with the circulation dynamics; thus, advection by the large-scale flow is either prescribed or neglected. This artificial decoupling of the diabatic and adiabatic tendencies can often cause rapid error growth in SCM integrations, especially in the Tropics where large-scale vertical advection is important. As a result, SCMs can quickly develop highly unrealistic thermodynamic structures, making it pointless to study their subsequent evolution.This paper suggests one way around this fundamental difficulty through a simple coupling of the diabatic and adiabatic tendencies. In essence, the local vertical velocity at any instant is specified by a formula that links the local vertical temperature advection to the evolution of SCM-generated diabatic heating rates up to that instant. This vertical velocity is then used to determine vertical humidity advection, and also horizontal temperature and humidity advection under an additional assumption that the column is embedded in a uniform environment. The parameters in the formula are estimated in a separate set of calculations, from the approach to equilibrium of a linearized global primitive equation model forced by steady heat sources. As a test, the parameterized dynamics are used to predict the linear model's local response to oscillating heat sources, and found to perform remarkably well over a wide range of space and time scales. In a second test, the parameterization is found to capture important aspects of a general circulation model's vertical advection and temperature tendencies and their lead lag relationships with diabatic heating fluctuations at convectively active locations in the
Mathematical Model of Porous Medium Dynamics
NASA Astrophysics Data System (ADS)
Gerschuk, Peotr; Sapozhnikov, Anatoly
1999-06-01
Semiempirical model describing porous material strains under pulse mechanical and thermal loadings is proposed. Porous medium is considered as continuous one but with special form of pressure dependence upon strain. This model takes into account principal features of porous materials behavior which can be observed when the material is strained in dynamic and static experiments ( non-reversibility of large strains, nonconvexity of loading curve). Elastoplastic properties of porous medium, its damages when it is strained and dynamic fracture are also taken into account. Dispersion of unidirectional motion caused by medium heterogeneity (porousness) is taken into acount by introducing the physical viscosity depending upon pores size. It is supposed that at every moment of time pores are in equilibrium with pressure i.e. kinetic of pores collapse is not taken into account. The model is presented by the system of differential equations connecting pressure and energy of porous medium with its strain. These equations close system of equations of motion and continuity which then is integrated numerically. The proposed model has been tested on carbon materials and porous copper . Results of calculation of these materials shock compressing are in satisfactory agreement with experimental data. Results of calculation of thin plate with porous copper layer collision are given as an illustration.
A dynamical model of tumour immunotherapy.
Frascoli, Federico; Kim, Peter S; Hughes, Barry D; Landman, Kerry A
2014-07-01
A coupled ordinary differential equation model of tumour-immune dynamics is presented and analysed. The model accounts for biological and clinical factors which regulate the interaction rates of cytotoxic T lymphocytes on the surface of the tumour mass. A phase plane analysis demonstrates that competition between tumour cells and lymphocytes can result in tumour eradication, perpetual oscillations, or unbounded solutions. To investigate the dependence of the dynamic behaviour on model parameters, the equations are solved analytically and conditions for unbounded versus bounded solutions are discussed. An analytic characterisation of the basin of attraction for oscillatory orbits is given. It is also shown that the tumour shape, characterised by a surface area to volume scaling factor, influences the size of the basin, with significant consequences for therapy design. The findings reveal that the tumour volume must surpass a threshold size that depends on lymphocyte parameters for the cancer to be completely eliminated. A semi-analytic procedure to calculate oscillation periods and determine their sensitivity to model parameters is also presented. Numerical results show that the period of oscillations exhibits notable nonlinear dependence on biologically relevant conditions.
MSMBuilder: Statistical Models for Biomolecular Dynamics.
Harrigan, Matthew P; Sultan, Mohammad M; Hernández, Carlos X; Husic, Brooke E; Eastman, Peter; Schwantes, Christian R; Beauchamp, Kyle A; McGibbon, Robert T; Pande, Vijay S
2017-01-10
MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov state models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models and time-structure based independent component analysis. MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python application programming interface. MSMBuilder was developed with careful consideration for compatibility with the broader machine learning community by following the design of scikit-learn. The package is used primarily by practitioners of molecular dynamics, but is just as applicable to other computational or experimental time-series measurements. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Multiscale model approach for magnetization dynamics simulations
NASA Astrophysics Data System (ADS)
De Lucia, Andrea; Krüger, Benjamin; Tretiakov, Oleg A.; Kläui, Mathias
2016-11-01
Simulations of magnetization dynamics in a multiscale environment enable the rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with frequency lower than a certain threshold set by the coarse scale micromagnetic model with no noticeable attenuation due to the interface between the models. As a comparison to exact analytical theory, we show that in a system with a Dzyaloshinskii-Moriya interaction leading to spin spirals, the simulated multiscale result is in good quantitative agreement with the analytical calculation.
Dynamic Data Integration Using Streamline Models
NASA Astrophysics Data System (ADS)
Datta-Gupta, A.
2002-12-01
Recent developments in petroleum reservoir characterization and in the management of uncertainty have lead to the ability of the industry to routinely generate large multimillion-cell detailed geologic models. Reconciling such high-resolution models to dynamic reservoir behavior (transient pressure and tracer response, multiphase production history) still remains an outstanding challenge because of the high computational costs associated with the solution of large inverse problems. Streamline-based flow simulation models can offer significant potential in this regard. In this presentation we will exploit an analogy between streamlines and seismic ray tracing to develop an efficient formalism for dynamic data integration into high-resolution subsurface models. Utilizing concepts from the asymptotic ray theory in seismic and diffusive electromagnetic imaging, we will generalize the streamline approach to incorporate transient pressure, tracer and multiphase production response during subsurface characterization. Data integration will be carried out in a manner analogous to seismic tomography and waveform imaging by first matching the `arrival time' and then the `amplitude' of the production response. Several field examples from the oil field and environmental applications will demonstrate the practical feasibility of the approach.
Consequence modeling using the fire dynamics simulator.
Ryder, Noah L; Sutula, Jason A; Schemel, Christopher F; Hamer, Andrew J; Van Brunt, Vincent
2004-11-11
The use of Computational Fluid Dynamics (CFD) and in particular Large Eddy Simulation (LES) codes to model fires provides an efficient tool for the prediction of large-scale effects that include plume characteristics, combustion product dispersion, and heat effects to adjacent objects. This paper illustrates the strengths of the Fire Dynamics Simulator (FDS), an LES code developed by the National Institute of Standards and Technology (NIST), through several small and large-scale validation runs and process safety applications. The paper presents two fire experiments--a small room fire and a large (15 m diameter) pool fire. The model results are compared to experimental data and demonstrate good agreement between the models and data. The validation work is then extended to demonstrate applicability to process safety concerns by detailing a model of a tank farm fire and a model of the ignition of a gaseous fuel in a confined space. In this simulation, a room was filled with propane, given time to disperse, and was then ignited. The model yields accurate results of the dispersion of the gas throughout the space. This information can be used to determine flammability and explosive limits in a space and can be used in subsequent models to determine the pressure and temperature waves that would result from an explosion. The model dispersion results were compared to an experiment performed by Factory Mutual. Using the above examples, this paper will demonstrate that FDS is ideally suited to build realistic models of process geometries in which large scale explosion and fire failure risks can be evaluated with several distinct advantages over more traditional CFD codes. Namely transient solutions to fire and explosion growth can be produced with less sophisticated hardware (lower cost) than needed for traditional CFD codes (PC type computer verses UNIX workstation) and can be solved for longer time histories (on the order of hundreds of seconds of computed time) with
Modeling of tower relief dynamics: Part 1
Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )
1993-10-01
In an environmentally responsible, safe and health-conscious design, a relief system must contain all relieving gases or vapors. The system must include treatment of these gases or vapors in a flare, scrubber or other appropriate device prior to discharge to the atmosphere. The benefit of a dynamic simulation is most significant in designing these systems. Dynamic modeling provides accurate answers to key questions which must be addressed. It identifies the design-setting relief scenario for any possible upset such as loss of reflux, power failure, loss of cooling water, fire, etc. It accurately quantifies the maximum relief rate and time dependency of the relief rates. This permits a safe relief system design that is not overly conservative.
A dynamic network model for interbank market
NASA Astrophysics Data System (ADS)
Xu, Tao; He, Jianmin; Li, Shouwei
2016-12-01
In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems
2016-01-01
Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of “ODEs and formalized flow diagrams” as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler’s behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918
Mathematic modeling of human amniotic fluid dynamics.
Mann, S E; Nijland, M J; Ross, M G
1996-10-01
We sought to develop a model quantifying the relative contributions of fetal swallowing and intramembranous flow to amniotic fluid dynamics during human gestation. We then used the model to simulate the impact of absent swallowing on amniotic fluid volume. The model was developed with published data for normal human amniotic fluid volume and composition, human fetal urine flow rate and composition (11 to 42 weeks), and extrapolated data from ovine lung fluid production. Fetal swallowing and intramembranous flow were calculated with assumptions that (1) swallowed fluid is isotonic to amniotic fluid, (2) intramembranous flow is free water diffusion, and (3) 50% of lung fluid is swallowed. The model was then applied to simulate absent fetal swallowing and variable (0%, 50%) proportions of swallowed lung fluid were used as a representation of esophageal atresia-tracheal fistula variations. Fetal swallowed volume and intramembranous flow linearly increase until 28 to 30 weeks. Daily swallowed volume then exponentially increases to a maximum of 1006 ml/day at term, whereas intramembranous flow continues on a linear trend to reach 393 ml/day at term. With absent swallowing and variable amounts of lung fluid swallowed (0%, 50%), predicted amniotic fluid volume is similar to normal values through 20 weeks, exceeds the 95% confidence interval for normal amniotic fluid volume at 29 to 30 weeks' gestation (approximately 2000 ml), and then exponentially increases. Predicted amniotic fluid osmolality (280 to 257 mOsm/kg) is slightly lower than actual values although within the clinically normal range. This model indicates that the normal reduction in amniotic fluid volume beginning at 34 weeks results from the marked increase in swallowed volume during the third trimester. Additionally, this model correlates well with the timing of the initial clinical presentation of polyhydramnios observed in some fetuses with conditions that result in absent or reduced swallowing or
Yi, Zheng; Lindner, Benjamin; Prinz, Jan -Hendrik; Noe, Frank; Smith, Jeremy C.
2013-11-01
Here, neutron scattering experiments directly probe the dynamics of complex molecules on the sub pico- to microsecond time scales. However, the assignment of the relaxations seen experimentally to specific structural rearrangements is difficult, since many of the underlying dynamical processes may exist on similar timescales. In an accompanying article, we present a theoretical approach to the analysis of molecular dynamics simulations with a Markov State Model (MSM) that permits the direct identification of structural transitions leading to each contributing relaxation process. Here, we demonstrate the use of the method by applying it to the configurational dynamics of the well-characterized alanine dipeptide. A practical procedure for deriving the MSM from an MD is introduced. The result is a 9-state MSM in the space of the backbone dihedral angles and the side-chain methyl group. The agreement between the quasielastic spectrum calculated directly from the atomic trajectories and that derived from the Markov state model is excellent. The dependence on the wavevector of the individual Markov processes is described. The procedure means that it is now practicable to interpret quasielastic scattering spectra in terms of well-defined intramolecular transitions with minimal a priori assumptions as to the nature of the dynamics taking place.
Modelling Market Dynamics with a "Market Game"
NASA Astrophysics Data System (ADS)
Katahira, Kei; Chen, Yu
In the financial market, traders, especially speculators, typically behave as to yield capital gains by the difference between selling and buying prices. Making use of the structure of Minority Game, we build a novel market toy model which takes account of such the speculative mind involving a round-trip trade to analyze the market dynamics as a system. Even though the micro-level behavioral rules of players in this new model is quite simple, its macroscopic aggregational output has the reproducibility of the well-known stylized facts such as volatility clustering and heavy tails. The proposed model may become a new alternative bottom-up approach in order to study the emerging mechanism of those stylized qualitative properties of asset returns.
Stochastic dynamic models and Chebyshev splines
Fan, Ruzong; Zhu, Bin; Wang, Yuedong
2015-01-01
In this article, we establish a connection between a stochastic dynamic model (SDM) driven by a linear stochastic differential equation (SDE) and a Chebyshev spline, which enables researchers to borrow strength across fields both theoretically and numerically. We construct a differential operator for the penalty function and develop a reproducing kernel Hilbert space (RKHS) induced by the SDM and the Chebyshev spline. The general form of the linear SDE allows us to extend the well-known connection between an integrated Brownian motion and a polynomial spline to a connection between more complex diffusion processes and Chebyshev splines. One interesting special case is connection between an integrated Ornstein–Uhlenbeck process and an exponential spline. We use two real data sets to illustrate the integrated Ornstein–Uhlenbeck process model and exponential spline model and show their estimates are almost identical. PMID:26045632
Apoptosis in virus infection dynamics models
Fan, Ruili; Dong, Yueping; Huang, Gang; Takeuchi, Yasuhiro
2014-01-01
In this paper, on the basis of the simplified two-dimensional virus infection dynamics model, we propose two extended models that aim at incorporating the influence of activation-induced apoptosis which directly affects the population of uninfected cells. The theoretical analysis shows that increasing apoptosis plays a positive role in control of virus infection. However, after being included the third population of cytotoxic T lymphocytes immune response in HIV-infected patients, it shows that depending on intensity of the apoptosis of healthy cells, the apoptosis can either promote or comfort the long-term evolution of HIV infection. Further, the discrete-time delay of apoptosis is incorporated into the pervious model. Stability switching occurs as the time delay in apoptosis increases. Numerical simulations are performed to illustrate the theoretical results and display the different impacts of a delay in apoptosis. PMID:24963975
Simulating aggregate dynamics in ocean biogeochemical models
NASA Astrophysics Data System (ADS)
Jackson, George A.; Burd, Adrian B.
2015-04-01
The dynamics of elements in the water column is complex, depending on multiple biological and physical processes operating at very different physical scales. Coagulation of particulate material is important for transforming particles and moving them in the water column. Mechanistic models of coagulation processes provide a means to predict these processes, help interpret observations, and provide insight into the processes occurring. However, most model applications have focused on describing simple marine systems and mechanisms. We argue that further model development, in close collaboration with field and experimental scientists, is required in order to extend the models to describe the large-scale elemental distributions and interactions being studied as part of GEOTRACES. Models that provide a fundamental description of trace element-particle interactions are required as are experimental tests of the mechanisms involved and the predictions arising from models. However, a comparison between simple and complicated models of aggregation and trace metal provides a means for understanding the implications of simplifying assumptions and providing guidance as to which simplifications are needed.
Flight Dynamic Model Exchange using XML
NASA Technical Reports Server (NTRS)
Jackson, E. Bruce; Hildreth, Bruce L.
2002-01-01
The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.
Mathematical modeling of infectious disease dynamics
Siettos, Constantinos I.; Russo, Lucia
2013-01-01
Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host–pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works. PMID:23552814
Models for inference in dynamic metacommunity systems
Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias
2010-01-01
A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.
Models for inference in dynamic metacommunity systems
Dorazio, R.M.; Kery, M.; Royle, J. Andrew; Plattner, M.
2010-01-01
A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species-and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity. ?? 2010 by the Ecological Society of America.
Modeling cell dynamics under mobile phone radiation.
Minelli, Tullio Antonio; Balduzzo, Maurizio; Milone, Francesco Ferro; Nofrate, Valentina
2007-04-01
Perturbations by pulse-modulated microwave radiation from GSM mobile phones on neuron cell membrane gating and calcium oscillations have been suggested as a possible mechanism underlying activation of brain states and electroencephalographic epiphenomena. As the employ of UMTS phones seems to reveal other symptoms, a unified phenomenological framework is needed. In order to explain possible effects of mobile phone radiation on cell oscillations, GSM and UMTS low-frequency envelopes have been detected, recorded and used as input in cell models. Dynamical systems endowed with contiguous regular and chaotic regimes suitable to produce stochastic resonance can both account for the perturbation of the neuro-electrical activity and even for the low intensity of the signal perceived by high sensitive subjects. Neuron models of this kind can be employed as a reductionist hint for the mentioned phenomenology. The Hindmarsh-Rose model exhibits frequency enhancement and regularization phenomena induced by weak GSM and UMTS. More realistic simulations of cell membrane gating and calcium oscillations have been performed with the help of an adaptation of the Chay-Keizer dynamical system. This scheme can explain the suspected subjective sensitivity to mobile phone signals under the thermal threshold, in terms of cell calcium regularity mechanisms. Concerning the two kinds of emission, the stronger occupation of the ELF band of last generation UMTS phones is compensated by lower power emitted.
Dynamical Vertex Approximation for the Hubbard Model
NASA Astrophysics Data System (ADS)
Toschi, Alessandro
A full understanding of correlated electron systems in the physically relevant situations of three and two dimensions represents a challenge for the contemporary condensed matter theory. However, in the last years considerable progress has been achieved by means of increasingly more powerful quantum many-body algorithms, applied to the basic model for correlated electrons, the Hubbard Hamiltonian. Here, I will review the physics emerging from studies performed with the dynamical vertex approximation, which includes diagrammatic corrections to the local description of the dynamical mean field theory (DMFT). In particular, I will first discuss the phase diagram in three dimensions with a special focus on the commensurate and incommensurate magnetic phases, their (quantum) critical properties, and the impact of fluctuations on electronic lifetimes and spectral functions. In two dimensions, the effects of non-local fluctuations beyond DMFT grow enormously, determining the appearance of a low-temperature insulating behavior for all values of the interaction in the unfrustrated model: Here the prototypical features of the Mott-Hubbard metal-insulator transition, as well as the existence of magnetically ordered phases, are completely overwhelmed by antiferromagnetic fluctuations of exponentially large extension, in accordance with the Mermin-Wagner theorem. Eventually, by a fluctuation diagnostics analysis of cluster DMFT self-energies, the same magnetic fluctuations are identified as responsible for the pseudogap regime in the holed-doped frustrated case, with important implications for the theoretical modeling of the cuprate physics.
Dynamical model for light composite fermions
NASA Astrophysics Data System (ADS)
Derman, Emanuel
1981-04-01
A simple dynamical model for the internal structure of the three light lepton and quark generations (νe,e,u,d), (νμ,μ,c,s), and (ντ,τ,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L∘,L-,U,D) with the same (SU3)c×SU2×U1 quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e-=[L-H], μ-=[L-HH], τ-=[L-HHH]. It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest MH~16 TeV and MF~100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as μ-->eδ). Phenomenological consequences and tests of the model are discussed.
Dynamical model for light composite fermions
Derman, E.
1981-04-01
A simple dynamical model for the internal structure of the three light lepton and quark generations (..nu../sub e/,e,u,d), (..nu../sub ..mu../,..mu..,c,s), and (..nu../sub tau/,tau,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L-italic/sup 0/,L/sup -/,U,D) with the same (SU/sub 3/)/sub c/ x SU/sub 2/ x U/sub 1/ quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e/sup -/=L/sup -/H), ..mu../sup -/=L/sup -/HH), tau/sup -/=L/sup -/HHH). It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest M/sub H/approx.16 TeV and M/sub F/approx.100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as ..mu -->..e..gamma..). Phenomenological consequences and tests of the model are discussed.
Oxygen and seizure dynamics: II. Computational modeling
Wei, Yina; Ullah, Ghanim; Ingram, Justin
2014-01-01
Electrophysiological recordings show intense neuronal firing during epileptic seizures leading to enhanced energy consumption. However, the relationship between oxygen metabolism and seizure patterns has not been well studied. Recent studies have developed fast and quantitative techniques to measure oxygen microdomain concentration during seizure events. In this article, we develop a biophysical model that accounts for these experimental observations. The model is an extension of the Hodgkin-Huxley formalism and includes the neuronal microenvironment dynamics of sodium, potassium, and oxygen concentrations. Our model accounts for metabolic energy consumption during and following seizure events. We can further account for the experimental observation that hypoxia can induce seizures, with seizures occurring only within a narrow range of tissue oxygen pressure. We also reproduce the interplay between excitatory and inhibitory neurons seen in experiments, accounting for the different oxygen levels observed during seizures in excitatory vs. inhibitory cell layers. Our findings offer a more comprehensive understanding of the complex interrelationship among seizures, ion dynamics, and energy metabolism. PMID:24671540
Improved dynamical modelling of the Arches cluster
NASA Astrophysics Data System (ADS)
Lee, Joowon; Kim, Sungsoo S.
2014-05-01
Recently, Clarkson et al. (2012) measured the intrinsic velocity dispersion of the Arches cluster, a young and massive star cluster in the Galactic center. Using the observed velocity dispersion profile and the surface brightness profile of Espinoza et al. (2009), they estimate the cluster's present-day mass to be ˜ 1.5×104 M⊙ by fitting an isothermal King model. In this study, we trace the best-fit initial mass for the Arches cluster using the same observed data set and also the anisotropic Fokker-Planck calculations for the dynamical evolution.
Dynamic model of the threshold displacement energy
NASA Astrophysics Data System (ADS)
Kupchishin, A. I.; Kupchishin, A. A.
2017-01-01
A dynamic (cascade-probability) model for calculating the threshold displacement energy of knocked-out atoms (Ed) was proposed taking into account the influence of the instability zone (spontaneous recombination). General expression was recorded for Ed depending on the formation energy of interstitial atoms Ef and vacancies Ei, on the energy transfer coefficient α and the number of interactions i needed to move the atom out of the instability zone. The parameters of primary particles were calculated. Comparison of calculations with experimental data gives a satisfactory agreement.
Modeling the dynamical systems on experimental data
Janson, N.B.; Anishchenko, V.S.
1996-06-01
An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog{close_quote}s heart, a human{close_quote}s heart and a blood circulation system of a white rat. Sampled one-dimensional realizations of these systems were taken as the initial data. Correlation dimensions were calculated to evaluate the embedding dimensions of the systems{close_quote} attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation. {copyright} {ital 1996 American Institute of Physics.}
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. PMID:26512019
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.
Scalar model for frictional precursors dynamics.
Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano
2015-02-02
Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective.
Scalar model for frictional precursors dynamics
Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano
2015-01-01
Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective. PMID:25640079
Complex networks repair strategies: Dynamic models
NASA Astrophysics Data System (ADS)
Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang
2017-09-01
Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree < k > and enhances network invulnerability.
Unsteady aerodynamics modeling for flight dynamics application
NASA Astrophysics Data System (ADS)
Wang, Qing; He, Kai-Feng; Qian, Wei-Qi; Zhang, Tian-Jiao; Cheng, Yan-Qing; Wu, Kai-Yuan
2012-02-01
In view of engineering application, it is practicable to decompose the aerodynamics into three components: the static aerodynamics, the aerodynamic increment due to steady rotations, and the aerodynamic increment due to unsteady separated and vortical flow. The first and the second components can be presented in conventional forms, while the third is described using a one-order differential equation and a radial-basis-function (RBF) network. For an aircraft configuration, the mathematical models of 6-component aerodynamic coefficients are set up from the wind tunnel test data of pitch, yaw, roll, and coupled yawroll large-amplitude oscillations. The flight dynamics of an aircraft is studied by the bifurcation analysis technique in the case of quasi-steady aerodynamics and unsteady aerodynamics, respectively. The results show that: (1) unsteady aerodynamics has no effect upon the existence of trim points, but affects their stability; (2) unsteady aerodynamics has great effects upon the existence, stability, and amplitudes of periodic solutions; and (3) unsteady aerodynamics changes the stable regions of trim points obviously. Furthermore, the dynamic responses of the aircraft to elevator deflections are inspected. It is shown that the unsteady aerodynamics is beneficial to dynamic stability for the present aircraft. Finally, the effects of unsteady aerodynamics on the post-stall maneuverability are analyzed by numerical simulation.
Hybrid modeling and prediction of dynamical systems
Lloyd, Alun L.; Flores, Kevin B.
2017-01-01
Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642
Computational social dynamic modeling of group recruitment.
Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.
2004-01-01
The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.
Graphical models for inferring single molecule dynamics
2010-01-01
Background The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET) versus time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well. Results The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem. Conclusions The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics. PMID:21034427
Gradient navigation model for pedestrian dynamics
NASA Astrophysics Data System (ADS)
Dietrich, Felix; Köster, Gerta
2014-06-01
We present a microscopic ordinary differential equation (ODE)-based model for pedestrian dynamics: the gradient navigation model. The model uses a superposition of gradients of distance functions to directly change the direction of the velocity vector. The velocity is then integrated to obtain the location. The approach differs fundamentally from force-based models needing only three equations to derive the ODE system, as opposed to four in, e.g., the social force model. Also, as a result, pedestrians are no longer subject to inertia. Several other advantages ensue: Model-induced oscillations are avoided completely since no actual forces are present. The derivatives in the equations of motion are smooth and therefore allow the use of fast and accurate high-order numerical integrators. At the same time, the existence and uniqueness of the solution to the ODE system follow almost directly from the smoothness properties. In addition, we introduce a method to calibrate parameters by theoretical arguments based on empirically validated assumptions rather than by numerical tests. These parameters, combined with the accurate integration, yield simulation results with no collisions of pedestrians. Several empirically observed system phenomena emerge without the need to recalibrate the parameter set for each scenario: obstacle avoidance, lane formation, stop-and-go waves, and congestion at bottlenecks. The density evolution in the latter is shown to be quantitatively close to controlled experiments. Likewise, we observe a dependence of the crowd velocity on the local density that compares well with benchmark fundamental diagrams.
AFDM: An Advanced Fluid-Dynamics Model
Wilhelm, D.
1990-09-01
This volume describes the Advanced Fluid-Dynamics Model (AFDM) for topologies, flow regimes, and interfacial areas. The objective of these models is to provide values for the interfacial areas between all components existing in a computational cell. The interfacial areas are then used to evaluate the mass, energy, and momentum transfer between the components. A new approach has been undertaken in the development of a model to convect the interfacial areas of the discontinuous velocity fields in the three-velocity-field environment of AFDM. These interfacial areas are called convectible surface areas. The continuous and discontinuous components are chosen using volume fraction and levitation criteria. This establishes so-called topologies for which the convectible surface areas can be determined. These areas are functions of space and time. Solid particulates that are limited to being discontinuous within the bulk fluid are assumed to have a constant size. The convectible surface areas are subdivided to model contacts between two discontinuous components or discontinuous components and the structure. The models have been written for the flow inside of large pools. Therefore, the structure is tracked only as a boundary to the fluid volume without having a direct influence on velocity or volume fraction distribution by means of flow regimes or boundary layer models. 17 refs., 7 tabs., 18 figs.
Modelling thrombosis using dissipative particle dynamics method
Filipovic, N; Kojic, M; Tsuda, A
2008-01-01
Aim. Arterial occlusion is a leading cause of cardiovascular disease. The main mechanism causing vessel occlusion is thrombus formation, which may be initiated by the activation of platelets. The focus of this study is on the mechanical aspects of platelet-mediated thrombosis which includes the motion, collision, adhesion and aggregation of activated platelets in the blood. A review of the existing continuum-based models is given. A mechanical model of platelet accumulation onto the vessel wall is developed using the dissipative particle dynamics (DPD) method in which the blood (i.e. colloidal-composed medium) is treated as a group of mesoscale particles interacting through conservative, dissipative, attractive and random forces. Methods. Colloidal fluid components (plasma and platelets) are discretized by mesoscopic (micrometre-size) particles that move according to Newton's law. The size of each mesoscopic particle is small enough to allow tracking of each constituent of the colloidal fluid, but significantly larger than the size of atoms such that, in contrast to the molecular dynamics approach, detailed atomic level analysis is not required. Results. To test this model, we simulated the deposition of platelets onto the wall of an expanded tube and compared our computed results with the experimental data of Karino et al. (Miscrovasc. Res. 17, 238–269, 1977). By matching our simulations to the experimental results, the platelet aggregation/adhesion binding force (characterized by an effective spring constant) was determined and found to be within a physiologically reasonable range. Conclusion. Our results suggest that the DPD method offers a promising new approach to the modelling of platelet-mediated thrombosis. The DPD model includes interaction forces between platelets both when they are in the resting state (non-activated) and when they are activated, and therefore it can be extended to the analysis of kinetics of binding and other phenomena relevant to
A dynamic localization model with stochastic backscatter
NASA Technical Reports Server (NTRS)
Carati, Daniele; Ghosal, Sandip
1994-01-01
The modeling of subgrid scales in large-eddy simulation (LES) has been rationalized by the introduction of the dynamic localization procedure. This method allows one to compute rather than prescribe the unknown coefficients in the subgrid-scale model. Formally, the LES equations are supposed to be obtained by applying to the Navier-Stokes equations a 'grid filter' operation. Though the subgrid stress itself is unknown, an identity between subgrid stresses generated by different filters has been derived. Although preliminary tests of the Dynamic Localization Model (DLM) with k-equation have been satisfactory, the use of a negative eddy viscosity to describe backscatter is probably a crude representation of the physics of reverse transfer of energy. Indeed, the model is fully deterministic. Knowing the filtered velocity field and the subgrid-scale energy, the subgrid stress is automatically determined. We know that the LES equations cannot be fully deterministic since the small scales are not resolved. This stems from an important distinction between equilibrium hydrodynamics and turbulence. In equilibrium hydrodynamics, the molecular motions are also not resolved. However, there is a clear separation of scale between these unresolved motions and the relevant hydrodynamic scales. The result of molecular motions can then be separated into an average effect (the molecular viscosity) and some fluctuations. Due to the large number of molecules present in a box with size of the order of the hydrodynamic scale, the ratio between fluctuations and the average effect should be very small (as a result of the 'law of large numbers'). For that reason, the hydrodynamic balance equations are usually purely deterministic. In turbulence, however, there is no clear separation of scale between small and large eddies. In that case, the fluctuations around a deterministic eddy viscosity term could be significant. An eddy noise would then appear through a stochastic term in the subgrid
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu_{40}Zr_{51}Al_{9} using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T_{x} ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T_{m} ~ 900K), and the crossover temperature is roughly twice of the glass-transition temperature (T_{g}). Below T_{x}, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T_{x} and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.
Modelling of snow avalanche dynamics: influence of model parameters
NASA Astrophysics Data System (ADS)
Bozhinskiy, A. N.
The three-parameter hydraulic model of snow avalanche dynamics including the coefficients of dry and turbulent friction and the coefficient of new-snow-mass entrainment was investigated. The 'Domestic' avalanche site in Elbrus region, Caucasus, Russia, was chosen as the model avalanche range. According to the model, the fixed avalanche run-out can be achieved with various combinations of model parameters. At the fixed value of the coefficient of entrainment me, we have a curve on a plane of the coefficients of dry and turbulent friction. It was found that the family of curves (me is a parameter) are crossed at the single point. The value of the coefficient of turbulent friction at the cross-point remained practically constant for the maximum and average avalanche run-outs. The conclusions obtained are confirmed by the results of modelling for six arbitrarily chosen avalanche sites: three in the Khibiny mountains, Kola Peninsula, Russia, two in the Elbrus region and one idealized site with an exponential longitudinal profile. The dependences of run-out on the coefficient of dry friction are constructed for all the investigated avalanche sites. The results are important for the statistical simulation of avalanche dynamics since they suggest the possibility of using only one random model parameter, namely, the coefficient of dry friction, in the model. The histograms and distribution functions of the coefficient of dry friction are constructed and presented for avalanche sites Nos 22 and 43 (Khibiny mountains) and 'Domestic', with the available series of field data.
Constructing Dynamic Event Trees from Markov Models
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-05-01
In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: a) partitioning the process variable state space into magnitude intervals (cells), b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank
A Simple General Model of Evolutionary Dynamics
NASA Astrophysics Data System (ADS)
Thurner, Stefan
Evolution is a process in which some variations that emerge within a population (of, e.g., biological species or industrial goods) get selected, survive, and proliferate, whereas others vanish. Survival probability, proliferation, or production rates are associated with the "fitness" of a particular variation. We argue that the notion of fitness is an a posteriori concept in the sense that one can assign higher fitness to species or goods that survive but one can generally not derive or predict fitness per se. Whereas proliferation rates can be measured, fitness landscapes, that is, the inter-dependence of proliferation rates, cannot. For this reason we think that in a physical theory of evolution such notions should be avoided. Here we review a recent quantitative formulation of evolutionary dynamics that provides a framework for the co-evolution of species and their fitness landscapes (Thurner et al., 2010, Physica A 389, 747; Thurner et al., 2010, New J. Phys. 12, 075029; Klimek et al., 2009, Phys. Rev. E 82, 011901 (2010). The corresponding model leads to a generic evolutionary dynamics characterized by phases of relative stability in terms of diversity, followed by phases of massive restructuring. These dynamical modes can be interpreted as punctuated equilibria in biology, or Schumpeterian business cycles (Schumpeter, 1939, Business Cycles, McGraw-Hill, London) in economics. We show that phase transitions that separate phases of high and low diversity can be approximated surprisingly well by mean-field methods. We demonstrate that the mathematical framework is suited to understand systemic properties of evolutionary systems, such as their proneness to collapse, or their potential for diversification. The framework suggests that evolutionary processes are naturally linked to self-organized criticality and to properties of production matrices, such as their eigenvalue spectra. Even though the model is phrased in general terms it is also practical in the sense
Radiative and dynamical modeling of Jupiter's atmosphere
NASA Astrophysics Data System (ADS)
Guerlet, Sandrine; Spiga, Aymeric
2016-04-01
Jupiter's atmosphere harbours a rich meteorology, with alternate westward and eastward zonal jets, waves signatures and long-living storms. Recent ground-based and spacecraft measurements have also revealed a rich stratospheric dynamics, with the observation of thermal signatures of planetary waves, puzzling meridional distribution of hydrocarbons at odds with predictions of photochemical models, and a periodic equatorial oscillation analogous to the Earth's quasi-biennal oscillation and Saturn's equatorial oscillation. These recent observations, along with the many unanswered questions (What drives and maintain the equatorial oscillations? How important is the seasonal forcing compared to the influence of internal heat? What is the large-scale stratospheric circulation of these giant planets?) motivated us to develop a complete 3D General Circulation Model (GCM) of Saturn and Jupiter. We aim at exploring the large-scale circulation, seasonal variability, and wave activity from the troposphere to the stratosphere of these giant planets. We will briefly present how we adapted our existing Saturn GCM to Jupiter. One of the main change is the addition of a stratospheric haze layer made of fractal aggregates in the auroral regions (poleward of 45S and 30N). This haze layer has a significant radiative impact by modifying the temperature up to +/- 15K in the middle stratosphere. We will then describe the results of radiative-convective simulations and how they compare to recent Cassini and ground-based temperature measurements. These simulations reproduce surprisingly well some of the observed thermal vertical and meridional gradients, but several important mismatches at low and high latitudes suggest that dynamics also plays an important role in shaping the temperature field. Finally, we will present full GCM simulations and discuss the main resulting features (waves and instabilities). We will also and discuss the impact of the choice of spatial resolution and
Macroscopic model for solvated ion dynamics
NASA Astrophysics Data System (ADS)
Chen, J.-H.; Adelman, S. A.
1980-02-01
A macroscopic treatment of solvated ion dynamics is developed and applied to calculate the limiting (zero concentration) conductance of cations in several aprotic solvents. The theory is based on a coupled set of electrostatic and hydrodynamic equations for the density, flow, and polarization fields induced in the polar solvent by a moving ion. These equations, which are derived by the Mori projection technique, include crucial local solvent structure (ion solvation) effects through solvent compressibility, and local constitutive parameters. If solvent structure is suppressed, the equations reduce to those derived previously by Onsager and Hubbard [J. B. Hubbard and L. Onsager, J. Chem. Phys. 67, 4850 (1977)]. The macroscopic equations are approximately decoupled into electrostatic and hydrodynamic parts. The decoupled equations are solved assuming a step density, viscosity, and dielectric constant model for the local solvent structure and dynamics. This yields analytic expressions for the viscous, ζV, and dielectric ζD, contributions to the ion friction coefficient. These expressions generalize, respectively, the Stokes and Zwanzig results for the (slip) viscous and dielectric friction so as to account for ion solvation effects. The friction coefficients involve a desolvation function Δ which depends on the local structure (density) and dynamics of the solvent. The drag coefficient results reduce in form to those of Zwanzig (within a flow gradient correction factor of 2/3) and Stokes for both weak (Δ→1) and strong (Δ→0) ion-solvent interaction. For Δ→1 the true ionic radius Ri appears in the drag formulas while for Δ→0 a renormalized solvated ion radius σ=Ri+2Rs (where Rs=solvent molecule radius) appears. The theory is fit to experimental cation conductances in pyridine, acetone, and acetonitrile by representing Δ by a two parameter switching function. Agreement between the model and experiment is satisfactory for all three solvents. Moreover
Microscopic model for ultrafast remagnetization dynamics.
Chimata, Raghuveer; Bergman, Anders; Bergqvist, Lars; Sanyal, Biplab; Eriksson, Olle
2012-10-12
In this Letter, we provide a microscopic model for the ultrafast remagnetization of atomic moments already quenched above the Stoner-Curie temperature by a strong laser fluence. Combining first-principles density functional theory, atomistic spin dynamics utilizing the Landau-Lifshitz-Gilbert equation, and a three-temperature model, we analyze the temporal evolution of atomic moments as well as the macroscopic magnetization of bcc Fe and hcp Co covering a broad time scale, ranging from femtoseconds to picoseconds. Our simulations show a variety of complex temporal behavior of the magnetic properties resulting from an interplay between electron, spin, and lattice subsystems, which causes an intricate time evolution of the atomic moment, where longitudinal and transversal fluctuations result in a macrospin moment that evolves highly nonmonotonically.
Modeling correlated human dynamics with temporal preference
NASA Astrophysics Data System (ADS)
Wang, Peng; Zhou, Tao; Han, Xiao-Pu; Wang, Bing-Hong
2014-03-01
We empirically study the activity pattern of individual blog-posting and observe the interevent time distributions decay as power-laws at both individual and population level. As different from previous studies, we find significant short-term memory in it. Moreover, the memory coefficient first decays in a power law and then turns to an exponential form. Our findings produce evidence for the strong short-term memory in human dynamics and challenge previous models. Accordingly, we propose a simple model based on temporal preference, which can well reproduce both the heavy-tailed nature and the strong memory effects. This work helps in understanding the temporal regularities of online human behaviors.
A model of anomalous chain translocation dynamics.
Chaudhury, Srabanti; Cherayil, Binny J
2008-12-18
A model of polymer translocation based on the stochastic dynamics of the number of monomers on one side of a pore-containing surface is formulated in terms of a one-dimensional generalized Langevin equation, in which the random force is assumed to be characterized by long-ranged temporal correlations. The model is introduced to rationalize anomalies in measured and simulated values of the average time of passage through the pore, which in general cannot be satisfactorily accounted for by simple Brownian diffusion mechanisms. Calculations are presented of the mean first passage time for barrier crossing and of the mean square displacement of a monomeric segment, in the limits of strong and weak diffusive bias. The calculations produce estimates of the exponents in various scaling relations that are in satisfactory agreement with available data.
Dynamic modelling of packaging material flow systems.
Tsiliyannis, Christos A
2005-04-01
A dynamic model has been developed for reused and recycled packaging material flows. It allows a rigorous description of the flows and stocks during the transition to new targets imposed by legislation, product demand variations or even by variations in consumer discard behaviour. Given the annual reuse and recycle frequency and packaging lifetime, the model determines all packaging flows (e.g., consumption and reuse) and variables through which environmental policy is formulated, such as recycling, waste and reuse rates and it identifies the minimum number of variables to be surveyed for complete packaging flow monitoring. Simulation of the transition to the new flow conditions is given for flows of packaging materials in Greece, based on 1995--1998 field inventory and statistical data.
Modeling quantum fluid dynamics at nonzero temperatures
Berloff, Natalia G.; Brachet, Marc; Proukakis, Nick P.
2014-01-01
The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluid model is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures. PMID:24704874
Microscopic to Macroscopic Dynamical Models of Sociality
NASA Astrophysics Data System (ADS)
Solis Salas, Citlali; Woolley, Thomas; Pearce, Eiluned; Dunbar, Robin; Maini, Philip; Social; Evolutionary Neuroscience Research Group (Senrg) Collaboration
To help them survive, social animals, such as humans, need to share knowledge and responsibilities with other members of the species. The larger their social network, the bigger the pool of knowledge available to them. Since time is a limited resource, a way of optimising its use is meeting amongst individuals whilst fulfilling other necessities. In this sense it is useful to know how many, and how often, early humans could meet during a given period of time whilst performing other necessary tasks, such as food gathering. Using a simplified model of these dynamics, which comprehend encounter and memory, we aim at producing a lower-bound to the number of meetings hunter-gatherers could have during a year. We compare the stochastic agent-based model to its mean-field approximation and explore some of the features necessary for the difference between low population dynamics and its continuum limit. We observe an emergent property that could have an inference in the layered structure seen in each person's social organisation. This could give some insight into hunter-gatherer's lives and the development of the social layered structure we have today. With support from the Mexican Council for Science and Technology (CONACyT), the Public Education Secretariat (SEP), and the Mexican National Autonomous University's Foundation (Fundacion UNAM).
Dynamics of Fst for the island model.
Rottenstreich, Sivan; Hamilton, Matthew B; Miller, Judith R
2007-12-01
F(st) is a measure of genetic differentiation in a subdivided population. Sewall Wright observed that F(st)=1/1+2Nm in a haploid diallelic infinite island model, where N is the effective population size of each deme and m is the migration rate. In demonstrating this result, Wright relied on the infinite size of the population. Natural populations are not infinite and therefore they change over time due to genetic drift. In a finite population, F(st) becomes a random variable that evolves over time. In this work we ask, given an initial population state, what are the dynamics of the mean and variance of F(st) under the finite island model? In application both of these quantities are critical in the evaluation of F(st) data. We show that after a time of order N generations the mean of F(st) is slightly biased below 1/1+2Nm. Further we show that the variance of F(st) is of order 1/d where d is the number of demes in the population. We introduce several new mathematical techniques to analyze coalescent genealogies in a dynamic setting.
Modeling habitat dynamics accounting for possible misclassification
Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.
2012-01-01
Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.
Aggregate Dynamics in AN Evolutionary Network Model
NASA Astrophysics Data System (ADS)
Seufert, Adrian M.; Schweitzer, Frank
We analyze a model of interacting agents (e.g. prebiotic chemical species) which are represented by nodes of a network, whereas their interactions are mapped onto directed links between these nodes. On a fast time scale, each agent follows an eigendynamics based on catalytic support from other nodes, whereas on a much slower time scale the network evolves through selection and mutation of its nodes-agent. In the first part of the paper, we explain the dynamics of the model by means of characteristic snapshots of the network evolution and confirm earlier findings on crashes and recoveries in the network structure. In the second part, we focus on the aggregate behavior of the network dynamics. We show that the disruptions in the network structure are smoothed out, so that the average evolution can be described by a growth regime followed by a saturation regime, without an initial random regime. For the saturation regime, we obtain a logarithmic scaling between the average connectivity per node
Dynamic models of lateritic bauxite formation
NASA Astrophysics Data System (ADS)
Zhukov, V. V.; Bogatyrev, B. A.
2012-09-01
2D dynamic models of bauxite formation in the weathering mantle covering denudation areas drained by river systems are discussed. The role of relief-forming factors (tectonic uplift, river erosion and denudation of drainage divides), the interrelation of hydrogeological and lithologic structure of the bauxitebearing weathering mantle, and the dynamics of zoning formation above and below groundwater level are described in the models. Creative and destructive epochs of lateritic bauxite formation differing in tectonic regime are distinguished. During the creative epochs, lateritic weathering develops against a background of decreasing denudation and an increase in areas of bauxite formation. The destructive epochs are characterized by intense denudation, cutting down the areas of lateritic bauxite formation and eventually leading to the complete removal of the weathering mantle. Different morphogenetic types and varieties of bauxite-bearing weathering mantles develop during creative and destructive epochs. The morphology of the weathering mantle sections at the deposits of Cenozoic lateritic bauxite in the present-day tropical zone of the Earth corresponds to the destructive epoch, which is characterized by declining areas of lateritic bauxite formation and will end with complete denudation of lateritic bauxite.
Dynamic publication model for neurophysiology databases.
Gardner, D; Abato, M; Knuth, K H; DeBellis, R; Erde, S M
2001-08-29
We have implemented a pair of database projects, one serving cortical electrophysiology and the other invertebrate neurones and recordings. The design for each combines aspects of two proven schemes for information interchange. The journal article metaphor determined the type, scope, organization and quantity of data to comprise each submission. Sequence databases encouraged intuitive tools for data viewing, capture, and direct submission by authors. Neurophysiology required transcending these models with new datatypes. Time-series, histogram and bivariate datatypes, including illustration-like wrappers, were selected by their utility to the community of investigators. As interpretation of neurophysiological recordings depends on context supplied by metadata attributes, searches are via visual interfaces to sets of controlled-vocabulary metadata trees. Neurones, for example, can be specified by metadata describing functional and anatomical characteristics. Permanence is advanced by data model and data formats largely independent of contemporary technology or implementation, including Java and the XML standard. All user tools, including dynamic data viewers that serve as a virtual oscilloscope, are Java-based, free, multiplatform, and distributed by our application servers to any contemporary networked computer. Copyright is retained by submitters; viewer displays are dynamic and do not violate copyright of related journal figures. Panels of neurophysiologists view and test schemas and tools, enhancing community support.
Dynamic Elasticity Model of Resilin Biopolymers
NASA Astrophysics Data System (ADS)
Hu, Xiao; Duki, Solomon
2013-03-01
Resilin proteins are `super elastic rubbers' in the flight and jumping systems of most insects, and can extend and retract millions of times. Natural resilin exhibits high resilience (> 95%) under high-frequency conditions, and could be stretched to over 300% of its original length with a low elastic modulus of 0.1-3 MPa. However, insight into the underlying molecular mechanisms responsible for resilin elasticity remains undefined. We report on the dynamic structure transitions and functions of full length resilin from fruit fly (D. melanogaster CG15920) and its different functional domains. A dynamic computational model is proposed to explain the super elasticity and energy conversion mechanisms of resilin, providing important insight into structure-function relationships for resilins, as well as other elastomeric proteins. A strong beta-turn transition was experimentally identified in the full length resilin and its non-elastic domains (Exon III). Changes in periodic long-range order were demonstrated during this transition, induced either by thermal or mechanical inputs, to confirm the universality of proposed mechanism. Further, this model offers new options for designing protein-based biopolymers with tunable material applications.
Modeling quantum fluid dynamics at nonzero temperatures.
Berloff, Natalia G; Brachet, Marc; Proukakis, Nick P
2014-03-25
The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluid model is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures.
Modeling Insurgent Network Structure and Dynamics
NASA Astrophysics Data System (ADS)
Gabbay, Michael; Thirkill-Mackelprang, Ashley
2010-03-01
We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.
Computational Fluid Dynamics Modeling of Bacillus anthracis ...
Journal Article Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived from computed tomography (CT) or µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. Four different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Despite the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the upper conducting airways of the human at the same air concentration of anthrax spores. This greater deposition of spores in the upper airways in the human resulted in lower penetration and deposition in the tracheobronchial airways and the deep lung than that predict
Coordinated supply chain dynamic production planning model
NASA Astrophysics Data System (ADS)
Chandra, Charu; Grabis, Janis
2001-10-01
Coordination of different and often contradicting interests of individual supply chain members is one of the important issues in supply chain management because the individual members can not succeed without success of the supply chain and vice versa. This paper investigates a supply chain dynamic production planning problem with emphasis on coordination. A planning problem is formally described using a supply chain kernel, which defines supply chain configuration, management policies, available resources and objectives both at supply chain or macro and supply chain member or micro levels. The coordinated model is solved in order to balance decisions made at the macro and micro levels and members' profitability is used as the coordination criterion. The coordinated model is used to determine inventory levels and production capacity across the supply chain. Application of the coordinated model distributes costs burden uniformly among supply chain members and preserves overall efficiency of the supply chain. Influence of the demand series uncertainty is investigated. The production planning model is a part of the integrated supply chain decision modeling system, which is shared among the supply chain members across the Internet.
Computational Fluid Dynamics Modeling of Bacillus anthracis ...
Journal Article Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived from computed tomography (CT) or µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. Four different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Despite the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the upper conducting airways of the human at the same air concentration of anthrax spores. This greater deposition of spores in the upper airways in the human resulted in lower penetration and deposition in the tracheobronchial airways and the deep lung than that predict
Highly Efficient Modeling of Dynamic Coronal Loops
NASA Astrophysics Data System (ADS)
Klimchuk, J. A.; Patsourakos, S.; Cargill, P. J.
2005-05-01
It now seems clear that many coronal loops, especially those observed by TRACE and EIT, are inherently dynamic and composed of large numbers of impulsively-heated strands. Modeling these loops in full detail is extremely challenging, and modeling entire active regions or the whole Sun is completely out of the question unless approximate techniques are used. We have developed a simplified set of equations that is remarkably accurate at describing the evolution of the thermodynamic variables (T, P, n, v) averaged along the magnetic field of an individual strand. The equations can be solved ten thousand times more quickly than the full 1D hydro equations. This "0D" model relaxes two key assumptions of Cargill's (1994) nanoflare model: (1) the heating can have any time-dependent profile and need not be instantaneous; and (2) thermal conduction cooling and radiation cooling occur together at all times, in varying proportions. We here describe the essential features of the model and show examples of how well it works.
Multi-Scale Modeling of Magnetospheric Dynamics
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Toth, G.
2012-01-01
Magnetic reconnection is a key element in many phenomena in space plasma, e.g. Coronal mass Ejections, Magnetosphere substorms. One of the major challenges in modeling the dynamics of large-scale systems involving magnetic reconnection is to quantifY the interaction between global evolution of the magnetosphere and microphysical kinetic processes in diffusion regions near reconnection sites. Recent advances in small-scale kinetic modeling of magnetic reconnection significantly improved our understanding of physical mechanisms controlling the dissipation in the vicinity of the reconnection site in collisionless plasma. However the progress in studies of small-scale geometries was not very helpful for large scale simulations. Global magnetosphere simulations usually include non-ideal processes in terms of numerical dissipation and/or ad hoc anomalous resistivity. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term 11 J did not produce fast reconnection rates observed in kinetic simulations. In collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is nongyrotropic pressure effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and replace ad hoc parameters such as "critical current density" and "anomalous resistivity" with a physically motivated model of dissipation. The primary mechanism controlling the dissipation in the vicinity of the reconnection site in incorporated into MHD description in terms of non-gyrotropic corrections to the induction equation. We will demonstrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution. Our approach allowed for the first time to model loading/unloading cycle in response to steady southward IMF driving. The role of solar wind parameters and
Dynamical Models of Terrestrial Planet Formation
NASA Astrophysics Data System (ADS)
Lunine, Jonathan I.; O'brien, David P.; Raymond, Sean N.; Morbidelli, Alessandro; Quinn, Thomas; Graps, Amara L.
2011-02-01
We review the problem of the formation of terrestrial planets, with particular emphasis on the interaction of dynamical and geochemical models. The lifetime of gas around stars in the process of formation is limited to a few million years based on astronomical observations, while isotopic dating of meteorites and the Earth-Moon system suggest that perhaps 50-100 million years were required for the assembly of the Earth. Therefore, much of the growth of the terrestrial planets in our own system is presumed to have taken place under largely gas-free conditions, and the physics of terrestrial planet formation is dominated by gravitational interactions and collisions. The earliest phase of terrestrial-planet formation involve the growth of km-sized or larger planetesimals from dust grains, followed by the accumulations of these planetesimals into ∼100 lunar- to Mars-mass bodies that are initially gravitationally isolated from one-another in a swarm of smaller planetesimals, but eventually grow to the point of significantly perturbing one-another. The mutual perturbations between the embryos, combined with gravitational stirring by Jupiter, lead to orbital crossings and collisions that drive the growth to Earth-sized planets on a timescale of 107-108 years. Numerical treatment of this process has focussed on the use of symplectic integrators which can rapidy integrate the thousands of gravitationally-interacting bodies necessary to accurately model planetary growth. While the general nature of the terrestrial planets-their sizes and orbital parameters-seem to be broadly reproduced by the models, there are still some outstanding dynamical issues. One of these is the presence of an embryo-sized body, Mars, in our system in place of the more massive objects that simulations tend to yield. Another is the effect such impacts have on the geochemistry of the growing planets; re-equilibration of isotopic ratios of major elements during giant impacts (for example) must be
A two-stage dynamic model for visual tracking.
Kristan, Matej; Kovacic, Stanislav; Leonardis, Aleš; Pers, Janez
2010-12-01
We propose a new dynamic model which can be used within blob trackers to track the target's center of gravity. A strong point of the model is that it is designed to track a variety of motions which are usually encountered in applications such as pedestrian tracking, hand tracking, and sports. We call the dynamic model a two-stage dynamic model due to its particular structure, which is a composition of two models: a liberal model and a conservative model. The liberal model allows larger perturbations in the target's dynamics and is able to account for motions in between the random-walk dynamics and the nearly constant-velocity dynamics. On the other hand, the conservative model assumes smaller perturbations and is used to further constrain the liberal model to the target's current dynamics. We implement the two-stage dynamic model in a two-stage probabilistic tracker based on the particle filter and apply it to two separate examples of blob tracking: 1) tracking entire persons and 2) tracking of a person's hands. Experiments show that, in comparison to the widely used models, the proposed two-stage dynamic model allows tracking with smaller number of particles in the particle filter (e.g., 25 particles), while achieving smaller errors in the state estimation and a smaller failure rate. The results suggest that the improved performance comes from the model's ability to actively adapt to the target's motion during tracking.
Dynamic thermodiffusion model for binary liquid mixtures
NASA Astrophysics Data System (ADS)
Eslamian, Morteza; Saghir, M. Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring’s reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, The Theory of Rate Processes: The Kinetics of Chemical Reactions, Viscosity, Diffusion and Electrochemical Phenomena (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models.
Dynamic thermodiffusion model for binary liquid mixtures.
Eslamian, Morteza; Saghir, M Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring's reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models.
A simple dynamic model of respiratory pump.
Calabrese, Pascale; Baconnier, Pierre; Laouani, Aicha; Fontecave-Jallon, Julie; Guméry, Pierre-Yves; Eberhard, André; Benchetrit, Gila
2010-09-01
To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane (J Appl Physiol 63(3):951-961, 1987) and introduce some dynamic properties of the respiratory system. The passive elements (rib cage and abdomen) are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles (active) force is applied to both compartments. Parameters of the model are identified in using experimental data of airflow signal measured by pneumotachography and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R(2) > or = 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing.
A Dynamic Fountain Model for Lunar Dust
NASA Technical Reports Server (NTRS)
Stubbs, T. J.; Vondrak, R. R.; Farrell, W. M.
2005-01-01
During the Apollo era of exploration it was discovered that sunlight was scattered at the terminators giving rise to horizon glow and streamers above the lunar surface. This was observed from the dark side of the Moon during sunset and sunrise by both surface landers and astronauts in orbit. These observations were quite unexpected, as the Moon was thought to be a pristine environment with a negligible atmosphere or exosphere. Subsequent investigations have shown that the sunlight was most likely scattered by electrostatically charged dust grains originating from the surface. It has since been demonstrated that this dust population could have serious implications for astronomical observations from the lunar surface. The lunar surface is electrostatically charged by the Moon s large-scale interaction with the local plasma environment and the photoemission of electrons due to solar ultra-violet (UV) light and X-rays. The like-charged surface and dust grains then act to repel each other, such that under certain conditions the dust grains are lifted above the surface. We present a dynamic fountain model which can explain how sub-micron dust is able to reach altitudes of up to approximately 100 km above the lunar surface. Previous static dust levitation models are most applicable to the heavier micron-sized grains in close proximity proximity to the surface, but they cannot explain the presence of extremely light grains at high altitudes. If we relax the static constraint applied to previous models, and instead assume that the grains are in constant motion (under the action of dynamic forces), a new picture emerges for the behavior of sub-micron lunar dust.
Computational modeling of intraocular gas dynamics
NASA Astrophysics Data System (ADS)
Noohi, P.; Abdekhodaie, M. J.; Cheng, Y. L.
2015-12-01
The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency.
Computational modeling of intraocular gas dynamics.
Noohi, P; Abdekhodaie, M J; Cheng, Y L
2015-12-18
The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency.
Dynamic hysteresis modeling including skin effect using diffusion equation model
NASA Astrophysics Data System (ADS)
Hamada, Souad; Louai, Fatima Zohra; Nait-Said, Nasreddine; Benabou, Abdelkader
2016-07-01
An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.
A nonlinear dynamic analogue model of substorms
NASA Astrophysics Data System (ADS)
Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Büchner, J.
Linear prediction filter studies have shown that the magnetospheric response to energy transfer from the solar wind contains both directly driven and unloading components. These studies have also shown that the magnetospheric response is significantly nonlinear and, thus, the linear prediction filtering technique and other correlative techniques which assume a linear magnetospheric response cannot give a complete deacription of that response. Here, the solar wind-magnetosphere interaction is discussed within the framework of deterministic nonlinear dynamics. An earlier dripping faucet mechanical analogue to the magnetosphere is first reviewed and then the plasma physical counterpart to the mechanical model is constructed. A Faraday loop in the magnetotail is considered and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. This Faraday loop response model contains analogues to both the directly driven and the storage-release magnetospheric responses and it includes, in a fundamental way, the inherent nonlinearity of the solar wind-magnetosphere system. It can be chancterized as a nonlinear, damped harmonic oscillator that is driven by the loading-unloading substorm cycle. The model is able to explain many of the features of the linear prediction filter results. In particular, at low geomagnetic activity levels the model exbibits the "regular dripping" response which provides an explanation for the unloading component at 1 hour lag in the linear prediction filters. Further, the model suggests that the disappearance of the unloading component in the linear prediction filters at high geomagnetic activity levels is due to a chaotic transition beyond which the loading-unloading mechanism becomes aperiodic. The model predicts
Modeling boreal fire and forest dynamics
NASA Astrophysics Data System (ADS)
de Groot, W. J.; McRae, D. J.; Cantin, A.
2009-04-01
The circumpolar boreal forest covers about 1.4 billion ha, representing 1/3 of global forest land. Approximately 2/3 of the boreal forest is located in Eurasia and the remainder in North America. Wildland fires annually burn an estimated 12-20 M ha across the entire boreal region, having a major influence on forest structure and composition. However, fire weather, fire behaviour, and fire ecology differ greatly between the boreal forests in eastern and western hemispheres, which have significant impact on tree survival, post-fire regeneration and forest succession. Every year, wildland fires in Canada and Alaska burn an average of 2-3 M ha, primarily by stand-replacing, high intensity crown fires. By comparison, Russian fires burn about 10-15 M ha annually, primarily by low to moderate intensity surface fires that cause minimal tree mortality. Fire weather conditions in the most fire prone regions of Russia are generally more severe than in similar regions of North America. Finally, the species composition of eastern and western boreal forests is also very different. Russian forests are dominated by larch (30%) and pine (28%) with lower components of spruce (14%) and poplar/birch hardwoods (18%) By contrast, Canadian forests are comprised mainly of spruce (35%), pine (22%), poplar/birch (16%), and fir (9%). All of these factors contribute to the variability in vegetation dynamics occurring within the circumpolar boreal region. This modeling study examines the interactions of fire weather, forest composition, fire behaviour, and fire ecology on forest vegetation dynamics within the boreal region. Similar active fire zones in western Canada and eastern Siberia were used as study sites. Historical weather data were collected for both locations and used to calculate fire weather data, which were used as primary driving variables for the Boreal Fire Effects model (BORFIRE). Fire behaviour was calculated in BORFIRE using data for major tree species at both study sites
Modelling Holocene peatland dynamics with an individual-based dynamic vegetation model
NASA Astrophysics Data System (ADS)
Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin
2017-05-01
Dynamic global vegetation models (DGVMs) are designed for the study of past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks. However, most DGVMs do not yet have detailed representations of permafrost and non-permafrost peatlands, which are an important store of carbon, particularly at high latitudes. We demonstrate a new implementation of peatland dynamics in a customized Arctic
version of the LPJ-GUESS DGVM, simulating the long-term evolution of selected northern peatland ecosystems and assessing the effect of changing climate on peatland carbon balance. Our approach employs a dynamic multi-layer soil with representation of freeze-thaw processes and litter inputs from a dynamically varying mixture of the main peatland plant functional types: mosses, shrubs and graminoids. The model was calibrated and tested for a sub-Arctic mire in Stordalen, Sweden, and validated at a temperate bog site in Mer Bleue, Canada. A regional evaluation of simulated carbon fluxes, hydrology and vegetation dynamics encompassed additional locations spread across Scandinavia. Simulated peat accumulation was found to be generally consistent with published data and the model was able to capture reported long-term vegetation dynamics, water table position and carbon fluxes. A series of sensitivity experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We found that the Stordalen mire may be expected to sequester more carbon in the first half of the 21st century due to milder and wetter climate conditions, a longer growing season, and the CO2 fertilization effect, turning into a carbon source after mid-century because of higher decomposition rates in response to warming soils.
Bio-Inspired Neural Model for Learning Dynamic Models
NASA Technical Reports Server (NTRS)
Duong, Tuan; Duong, Vu; Suri, Ronald
2009-01-01
A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.
Analytic wave model of Stark deceleration dynamics
Gubbels, Koos; Meijer, Gerard; Friedrich, Bretislav
2006-06-15
Stark deceleration relies on time-dependent inhomogeneous electric fields which repetitively exert a decelerating force on polar molecules. Fourier analysis reveals that such fields, generated by an array of field stages, consist of a superposition of partial waves with well-defined phase velocities. Molecules whose velocities come close to the phase velocity of a given wave get a ride from that wave. For a square-wave temporal dependence of the Stark field, the phase velocities of the waves are found to be odd-fraction multiples of a fundamental phase velocity {lambda}/{tau}, with {lambda} and {tau} the spatial and temporal periods of the field. Here we study explicitly the dynamics due to any of the waves as well as due to their mutual perturbations. We first solve the equations of motion for the case of single-wave interactions and exploit their isomorphism with those for the biased pendulum. Next we analyze the perturbations of the single-wave dynamics by other waves and find that these have no net effect on the phase stability of the acceleration or deceleration process. Finally, we find that a packet of molecules can also ride a wave which results from an interference of adjacent waves. In this case, small phase stability areas form around phase velocities that are even-fraction multiples of the fundamental velocity. A detailed comparison with classical trajectory simulations and with experiment demonstrates that the analytic 'wave model' encompasses all the longitudinal physics encountered in a Stark decelerator.
Modelling of the Pele Fragmentation Dynamics
NASA Astrophysics Data System (ADS)
Verreault, Jimmy
2013-06-01
The Penetrator with Enhanced Lateral Effect (PELE) is a type of explosive-free projectile that undergoes radial fragmentation upon an impact with a target plate. This type of projectile is composed of a brittle cylindrical shell (the jacket) filled in its core with a material characterized with a large Poisson's ratio. Upon an impact with a target, the axial compression causes the filling to expand in the radial direction. However, due to the brittleness of the jacket material, very little radial deformation can occur which creates a radial stress between the two materials and a hoop stress in the jacket. Fragmentation of the jacket occurs if the hoop stress exceeds the material's ultimate stress. The PELE fragmentation dynamics is explored via Finite-Element Method (FEM) simulations using the AUTODYN explicit dynamics hydrocode. The numerical results are compared with an analytical model based on wave interactions, as well as with the experimental investigation of Paulus and Schirm (1996). The comparison is based on the mechanical stress in the filling, the resulting radial velocity of the fragments, the number of fragments generated and their mass distribution.
Modelling of the PELE fragmentation dynamics
NASA Astrophysics Data System (ADS)
Verreault, J.
2014-05-01
The Penetrator with Enhanced Lateral Effect (PELE) is a type of explosive-free projectile that undergoes radial fragmentation upon an impact with a target plate. This type of projectile is composed of a brittle cylindrical shell (the jacket) filled in its core with a material characterized with a large Poisson's ratio. Upon an impact with a target, the axial compression causes the filling to expand in the radial direction. However, due to the brittleness of the jacket material, very little radial deformation can occur which creates a radial stress between the two materials and a hoop stress in the jacket. Fragmentation of the jacket occurs if the hoop stress exceeds the material's ultimate stress. The PELE fragmentation dynamics is explored via Finite-Element Method (FEM) simulations using the Autodyn explicit dynamics hydrocode. The numerical results are compared with an analytical model based on wave interactions, as well as with the experimental investigation of Paulus and Schirm (1996). The comparison is based on the mechanical stress in the filling and the qualitative fragmentation of the jacket.
Molecular modelling and molecular dynamics of CFTR.
Callebaut, Isabelle; Hoffmann, Brice; Lehn, Pierre; Mornon, Jean-Paul
2017-01-01
The cystic fibrosis transmembrane conductance regulator (CFTR) protein is a member of the ATP-binding cassette (ABC) transporter superfamily that functions as an ATP-gated channel. Considerable progress has been made over the last years in the understanding of the molecular basis of the CFTR functions, as well as dysfunctions causing the common genetic disease cystic fibrosis (CF). This review provides a global overview of the theoretical studies that have been performed so far, especially molecular modelling and molecular dynamics (MD) simulations. A special emphasis is placed on the CFTR-specific evolution of an ABC transporter framework towards a channel function, as well as on the understanding of the effects of disease-causing mutations and their specific modulation. This in silico work should help structure-based drug discovery and design, with a view to develop CFTR-specific pharmacotherapeutic approaches for the treatment of CF in the context of precision medicine.
Vortex dynamics in nonrelativistic Abelian Higgs model
NASA Astrophysics Data System (ADS)
Kozhevnikov, A. A.
2015-11-01
The dynamics of the gauge vortex with arbitrary form of a contour is considered in the framework of the nonrelativistic Abelian Higgs model, including the possibility of the gauge field interaction with the fermion asymmetric background. The equations for the time derivatives of the curvature and the torsion of the vortex contour generalizing the Betchov-Da Rios equations in hydrodynamics, are obtained. They are applied to study the conservation of helicity of the gauge field forming the vortex, twist, and writhe numbers of the vortex contour. It is shown that the conservation of helicity is broken when both terms in the equation of the vortex motion are present, the first due to the exchange of excitations of the phase and modulus of the scalar field and the second one due to the coupling of the gauge field forming the vortex, with the fermion asymmetric background.
Nonlinear dynamical model of human gait
NASA Astrophysics Data System (ADS)
West, Bruce J.; Scafetta, Nicola
2003-05-01
We present a nonlinear dynamical model of the human gait control system in a variety of gait regimes. The stride-interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations becomes more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. Human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way.
Dynamic model of flexible phytoplankton nutrient uptake
Bonachela, Juan A.; Raghib, Michael; Levin, Simon A.
2011-01-01
The metabolic machinery of marine microbes can be remarkably plastic, allowing organisms to persist under extreme nutrient limitation. With some exceptions, most theoretical approaches to nutrient uptake in phytoplankton are largely dominated by the classic Michaelis–Menten (MM) uptake functional form, whose constant parameters cannot account for the observed plasticity in the uptake apparatus. Following seminal ideas by earlier researchers, we propose a simple cell-level model based on a dynamic view of the uptake process whereby the cell can regulate the synthesis of uptake proteins in response to changes in both internal and external nutrient concentrations. In our flexible approach, the maximum uptake rate and nutrient affinity increase monotonically as the external nutrient concentration decreases. For low to medium nutrient availability, our model predicts uptake and growth rates larger than the classic MM counterparts, while matching the classic MM results for large nutrient concentrations. These results have important consequences for global coupled models of ocean circulation and biogeochemistry, which lack this regulatory mechanism and are thus likely to underestimate phytoplankton abundances and growth rates in oligotrophic regions of the ocean. PMID:22143781
Persistent agents in Axelrod's social dynamics model
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Neves, Ubiraci P. C.
2016-01-01
Axelrod's model of social dynamics has been studied under the effect of external media. Here we study the formation of cultural domains in the model by introducing persistent agents. These are agents whose cultural traits are not allowed to change but may be spread through local neighborhood. In the absence of persistent agents, the system is known to present a transition from a monocultural to a multicultural regime at some critical Q (number of traits). Our results reveal a dependence of critical Q on the occupation probability p of persistent agents and we obtain the phase diagram of the model in the (p,Q) -plane. The critical locus is explained by the competition of two opposite forces named here barrier and bonding effects. Such forces are verified to be caused by non-persistent agents which adhere (adherent agents) to the set of traits of persistent ones. The adherence (concentration of adherent agents) as a function of p is found to decay for constant Q. Furthermore, adherence as a function of Q is found to decay as a power law with constant p.
Modeling the dynamics of piano keys
NASA Astrophysics Data System (ADS)
Brenon, Celine; Boutillon, Xavier
2003-10-01
The models of piano keys available in the literature are crude: two degrees of freedom and a very few dynamical or geometrical parameters. Experiments on different piano mechanisms (upright, grand, one type of numerical keyboard) exhibit strong differences in the two successive phases of the key motion which are controlled by the finger. Understanding the controllability of the escapement velocity (typically a few percents for professional pianists), the differences between upright and grand pianos, the rationale for the numerous independent adjustments by technicians, and the feel by the pianist require sophisticated modeling. In addition to the inertia of the six independently moving parts of a grand piano mechanism, a careful modeling of friction at pivots and between the jack and the roll, of damping and nonlinearities in felts, and of internal springs will be presented. Simulations will be confronted to the measurements of the motions of the different parts. Currently, the first phase of the motion and the transition to the second phase are well understood while some progress must still be made in order to describe correctly this short but important phase before the escapement of the hammer. [Work done in part at the Laboratory for Musical Acoustics, Paris.
CIDGA - Coupling of Interior Dynamic models with Global Atmosphere models
NASA Astrophysics Data System (ADS)
Noack, Lena; Plesa, Ana-Catalina; Breuer, Doris
2010-05-01
Atmosphere temperatures and in particular the surface temperatures mostly depend on the solar heat flux and the atmospheric composition. The latter can be influenced by interior processes of the planet, i.e. volcanism that releases greenhouse gases such as H2O, CO2 and methane into the atmosphere and plate tectonics through which atmospheric CO2 is recycled via carbonates into the mantle. An increasing concentration of greenhouse gases in the atmosphere results in an increase of the surface temperature. Changes in the surface temperature on the other hand may influence the cooling behaviour of the planet and hence influence its volcanic activity [Phillips et al., 2001]. This feedback relation between mantle convection and atmosphere is not very well understood, since until now mostly either the interior dynamic of a planet or its atmosphere was investigated separately. 2D or 3D mantle convection models to the authors' knowledge haven't been coupled to the atmosphere so far. We have used the 3D spherical simulation code GAIA [Hüttig et al., 2008] including partial melt production and coupled it with the atmosphere module CIDGA using a gray greenhouse model for varying H2O concentrations. This way, not only the influence of mantle dynamics on the atmosphere can be investigated, but also the recoupling effect, that the surface temperature has on the mantle dynamics. So far, we consider one-plate planets without crustal and thus volatile recycling. Phillips et al. [2001] already investigated the coupling effect of the surface temperature on mantle dynamics by using simple parameterized convection models for Venus. In their model a positive feedback mechanism has been observed, i.e., an increase of the surface temperature leads to an increase of partial melt and hence an increase of atmosphere density and surface temperature. Applying our model to Venus, we show that an increase of surface temperature leads not only to an increase of partial melt in the mantle; it also
A dynamic model of reasoning and memory.
Hawkins, Guy E; Hayes, Brett K; Heit, Evan
2016-02-01
Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data.
Dynamic models in research and management of biological invasions.
Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R
2017-03-25
Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.
Kinematical and Dynamical Modeling of Elliptical Galaxies
NASA Astrophysics Data System (ADS)
Mamon, G. A.; Łokas, E.; Dekel, A.; Stoehr, F.; Cox, T. J.
Elements of kinematical and dynamical modeling of elliptical galaxies are presented. In projection, NFW models resemble Sérsic models, but with a very narrow range of shapes (m=3±1). The total density profile of ellipticals cannot be NFW-like because the predicted local M/L and aperture velocity dispersion within an effective radius (R_e) are much lower than observed. Stars must then dominate ellipticals out to a few R_e. Fitting an NFW model to the total density profile of Sérsic+NFW (stars+dark matter [DM]) ellipticals results in very high concentration parameters, as found by X-ray observers. Kinematical modeling of ellipticals assuming an isotropic NFW DM model underestimates M/L at the virial radius by a factor of 1.6 to 2.4, because dissipationless ΛCDM halos have slightly different density profiles and slightly radial velocity anisotropy. In N-body+gas simulations of ellipticals as merger remnants of spirals embedded in DM halos, the slope of the DM density profile is steeper when the initial spiral galaxies are gas-rich. The Hansen & Moore (2006) relation between anisotropy and the slope of the density profile breaks down for gas and DM, but the stars follow an analogous relation with slightly less radial anisotropies for a given density slope. Using kurtosis (h_4) to infer anisotropy in ellipticals is dangerous, as h4 is also sensitive to small levels of rotation. The stationary Jeans equation provides accurate masses out to 8 R_e. The discrepancy between the modeling of Romanowsky et al. (2003), indicating a dearth of DM in ellipticals, and the simulations analyzed by Dekel et al. (2005), which match the spectroscopic observations of ellipticals, is partly due to radial anisotropy and to observing oblate ellipticals face-on. However, one of the 15 solutions to the orbit modeling of Romanowsky et al. is found to have an amount and concentration of DM consistent with ΛCDM predictions.
ERIC Educational Resources Information Center
Kaplan, David
2005-01-01
This article considers the problem of estimating dynamic linear regression models when the data are generated from finite mixture probability density function where the mixture components are characterized by different dynamic regression model parameters. Specifically, conventional linear models assume that the data are generated by a single…
Progress towards Continental River Dynamics modeling
NASA Astrophysics Data System (ADS)
Yu, Cheng-Wei; Zheng, Xing; Liu, Frank; Maidment, Daivd; Hodges, Ben
2017-04-01
The high-resolution National Water Model (NWM), launched by U.S. National Oceanic and Atmospheric Administration (NOAA) in August 2016, has shown it is possible to provide real-time flow prediction in rivers and streams across the entire continental United States. The next step for continental-scale modeling is moving from reduced physics (e.g. Muskingum-Cunge) to full dynamic modeling with the Saint-Venant equations. The Simulation Program for River Networks (SPRNT) provides a computational approach for the Saint-Venant equations, but obtaining sufficient channel bathymetric data and hydraulic roughness is seen as a critical challenge. However, recent work has shown the Height Above Nearest Drainage (HAND) method can be applied with the National Elevation Dataset (NED) to provide automated estimation of effective channel bathymetry suitable for large-scale hydraulic simulations. The present work examines the use of SPRNT with the National Hydrography Dataset (NHD) and HAND-derived bathymetry for automated generation of rating curves that can be compared to existing data. The approach can, in theory, be applied to every stream reach in the NHD and thus provide flood guidance where none is available. To test this idea we generated 2000+ rating curves in two catchments in Texas and Alabama (USA). Field data from the USGS and flood records from an Austin, Texas flood in May 2015 were used as validation. Large-scale implementation of this idea requires addressing several critical difficulties associated with numerical instabilities, including ill-posed boundary conditions generated in automated model linkages and inconsistencies in the river geometry. A key to future progress is identifying efficient approaches to isolate numerical instability contributors in a large time-space varying solution. This research was supported in part by the National Science Foundation under grant number CCF-1331610.
An Extension Dynamic Model Based on BDI Agent
NASA Astrophysics Data System (ADS)
Yu, Wang; Feng, Zhu; Hua, Geng; WangJing, Zhu
this paper's researching is based on the model of BDI Agent. Firstly, This paper analyze the deficiencies of the traditional BDI Agent model, Then propose an extension dynamic model of BDI Agent based on the traditional ones. It can quickly achieve the internal interaction of the tradition model of BDI Agent, deal with complex issues under dynamic and open environment and achieve quick reaction of the model. The new model is a natural and reasonable model by verifying the origin of civilization using the model of monkeys to eat sweet potato based on the design of the extension dynamic model. It is verified to be feasible by comparing the extended dynamic BDI Agent model with the traditional BDI Agent Model uses the SWARM, it has important theoretical significance.
Dynamics in Higher Education Politics: A Theoretical Model
ERIC Educational Resources Information Center
Kauko, Jaakko
2013-01-01
This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…
Dynamics in Higher Education Politics: A Theoretical Model
ERIC Educational Resources Information Center
Kauko, Jaakko
2013-01-01
This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…
A Model of Active Layer Dynamics
NASA Astrophysics Data System (ADS)
Ossola, I.; Travis, B. J.
2009-12-01
The role that permafrost plays in the global carbon cycle and its effect on climate change is receiving increasing attention. Permafrost worldwide has been calculated to hold approximately 1600 Gt of carbon, second only to the oceans in capacity. Despite its thinness relative to the permafrost layer below it, the active layer is pivotal since the dynamics of the active layer controls the flow of gases, water and energy between the atmosphere and the permafrost. Further, lateral movement of water through the active layer can impact arctic lakes and rivers. Using the computer code ARCHY we can simulate flow of water and gases (methane, carbon dioxide and oxygen) through multiple layers of varying soil properties, the activity of several microbial species (aerobic and anaerobic), and freezing and thawing in the active layer in response to daily and seasonal temperature oscillations. Our goal is to improve understanding of the active layer by computational modeling of its coupled hydrologic, thermal and microbial processes and relating model response to observations.
Supercomputer modeling of volcanic eruption dynamics
Kieffer, S.W.; Valentine, G.A.; Woo, Mahn-Ling
1995-06-01
Our specific goals are to: (1) provide a set of models based on well-defined assumptions about initial and boundary conditions to constrain interpretations of observations of active volcanic eruptions--including movies of flow front velocities, satellite observations of temperature in plumes vs. time, and still photographs of the dimensions of erupting plumes and flows on Earth and other planets; (2) to examine the influence of subsurface conditions on exit plane conditions and plume characteristics, and to compare the models of subsurface fluid flow with seismic constraints where possible; (3) to relate equations-of-state for magma-gas mixtures to flow dynamics; (4) to examine, in some detail, the interaction of the flowing fluid with the conduit walls and ground topography through boundary layer theory so that field observations of erosion and deposition can be related to fluid processes; and (5) to test the applicability of existing two-phase flow codes for problems related to the generation of volcanic long-period seismic signals; (6) to extend our understanding and simulation capability to problems associated with emplacement of fragmental ejecta from large meteorite impacts.
Research of cyclist's spine dynamical model.
Griskevicius, Julius; Linkel, Arturas; Pauk, Jolanta
2014-01-01
The purpose of the paper is to present a dynamic model of bicyclist's lumbar spine for the evaluation of linear and angular variation of intervertebral distance in sagittal plane. Ten degrees of freedom biomechanical model of the spine was solved numerically. Larger loads acting on a cyclist spine occur mostly while sitting in a sport position in comparison with recreation or middle sitting. The load on lumbar spine region is influenced by cycle's tire pressure, road bumps and wheeling speed. The biggest linear and angular displacements were found between L4-L5 vertebras. The biggest load protractile spine muscle experiences in the sport sitting position. Maximum vertebrae rotation and linear variation values in wheeling regime with 1.5 Bar tyres pressure and at a speed of 10 km/h are 0.46° and 0.46 mm. Maximum vertebrae rotation and linear variation values for a 23 year old, 1.74 m high and 73 kg of mass (bicycle mass~7 kg) man in wheeling regime with 3.5 Bar tyres pressure and at a speed of 30 km/h are 3.9° and 1.23 mm. The biggest variation of rotation in sagittal plane between two nearest lumbar spines is about 1°. Because of this displacement the frontal part of last mentioned disc is compressed with 530 N more and dorsal disc part as much less.
Dynamical models of Saturn's Phoebe ring
NASA Astrophysics Data System (ADS)
Tamayo, Daniel; Markham, Stephen; Hedman, Matthew M.; Burns, Joseph A.
2014-05-01
Saturn has the distinction of hosting the largest observed ring system in the solar sytem, the Phoebe Ring. Its vertical extent implicates Saturn’s irregular and distant satellite Phoebe as the source, with material being liberated through collisions. Owing to radiation forces, dusty debris is then swept inward toward Saturn on long timescales, spreading into a disk two orders of magnitude larger than Saturn’s more famous main rings. Previous work indicates that Saturn’s moon Iapetus should sweep up the majority of this infalling dark material. This would explain its striking two-faced surface, with one hemisphere ten times darker than the other. However, there is yet no direct observational confirmation of this mass transfer process. An important prediction for this model of Iapetus’ hemispherical dichotomy is that Iapetus should carve out an inner edge to the Phoebe ring. While scattered light from Saturn thwarts all attempts to detect this inner edge from Earth, we have recently developed a technique for detecting the Phoebe ring using the Cassini spacecraft. Preliminary work suggests we have found such an inner edge.In order to meaningfully interpret our findings, we require a dynamical model for the debris decaying inward from Phoebe. We will present the results of our analytical and numerical investigations.
A dynamic model of Venus's gravity field
NASA Technical Reports Server (NTRS)
Kiefer, W. S.; Richards, M. A.; Hager, B. H.; Bills, B. G.
1984-01-01
Unlike Earth, long wavelength gravity anomalies and topography correlate well on Venus. Venus's admittance curve from spherical harmonic degree 2 to 18 is inconsistent with either Airy or Pratt isostasy, but is consistent with dynamic support from mantle convection. A model using whole mantle flow and a high viscosity near surface layer overlying a constant viscosity mantle reproduces this admittance curve. On Earth, the effective viscosity deduced from geoid modeling increases by a factor of 300 from the asthenosphere to the lower mantle. These viscosity estimates may be biased by the neglect of lateral variations in mantle viscosity associated with hot plumes and cold subducted slabs. The different effective viscosity profiles for Earth and Venus may reflect their convective styles, with tectonism and mantle heat transport dominated by hot plumes on Venus and by subducted slabs on Earth. Convection at degree 2 appears much stronger on Earth than on Venus. A degree 2 convective structure may be unstable on Venus, but may have been stabilized on Earth by the insulating effects of the Pangean supercontinental assemblage.
A general dynamic model of flexible robot arms for control
NASA Technical Reports Server (NTRS)
Ding, X.; Tarn, T. J.; Bejczy, A. K.
1989-01-01
Hamilton's principle is used to derive the dynamic model for a large class of flexible robot arms. The resultant dynamic model consists of a system of partial differential-integral equations and the dynamic boundary conditions associated with it. Some properties of the model are observed, and its application to control is discussed. This model represents an infinite-dimensional nonlinear dynamic system and yet can be turned into a finite-dimensional system that could be obtained by modal expansion, if it is desired. This provides more flexibility for control purposes as well as for the analysis of the system.
Bayesian Estimation of Random Coefficient Dynamic Factor Models
ERIC Educational Resources Information Center
Song, Hairong; Ferrer, Emilio
2012-01-01
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…
Bayesian Estimation of Random Coefficient Dynamic Factor Models
ERIC Educational Resources Information Center
Song, Hairong; Ferrer, Emilio
2012-01-01
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…
COMPUTATIONAL FLUID DYNAMICS MODELING ANALYSIS OF COMBUSTORS
Mathur, M.P.; Freeman, Mark; Gera, Dinesh
2001-11-06
In the current fiscal year FY01, several CFD simulations were conducted to investigate the effects of moisture in biomass/coal, particle injection locations, and flow parameters on carbon burnout and NO{sub x} inside a 150 MW GEEZER industrial boiler. Various simulations were designed to predict the suitability of biomass cofiring in coal combustors, and to explore the possibility of using biomass as a reburning fuel to reduce NO{sub x}. Some additional CFD simulations were also conducted on CERF combustor to examine the combustion characteristics of pulverized coal in enriched O{sub 2}/CO{sub 2} environments. Most of the CFD models available in the literature treat particles to be point masses with uniform temperature inside the particles. This isothermal condition may not be suitable for larger biomass particles. To this end, a stand alone program was developed from the first principles to account for heat conduction from the surface of the particle to its center. It is envisaged that the recently developed non-isothermal stand alone module will be integrated with the Fluent solver during next fiscal year to accurately predict the carbon burnout from larger biomass particles. Anisotropy in heat transfer in radial and axial will be explored using different conductivities in radial and axial directions. The above models will be validated/tested on various fullscale industrial boilers. The current NO{sub x} modules will be modified to account for local CH, CH{sub 2}, and CH{sub 3} radicals chemistry, currently it is based on global chemistry. It may also be worth exploring the effect of enriched O{sub 2}/CO{sub 2} environment on carbon burnout and NO{sub x} concentration. The research objective of this study is to develop a 3-Dimensional Combustor Model for Biomass Co-firing and reburning applications using the Fluent Computational Fluid Dynamics Code.
AIR INGRESS ANALYSIS: COMPUTATIONAL FLUID DYNAMIC MODELS
Chang H. Oh; Eung S. Kim; Richard Schultz; Hans Gougar; David Petti; Hyung S. Kang
2010-08-01
The Idaho National Laboratory (INL), under the auspices of the U.S. Department of Energy, is performing research and development that focuses on key phenomena important during potential scenarios that may occur in very high temperature reactors (VHTRs). Phenomena Identification and Ranking Studies to date have ranked an air ingress event, following on the heels of a VHTR depressurization, as important with regard to core safety. Consequently, the development of advanced air ingress-related models and verification and validation data are a very high priority. Following a loss of coolant and system depressurization incident, air will enter the core of the High Temperature Gas Cooled Reactor through the break, possibly causing oxidation of the in-the core and reflector graphite structure. Simple core and plant models indicate that, under certain circumstances, the oxidation may proceed at an elevated rate with additional heat generated from the oxidation reaction itself. Under postulated conditions of fluid flow and temperature, excessive degradation of the lower plenum graphite can lead to a loss of structural support. Excessive oxidation of core graphite can also lead to the release of fission products into the confinement, which could be detrimental to a reactor safety. Computational fluid dynamic model developed in this study will improve our understanding of this phenomenon. This paper presents two-dimensional and three-dimensional CFD results for the quantitative assessment of the air ingress phenomena. A portion of results of the density-driven stratified flow in the inlet pipe will be compared with results of the experimental results.
Dynamic modelling and analysis of space webs
NASA Astrophysics Data System (ADS)
Yu, Yang; Baoyin, HeXi; Li, JunFeng
2011-04-01
Future space missions demand operations on large flexible structures, for example, space webs, the lightweight cable nets deployable in space, which can serve as platforms for very large structures or be used to capture orbital objects. The interest in research on space webs is likely to increase in the future with the development of promising applications such as Furoshiki sat-ellite of JAXA, Robotic Geostationary Orbit Restorer (ROGER) of ESA and Grapple, Retrieve And Secure Payload (GRASP) of NASA. Unlike high-tensioned nets in civil engineering, space webs may be low-tensioned or tensionless, and extremely flexible, owing to the microgravity in the orbit and the lack of support components, which may cause computational difficulties. Mathematical models are necessary in the analysis of space webs, especially in the conceptual design and evaluation for prototypes. A full three-dimensional finite element (FE) model was developed in this work. Trivial truss elements were adopted to reduce the computational complexity. Considering cable is a compression-free material and its tensile stiffness is also variable, we introduced the cable material constitutive relationship to work out an accurate and feasible model for prototype analysis and design. In the static analysis, the stress distribution and global deformation of the webs were discussed to get access to the knowledge of strength of webs with different types of meshes. In the dynamic analysis, special attention was paid to the impact problem. The max stress and global deformation were investigated. The simulation results indicate the interesting phenomenon which may be worth further research.
NASA Astrophysics Data System (ADS)
Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.
2015-04-01
Coarse-grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse-grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse-graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. In this paper, we consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse-graining (MS-CG) method of Voth and coworkers. We propose a method of converting a MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that were studied by Zwanzig [J. Stat. Phys. 9, 215 (1973)]. The properties of the fictitious particles can be inferred from analysis of the dynamics of all-atom simulations of the system of interest. This is analogous to the fact that the MS-CG method generates the CG potential from analysis of equilibrium structures observed in all-atom simulation data. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics programs. We present tests of this method on a series of simple examples that demonstrate that
Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.
2015-04-21
Coarse-grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse-grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse-graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. In this paper, we consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse-graining (MS-CG) method of Voth and coworkers. We propose a method of converting a MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that were studied by Zwanzig [J. Stat. Phys. 9, 215 (1973)]. The properties of the fictitious particles can be inferred from analysis of the dynamics of all-atom simulations of the system of interest. This is analogous to the fact that the MS-CG method generates the CG potential from analysis of equilibrium structures observed in all-atom simulation data. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics programs. We present tests of this method on a series of simple examples that demonstrate that
Dynamic hysteretic sensing model of bending-mode Galfenol transducer
NASA Astrophysics Data System (ADS)
Cao, Shuying; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei
2015-05-01
A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.
A dynamic model for the Lagrangian stochastic dispersion coefficient
Pesmazoglou, I.; Navarro-Martinez, S.; Kempf, A. M.
2013-12-15
A stochastic sub-grid model is often used to accurately represent particle dispersion in turbulent flows using large eddy simulations. Models of this type have a free parameter, the dispersion coefficient, which is not universal and is strongly grid-dependent. In the present paper, a dynamic model for the evaluation of the coefficient is proposed and validated in decaying homogeneous isotropic turbulence. The grid dependence of the static coefficient is investigated in a turbulent mixing layer and compared to the dynamic model. The dynamic model accurately predicts dispersion statistics and resolves the grid-dependence. Dispersion statistics of the dynamically calculated constant are more accurate than any static coefficient choice for a number of grid spacings. Furthermore, the dynamic model produces less numerical artefacts than a static model and exhibits smaller sensitivity in the results predicted for different particle relaxation times.
Dynamic hysteretic sensing model of bending-mode Galfenol transducer
Cao, Shuying Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei
2015-05-07
A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.
System Dynamics Modeling for Supply Chain Information Sharing
NASA Astrophysics Data System (ADS)
Feng, Yang
In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.
McCollum, Gin; Roberts, Patrick D
2004-12-01
Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning. Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.
A dynamic fault tree model of a propulsion system
NASA Technical Reports Server (NTRS)
Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila
2006-01-01
We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.
A dynamic fault tree model of a propulsion system
NASA Technical Reports Server (NTRS)
Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila
2006-01-01
We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.
Spatiotemporal modelling of viral infection dynamics
NASA Astrophysics Data System (ADS)
Beauchemin, Catherine
Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than
Analysing the temporal dynamics of model performance for hydrological models
NASA Astrophysics Data System (ADS)
Reusser, D. E.; Blume, T.; Schaefli, B.; Zehe, E.
2009-07-01
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physics-based model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.
Analysing the temporal dynamics of model performance for hydrological models
NASA Astrophysics Data System (ADS)
Reusser, D. E.; Blume, T.; Schaefli, B.; Zehe, E.
2008-11-01
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physics-based model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns which can lead to the identification of model structural errors.
Modeling Nanocomposites for Molecular Dynamics (MD) Simulations
2015-01-01
Maximum 200 Words) The minimum energy configuration for Molecular Dynamics (MD) simulations is found for a carbon nanotube (CNT)/polymer... Carbon Nanotubes (CNTs), Molecular Dynamics Simulations 15. NUMBER OF PAGES 18 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT... Carbon Nanotubes ,” Macromolecules, Volume 39, Number 16, pp. 5194-5205, July 2006. 6. “VMD-Visual Molecular Dynamics ,” March 2014, http
Nonlinear dynamics of avian influenza epidemic models.
Liu, Sanhong; Ruan, Shigui; Zhang, Xinan
2017-01-01
Avian influenza is a zoonotic disease caused by the transmission of the avian influenza A virus, such as H5N1 and H7N9, from birds to humans. The avian influenza A H5N1 virus has caused more than 500 human infections worldwide with nearly a 60% death rate since it was first reported in Hong Kong in 1997. The four outbreaks of the avian influenza A H7N9 in China from March 2013 to June 2016 have resulted in 580 human cases including 202 deaths with a death rate of nearly 35%. In this paper, we construct two avian influenza bird-to-human transmission models with different growth laws of the avian population, one with logistic growth and the other with Allee effect, and analyze their dynamical behavior. We obtain a threshold value for the prevalence of avian influenza and investigate the local or global asymptotical stability of each equilibrium of these systems by using linear analysis technique or combining Liapunov function method and LaSalle's invariance principle, respectively. Moreover, we give necessary and sufficient conditions for the occurrence of periodic solutions in the avian influenza system with Allee effect of the avian population. Numerical simulations are also presented to illustrate the theoretical results. Copyright © 2016 Elsevier Inc. All rights reserved.
Protoplaneary Dynamics Uncovered through Synthetic Spectral Modeling
NASA Astrophysics Data System (ADS)
Kronberg, Martin
2010-01-01
One of the key problems in planetary formation research is to determine the properties and dynamics of protoplaneary accretion disks where all planetary formation occurs. An increasingly useful probe into these systems is near infrared spectroscopy of ro-vibrational CO emission. The goal of the study is to develop techniques that utilize synthetic spectra generated via a modeling algorithm fitted to actual spectral data gathered from protoplanetary systems to determine specific properties of the system. We currently have a working algorithm which generates synthetic spectra based upon a number of degenerate parameters. In order to generate the best fit given the degenerate nature of the parameters we are developing a Monte Carlo algorithm that will determine local as well as absolute minima in a ten dimensional surface plot. Once this is completed we will utilize two CONDOR clusters to generate fits for hundreds of known protoplanetary systems.The result will be the largest, most descriptive database of protoplanetary systems, an essential tool for planetary and stellar researchers. This project was funded by a partnership between the National Science Foundation (NSF AST-0552798), Research Experiences for Undergraduates (REU), and the Department of Defense (DoD) ASSURE (Awards to Stimulate and Support Undergraduate Research Experiences) programs.
Modeling proteasome dynamics in Parkinson's disease
NASA Astrophysics Data System (ADS)
Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H.; Pigolotti, Simone; Otzen, Daniel
2009-09-01
In Parkinson's disease (PD), there is evidence that α-synuclein (αSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin-proteasome system. Here, we develop a simple dynamical model for the on-going conflict between αSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature αSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the αSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system.
Dynamical Properties of Polymers: Computational Modeling
CURRO, JOHN G.; ROTTACH, DANA; MCCOY, JOHN D.
2001-01-01
The free volume distribution has been a qualitatively useful concept by which dynamical properties of polymers, such as the penetrant diffusion constant, viscosity, and glass transition temperature, could be correlated with static properties. In an effort to put this on a more quantitative footing, we define the free volume distribution as the probability of finding a spherical cavity of radius R in a polymer liquid. This is identical to the insertion probability in scaled particle theory, and is related to the chemical potential of hard spheres of radius R in a polymer in the Henry's law limit. We used the Polymer Reference Interaction Site Model (PRISM) theory to compute the free volume distribution of semiflexible polymer melts as a function of chain stiffness. Good agreement was found with the corresponding free volume distributions obtained from MD simulations. Surprisingly, the free volume distribution was insensitive to the chain stiffness, even though the single chain structure and the intermolecular pair correlation functions showed a strong dependence on chain stiffness. We also calculated the free volume distributions of polyisobutylene (PIB) and polyethylene (PE) at 298K and at elevated temperatures from PRISM theory. We found that PIB has more of its free volume distributed in smaller size cavities than for PE at the same temperature.
Modelling dynamics with context-free grammars
NASA Astrophysics Data System (ADS)
García-Huerta, Juan-M.; Jiménez-Hernández, Hugo; Herrera-Navarro, Ana-M.; Hernández-Díaz, Teresa; Terol-Villalobos, Ivan
2014-03-01
This article presents a strategy to model the dynamics performed by vehicles in a freeway. The proposal consists on encode the movement as a set of finite states. A watershed-based segmentation is used to localize regions with high-probability of motion. Each state represents a proportion of a camera projection in a two-dimensional space, where each state is associated to a symbol, such that any combination of symbols is expressed as a language. Starting from a sequence of symbols through a linear algorithm a free-context grammar is inferred. This grammar represents a hierarchical view of common sequences observed into the scene. Most probable grammar rules express common rules associated to normal movement behavior. Less probable rules express themselves a way to quantify non-common behaviors and they might need more attention. Finally, all sequences of symbols that does not match with the grammar rules, may express itself uncommon behaviors (abnormal). The grammar inference is built with several sequences of images taken from a freeway. Testing process uses the sequence of symbols emitted by the scenario, matching the grammar rules with common freeway behaviors. The process of detect abnormal/normal behaviors is managed as the task of verify if any word generated by the scenario is recognized by the grammar.
Modeling Statistical and Dynamic Features of Earthquakes
NASA Astrophysics Data System (ADS)
Rydelek, P. A.; Suyehiro, K.; Sacks, S. I.; Smith, D. E.; Takanami, T.; Hatano, T.
2015-12-01
The cellular automaton earthquake model by Sacks and Rydelek (1995) is extended to explain spatio-temporal change in seismicity with the regional tectonic stress buildup. Our approach is to apply a simple Coulomb failure law to our model space of discrete cells, which successfully reproduces empirical laws (e.g. Gutenberg-Richter law) and dynamic failure characteristics (e.g. stress drop vs. magnitude and asperities) of earthquakes. Once the stress condition supersedes the Coulomb threshold on a discrete cell, its accumulated stress is transferred to only neighboring cells, which cascades to more neighboring cells to create various size ruptures. A fundamental point here is the cellular view of the continuous earth. We suggest the cell size varies regionally with the maturity of the faults of the region. Seismic gaps (e.g. Mogi, 1979) and changes in seismicity such as indicated by b-values have been known but poorly understood. There have been reports of magnitude dependent seismic quiescence before large event at plate boundaries and intraplate (Smith et al., 2013). Recently, decreases in b-value for large earthquakes have been reported (Nanjo et al., 2012) as anticipated from lab experiments (Mogi, 1963). Our model reproduces the b-value decrease towards eventual large earthquake (increasing tectonic stress and its heterogeneous distribution). We succeeded in reproducing the cut-off of larger events above some threshold magnitude (M3-4) by slightly increasing the Coulomb failure level for only 2 % or more of the highly stressed cells. This is equivalent to reducing the pore pressure in these distributed cells. We are working on the model to introduce the recovery of pore pressure incorporating the observed orders of magnitude higher permeability fault zones than the surrounding rock (Lockner, 2009) allowing for a large earthquake to be generated. Our interpretation requires interactions of pores and fluids. We suggest heterogeneously distributed patches hardened
An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409
Dynamical coarse grained models with realistic time dependence
NASA Astrophysics Data System (ADS)
Andersen, Hans
2015-03-01
Coarse grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. We consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse Graining (MS-CG) method of Voth and coworkers. We propose a method of converting an MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that was studied by Zwanzig [R. Zwanzig, J. Stat. Phys. 9, 215 (1973)]. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics simulation programs. We present tests of this method on a series of simple examples that demonstrate that the method provides realistic dynamical CG models that have non-Markovian or close to Markovian behavior that is consistent with the actual dynamical behavior of the all-atom system used to construct the CG model. The dynamic CG models have computational requirements that are similar to
Dynamics of some neural network models with delay.
Ruan, J; Li, L; Lin, W
2001-05-01
The dynamics of the neuronic model described by the one-dimensional delay functional differential equation are studied in this paper. We give a strict and detailed analysis of dynamical characteristic of this model by the Lyapunov functional approach and Hopf bifurcation proposition. Furthermore, numerical simulations, as well as Lyapunov exponents, are presented to support our conjectures about the appearance of complex dynamics such as chaos. We also investigate the dynamics of the neural network model described by the n-dimensional delay functional differential equation with a symmetrical weight matrix, and corresponding simulation results are included as concrete examples.
Divisibility of quantum dynamical maps and collision models
NASA Astrophysics Data System (ADS)
Filippov, S. N.; Piilo, J.; Maniscalco, S.; Ziman, M.
2017-09-01
The divisibility of dynamical maps is visualized by trajectories in the parameter space and analyzed within the framework of collision models. We introduce ultimate completely positive (CP) divisible processes, which lose CP divisibility under infinitesimal perturbations, and characterize Pauli dynamical semigroups exhibiting such a property. We construct collision models with factorized environment particles, which realize additivity and multiplicativity of generators of CP divisible maps. A mixture of dynamical maps is obtained with the help of correlated environment. The mixture of ultimate CP divisible processes is shown to result in a class of eternal CP indivisible evolutions. We explicitly find collision models leading to weakly and essentially non-Markovian Pauli dynamical maps.
A review of dynamics modelling of friction wedge suspensions
NASA Astrophysics Data System (ADS)
Wu, Qing; Cole, Colin; Spiryagin, Maksym; Sun, Yan Quan
2014-11-01
Three-piece bogies with friction wedge suspensions are the most widely used bogies in heavy haul trains. Fiction wedge suspensions play a key role in these wagon systems. This article reviews current techniques in dynamic modelling of friction wedge suspension with various motivations: to improve dynamic models of friction wedge suspensions so as to improve general wagon dynamics simulations; to seek better friction wedge suspension models for wagon stability assessments in complex train systems; to improve the modelling of other friction devices, such as friction draft gear. Relevant theories and friction wedge suspension models developed by using commercial simulation packages and in-house simulation packages are reviewed.
Stochastic Online Learning in Dynamic Networks under Unknown Models
2016-08-02
Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for...12211 Research Triangle Park, NC 27709-2211 Online learning, multi-armed bandit, dynamic networks REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S... Online Learning in Dynamic Networks under Unknown Models Report Title This research aims to develop fundamental theories and practical algorithms for
Dynamical Widom-Rowlinson Model and Its Mesoscopic Limit
NASA Astrophysics Data System (ADS)
Finkelshtein, Dmitri; Kondratiev, Yuri; Kutoviy, Oleksandr; Oliveira, Maria João
2015-01-01
We consider the non-equilibrium dynamics for the Widom-Rowlinson model (without hard-core) in the continuum. The Lebowitz-Penrose-type scaling of the dynamics is studied and the system of the corresponding kinetic equations is derived. In the space-homogeneous case, the equilibrium points of this system are described. Their structure corresponds to the dynamical phase transition in the model. The bifurcation of the system is shown.
An integrated dynamic model of a flexible wind turbine
NASA Astrophysics Data System (ADS)
Bongers, Peter M. M.; Bierbooms, Wim A. A.; Dijkstra, Sjoerd; Vanholten, Theo
1990-06-01
A model to study the dynamic behavior of flexible wind turbines was developed. The different subsystems of the wind turbine are individually modeled with about the same degree of accuracy. The aerodynamic part describes wind shear, gravity effects, unsteady effects, and dynamic inflow. The rotor blades are provided with degrees of freedom in lag and flap directions. The tower construction is modeled including the first bending mode. The first torsional mode of the transmission is included in the model. The model of synchronous generator with dc link consists of a nonlinear fourth order model, including saturation effects. The different models of the subsystems are coupled into one integrated dynamic model which is implemented as simulation code in the DUWECS (Delf University Wind Energy Converter Simulation Package) program. The DUWECS program is developed in such a manner that it is an easy to handle tool for the study of the dynamic features of wind turbine systems.
[A Dynamic Developmental Model of Suicide.] Commentary.
ERIC Educational Resources Information Center
Campbell, Robert L.
1996-01-01
Discusses Mishara's use of phrase space analysis to chart the developmental dynamics of suicide. Contends that developmentalists should concern themselves with mental ontology, especially epistemic questions, in order to advance understanding of the development of the human mind. Considers the affinity of interactivism with a dynamic systems…
Concepts and tools for predictive modeling of microbial dynamics.
Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F
2004-09-01
Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.
Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects
ERIC Educational Resources Information Center
Qian, Minghui; Hu, Ridong; Chen, Jianwei
2016-01-01
Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…
Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects
ERIC Educational Resources Information Center
Qian, Minghui; Hu, Ridong; Chen, Jianwei
2016-01-01
Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…
A coarse wood dynamics model for the Western Cascades.
K. Mellen; A. Ager
2002-01-01
The Coarse Wood Dynamics Model (CWDM) analyzes the dynamics (fall, fragmentation, and decomposition) of Douglas-fir (Pseudotsuga menziesii) and western hemlock (Tsuga heterophylla) snags and down logs in forested ecosystems of the western Cascades of Oregon and Washington. The model predicts snag fall, height loss and decay,...
Modelling Seasonal Carbon Dynamics on Fen Peatlands
NASA Astrophysics Data System (ADS)
Giebels, Michael; Beyer, Madlen; Augustin, Jürgen; Roppel, Mario; Juszczak, Radoszlav; Serba, Tomasz
2010-05-01
In Germany more than 99 % of fens have lost their carbon and nutrient sink function due to heavy drainage and agricultural land use especially during the last decades and thus resulted in compression and heavy peat loss (CHARMAN 2002; JOOSTEN & CLARKE 2002; SUCCOW & JOOSTEN 2001; AUGUSTIN et al. 1996; KUNTZE 1993). Therefore fen peatlands play an important part (4-5 %) in the national anthropogenic trace gas budget. But only a small part of drained and agricultural used fens in NE Germany can be restored. Knowledge of the influence of land use to trace gas exchange is important for mitigation of the climate impact of the anthropogenic peatland use. We study carbon exchanges between soil and atmosphere on several fen peatland use areas at different sites in NE-Germany. Our research covers peatlands of supposed strongly climate forcing land use (cornfield and intensive pasture) and of probably less forcing, alternative types (meadow and extensive pasture) as well as rewetted (formerly drained) areas and near-natural sites like a low-degraded fen and a wetted alder woodland. We measured trace gas fluxes with manual and automatic chambers in periodic routines since spring 2007. The used chamber technique bases on DROESLER (2005). In total we now do research at 22 sites situated in 5 different locations covering agricultural, varying states of rewetted and near-natural treatments. We present results of at least 2 years of measurements on our site of varying types of agricultural land use. There we found significant differences in the annual carbon balances depending on the genesis of the observed sites and the seasonal dynamics. Annual balances were constructed by applying single respiration and photosynthesis CO2 models for each measurement campaign. These models were based on LLOYD-TAYLOR (1994) and Michaelis-Menten-Kinetics respectively. Crosswise comparison of different site treatments combined with the seasonal environmental observations give good hints for the
A Dynamic Systems Model of Cognitive and Language Growth.
ERIC Educational Resources Information Center
van Geert, Paul
1991-01-01
A conceptual framework of cognitive growth is sketched and a mathematical model of cognitive growth is presented with the conclusion that the most plausible model is a model of logistic growth with delayed feedback. The model is transformed into a dynamic systems model based on the logistic-growth equation. (SLD)
Dynamic Model Validation with Governor Deadband on the Eastern Interconnection
Kou, Gefei; Hadley, Stanton W; Liu, Yilu
2014-04-01
This report documents the efforts to perform dynamic model validation on the Eastern Interconnection (EI) by modeling governor deadband. An on-peak EI dynamic model is modified to represent governor deadband characteristics. Simulation results are compared with synchrophasor measurements collected by the Frequency Monitoring Network (FNET/GridEye). The comparison shows that by modeling governor deadband the simulated frequency response can closely align with the actual system response.
Benchmarking novel approaches for modelling species range dynamics.
Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E
2016-08-01
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches
Dynamical systems and spherically symmetric cosmological models
NASA Astrophysics Data System (ADS)
He, Yanjing
2006-06-01
In this thesis we present a study of the timelike self-similar spherically symmetric cosmological models with two scalar fields with exponential potentials. We first define precisely the timelike self-similar spherically symmetric (TSS) spacetimes. We write the TSS metric in a conformally isometric form in a coordinate system adapted to the geometry of the spacetime manifold. In this coordinate system, both the metric functions of the TSS spacetimes and the potential functions of the scalar fields can be simplified to four undetermined functions of a single coordinate. As a result, the Einstein field equations reduce to an autonomous system of first-order ODEs and polynomial constraints in terms of these undetermined functions. By introducing new bounded variables as well as a new independent variable and solving the constraints, we are able to apply the theory of dynamical systems to study the properties of the TSS solutions. By finding invariant sets and associated monotonic functions, by applying the LaSalle Invariance Principle and the Monotonicity Principle, by applying the [straight phi] t -connected property of a limit set, and using other theorems, we prove that all of the TSS trajectories are heteroclinic trajectories. In addition, we conduct numerical simulations to confirm and support the qualitative analysis. We obtain all possible types of TSS solutions, by analyzing the qualitative behavior of the original system of ODES from those of the reduced one. We obtain asymptotic expressions for the TSS solutions (e.g., the asymptotic expressions for the metric functions, the source functions and the Ricci scalar). In particular, self-similar flat Friedmann-Robertson-Walker spacetimes are examined in order to obtain insights into the issues related to the null surface in general TSS spacetimes in these coordinates. A discussion of the divergence of the spacetime Ricci scalar and the possible extension of the TSS solutions across the null boundary is presented
Automatic code generation from the OMT-based dynamic model
Ali, J.; Tanaka, J.
1996-12-31
The OMT object-oriented software development methodology suggests creating three models of the system, i.e., object model, dynamic model and functional model. We have developed a system that automatically generates implementation code from the dynamic model. The system first represents the dynamic model as a table and then generates executable Java language code from it. We used inheritance for super-substate relationships. We considered that transitions relate to states in a state diagram exactly as operations relate to classes in an object diagram. In the generated code, each state in the state diagram becomes a class and each event on a state becomes an operation on the corresponding class. The system is implemented and can generate executable code for any state diagram. This makes the role of the dynamic model more significant and the job of designers even simpler.
Multibody dynamics model building using graphical interfaces
NASA Technical Reports Server (NTRS)
Macala, Glenn A.
1989-01-01
In recent years, the extremely laborious task of manually deriving equations of motion for the simulation of multibody spacecraft dynamics has largely been eliminated. Instead, the dynamicist now works with commonly available general purpose dynamics simulation programs which generate the equations of motion either explicitly or implicitly via computer codes. The user interface to these programs has predominantly been via input data files, each with its own required format and peculiarities, causing errors and frustrations during program setup. Recent progress in a more natural method of data input for dynamics programs: the graphical interface, is described.
System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...
XML-based 3D model visualization and simulation framework for dynamic models
NASA Astrophysics Data System (ADS)
Kim, Taewoo; Fishwick, Paul A.
2002-07-01
Relatively recent advances in computer technology enable us to create three-dimensional (3D) dynamic models and simulate them within a 3D web environment. The use of such models is especially valuable when teaching simulation, and the concepts behind dynamic models, since the models are made more accessible to the students. Students tend to enjoy a construction process in which they are able to employ their own cultural and aesthetic forms. The challenge is to create a language that allows for a grammar for modeling, while simultaneously permitting arbitrary presentation styles. For further flexibility, we need an effective way to represent and simulate dynamic models that can be shared by modelers over the Internet. We present an Extensible Markup Language (XML)-based framework that will guide a modeler in creating personalized 3D models, visualizing its dynamic behaviors, and simulating the created models. A model author will use XML files to represent geometries and topology of a dynamic model. Model Fusion Engine, written in Extensible Stylesheet Language Transformation (XSLT), expedites the modeling process by automating the creation of dynamic models with the user-defined XML files. Modelers can also link simulation programs with a created model to analyze the characteristics of the model. The advantages of this system lie in the education of modeling and simulating dynamic models, and in the exploitation of visualizing the dynamic model behaviors.
A tribo-dynamic model of a spur gear pair
NASA Astrophysics Data System (ADS)
Li, S.; Kahraman, A.
2013-09-01
In this study, a tribo-dynamics model for spur gear pairs is proposed. The model couples a mixed elastohydrodynamic lubrication model of a spur gear pair with a transverse-torsional dynamic model. The lubrication model provides the dynamic model with friction forces and moments that couple the vibrations of the gears along the off-line-of-action direction to other gear vibrations. In addition, it predicts damping coefficient at the gear mesh in a physics-based manner from the energy loss associated with viscous shearing across the fluid film. In return, the dynamic model predicts the dynamic tooth forces and surface velocities to be used in the lubrication model. An iterative computational scheme is proposed to implement the lubrication and dynamics models simultaneously to couple tribological and dynamic behaviors of a spur gear pair fully. An example gear pair is analyzed using the proposed model to demonstrate this two-way relationship and quantify the impact of operating conditions, surface roughness and lubrication characteristics on the tribo-dynamics response. Dynamic gear mesh tooth forces predicted by the dynamic model are used in the EHL model as the loading. Surface velocity fluctuations due to gear vibrations are included in the EHL formulation in the definition of rolling and sliding velocities as well as non-Newtonian flow coefficients. A physics-based, time-varying, viscous gear mesh damping is defined from the EHL formulations to be used in the dynamic model along the OLOA direction. Since the EHL model considers rough surfaces, the roughness effects in addition to the operating speed, load and temperature effects are all included in the gear mesh damping. Time-varying friction forces acting in the OLOA direction and friction moments acting in torsional direction are computed from the EHL model to be used in the dynamic model to couple LOA and OLOA motions properly. Effects of surface roughness and operating speed, load and temperature conditions on
Modeling Dynamic Fracture of Cryogenic Pellets
Parks, Paul
2016-06-30
This work is part of an investigation with the long-range objective of predicting the size distribution function and velocity dispersion of shattered pellet fragments after a large cryogenic pellet impacts a solid surface at high velocity. The study is vitally important for the shattered pellet injection (SPI) technique, one of the leading technologies being implemented at ORNL for the mitigation of disruption damage on current tokamaks and ITER. The report contains three parts that are somewhat interwoven. In Part I we formulated a self-similar model for the expansion dynamics and velocity dispersion of the debris cloud following pellet impact against a thick (rigid) target plate. Also presented in Part I is an analytical fracture model that predicts the nominal or mean size of the fragments in the debris cloud and agrees well with known SPI data. The aim of Part II is to gain an understanding of the pellet fracturing process when a pellet is shattered inside a miter tube with a sharp bend. Because miter tubes have a thin stainless steel (SS) wall a permanent deformation (dishing) of the wall is produced at the site of the impact. A review of the literature indicates that most projectile impact on thin plates are those for which the target is deformed and the projectile is perfectly rigid. Such impacts result in “projectile embedding” where the projectile speed is reduced to zero during the interaction so that all the kinetic energy (KE) of the projectile goes into the energy stored in plastic deformation. Much of the literature deals with perforation of the target. The problem here is quite different; the softer pellet easily undergoes complete material failure causing only a small transfer of KE to stored energy of wall deformation. For the real miter tube, we derived a strain energy function for the wall deflection using a non-linear (plastic) stress-strain relation for 304 SS. Using a dishing profile identical to the linear Kirchkoff-Love profile (for lack
The Rigid-Flexible System Dynamics Model of Highline Cable
NASA Astrophysics Data System (ADS)
Xing, Daoqi; Li, Nan; Zhang, Shiyun
The paper researches rigid flexible system dynamics model of the rope, and used it to simulate sealift Highline based on the multi-body dynamics theory. Meanwhile the paper simulated to the sea dry cargo replenishment of transverse process, then gain the conclusion that the rigid flexible dynamic model get in the paper is more close to the Caucasus, and the dynamic calculation results closer to the actual situation, through the analysis of simulation results, and combined with the actual situation in the Caucasus the structure of overhead cable.
Modelling and Analysis of a New Piezoelectric Dynamic Balance Regulator
Du, Zhe; Mei, Xue-Song; Xu, Mu-Xun
2012-01-01
In this paper, a new piezoelectric dynamic balance regulator, which can be used in motorised spindle systems, is presented. The dynamic balancing adjustment mechanism is driven by an in-plane bending vibration from an annular piezoelectric stator excited by a high-frequency sinusoidal input voltage. This device has different construction, characteristics and operating principles than a conventional balance regulator. In this work, a dynamic model of the regulator is first developed using a detailed analytical method. Thereafter, MATLAB is employed to numerically simulate the relations between the dominant parameters and the characteristics of the regulator based on thedynamic model. Finally, experimental measurements are used to certify the validity of the dynamic model. Consequently, the mathematical model presented and analysed in this paper can be used as a tool for optimising the design of a piezoelectric dynamic balance regulator during steady state operation. PMID:23202182
A stochastic metapopulation model accounting for habitat dynamics.
Ross, J V
2006-06-01
A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.
Developing a dynamic pharmacophore model for HIV-1 integrase.
Carlson, H A; Masukawa, K M; Rubins, K; Bushman, F D; Jorgensen, W L; Lins, R D; Briggs, J M; McCammon, J A
2000-06-01
We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of "dynamic" pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a "static" pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.
Developing a Dynamic Pharmacophore Model for HIV-1 Integrase
Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen; Bushman, Frederic; Jorgensen, William L.; Lins, Roberto; Briggs, James; Mccammon, Andy
2000-05-11
We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.
Comparisons of Four Methods for Estimating a Dynamic Factor Model
ERIC Educational Resources Information Center
Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.
2008-01-01
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…
Comparisons of Four Methods for Estimating a Dynamic Factor Model
ERIC Educational Resources Information Center
Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.
2008-01-01
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…
Model based control of dynamic atomic force microscope
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope
NASA Astrophysics Data System (ADS)
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H∞ control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model and simulation of Krause model in dynamic open network
NASA Astrophysics Data System (ADS)
Zhu, Meixia; Xie, Guangqiang
2017-08-01
The construction of the concept of evolution is an effective way to reveal the formation of group consensus. This study is based on the modeling paradigm of the HK model (Hegsekmann-Krause). This paper analyzes the evolution of multi - agent opinion in dynamic open networks with member mobility. The results of the simulation show that when the number of agents is constant, the interval distribution of the initial distribution will affect the number of the final view, The greater the distribution of opinions, the more the number of views formed eventually; The trust threshold has a decisive effect on the number of views, and there is a negative correlation between the trust threshold and the number of opinions clusters. The higher the connectivity of the initial activity group, the more easily the subjective opinion in the evolution of opinion to achieve rapid convergence. The more open the network is more conducive to the unity of view, increase and reduce the number of agents will not affect the consistency of the group effect, but not conducive to stability.
A simplified dynamic model of the T700 turboshaft engine
NASA Technical Reports Server (NTRS)
Duyar, Ahmet; Gu, Zhen; Litt, Jonathan S.
1992-01-01
A simplified open-loop dynamic model of the T700 turboshaft engine, valid within the normal operating range of the engine, is developed. This model is obtained by linking linear state space models obtained at different engine operating points. Each linear model is developed from a detailed nonlinear engine simulation using a multivariable system identification and realization method. The simplified model may be used with a model-based real time diagnostic scheme for fault detection and diagnostics, as well as for open loop engine dynamics studies and closed loop control analysis utilizing a user generated control law.
NASA Technical Reports Server (NTRS)
Tan, C. M.; Carr, L. W.
1996-01-01
A variety of empirical and computational fluid dynamics two-dimensional (2-D) dynamic stall models were compared to recently obtained three-dimensional (3-D) dynamic stall data in a workshop on modeling of 3-D dynamic stall of an unswept, rectangular wing, of aspect ratio 10. Dynamic stall test data both below and above the static stall angle-of-attack were supplied to the participants, along with a 'blind' case where only the test conditions were supplied in advance, with results being compared to experimental data at the workshop itself. Detailed graphical comparisons are presented in the report, which also includes discussion of the methods and the results. The primary conclusion of the workshop was that the 3-D effects of dynamic stall on the oscillating wing studied in the workshop can be reasonably reproduced by existing semi-empirical models once 2-D dynamic stall data have been obtained. The participants also emphasized the need for improved quantification of 2-D dynamic stall.
Fractional-order in a macroeconomic dynamic model
NASA Astrophysics Data System (ADS)
David, S. A.; Quintino, D. D.; Soliani, J.
2013-10-01
In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.
Mathematical modeling of microtubule dynamics: insights into physiology and disease.
Buxton, Gavin A; Siedlak, Sandra L; Perry, George; Smith, Mark A
2010-12-01
Computer models of microtubule dynamics have provided the basis for many of the theories on the cellular mechanics of the microtubules, their polymerization kinetics, and the diffusion of tubulin and tau. In the three-dimensional model presented here, we include the effects of tau concentration and the hydrolysis of GTP-tubulin to GDP-tubulin and observe the emergence of microtubule dynamic instability. This integrated approach simulates the essential physics of microtubule dynamics in a cellular environment. The model captures the structure of the microtubules as they undergo steady state dynamic instabilities in this simplified geometry, and also yields the average number, length, and cap size of the microtubules. The model achieves realistic geometries and simulates cellular structures found in degenerating neurons in disease states such as Alzheimer disease. Further, this model can be used to simulate microtubule changes following the addition of antimitotic drugs which have recently attracted attention as chemotherapeutic agents.
Subcycled dynamics in the Spectral Community Atmosphere Model, version 4
Taylor, Mark; Evans, Katherine J; Hack, James J; Worley, Patrick H
2010-01-01
To gain computational efficiency, a split explicit time integration scheme has been implemented in the CAM spectral Eulerian dynamical core. In this scheme, already present in other dynamical core options within the Community Atmosphere Model, version 4 (CAM), the fluid dynamics portion of the model is subcycled to allow a longer time step for the parameterization schemes. The physics parameterization of CAM is not subject to the stability restrictions of the fluid dynamics, and thus finer spatial resolutions of the model do not require the physics time step to be reduced. A brief outline of the subcycling algorithm implementation and resulting model efficiency improvement is presented. A discussion regarding the effect of the climate statistics derived from short model runs is provided.
Generic solar photovoltaic system dynamic simulation model specification
Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas
2013-10-01
This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intended to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.
Stochastic models of cover class dynamics. [remote sensing of vegetation
NASA Technical Reports Server (NTRS)
Barringer, T. H.; Robinson, V. B.
1981-01-01
Investigations related to satellite remote sensing of vegetation have been concerned with questions of signature identification and extension, cover inventory accuracy, and change detection and monitoring. Attention is given to models of ecological succession, present directions in successional modeling and analysis, nondynamic spatial models, issues in the analysis of spatial data, and aspects of spatial modeling. Issues in time-series analysis are considered along with dynamic spatial models, and problems of model specification and identification.
Dynamic Evolution Model Based on Social Network Services
NASA Astrophysics Data System (ADS)
Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen
2013-11-01
Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.
Dynamic wake distortion model for helicopter maneuvering flight
NASA Astrophysics Data System (ADS)
Zhao, Jinggen
A new rotor dynamic wake distortion model, which can be used to account for the rotor transient wake distortion effect on inflow across the rotor disk during helicopter maneuvering and transitional flight in both hover and forward flight conditions, is developed. The dynamic growths of the induced inflow perturbation across rotor disk during different transient maneuvers, such as a step pitch or roll rate, a step climb rate and a step change of advance ratio are investigated by using a dynamic vortex tube analysis. Based on the vortex tube results, a rotor dynamic wake distortion model, which is expressed in terms of a set of ordinary differential equations, with rotor longitudinal and lateral wake curvatures, wake skew and wake spacing as states, is developed. Also, both the Pitt-Peters dynamic inflow model and the Peters-He finite state inflow model for axial or forward flight are augmented to account for rotor dynamic wake distortion effect during helicopter maneuvering flight. To model the aerodynamic interaction among main rotor, tail rotor and empennage caused by rotor wake curvature effect during helicopter maneuvering flight, a reduced order model based on a vortex tube analysis is developed. Both the augmented Pitt-Peters dynamic inflow model and the augmented Peters-He finite state inflow model, combined with the developed dynamic wake distortion model, together with the interaction model are implemented in a generic helicopter simulation program of UH-60 Black Hawk helicopter and the simulated vehicle control responses in both time domain and frequency domain are compared with flight test data of a UH-60 Black Hawk helicopter in both hover and low speed forward flight conditions.
A System Dynamic Model of Leader Emergence
2008-03-01
complexity and organizational sciences. Applying complexity science to leadership research expands previous notions of leadership beyond dyadic...Contingency approaches to leadership suggest that environmental conditions combined with leader behavoirs , determine leader effectiveness (Judge...events and represents the foundation of understanding system dynamics. Feedback in organizational behavior parlance is simply the reaction to a
A dynamical model for bark beetle outbreaks
Vlastimil Krivan; Mark Lewis; Barbara J. Bentz; Sharon Bewick; Suzanne M. Lenhart; Andrew Liebhold
2016-01-01
Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees...
Modelling emergent patterns of dynamic desert ecosystems
USDA-ARS?s Scientific Manuscript database
In many desert ecosystems vegetation is both patchy and dynamic: vegetated areas are interspersed with patches of bare ground, and both the positioning and the species composition of the vegetated areas exhibit change through time. These characteristics lead to the emergence of multi-scale patterns ...
Modeling Academic Education Processes by Dynamic Storyboarding
ERIC Educational Resources Information Center
Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer
2009-01-01
In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…
Modeling Academic Education Processes by Dynamic Storyboarding
ERIC Educational Resources Information Center
Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer
2009-01-01
In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…
Biomolecular Modeling in a Process Dynamics and Control Course
ERIC Educational Resources Information Center
Gray, Jeffrey J.
2006-01-01
I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large-scale…
Biomolecular Modeling in a Process Dynamics and Control Course
ERIC Educational Resources Information Center
Gray, Jeffrey J.
2006-01-01
I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large-scale…
Exploring the Components of Dynamic Modeling Techniques
ERIC Educational Resources Information Center
Turnitsa, Charles Daniel
2012-01-01
Upon defining the terms modeling and simulation, it becomes apparent that there is a wide variety of different models, using different techniques, appropriate for different levels of representation for any one system to be modeled. Selecting an appropriate conceptual modeling technique from those available is an open question for the practitioner.…
[Dynamic modeling of potato phenological development].
Huang, Chongping; Zhang, Fang; Wang, Aihua; Hu, Bingmin; Yang, Jingping
2004-07-01
By means of systematic demonstration, this study found the mathematical relationship among several temperature driven nonlinear models for crop growth, and amended the limitation of the past nonlinear model in biological usage and the improved model with more general definition. Integrated with four years' field experimental data and Gauss function based temperature effectiveness model submitted in this study, the phenological development model for potato crop was established under different ecological conditions. The phenological development model explained the digital contribution of soil temperature increment on potato growth, and verified by the experimental data from different years and different conditions. There were strict co-relationships between modeling data and experimental data.
A dynamical model for generating synthetic Phonocardiogram signals
Almasi, Ali; Shamsollahi, Mohammad-Bagher; Senhadji, Lotfi
2011-01-01
In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This model is inspired of Electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can be employed to assess biomedical signal processing techniques. PMID:22255630
Modelling the Structure and Dynamics of Biological Pathways
O’Hara, Laura; Livigni, Alessandra; Chen, Sz-Hau; Raza, Sobia; Digard, Paul; Smith, Lee B.; Freeman, Tom C.
2016-01-01
There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems. PMID:27509052
A 4096 atom model of amorphous silicon: Structure and dynamics
NASA Astrophysics Data System (ADS)
Feldman, Joseph L.; Bickham, Scott R.; Davidson, Brian N.; Wooten, Frederick
1997-03-01
We present structural and lattice dynamical information for a 4096 atom model of amorphous silicon. The structural model was obtained, similarly to previously published smaller models, using periodic boundary conditions, the Wooten-Winer-Weaire bond-switching algorithm, and the Broughton-Li relaxation with respect to the Stillinger-Weber potential. The structure is dynamically stable and there is no evidence in the radial distribution function of medium range order. For examining this large model, we use a 1000 processor Connection Machine to compute all the eigenvalues and eigenvectors exactly. The phonon density of states and inverse participation ratio are compared with results for related 216, 432 and 1000-atom models.
Dynamic heat capacity of the east model and of a bead-spring polymer model.
McCoy, John Dwane; Brown, Jonathan R.; Adolf, Douglas Brian
2011-10-01
In this report we have presented a brief review of the glass transition and one means of characterizing glassy materials: linear and nonlinear thermodynamic oscillatory experiments to extract the dynamic heat capacity. We have applied these methods to the east model (a variation of the Ising model for glass forming systems) and a simple polymeric system via molecular dynamics simulation, and our results match what is seen in experiment. For the east model, since the dynamics are so simple, a mathematical model is developed that matches the simulated dynamics. For the polymeric system, since the system is a simulation, we can instantaneously 'quench' the system - removing all vibrational energy - to separate the vibrational dynamics from dynamics associated with particle rearrangements. This shows that the long-time glassy dynamics are due entirely to the particle rearrangements, i.e. basin jumping on the potential energy landscape. Finally, we present an extension of linear dynamic heat capacity to the nonlinear regime.
The Peyrard-Bishop-Dauxois Model of DNA Dynamics
NASA Astrophysics Data System (ADS)
Alexandrov, Boian; Bishop, Alan; Usheva, Anny; Rasmussen, Kim
2008-03-01
This presentation details aspects of the rapid development of the connection between the dynamics of double strand DNA, and experimental findings that has occurred in the recent years. We will approach this topic by demonstrating the Peyrard-Bishop-Dauxois model's ability to provide useful insight on several experimental observations. Specifically, we will discuss the melting behavior of various DNA sequences, and mechanical unzipping through dynamic force spectroscopy. Focusing on viral transcription initiation we will further show how the connection between DNA dynamics and DNA's biological functionality is becoming increasingly strong. Finally, we will describe a probable connection between DNA dynamics and the ability of repair proteins to recognize UV-radiation damages.
Dynamical modeling of drug effect using hybrid systems
2012-01-01
Drug discovery today is a complex, expensive, and time-consuming process with high attrition rate. A more systematic approach is needed to combine innovative approaches in order to lead to more effective and efficient drug development. This article provides systematic mathematical analysis and dynamical modeling of drug effect under gene regulatory network contexts. A hybrid systems model, which merges together discrete and continuous dynamics into a single dynamical model, is proposed to study dynamics of the underlying regulatory network under drug perturbations. The major goal is to understand how the system changes when perturbed by drugs and give suggestions for better therapeutic interventions. A realistic periodic drug intake scenario is considered, drug pharmacokinetics and pharmacodynamics information being taken into account in the proposed hybrid systems model. Simulations are performed using MATLAB/SIMULINK to corroborate the analytical results. PMID:23268741
Dynamic decision modeling in medicine: a critique of existing formalisms.
Leong, T. Y.
1993-01-01
Dynamic decision models are frameworks for modeling and solving decision problems that take into explicit account the effects of time. These formalisms are based on structural and semantical extensions of conventional decision models, e.g., decision trees and influence diagrams, with the mathematical definitions of finite-state semi-Markov processes. This paper identifies the common theoretical basis of existing dynamic decision modeling formalisms, and compares and contrasts their applicability and efficiency. It also argues that a subclass of such dynamic decision problems can be formulated and solved more effectively with non-graphical techniques. Some insights gained from this exercise on automating the dynamic decision making process are summarized. PMID:8130519
Equilibrium and Disequilibrium Dynamics in Cobweb Models with Time Delays
NASA Astrophysics Data System (ADS)
Gori, Luca; Guerrini, Luca; Sodini, Mauro
2015-06-01
This paper aims to study price dynamics in two different continuous time cobweb models with delays close to [Hommes, 1994]. In both cases, the stationary equilibrium may be not representative of the long-term dynamics of the model, since it is possible to observe endogenous and persistent fluctuations (supercritical Hopf bifurcations) even if a deterministic context without external shocks is considered. In the model in which markets are in equilibrium every time, we show that the existence of time delays in the expectations formation mechanism may cause chaotic dynamics similar to those obtained in [Hommes, 1994] in a discrete time context. From a mathematical point of view, we apply the Poincaré-Lindstedt perturbation method to study the local dynamic properties of the models. In addition, several numerical experiments are used to investigate global properties of the systems.
Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models
Background/Question/MethodsDynamic ecological processes may be influenced by many factors. Simulation models thatmimic these processes often have complex implementations with many parameters. Sensitivityanalyses are subsequently used to identify critical parameters whose uncertai...
The ising model on the dynamical triangulated random surface
Aleinov, I.D.; Migelal, A.A.; Zmushkow, U.V. )
1990-04-20
The critical properties of Ising model on the dynamical triangulated random surface embedded in D-dimensional Euclidean space are investigated. The strong coupling expansion method is used. The transition to thermodynamical limit is performed by means of continuous fractions.
Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models
Background/Question/MethodsDynamic ecological processes may be influenced by many factors. Simulation models thatmimic these processes often have complex implementations with many parameters. Sensitivityanalyses are subsequently used to identify critical parameters whose uncertai...
Physiology-based gap model of forest dynamics
Friend, A.D.; Schugart, H.H.; Running, S.W.
1993-01-01
A computer model of forest growth and ecosystem processes is presented. The model, HYBRID, is derived from a forest gap model, an ecosystem process model, and a photosynthesis model. In HYBRID individual trees fix and respire carbon, and lose water daily; carbon partitioning occurs at the end of each year. HYBRID obviates many of the limitations of both gap models and ecosystem process models. The growth equations of gap models are replaced with functionally realistic equations and processes for carbon fixation and partitioning, resulting in a dynamic model in which competition and physiology play important roles.
Forest forming process and dynamic vegetation models under global change
A. Shvidenko; E. Gustafson
2009-01-01
The paper analyzes mathematical models that are used to project the dynamics of forest ecosystems on different spatial and temporal scales. Landscape disturbance and succession models (LDSMs) are of a particular interest for studying the forest forming process in Northern Eurasia. They have a solid empirical background and are able to model ecological processes under...
A Dynamic Systems Theory Model of Visual Perception Development
ERIC Educational Resources Information Center
Coté, Carol A.
2015-01-01
This article presents a model for understanding the development of visual perception from a dynamic systems theory perspective. It contrasts to a hierarchical or reductionist model that is often found in the occupational therapy literature. In this proposed model vision and ocular motor abilities are not foundational to perception, they are seen…
Dynamical Analysis in the Mathematical Modelling of Human Blood Glucose
ERIC Educational Resources Information Center
Bae, Saebyok; Kang, Byungmin
2012-01-01
We want to apply the geometrical method to a dynamical system of human blood glucose. Due to the educational importance of model building, we show a relatively general modelling process using observational facts. Next, two models of some concrete forms are analysed in the phase plane by means of linear stability, phase portrait and vector…
Dynamic Modeling of Marine Bioluminescence and Night Time Leaving Radiance
2012-09-30
physical model is based on the Navy Coastal Ocean Model (NCOM), the biochemical model simulates dynamics of two sizes of phytoplankton, zooplankton ...layer of bioluminescent zooplankton were replaced by water masses advected from the northern coast of the bay with a relatively high presence of mostly
Particle hopping vs. fluid-dynamical models for traffic flow
Nagel, K.
1995-12-31
Although particle hopping models have been introduced into traffic science in the 19509, their systematic use has only started recently. Two reasons for this are, that they are advantageous on modem computers, and that recent theoretical developments allow analytical understanding of their properties and therefore more confidence for their use. In principle, particle hopping models fit between microscopic models for driving and fluiddynamical models for traffic flow. In this sense, they also help closing the conceptual gap between these two. This paper shows connections between particle hopping models and traffic flow theory. It shows that the hydrodynamical limits of certain particle hopping models correspond to the Lighthill-Whitham theory for traffic flow, and that only slightly more complex particle hopping models produce already the correct traffic jam dynamics, consistent with recent fluid-dynamical models for traffic flow. By doing so, this paper establishes that, on the macroscopic level, particle hopping models are at least as good as fluid-dynamical models. Yet, particle hopping models have at least two advantages over fluid-dynamical models: they straightforwardly allow microscopic simulations, and they include stochasticity.
A Dynamic Systems Theory Model of Visual Perception Development
ERIC Educational Resources Information Center
Coté, Carol A.
2015-01-01
This article presents a model for understanding the development of visual perception from a dynamic systems theory perspective. It contrasts to a hierarchical or reductionist model that is often found in the occupational therapy literature. In this proposed model vision and ocular motor abilities are not foundational to perception, they are seen…
AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS
We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...
Growth of Cognitive Abilities: Dynamic Models and Scaling.
ERIC Educational Resources Information Center
Eckstein, Shulamith Graus
2000-01-01
Extends dynamic model of cognitive growth proposed by van Geert in three directions: (1) added a term to consider exposure to material to be learned; (2) developed method to apply model to cross-sectional studies; and (3) developed procedure to scale cognitive abilities tests with items of varying difficulty. Tests model with 2- to 15-year-olds'…
AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS
We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...
Dynamical Analysis in the Mathematical Modelling of Human Blood Glucose
ERIC Educational Resources Information Center
Bae, Saebyok; Kang, Byungmin
2012-01-01
We want to apply the geometrical method to a dynamical system of human blood glucose. Due to the educational importance of model building, we show a relatively general modelling process using observational facts. Next, two models of some concrete forms are analysed in the phase plane by means of linear stability, phase portrait and vector…
Local dynamic subgrid-scale models in channel flow
NASA Technical Reports Server (NTRS)
Cabot, William H.
1994-01-01
The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.
Exploring a Dynamic Model of Trust Management Presentation
2013-08-01
Integrity (ABI) • Parsimonious foundation of trustworthiness indicators (Mayer et al., 1995) – Ability: that group of skills, competencies , and...trustworthiness indicators in the dynamic trust model [Mayer, 1995] • Three factors in the dynamic trust model: – Ability ( competence ), Benevolence...are while you are making the judgment – By culture e.g. individualistic vs. collectivistic cultural influences – competence vs. benevolence
Modeling and Parameterization Study of Radiance in a Dynamic Ocean
2012-09-30
simulation of nonlinear capillary-gravity waves (CGW) • develop numerical capabilities for free-surface turbulence ( FST ) and the resultant surface...based simulations and modeling to solve the problem of ocean RT in a dynamic SBL environment that includes CGW and FST . The complex dynamic...processes of the ocean SBL, the nonlinear CGW interactions, and the development and transport of FST are modeled using physics-based computations. The
Dynamical mean field solution of the Bose-Hubbard model.
Anders, Peter; Gull, Emanuel; Pollet, Lode; Troyer, Matthias; Werner, Philipp
2010-08-27
We present the effective action and self-consistency equations for the bosonic dynamical mean field approximation to the bosonic Hubbard model and show that it provides remarkably accurate phase diagrams and correlation functions. To solve the bosonic dynamical mean field equations, we use a continuous-time Monte Carlo method for bosonic impurity models based on a diagrammatic expansion in the hybridization and condensate coupling. This method is readily generalized to bosonic mixtures, spinful bosons, and Bose-Fermi mixtures.
Modeling of Network Dynamics under Markovian and Structural Perturbations
2011-03-04
U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Markov Dynamics, Networks, Structural...Models by Using Stock Price Data and Basic Statistics, Neural, Parallel & Scientific Computations, Vol. 18(2010), pp. 269-282. 8...Large Deviations with Applications to Exit Times for switched Markov Processes 3. G. S. Ladde and Arnut Paothong, Dynamic Modeling and
Critical domain-wall dynamics of model B.
Dong, R H; Zheng, B; Zhou, N J
2009-05-01
With Monte Carlo methods, we simulate the critical domain-wall dynamics of model B, taking the two-dimensional Ising model as an example. In the macroscopic short-time regime, a dynamic scaling form is revealed. Due to the existence of the quasirandom walkers, the magnetization shows intrinsic dependence on the lattice size L . An exponent which governs the L dependence of the magnetization is measured to be sigma=0.243(8) .
Ship Dynamics in the Surf Zone Model Testing
2008-07-01
Department Technical Report Ship Dynamics in the Surf Zone Model Testing By Miguel Quintero Faydra Schaffer N SW C C D -C IS D -2 00 8...Dynamics in the Surf Zone Model Testing 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 5d. PROJECT NUMBER 6. AUTHOR(S) 5e. TASK...NUMBER Miguel Quintero and Faydra Schaffer 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) AND ADDRESS(ES) 8
Chaotic dynamics in the seasonally forced SIR epidemic model.
Barrientos, Pablo G; Rodríguez, J Ángel; Ruiz-Herrera, Alfonso
2017-04-22
We prove analytically the existence of chaotic dynamics in the forced SIR model. Although numerical experiments have already suggested that this model can exhibit chaotic dynamics, a rigorous proof (without computer-aided) was not given before. Under seasonality in the transmission rate, the coexistence of low birth and mortality rates with high recovery and transmission rates produces infinitely many periodic and aperiodic patterns together with sensitive dependence on the initial conditions.
Developing Generic Dynamic Models for the 2030 Eastern Interconnection Grid
Kou, Gefei; Hadley, Stanton W; Markham, Penn N; Liu, Yilu
2013-12-01
The Eastern Interconnection Planning Collaborative (EIPC) has built three major power flow cases for the 2030 Eastern Interconnection (EI) based on various levels of energy/environmental policy conditions, technology advances, and load growth. Using the power flow cases, this report documents the process of developing the generic 2030 dynamic models using typical dynamic parameters. The constructed model was validated indirectly using the synchronized phasor measurements by removing the wind generation temporarily.
New model describing the dynamical behaviour of penetration rates
NASA Astrophysics Data System (ADS)
Tashiro, Tohru; Minagawa, Hiroe; Chiba, Michiko
2013-02-01
We propose a hierarchical logistic equation as a model to describe the dynamical behaviour of a penetration rate of a prevalent stuff. In this model, a memory, how many people who already possess it a person who does not process it yet met, is considered, which does not exist in the logistic model. As an application, we apply this model to iPod sales data, and find that this model can approximate the data much better than the logistic equation.
A simplified dynamic model of the Space Shuttle main engine
NASA Technical Reports Server (NTRS)
Duyar, Ahmet; Eldem, Vasfi; Merrill, Walter; Guo, Ten-Huei
1991-01-01
A simplified model is presented of the space shuttle main engine (SSME) dynamics valid within the range of operation of the engine. This model is obtained by linking the linearized point models obtained at 25 different operating points of SSME. The simplified model was developed for use with a model-based diagnostic scheme for failure detection and diagnostics studies, as well as control design purposes.
NASA Astrophysics Data System (ADS)
Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco
2016-04-01
Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.
NASA Astrophysics Data System (ADS)
Haberman, Keith
2001-07-01
A micromechanically based constitutive model for the dynamic inelastic behavior of brittle materials, specifically "Dionysus-Pentelicon marble" with distributed microcracking is presented. Dionysus-Pentelicon marble was used in the construction of the Parthenon, in Athens, Greece. The constitutive model is a key component in the ability to simulate this historic explosion and the preceding bombardment form cannon fire that occurred at the Parthenon in 1678. Experiments were performed by Rosakis (1999) that characterized the static and dynamic response of this unique material. A micromechanical constitutive model that was previously successfully used to model the dynamic response of granular brittle materials is presented. The constitutive model was fitted to the experimental data for marble and reproduced the experimentally observed basic uniaxial dynamic behavior quite well. This micromechanical constitutive model was then implemented into the three dimensional nonlinear lagrangain finite element code Dyna3d(1998). Implementing this methodology into the three dimensional nonlinear dynamic finite element code allowed the model to be exercised on several preliminary impact experiments. During future simulations, the model is to be used in conjunction with other numerical techniques to simulate projectile impact and blast loading on the Dionysus-Pentelicon marble and on the structure of the Parthenon.
Guided crowd dynamics via modified social force model
NASA Astrophysics Data System (ADS)
Yang, Xiaoxia; Dong, Hairong; Wang, Qianling; Chen, Yao; Hu, Xiaoming
2014-10-01
Pedestrian dynamics is of great theoretical significance for strategy design of emergency evacuation. Modification of pedestrian dynamics based on the social force model is presented to better reflect pedestrians' behavioral characteristics in emergency. Specifically, the modified model can be used for guided crowd dynamics in large-scale public places such as subway stations and stadiums. This guided crowd model is validated by explicitly comparing its density-speed and density-flow diagrams with fundamental diagrams. Some social phenomena such as gathering, balance and conflicts are clearly observed in simulation, which further illustrate the effectiveness of the proposed modeling method. Also, time delay for pedestrians with time-dependent desired velocities is observed and explained using the established model in this paper. Furthermore, this guided crowd model is applied to the simulation system of Beijing South Railway Station for predictive evacuation experiments.
Mobility and dynamics modeling for unmanned ground vehicle motion planning
NASA Astrophysics Data System (ADS)
Witus, Gary
1999-07-01
This paper presents an approach to modeling unmanned ground vehicle (UGV) mobility performance and vehicle dynamics for evaluating the feasibility and cost of alternative motion plans. Feasibility constraints include power, traction, and roll stability limits. Sensor stabilization performance is considered in a system-level constraint requiring that the obstacle detection distance exceed the stopping distance. Mission time and power requirements are inputs to a multi- attribute cost function for planning under uncertainty. The modeling approach combines a theoretical first-principles mathematical model with an empirical knowledge-based model. The first-principles model predicts performance in an idealized deterministic environment. On-board vehicle dynamics control, for dynamic load balancing and traction management, legitimize some of the simplifying assumptions. The knowledge- based model uses historical relationships to predict the mean and variance of total system performance accounting for the contributions of unplanned reactive behaviors, local terrain variations, and vehicle response transients.
Dynamic analysis of grinding using the population balance model
Williams, M.C. |
1995-12-31
The dynamic behavior of batch mill, CSTR mill, and a closed grinding network consisting of a mill, sump, and cyclone was analyzed using the dynamic population balance model (PBM). The dynamic solution of the PBM of a batch, CSTR and a closed grinding network consisting of a mill, sump, and cyclone forms the basis of the dynamic analysis presented here. Two numerical dynamic solution approaches were used. These are: (1) providing additional constraints on breakage selection functions or (2) performing the Arbiter-Bhrany (or other) normalization of the selection functions. Actual experimental anthracite batch grinding data was used to obtain the functionality of the batch dynamic mill selection and breakage functions for a real physical system. The Levenberg-Marquardt algorithm for systems of constrained non-linear equations is used to solve the batch dynamic PBM grinding equations to obtain the grinding selection and breakage rate functions. The mill, sump and hydrocyclone were modeled as a CSTR operating at various retention times. Batch dynamic PBM data was used to provide the mill kinetic and breakage selection function data. Different dynamic solutions were obtained depending on the numerical approach used. Each solution approach to a dynamic PBM with transport, while giving the same prediction for a single batch grinding time, gives different solutions or predictions for mill composition for other grinding times. This fact makes dynamic nodal analysis and control problematic. The fact that the constraint solution approach gives a solution may suggest that normalization for closed networks is not necessary. Differences in solutions to the PBM cannot be excused away by inaccuracies in the data used to model the grinding phenomenon.
Minimal model for dynamic bonding in colloidal transient networks
NASA Astrophysics Data System (ADS)
Krinninger, Philip; Fortini, Andrea; Schmidt, Matthias
2016-04-01
We investigate a model for colloidal network formation using Brownian dynamics computer simulations. Hysteretic springs establish transient bonds between particles with repulsive cores. If a bonded pair of particles is separated by a cutoff distance, the spring vanishes and reappears only if the two particles contact each other. We present results for the bond lifetime distribution and investigate the properties of the van Hove dynamical two-body correlation function. The model displays crossover from fluidlike dynamics, via transient network formation, to arrested quasistatic network behavior.
Badlands: A parallel basin and landscape dynamics model
NASA Astrophysics Data System (ADS)
Salles, T.
Over more than three decades, a number of numerical landscape evolution models (LEMs) have been developed to study the combined effects of climate, sea-level, tectonics and sediments on Earth surface dynamics. Most of them are written in efficient programming languages, but often cannot be used on parallel architectures. Here, I present a LEM which ports a common core of accepted physical principles governing landscape evolution into a distributed memory parallel environment. Badlands (acronym for BAsin anD LANdscape DynamicS) is an open-source, flexible, TIN-based landscape evolution model, built to simulate topography development at various space and time scales.
Operational dynamic modeling transcending quantum and classical mechanics.
Bondar, Denys I; Cabrera, Renan; Lompay, Robert R; Ivanov, Misha Yu; Rabitz, Herschel A
2012-11-09
We introduce a general and systematic theoretical framework for operational dynamic modeling (ODM) by combining a kinematic description of a model with the evolution of the dynamical average values. The kinematics includes the algebra of the observables and their defined averages. The evolution of the average values is drawn in the form of Ehrenfest-like theorems. We show that ODM is capable of encompassing wide-ranging dynamics from classical non-relativistic mechanics to quantum field theory. The generality of ODM should provide a basis for formulating novel theories.
Operational Dynamic Modeling Transcending Quantum and Classical Mechanics
NASA Astrophysics Data System (ADS)
Bondar, Denys I.; Cabrera, Renan; Lompay, Robert R.; Ivanov, Misha Yu.; Rabitz, Herschel A.
2012-11-01
We introduce a general and systematic theoretical framework for operational dynamic modeling (ODM) by combining a kinematic description of a model with the evolution of the dynamical average values. The kinematics includes the algebra of the observables and their defined averages. The evolution of the average values is drawn in the form of Ehrenfest-like theorems. We show that ODM is capable of encompassing wide-ranging dynamics from classical non-relativistic mechanics to quantum field theory. The generality of ODM should provide a basis for formulating novel theories.
Dynamics of the Kitaev chain model under parametric pumping
NASA Astrophysics Data System (ADS)
Zvyagin, A. A.
2014-07-01
Dynamics of the Kitaev chain model under the effect of parametric pumping is studied. Two contributions to dynamical characteristics are considered: from the extended eigenstates and from the edge bound state (zero Majorana modes). It is shown that in the dynamical regime the frequencies of Rabi oscillations for zero Majorana modes are much larger than those related to gapped extended states. In the steady-state regime, the Rabi oscillations are blurred due to relaxation processes, and only oscillations of the characteristics of the model with the pumping frequency exist, producing absorption of the pumping power by extended states. Experimental realizations of the considered effect are discussed.
Modeling, clustering, and segmenting video with mixtures of dynamic textures.
Chan, Antoni B; Vasconcelos, Nuno
2008-05-01
A dynamic texture is a spatio-temporal generative model for video, which represents video sequences as observations from a linear dynamical system. This work studies the mixture of dynamic textures, a statistical model for an ensemble of video sequences that is sampled from a finite collection of visual processes, each of which is a dynamic texture. An expectationmaximization (EM) algorithm is derived for learning the parameters of the model, and the model is related to previous works in linear systems, machine learning, time-series clustering, control theory, and computer vision. Through experimentation, it is shown that the mixture of dynamic textures is a suitable representation for both the appearance and dynamics of a variety of visual processes that have traditionally been challenging for computer vision (e.g. fire, steam, water, vehicle and pedestrian traffic, etc.). When compared with state-of-the-art methods in motion segmentation, including both temporal texture methods and traditional representations (e.g. optical flow or other localized motion representations), the mixture of dynamic textures achieves superior performance in the problems of clustering and segmenting video of such processes.
Gradient dynamics models for liquid films with soluble surfactant
NASA Astrophysics Data System (ADS)
Thiele, Uwe; Archer, Andrew J.; Pismen, Len M.
2016-12-01
In this paper we propose equations of motion for the dynamics of liquid films of surfactant suspensions that consist of a general gradient dynamics framework based on an underlying energy functional. This extends the gradient dynamics approach to dissipative nonequilibrium thin-film systems with several variables and casts their dynamic equations into a form that reproduces Onsager's reciprocity relations. We first discuss the general form of gradient dynamics models for an arbitrary number of fields and discuss simple well-known examples with one or two fields. Next we develop the three-field gradient dynamics model for a thin liquid film covered by soluble surfactant and discuss how it automatically results in consistent convective (driven by pressure gradients, Marangoni forces, and Korteweg stresses), diffusive, adsorption or desorption, and evaporation fluxes. We then show that in the dilute limit, the model reduces to the well-known hydrodynamic form that includes Marangoni fluxes due to a linear equation of state. In this case the energy functional incorporates wetting energy, surface energy of the free interface (constant contribution plus an entropic term), and bulk mixing entropy. Subsequently, as an example, we show how various extensions of the energy functional result in consistent dynamical models that account for nonlinear equations of state, concentration-dependent wettability, and surfactant and film bulk decomposition phase transitions. We conclude with a discussion of further possible extensions towards systems with micelles, surfactant adsorption at the solid substrate, and bioactive behavior.
A Lagrangian dynamic subgrid-scale model turbulence
NASA Technical Reports Server (NTRS)
Meneveau, C.; Lund, T. S.; Cabot, W.
1994-01-01
A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.
Dynamic reactor modeling with applications to SPR and ZEDNA
Suo-Anttila, Ahti Jorma
2011-12-01
A dynamic reactor model has been developed for pulse-type reactor applications. The model predicts reactor power, axial and radial fuel expansion, prompt and delayed neutron population, and prompt and delayed gamma population. All model predictions are made as a function of time. The model includes the reactivity effect of fuel expansion on a dynamic timescale as a feedback mechanism for reactor power. All inputs to the model are calculated from first principles, either directly by solving systems of equations, or indirectly from Monte Carlo N-Particle Transport Code (MCNP) derived results. The model does not include any empirical parameters that can be adjusted to match experimental data. Comparisons of model predictions to actual Sandia Pulse Reactor SPR-III pulses show very good agreement for a full range of pulse magnitudes. The model is also applied to Z-pinch externally driven neutron assembly (ZEDNA) type reactor designs to model both normal and off-normal ZEDNA operations.
Dynamic inverse models in human-cyber-physical systems
NASA Astrophysics Data System (ADS)
Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar
2016-05-01
Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.
Dynamical real space renormalization group applied to sandpile models.
Ivashkevich, E V; Povolotsky, A M; Vespignani, A; Zapperi, S
1999-08-01
A general framework for the renormalization group analysis of self-organized critical sandpile models is formulated. The usual real space renormalization scheme for lattice models when applied to nonequilibrium dynamical models must be supplemented by feedback relations coming from the stationarity conditions. On the basis of these ideas the dynamically driven renormalization group is applied to describe the boundary and bulk critical behavior of sandpile models. A detailed description of the branching nature of sandpile avalanches is given in terms of the generating functions of the underlying branching process.
ERCOT's Dynamic Model of Wind Turbine Generators: Preprint
Muljadi, E.; Butterfield, C. P.; Conto, J.; Donoho, K.
2005-08-01
By the end of 2003, the total installed wind farm capacity in the Electric Reliability Council of Texas (ERCOT) system was approximately 1 gigawatt (GW) and the total in the United States was about 5 GW. As the number of wind turbines installed throughout the United States increases, there is a greater need for dynamic wind turbine generator models that can properly model entire power systems for different types of analysis. This paper describes the ERCOT dynamic models and simulations of a simple network with different types of wind turbine models currently available.
Modeling Tools Predict Flow in Fluid Dynamics
NASA Technical Reports Server (NTRS)
2010-01-01
"Because rocket engines operate under extreme temperature and pressure, they present a unique challenge to designers who must test and simulate the technology. To this end, CRAFT Tech Inc., of Pipersville, Pennsylvania, won Small Business Innovation Research (SBIR) contracts from Marshall Space Flight Center to develop software to simulate cryogenic fluid flows and related phenomena. CRAFT Tech enhanced its CRUNCH CFD (computational fluid dynamics) software to simulate phenomena in various liquid propulsion components and systems. Today, both government and industry clients in the aerospace, utilities, and petrochemical industries use the software for analyzing existing systems as well as designing new ones."
DYNAMICAL MODEL OF AN EXPANDING SHELL
Pe'er, Asaf
2012-06-10
Expanding blast waves are ubiquitous in many astronomical sources, such as supernova remnants, X-ray emitting binaries, and gamma-ray bursts. I consider here the dynamics of such an expanding blast wave, both in the adiabatic and the radiative regimes. As the blast wave collects material from its surroundings, it decelerates. A full description of the temporal evolution of the blast wave requires consideration of both the energy density and the pressure of the shocked material. The obtained equation is different from earlier works in which only the energy was considered. The solution converges to the familiar results in both the ultrarelativistic and the sub-relativistic (Newtonian) regimes.
Generalized force model of traffic dynamics
NASA Astrophysics Data System (ADS)
Helbing, Dirk; Tilch, Benno
1998-07-01
Floating car data of car-following behavior in cities were compared to existing microsimulation models, after their parameters had been calibrated to the experimental data. With these parameter values, additional simulations have been carried out, e.g., of a moving car which approaches a stopped car. It turned out that, in order to manage such kinds of situations without producing accidents, improved traffic models are needed. Good results were obtained with the proposed generalized force model.
LETTER: Dynamic instability in a phenomenological model of correlated assets
NASA Astrophysics Data System (ADS)
Raffaelli, Giacomo; Marsili, Matteo
2006-08-01
We show that financial correlations exhibit a non-trivial dynamic behaviour. We introduce a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affected by investment based on it. We show that such a feedback on correlations gives rise to an instability when the volume of investment exceeds a critical value. Close to the critical point the model exhibits dynamical correlations very similar to those observed in real markets. Maximum likelihood estimates of the model's parameter for empirical data indeed confirm this conclusion, thus suggesting that real markets operate close to a dynamically unstable point.
Dynamic brittle material response based on a continuum damage model
Chen, E.P.
1994-12-31
The response of brittle materials to dynamic loads was studied in this investigation based on a continuum damage model. Damage mechanism was selected to be interaction and growth of subscale cracks. Briefly, the cracks are activated by bulk tension and the density of activated cracks are described by a Weibull statistical distribution. The moduli of a cracked solid derived by Budiansky and O`Connell are then used to represent the global material degradation due to subscale cracking. This continuum damage model was originally developed to study rock fragmentation and was modified in the present study to improve on the post-limit structural response. The model was implemented into a transient dynamic explicit finite element code PRONTO 2D and then used for a numerical study involving the sudden stretching of a plate with a centrally located hole. Numerical results characterizing the dynamic responses of the material were presented. The effect of damage on dynamic material behavior was discussed.
Dynamical aspects in modeling long cantilevering workpieces in tool grinding
NASA Astrophysics Data System (ADS)
de Payrebrune, K. M.; Kröger, M.
2015-10-01
Tool grinding is a complex process in which temporal dynamics of workpiece and grinding wheel, and the material removal process itself, affect the quality of the workpiece. Many existing models already provide the option to study the dynamics of workpiece and grinding wheel or cutting forces and material removal processes, but mostly do not combine these aspects. Here, workpiece dynamics are studied in relation to its structural and geometrical changing properties during machining, and are used to simulate the vibrations and deformation of the workpiece during grinding. In combination with models for the grinding wheel and the material removal process, dependencies of the workpiece dynamics on the workpieces quality are studied and results from this hybrid model are in excellent agreement with empirical measurements. Furthermore, the results demonstrate the significant effects of deformations of the workpiece on its final geometry.
Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research
NASA Technical Reports Server (NTRS)
Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter
2008-01-01
Under the NASA Fundamental Aeronautics Program, the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero-Propulso-Servo-Elastic model and for propulsion efficiency studies.
Structural Identifiability of Dynamic Systems Biology Models
Villaverde, Alejandro F.
2016-01-01
A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726
Structural Identifiability of Dynamic Systems Biology Models.
Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis
2016-10-01
A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.
Development of a Stirling System Dynamic Model With Enhanced Thermodynamics
NASA Technical Reports Server (NTRS)
Regan, Timothy F.; Lewandowski, Edward J.
2005-01-01
The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.
Integrating microbial diversity in soil carbon dynamic models parameters
NASA Astrophysics Data System (ADS)
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten