Dynamic colloidal assembly pathways via low dimensional models
Energy Technology Data Exchange (ETDEWEB)
Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu [Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Thyagarajan, Raghuram; Ford, David M. [Chemical Engineering, University of Massachusetts, Amherst, Massachusetts 01003 (United States)
2016-05-28
Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterized by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.
Low dimensional modeling of wall turbulence
Aubry, Nadine
2015-11-01
In this talk we will review the original low dimensional dynamical model of the wall region of a turbulent boundary layer [Aubry, Holmes, Lumley and Stone, Journal of Fluid Dynamics 192, 1988] and discuss its impact on the field of fluid dynamics. We will also invite a few researchers who would like to make brief comments on the influence Lumley had on their research paths. In collaboration with Philip Holmes, Program in Applied and Computational Mathematics and Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ.
PREFACE: Dynamics of low-dimensional systems Dynamics of low-dimensional systems
Bernasconi, M.; Miret-Artés, S.; Toennies, J. P.
2012-03-01
vibrational spectra of clusters and carbon-based nanostructures, just to name a few of the low-dimensional systems addressed in this special issue, can be both accurately computed from first principles and measured experimentally. Even less computationally demanding semi-empirical simulations based on tight-binding or continuum models play a crucial role in assessing, for instance, the interplay between morphology, defects and the elastic properties of low-dimensional systems. The impressive amount of work and progress achieved in the past decade within the general theory and spectroscopy of the dynamics of low-dimensional systems is marked by several relevant trends that are exemplified by the contributions gathered together in this special issue. They span a wide spectrum of experimental and theoretical methods applied to the study of the dynamical properties of low-dimensional systems and new emerging phenomena at the nanoscale, such as the peculiar optical properties of ring shaped quantum dots, plasmon dynamics in metallic nanoclusters and the relaxation dynamics of nanomagnets. This issue is dedicated to our esteemed colleague Giorgio Benedek on the occasion of his 70th birthday. It collects together a number of papers written by authors from all over the world with a recognized reputation in the above mentioned fields where Giorgio Benedek has made important and fundamental contributions. Dynamics of low-dimensional systems contents Narratives Giorgio Benedek: an extraordinary universal scientist M Bernasconi, S Miret-Artés and J P Toennies Helium and carbon: two friends for life Giorgio Benedek Special Issue Papers Temperature dependence in atom-surface scattering Eli Pollak and J R Manson Density functional study of the decomposition pathways of SiH3 and GeH3 at the Si(100) and Ge(100) surfaces M Ceriotti, F Montalenti and M Bernasconi Comparative study of vibrations in submonolayer structures of potassium on Pt(111) G G Rusina, S V Eremeev, S D Borisova and E V
Are low-dimensional dynamics typical in magnetically confined plasmas?
International Nuclear Information System (INIS)
Ball, R.; Dewar, R.L.
2000-01-01
Full text: Since 1988 there have been many serious attempts to construct low-dimensional dynamical systems that model L-H transitions and associated oscillatory phenomena in magnetically confined plasmas. Such models usually consist of coupled ordinary differential equations in a few dynamical state variables and several parameters that represent physical properties or external controls. The advantages of a unified, low-dimensional approach to modelling plasma behaviour are multifold. Most importantly, the qualitative analysis of nonlinear ODE and algebraic systems is supported by a substantial body of theory. The toolkits of singularity and stability theory are well-developed and accessible, and contain the right tools for the job of charting the state and parameter space. One of the driving forces behind the development of low-dimensional dynamical models is the predictive potential of a parameter map. For example, a model that talks of the shape and extent of hysteresis in the L-H transition would help engineers who are interested in controlling access to H-mode. We can express this problem another way: given the enormous number of variables and parameters that could be varied around a hysteretic regime, it would be cheaper to know in advance which ones actually do influence the quality and quantity of the hysteresis. The quest for a low-dimensional state space that contains the qualitative dynamics of L-H transitions also introduces other problems. We need to identify the essential (few) dynamical variables and the essential (few) independent parameter groups, clarify the mechanisms for the feedback that is modelled by nonlinear terms, and identify symmetries in the physics. Before jumping the gun on these questions the fundamental issue should be addressed of whether a confined plasma, having many important length and time scales, steep gradients, strong anisotropy, and an uncountable multiplicity of states, can indeed exhibit low-dimensional dynamics. In this
A low dimensional dynamical system for the wall layer
Aubry, N.; Keefe, L. R.
1987-01-01
Low dimensional dynamical systems which model a fully developed turbulent wall layer were derived.The model is based on the optimally fast convergent proper orthogonal decomposition, or Karhunen-Loeve expansion. This decomposition provides a set of eigenfunctions which are derived from the autocorrelation tensor at zero time lag. Via Galerkin projection, low dimensional sets of ordinary differential equations in time, for the coefficients of the expansion, were derived from the Navier-Stokes equations. The energy loss to the unresolved modes was modeled by an eddy viscosity representation, analogous to Heisenberg's spectral model. A set of eigenfunctions and eigenvalues were obtained from direct numerical simulation of a plane channel at a Reynolds number of 6600, based on the mean centerline velocity and the channel width flow and compared with previous work done by Herzog. Using the new eigenvalues and eigenfunctions, a new ten dimensional set of ordinary differential equations were derived using five non-zero cross-stream Fourier modes with a periodic length of 377 wall units. The dynamical system was integrated for a range of the eddy viscosity prameter alpha. This work is encouraging.
Mangiarotti, Sylvain; Drapeau, Laurent
2013-04-01
The global modeling approach aims to obtain parsimonious models of observed dynamics from few or single time series (Letellier et al. 2009). Specific algorithms were developed and validated for this purpose (Mangiarotti et al. 2012a). This approach was applied to the dynamics of cereal crops in semi-arid region using the vegetation index derived from satellite data as a proxy of the dynamics. A low-dimensional autonomous model could be obtained. The corresponding attractor is characteristic of weakly dissipative chaos and exhibits a toroidal-like structure. At present, only few theoretical cases of such chaos are known, and none was obtained from real world observations. Under smooth conditions, a robust validation of three-dimensional chaotic models can be usually performed based on the topological approach (Gilmore 1998). Such approach becomes more difficult for weakly dissipative systems, and almost impossible under noisy observational conditions. For this reason, another validation approach is developed which consists in comparing the forecasting skill of the model to other forecasts for which no dynamical model is required. A data assimilation process is associated to the model to estimate the model's skill; several schemes are tested (simple re-initialization, Extended and Ensemble Kalman Filters and Back and Forth Nudging). Forecasts without model are performed based on the search of analogous states in the phase space (Mangiarotti et al. 2012b). The comparison reveals the quality of the model's forecasts at short to moderate horizons and contributes to validate the model. These results suggest that the dynamics of cereal crops can be reasonably approximated by low-dimensional chaotic models, and also bring out powerful arguments for chaos. Chaotic models have often been used as benchmark to test data assimilation schemes; the present work shows that such tests may not only have a theoretical interest, but also almost direct applicative potential. Moreover
Directory of Open Access Journals (Sweden)
Karishma eChhabria
2016-03-01
Full Text Available The motivation of developing simple minimal models for neuro-glio-vascular system arises from a recent modeling study elucidating the bidirectional information flow within the neuro-glio-vascular system having 89 dynamic equations (Chander and Chakravarthy 2012. While this was one of the first attempts at formulating a comprehensive model for neuro-glia-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the neuro-glio-vascular system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system which takes neural firing rate as input and returns an ‘energy’ variable (analogous to ATP as output. To this end we present two models: Biophysical neuro-energy (Model #1 with 5 variables, comprising of KATP channel activity governed by neuronal ATP dynamics and the Dynamic threshold (Model #2 with 3 variables depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes such as continuous spiking, phasic and tonic bursting depending on the ATP production coefficient, εp and external current. We then demonstrate that in a network comprising of such energy-dependent neuron units, εp could modulate the Local field potential (LFP frequency and amplitude. Interestingly, low frequency LFP dominates under low εp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed ‘neuron-energy’ unit may be implemented in building models of neuro-glio-vascular networks to simulate data obtained from multimodal neuroimaging systems such as fNIRS-EEG and fMRI-EEG. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies such as non-invasive brain stimulation for
Chhabria, Karishma; Chakravarthy, V Srinivasa
2016-01-01
The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low--dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an "energy" variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising KATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛp, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛp could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed "neuron-energy" unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as
Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach
2013-09-30
statistically extratropical storms and extremes, and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson, Lei Wang...forecast models, as well as in the understanding they have generated. Adam Sobel, Daehyun Kim and Shuguang Wang. Extratropical variability and...predictability. Determine the extent to which extratropical monthly and seasonal low-frequency variability (LFV, i.e. PNA, NAO, as well as other regional
Scientific data interpolation with low dimensional manifold model
Zhu, Wei; Wang, Bao; Barnard, Richard; Hauck, Cory D.; Jenko, Frank; Osher, Stanley
2018-01-01
We propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace-Beltrami operator in the Euler-Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on data compression and interpolation from both regular and irregular samplings.
Scientific data interpolation with low dimensional manifold model
International Nuclear Information System (INIS)
Zhu, Wei; Wang, Bao; Barnard, Richard C.; Hauck, Cory D.
2017-01-01
Here, we propose to apply a low dimensional manifold model to scientific data interpolation from regular and irregular samplings with a significant amount of missing information. The low dimensionality of the patch manifold for general scientific data sets has been used as a regularizer in a variational formulation. The problem is solved via alternating minimization with respect to the manifold and the data set, and the Laplace–Beltrami operator in the Euler–Lagrange equation is discretized using the weighted graph Laplacian. Various scientific data sets from different fields of study are used to illustrate the performance of the proposed algorithm on data compression and interpolation from both regular and irregular samplings.
Truccolo, Wilson
2016-11-01
This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.
Dynamic screening and electron dynamics in low-dimensional metal systems
International Nuclear Information System (INIS)
Silkin, V.M.; Quijada, M.; Vergniory, M.G.; Alducin, M.; Borisov, A.G.; Diez Muino, R.; Juaristi, J.I.; Sanchez-Portal, D.; Chulkov, E.V.; Echenique, P.M.
2007-01-01
Recent advances in the theoretical description of dynamic screening and electron dynamics in metallic media are reviewed. The time-dependent building-up of screening in different situations is addressed. Perturbative and non-perturbative theories are used to study electron dynamics in low-dimensional systems, such as metal clusters, image states, surface states and quantum wells. Modification of the electronic lifetimes due to confinement effects is analyzed as well
Gritsev, Vladimir; Demler, Eugene; Lukin, Mikhail; Polkovnikov, Anatoli
2007-11-16
We study the problem of rapid change of the interaction parameter (quench) in a many-body low-dimensional system. It is shown that, measuring the correlation functions after the quench, the information about a spectrum of collective excitations in a system can be obtained. This observation is supported by analysis of several integrable models and we argue that it is valid for nonintegrable models as well. Our conclusions are supplemented by performing exact numerical simulations on finite systems. We propose that measuring the power spectrum in a dynamically split 1D Bose-Einsten condensate into two coupled condensates can be used as an experimental test of our predictions.
Lecca, Paola; Mura, Ivan; Re, Angela; Barker, Gary C; Ihekwaba, Adaoha E C
2016-01-01
Chaotic behavior refers to a behavior which, albeit irregular, is generated by an underlying deterministic process. Therefore, a chaotic behavior is potentially controllable. This possibility becomes practically amenable especially when chaos is shown to be low-dimensional, i.e., to be attributable to a small fraction of the total systems components. In this case, indeed, including the major drivers of chaos in a system into the modeling approach allows us to improve predictability of the systems dynamics. Here, we analyzed the numerical simulations of an accurate ordinary differential equation model of the gene network regulating sporulation initiation in Bacillus subtilis to explore whether the non-linearity underlying time series data is due to low-dimensional chaos. Low-dimensional chaos is expectedly common in systems with few degrees of freedom, but rare in systems with many degrees of freedom such as the B. subtilis sporulation network. The estimation of a number of indices, which reflect the chaotic nature of a system, indicates that the dynamics of this network is affected by deterministic chaos. The neat separation between the indices obtained from the time series simulated from the model and those obtained from time series generated by Gaussian white and colored noise confirmed that the B. subtilis sporulation network dynamics is affected by low dimensional chaos rather than by noise. Furthermore, our analysis identifies the principal driver of the networks chaotic dynamics to be sporulation initiation phosphotransferase B (Spo0B). We then analyzed the parameters and the phase space of the system to characterize the instability points of the network dynamics, and, in turn, to identify the ranges of values of Spo0B and of the other drivers of the chaotic dynamics, for which the whole system is highly sensitive to minimal perturbation. In summary, we described an unappreciated source of complexity in the B. subtilis sporulation network by gathering
Low Dimensional Semiconductor Structures Characterization, Modeling and Applications
Horing, Norman
2013-01-01
Starting with the first transistor in 1949, the world has experienced a technological revolution which has permeated most aspects of modern life, particularly over the last generation. Yet another such revolution looms up before us with the newly developed capability to control matter on the nanometer scale. A truly extraordinary research effort, by scientists, engineers, technologists of all disciplines, in nations large and small throughout the world, is directed and vigorously pressed to develop a full understanding of the properties of matter at the nanoscale and its possible applications, to bring to fruition the promise of nanostructures to introduce a new generation of electronic and optical devices. The physics of low dimensional semiconductor structures, including heterostructures, superlattices, quantum wells, wires and dots is reviewed and their modeling is discussed in detail. The truly exceptional material, Graphene, is reviewed; its functionalization and Van der Waals interactions are included h...
Low-dimensional model of resistive interchange convection in magnetized plasma
International Nuclear Information System (INIS)
Bazdenkov, S.; Sato, Tetsuya
1997-09-01
Self-organization and generation of large shear flow component in turbulent resistive interchange convection in magnetized plasma is considered. The effect of plasma density-electrostatic potential coupling via the inertialess electron dynamics along the magnetic field is shown to play significant role in the onset of shear component. The results of large-scale numerical simulation and low-dimensional (reduced) model are presented and compared. (author)
Jordan-Wigner fermionization and the theory of low-dimensional quantum spin models
International Nuclear Information System (INIS)
Derzhko, O.
2007-01-01
The idea of mapping quantum spin lattice model onto fermionic lattice model goes back to Jordan and Wigner (1928) who transformed s = 1/2 operators which commute at different lattice sites into fermionic operators. Later on the Jordan-Wigner transformation was used for mapping one-dimensional s = 1/2 isotropic XY (XX) model onto an exactly solvable tight-binding model of spinless fermions (Lieb, Schultz and Mattis, 1961). Since that times the Jordan-Wigner transformation is known as a powerful tool in the condensed matter theory especially in the theory of low-dimensional quantum spin systems. The aim of these lectures is to review the applications of the Jordan-Wigner fermionization technique for calculating dynamic properties of low-dimensional quantum spin models. The dynamic quantities (such as dynamic structure factors or dynamic susceptibilities) are observable directly or indirectly in various experiments. The frequency and wave-vector dependence of the dynamic quantities yields valuable information about the magnetic structure of materials. Owing to a tremendous recent progress in synthesizing low-dimensional magnetic materials detailed comparisons of theoretical results with direct experimental observation are becoming possible. The lectures are organized as follows. After a brief introduction of the Jordan-Wigner transformation for one-dimensional spin one half systems and some of its extensions for higher dimensions and higher spin values we focus on the dynamic properties of several low-dimensional quantum spin models. We start from a famous s = 1/2 XX chain. As a first step we recall well-known results for dynamics of the z-spin-component fluctuation operator and then turn to dynamics of the dimer and trimer fluctuation operators. The dynamics of the trimer fluctuations involves both the two fermion (one particle and one hole) and the four-fermion (two particles and two holes) excitations. We discuss some properties of the two-fermion and four
DEFF Research Database (Denmark)
Hvam, Jørn Märcher; Langbein, Wolfgang; Borri, Paola
1999-01-01
Coherent optical spectroscopy in the form of nonlinear transient four-wave mixing (TFWM) and linear resonant Rayleigh scattering (RRS) has been applied to investigate the exciton dynamics of low-dimensional semiconductor heterostructures. The dephasing times of excitons are determined from...
ABC-model analysis of gain-switched pulse characteristics in low-dimensional semiconductor lasers
Bao, Xumin; Liu, Yuejun; Weng, Guoen; Hu, Xiaobo; Chen, Shaoqiang
2018-01-01
The gain-switching dynamics of low-dimensional semiconductor lasers is simulated numerically by using a two-dimensional rate-equation model. Use is also made of the ABC model, where the carrier recombination rate is described by a function of carrier densities including Shockley - Read - Hall (SRH) recombination coefficient A, spontaneous emission coefficient B and Auger recombination coefficient C. Effects of the ABC parameters on the ultrafast gain-switched pulse characteristics with high-density pulse excitation are analysed. It is found that while the parameter A has almost no obvious effects, the parameters B and C have distinctly different effects: B influences significantly the delay time of the gain-switched pulse, while C affects mainly the pulse intensity.
Savin, Alexander V.; Kosevich, Yuriy A.; Cantarero, Andres
2012-08-01
We present a detailed description of semiquantum molecular dynamics simulation of stochastic dynamics of a system of interacting particles. Within this approach, the dynamics of the system is described with the use of classical Newtonian equations of motion in which the effects of phonon quantum statistics are introduced through random Langevin-like forces with a specific power spectral density (the color noise). The color noise describes the interaction of the molecular system with the thermostat. We apply this technique to the simulation of thermal properties and heat transport in different low-dimensional nanostructures. We describe the determination of temperature in quantum lattice systems, to which the equipartition limit is not applied. We show that one can determine the temperature of such a system from the measured power spectrum and temperature- and relaxation-rate-independent density of vibrational (phonon) states. We simulate the specific heat and heat transport in carbon nanotubes, as well as the heat transport in molecular nanoribbons with perfect (atomically smooth) and rough (porous) edges, and in nanoribbons with strongly anharmonic periodic interatomic potentials. We show that the effects of quantum statistics of phonons are essential for the carbon nanotube in the whole temperature range T<500K, in which the values of the specific heat and thermal conductivity of the nanotube are considerably less than that obtained within the description based on classical statistics of phonons. This conclusion is also applicable to other carbon-based materials and systems with high Debye temperature like graphene, graphene nanoribbons, fullerene, diamond, diamond nanowires, etc. We show that the existence of rough edges and quantum statistics of phonons change drastically the low-temperature thermal conductivity of the nanoribbon in comparison with that of the nanoribbon with perfect edges and classical phonon dynamics and statistics. The semiquantum molecular
Low-dimensional modeling of a driven cavity flow with two free parameters
DEFF Research Database (Denmark)
Jørgensen, Bo Hoffmann; Sørensen, Jens Nørkær; Brøns, Morten
2003-01-01
. By carrying out such a procedure one obtains a low-dimensional model consisting of a reduced set of Ordinary Differential Equations (ODEs) which models the original equations. A technique called Sequential Proper Orthogonal Decomposition (SPOD) is developed to perform decompositions suitable for low...... parameters to appear in the inhomogeneous boundary conditions without the addition of any constraints. This is necessary because both the driving lid and the rotating rod are controlled simultaneously. Apparently, the results reported for this model are the first to be obtained for a low-dimensional model...
Effective method for construction of low-dimensional models for heat transfer process
Energy Technology Data Exchange (ETDEWEB)
Blinov, D.G.; Prokopov, V.G.; Sherenkovskii, Y.V.; Fialko, N.M.; Yurchuk, V.L. [National Academy of Sciences of Ukraine, Kiev (Ukraine). Inst. of Engineering Thermophysics
2004-12-01
A low-dimensional model based on the method of proper orthogonal decomposition (POD) and the method of polyargumental systems (MPS) for thermal conductivity problems with strongly localized source of heat has been presented. The key aspect of these methods is that they enable to avoid weak points of other projection methods, which consists in a priori choice of basis functions. It enables us to use the MPS method and the POD method as convenient means to construct low-dimensional models of heat and mass transfer problems. (Author)
Low dimensional chaotic models for the plague epidemic in Bombay (1896–1911)
International Nuclear Information System (INIS)
Mangiarotti, Sylvain
2015-01-01
A plague epidemic broke out in Bombay in 1896 and became endemic. From 1905 to 1911, the epidemic was closely monitored by an Advisory Committee appointed to investigate the causes of the disease in any way. An impressive quantity of information was gathered, analyzed and published. Published data include records of the number of people who died from plague, and of the two main populations of rodents which were infected by plague in Bombay city. In the present paper, these data are revisited using a global modeling technique. This technique is applied to both single and multivariate observational time series. Several models are obtained for which a chaotic behavior can be observed. Obtaining such models proves that the dynamics of plague can be approximated by low-dimensional deterministic systems that can produce chaos. The multivariate models give a strong argument for interactive couplings between the epidemic and the epizootics of the two main species of rat. An interpretation of this coupling is given.
On low-dimensional models at NMR line shape analysis in nanomaterial systems
Kucherov, M. M.; Falaleev, O. V.
2018-03-01
We present a model of localized spin dynamics at room temperature for the low-dimensional solid-state spin system, which contains small ensembles of magnetic nuclei (N ~ 40). The standard spin Hamiltonian (XXZ model) is the sum of the Zeeman term in a strong external magnetic field and the magnetic dipole interaction secular term. The 19F spins in a single crystal of fluorapatite [Ca5(PO4)3F] have often been used to approximate a one-dimensional spin system. If the constant external field is parallel to the c axis, the 3D 19F system may be treated as a collection of many identical spin chains. When considering the longitudinal part of the secular term, we suggest that transverse component of a spin in a certain site rotates in a constant local magnetic field. This field changes if the spin jumps to another site. On return, this spin continues to rotate in the former field. Then we expand the density matrix in a set of eigenoperators of the Zeeman Hamiltonian. A system of coupled differential equations for the expansion coefficients then solved by straightforward numerical methods, and the fluorine NMR line shapes of fluorapatite for different chain lengths are calculated.
Sartori, Massimo; Gizzi, Leonardo; Lloyd, David G; Farina, Dario
2013-01-01
Human locomotion has been described as being generated by an impulsive (burst-like) excitation of groups of musculotendon units, with timing dependent on the biomechanical goal of the task. Despite this view being supported by many experimental observations on specific locomotion tasks, it is still unknown if the same impulsive controller (i.e., a low-dimensional set of time-delayed excitastion primitives) can be used as input drive for large musculoskeletal models across different human locomotion tasks. For this purpose, we extracted, with non-negative matrix factorization, five non-negative factors from a large sample of muscle electromyograms in two healthy subjects during four motor tasks. These included walking, running, sidestepping, and crossover cutting maneuvers. The extracted non-negative factors were then averaged and parameterized to obtain task-generic Gaussian-shaped impulsive excitation curves or primitives. These were used to drive a subject-specific musculoskeletal model of the human lower extremity. Results showed that the same set of five impulsive excitation primitives could be used to predict the dynamics of 34 musculotendon units and the resulting hip, knee and ankle joint moments (i.e., NRMSE = 0.18 ± 0.08, and R (2) = 0.73 ± 0.22 across all tasks and subjects) without substantial loss of accuracy with respect to using experimental electromyograms (i.e., NRMSE = 0.16 ± 0.07, and R (2) = 0.78 ± 0.18 across all tasks and subjects). Results support the hypothesis that biomechanically different motor tasks might share similar neuromuscular control strategies. This might have implications in neurorehabilitation technologies such as human-machine interfaces for the torque-driven, proportional control of powered prostheses and orthoses. In this, device control commands (i.e., predicted joint torque) could be derived without direct experimental data but relying on simple parameterized Gaussian-shaped curves, thus decreasing the input drive
Tegner, Jesper; Zenil, Hector; Kiani, Narsis A.; Ball, Gordon; Gomez-Cabrero, David
2016-01-01
Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems.
Tegner, Jesper
2016-10-04
Systems in nature capable of collective behaviour are nonlinear, operating across several scales. Yet our ability to account for their collective dynamics differs in physics, chemistry and biology. Here, we briefly review the similarities and differences between mathematical modelling of adaptive living systems versus physico-chemical systems. We find that physics-based chemistry modelling and computational neuroscience have a shared interest in developing techniques for model reductions aiming at the identification of a reduced subsystem or slow manifold, capturing the effective dynamics. By contrast, as relations and kinetics between biological molecules are less characterized, current quantitative analysis under the umbrella of bioinformatics focuses on signal extraction, correlation, regression and machine-learning analysis. We argue that model reduction analysis and the ensuing identification of manifolds bridges physics and biology. Furthermore, modelling living systems presents deep challenges as how to reconcile rich molecular data with inherent modelling uncertainties (formalism, variables selection and model parameters). We anticipate a new generative data-driven modelling paradigm constrained by identified governing principles extracted from low-dimensional manifold analysis. The rise of a new generation of models will ultimately connect biology to quantitative mechanistic descriptions, thereby setting the stage for investigating the character of the model language and principles driving living systems.
Directory of Open Access Journals (Sweden)
Ezequiel M Arneodo
Full Text Available Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform.
Salty popcorn in a homogeneous low-dimensional toy model of holographic QCD
International Nuclear Information System (INIS)
Elliot-Ripley, Matthew
2017-01-01
Recently, a homogeneous ansatz has been used to study cold dense nuclear matter in the Sakai–Sugimoto model of holographic QCD. To justify this homogeneous approximation we here investigate a homogeneous ansatz within a low-dimensional toy version of Sakai–Sugimoto to study finite baryon density configurations and compare it to full numerical solutions. We find the ansatz corresponds to enforcing a dyon salt arrangement in which the soliton solutions are split into half-soliton layers. Within this ansatz we find analogues of the proposed baryonic popcorn transitions, in which solutions split into multiple layers in the holographic direction. The homogeneous results are found to qualitatively match the full numerical solutions, lending confidence to the homogeneous approximations of the full Sakai–Sugimoto model. In addition, we find exact compact solutions in the high density, flat space limit which demonstrate the existence of further popcorn transitions to three layers and beyond. (paper)
Semiparametric modeling: Correcting low-dimensional model error in parametric models
International Nuclear Information System (INIS)
Berry, Tyrus; Harlim, John
2016-01-01
In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.
Energy Technology Data Exchange (ETDEWEB)
Weber, Carsten
2008-07-01
This work is focused on the optical dynamics of mesoscopic semiconductor heterostructures, using as prototypes zero-dimensional quantum dots and quantum cascade lasers which consist of quasitwo- dimensional quantum wells. Within a density matrix theory, a microscopic many-particle theory is applied to study scattering effects in these structures: the coupling to external as well as local fields, electron-phonon coupling, coupling to impurities, and Coulomb coupling. For both systems, the investigated effects are compared to experimentally observed results obtained during the past years. In quantum dots, the three-dimensional spatial confinement leads to the necessity to consider a quantum kinetic description of the dynamics, resulting in non-Markovian electron-phonon effects. This can be seen in the spectral phonon sidebands due to interaction with acoustic phonons as well as a damping of nonlinear Rabi oscillations which shows a nonmonotonous intensity and pulse duration dependence. An analysis of the inclusion of the self-interaction of the quantum dot shows that no dynamical local field terms appear for the simple two-level model. Considering local fields which have their origin in many quantum dots, consequences for a two-level quantum dot such as a zero-phonon line broadening and an increasing signal in photon echo experiments are found. For the use of quantum dots in an optical spin control scheme, it is found that the dephasing due to the electron-phonon interaction can be dominant in certain regimes. Furthermore, soliton and breather solutions are studied analytically in nonlinear quantum dot ensembles. Generalizing to quasi-two-dimensional structures, the intersubband dynamics of quantum cascade laser structures is investigated. A dynamical theory is considered in which the temporal evolution of the subband populations and the current density as well as the influence of scattering effects is studied. In the nonlinear regime, the scattering dependence and
Montagnese, Matteo; Otter, Marian; Zotos, Xenophon; Fishman, Dmitry A; Hlubek, Nikolai; Mityashkin, Oleg; Hess, Christian; Saint-Martin, Romuald; Singh, Surjeet; Revcolevschi, Alexandre; van Loosdrecht, Paul H M
2013-04-05
Thirty-five years ago, Sanders and Walton [Phys. Rev. B 15, 1489 (1977)] proposed a method to measure the phonon-magnon interaction in antiferromagnets through thermal transport which so far has not been verified experimentally. We show that a dynamical variant of this approach allows direct extraction of the phonon-magnon equilibration time, yielding 400 μs for the cuprate spin-ladder system Ca(9)La(5)Cu(24)O(41). The present work provides a general method to directly address the spin-phonon interaction by means of dynamical transport experiments.
Quasiclassical methods for spin-charge coupled dynamics in low-dimensional systems
Energy Technology Data Exchange (ETDEWEB)
Corini, Cosimo
2009-06-12
Spintronics is a new field of study whose broad aim is the manipulation of the spin degrees of freedom in solid state systems. One of its main goals is the realization of devices capable of exploiting, besides the charge, the carriers' - and possibly the nuclei's - spin. The presence of spin-orbit coupling in a system enables the spin and charge degrees of freedom to ''communicate'', a favorable situation if one is to realize such devices. More importantly, it offers the opportunity of doing so by relying solely on electric fields, whereas magnetic fields are otherwise required. Eminent examples of versatile systems with built-in and variously tunable spin-orbit interaction are two-dimensional electron - or hole - gases. The study of spin-charge coupled dynamics in such a context faces a large number of open questions, both of the fundamental and of the more practical type. To tackle the problem we rely on the quasiclassical formalism. This is an approximate quantum-field theoretical formulation with a solid microscopic foundation, perfectly suited for describing phenomena at the mesoscopic scale, and bearing a resemblance to standard Boltzmann theory which makes for physical transparency. Originally born to deal with transport in electron-phonon systems, we first generalize it to the case in which spin-orbit coupling is present, and then move on to apply it to specific situations and phenomena. Among these, to the description of the spin Hall effect and of voltage induced spin polarizations in two-dimensional electron gases under a variety of conditions - stationary or time-dependent, in the presence of magnetic and non-magnetic disorder, in the bulk or in confined geometries -, and to the problem of spin relaxation in narrow wires. (orig.)
Quasiclassical methods for spin-charge coupled dynamics in low-dimensional systems
International Nuclear Information System (INIS)
Corini, Cosimo
2009-01-01
Spintronics is a new field of study whose broad aim is the manipulation of the spin degrees of freedom in solid state systems. One of its main goals is the realization of devices capable of exploiting, besides the charge, the carriers' - and possibly the nuclei's - spin. The presence of spin-orbit coupling in a system enables the spin and charge degrees of freedom to ''communicate'', a favorable situation if one is to realize such devices. More importantly, it offers the opportunity of doing so by relying solely on electric fields, whereas magnetic fields are otherwise required. Eminent examples of versatile systems with built-in and variously tunable spin-orbit interaction are two-dimensional electron - or hole - gases. The study of spin-charge coupled dynamics in such a context faces a large number of open questions, both of the fundamental and of the more practical type. To tackle the problem we rely on the quasiclassical formalism. This is an approximate quantum-field theoretical formulation with a solid microscopic foundation, perfectly suited for describing phenomena at the mesoscopic scale, and bearing a resemblance to standard Boltzmann theory which makes for physical transparency. Originally born to deal with transport in electron-phonon systems, we first generalize it to the case in which spin-orbit coupling is present, and then move on to apply it to specific situations and phenomena. Among these, to the description of the spin Hall effect and of voltage induced spin polarizations in two-dimensional electron gases under a variety of conditions - stationary or time-dependent, in the presence of magnetic and non-magnetic disorder, in the bulk or in confined geometries -, and to the problem of spin relaxation in narrow wires. (orig.)
Klein, Johannes R; Flender, Oliver; Scholz, Mirko; Oum, Kawon; Lenzer, Thomas
2016-04-28
We provide an investigation of the charge carrier dynamics of the (MAI)(x)(PbI2)(1-x) system in the range x = 0.32-0.90 following the recently published "pseudobinary phase-composition processing diagram" of Song et al. (Chem. Mater., 2015, 27, 4612). The dynamics were studied using ultrafast pump-supercontinuum probe spectroscopy over the pump fluence range 2-50 μJ cm(-2), allowing for a wide variation of the initial carrier density. At high MAI excess (x = 0.90), low-dimensional perovskites (LDPs) are formed, and their luminescence spectra are significantly blue-shifted by ca. 50 nm and broadened compared to the 3D perovskite. The shift is due to quantum confinement effects, and the inhomogeneous broadening arises from different low-dimensional structures (predominantly 2D, but presumably also 1D and 0D). Accurate transient carrier temperatures are extracted from the transient absorption spectra. The regimes of carrier-carrier, carrier-optical phonon and acoustic phonon scattering are clearly distinguished. Perovskites with mole fractions x ≤ 0.71 exhibit extremely fast carrier cooling (ca. 300 fs) at low fluence of 2 μJ cm(-2), however cooling slows down significantly at high fluence of 50 μJ cm(-2) due to the "hot phonon effect" (ca. 2.8 ps). A kinetic analysis of the electron-hole recombination dynamics provides second-order recombination rate constants k2 which decrease from 5.3 to 1.5 × 10(-9) cm(3) s(-1) in the range x = 0.32-0.71. In contrast, recombination in the LDPs (x = 0.90) is more than one order of magnitude faster, 6.4 × 10(-8) cm(3) s(-1), which is related to the confined perovskite structure. Recombination in these LDPs should be however still slow enough for their potential application as efficient broadband emitters or solar light-harvesting materials.
Groebner Basis Methods for Stationary Solutions of a Low-Dimensional Model for a Shear Flow
Pausch, Marina; Grossmann, Florian; Eckhardt, Bruno; Romanovski, Valery G.
2014-10-01
We use Groebner basis methods to extract all stationary solutions for the nine-mode shear flow model described in Moehlis et al. (New J Phys 6:56, 2004). Using rational approximations to irrational wave numbers and algebraic manipulation techniques we reduce the problem of determining all stationary states to finding roots of a polynomial of order 30. The coefficients differ by 30 powers of 10, so that algorithms for extended precision are needed to extract the roots reliably. We find that there are eight stationary solutions consisting of two distinct states, each of which appears in four symmetry-related phases. We discuss extensions of these results for other flows.
Low dimensionality semiconductors: modelling of excitons via a fractional-dimensional space
Christol, P.; Lefebvre, P.; Mathieu, H.
1993-09-01
An interaction space with a fractionnal dimension is used to calculate in a simple way the binding energies of excitons confined in quantum wells, superlattices and quantum well wires. A very simple formulation provides this energy versus the non-integer dimensionality of the physical environment of the electron-hole pair. The problem then comes to determining the dimensionality α. We show that the latter can be expressed from the characteristics of the microstructure. α continuously varies from 3 (bulk material) to 2 for quantum wells and superlattices, and from 3 to 1 for quantum well wires. Quite a fair agreement is obtained with other theoretical calculations and experimental data, and this model coherently describes both three-dimensional limiting cases for quantum wells (L_wrightarrow 0 and L_wrightarrow infty) and the whole range of periods of the superlattice. Such a simple model presents a great interest for spectroscopists though it does not aim to compete with accurate but often tedious variational calculations. Nous utilisons un espace des interactions doté d'une dimension fractionnaire pour calculer simplement l'énergie de liaison des excitons confinés dans les puits quantiques, superréseaux et fils quantiques. Une formulation très simple donne cette énergie en fonction de la dimensionalité non-entière de l'environnement physique de la paire électron-trou. Le problème revient alors à déterminer cette dimensionalité α, dont nous montrons qu'une expression peut être déduite des caractéristiques de la microstructure. α varie continûment de 3 (matériau massif) à 2 pour un puits quantique ou un superréseau, et de 3 à 1 pour un fil quantique, selon le confinement du mouvement des porteurs. Les comparaisons avec d'autres calculs théoriques et données expérimentales sont toujours très convenables, et cette théorie décrit d'une façon cohérente les limites tridimensionnelles du puits quantique (L_wrightarrow 0 et L
Low dimensional equivalence of core neutronics model and its application to transient analysis
International Nuclear Information System (INIS)
Song Hongbing; Zhao Fuyu
2015-01-01
Three-dimensional coupled neutronics thermal-hydraulics reactor analysis is time consuming and occupies huge memory. A one-dimensional model is preferable than the three one in nuclear system analysis, control system design and load following. In this paper, a corewide three dimensional to one dimensional equivalent method has been developed. On the basis of this method 1D axial few groups constants were obtained. The equivalent cross sections were calculated by general spatial homogenization while the transverse buckling was computed through an equivalence based on the 3D flux conservation. Three steady test cases were performed on one dimensional finite difference code ODTAC and the results were compared with TRIVAC-5. The comparison shows that the one dimensional axial power distribution computed by ODTAC correlates well with the three dimensional results calculated by TRIVAC-5. In this study, DRAGON-4 was used to generate the few-group constants of fuel assemblies and the reflector few-group parameters were calculated by WIMS-D4. These collapsed few-group constants were tabulated in a database sorted in ascending order of fuel temperature, coolant temperature and concentration of boric acid. Trilinear interpolation was adopted in cross sections feedback during the transient analysis. In this paper, G1 rod drop accident (RDA) and G1 rod ejection accident (REA) were performed on ODTAC and the computation results were consistent of the physical rules. (author)
Unconventional and intertwined orders of the low-dimensional Hubbard model
International Nuclear Information System (INIS)
Leprevost, Alexandre
2015-01-01
The understanding of superconductivity exhibited at high critical temperature by certain transition metal oxides remains a central issue in theoretical condensed matter physics. In this context, and since the historical proposal by P. W. Anderson, the repulsive Hubbard model in two dimensions became a paradigm in an attempt to capture the essential properties of non-conventional superconducting materials. However, the determination of the exact ground state encounters the exponential complexity of the quantum many-body problem. The main purpose of this thesis is to develop a variational scheme free of any hypothesis concerning magnetic, charge or superconducting orders likely to emerge from the Hamiltonian at low energy. The originality of the approach is found in the introduction of correlations by restoring, before variation, symmetries deliberately broken in a trial state given by a superposition of versatile wavefunctions of Hartree-Fock and Bogoliubov-de Gennes types. For small clusters of two and four sites, we show analytically that this symmetry entangled mean field method allows to find the exact ground state regardless of the strength of the on-site interaction. For larger hole-doped clusters and in the strongly correlated regime, we highlight an arrangement of magnetic moments in a spiral or in a spin density wave that is then accompanied by inhomogeneities in the form of regularly distributed stripes. Moreover, such orders are intertwined with long range d-wave pairing correlations, which, in the thermodynamic limit, sign superconductivity. These results are obtained through systematic simulations in a four-leg tube geometry that can be realized experimentally using cold atoms trapped in optical lattices. (author) [fr
Topological organization of (low-dimensional) chaos
International Nuclear Information System (INIS)
Tufillaro, N.B.
1992-01-01
Recent progress toward classifying low-dimensional chaos measured from time series data is described. This classification theory assigns a template to the time series once the time series is embedded in three dimensions. The template describes the primary folding and stretching mechanisms of phase space responsible for the chaotic motion. Topological invariants of the unstable periodic orbits in the closure of the strange set are calculated from the (reconstructed) template. These topological invariants must be consistent with ampersand ny model put forth to describe the time series data, and are useful in invalidating (or gaining confidence in) any model intended to describe the dynamical system generating the time series
Intercalation compounds of NbSe2 und SnSe2. Model systems for low-dimensional superconductors
International Nuclear Information System (INIS)
Herzinger, Michael
2013-01-01
experienced a renascence of research activities. Especially, since it represents a well-suited candidate for probing the multi-band model in a quasi-two-dimensional superconductor, due to the negligible vortex pinning in NbSe 2 single crystals. In order to enhance the anisotropic character we intercalated high quality 2H-NbSe 2 single crystals with the organometallic donor molecule cobaltocene, leading to an expansion of the lattice parameter in c direction from 12.53 Aa to 23.81 Aa. While the intercalation of organic compounds (which usually act as electron donors) reduces the superconducting transition temperature Tc from 7.1 K in 2H-NbSe 2 to temperatures below Tc 2 {CoCp 2 } 0.26 with Tc = 7.35 K. Furthermore, the strong increase of the upper critical magnetic field B c2 = 18.5 T in comparison to the native parent compound (B c2 (NbSe 2 ) = 14,5 T) indicates a more pronounced anisotropic behavior. Resistivity, susceptibility and specific heat studies parallel and perpendicular to the NbSe 2 -layers of 2H-NbSe 2 {CoCp 2 } 0.26 reveal both, a field-dependent reentrant superconductivity and a reversibility of the magnetization M(B) over a wide range above 3.5 T, also observed in the native parent NbSe2. Both intercalated materials NbSe 2 {CoCp 2 } x and SnSe2{CoCp 2 } x are good candidates for further theoretical investigation of the low dimensional superconductivity. The experimental results of the layered materials presented in this thesis will contribute to a better understanding of the low dimensional superconducting behavior.
Lausch, Tobias; Widera, Artur; Fleischhauer, Michael
2018-03-01
We numerically study the relaxation dynamics of a single, heavy impurity atom interacting with a finite one- or two-dimensional, ultracold Bose gas. While there is a clear separation of time scales between processes resulting from single- and two-phonon scattering in three spatial dimensions, the thermalization in lower dimensions is dominated by two-phonon processes. This is due to infrared divergences in the corresponding scattering rates in the thermodynamic limit, which are a manifestation of the Mermin-Wagner-Hohenberg theorem. This makes it necessary to include second-order phonon scattering above a crossover temperature T2ph . T2ph scales inversely with the system size and is much smaller than currently experimentally accessible.
International Nuclear Information System (INIS)
Malic, Ermin
2008-01-01
This work focuses on the theoretical investigation of optical properties of low-dimensional nanostructures, specifically single-walled carbon nanotubes (CNTs) and self-assembled InAs/GaAs quantum dots (QDs). The density-matrix formalism is applied to explain recent experimental results and to give insight into the underlying physics. A microscopic calculation of the absorption coefficient and the Rayleigh scattering cross section is performed by a novel approach combining the density-matrix formalism with the tight-binding wave functions. The calculated spectra of metallic nanotubes show a double-peaked structure resulting from the trigonal warping effect. The intensity ratios of the four lowest-lying transitions in both absorption and Rayleigh spectra can be explained by the different behavior of the optical matrix elements along the high-symmetry lines K-Γ and K-M. The Rayleigh line shape is predicted to be asymmetric, with an enhanced cross section for lower photon energies arising from non-resonant contributions of the optical susceptibility. Furthermore, the Coulomb interaction is shown to be maximal when the momentum transfer is low. For intersubband processes with a perpendicular momentum transfer, the coupling strength is reduced to less than 5%. The chirality and diameter dependence of the excitonic binding energy and the transition frequency are presented in Kataura plots. Furthermore, the influence of the surrounding environment on the optical properties of CNTs is investigated. Extending the confinement to all three spatial dimensions, semiconductor Bloch equation are derived to describe the dynamics in QD semiconductor lasers and amplifiers. A detailed microscopic analysis of the nonlinear turn-on dynamics of electrically pumped InAs/GaAs QD lasers is performed, showing the generation of relaxation oscillations on a nanosecond time scale in both the photon and charge carrier density. The theory predicts a strong damping of relaxation oscillations
Energy Technology Data Exchange (ETDEWEB)
Malic, Ermin
2008-09-02
This work focuses on the theoretical investigation of optical properties of low-dimensional nanostructures, specifically single-walled carbon nanotubes (CNTs) and self-assembled InAs/GaAs quantum dots (QDs). The density-matrix formalism is applied to explain recent experimental results and to give insight into the underlying physics. A microscopic calculation of the absorption coefficient and the Rayleigh scattering cross section is performed by a novel approach combining the density-matrix formalism with the tight-binding wave functions. The calculated spectra of metallic nanotubes show a double-peaked structure resulting from the trigonal warping effect. The intensity ratios of the four lowest-lying transitions in both absorption and Rayleigh spectra can be explained by the different behavior of the optical matrix elements along the high-symmetry lines K-{gamma} and K-M. The Rayleigh line shape is predicted to be asymmetric, with an enhanced cross section for lower photon energies arising from non-resonant contributions of the optical susceptibility. Furthermore, the Coulomb interaction is shown to be maximal when the momentum transfer is low. For intersubband processes with a perpendicular momentum transfer, the coupling strength is reduced to less than 5%. The chirality and diameter dependence of the excitonic binding energy and the transition frequency are presented in Kataura plots. Furthermore, the influence of the surrounding environment on the optical properties of CNTs is investigated. Extending the confinement to all three spatial dimensions, semiconductor Bloch equation are derived to describe the dynamics in QD semiconductor lasers and amplifiers. A detailed microscopic analysis of the nonlinear turn-on dynamics of electrically pumped InAs/GaAs QD lasers is performed, showing the generation of relaxation oscillations on a nanosecond time scale in both the photon and charge carrier density. The theory predicts a strong damping of relaxation oscillations
Wang, Shu-Fan; Lai, Shang-Hong
2011-10-01
Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.
Czech Academy of Sciences Publication Activity Database
Pánek, D.; Hrušák, J.; Doležel, Ivo
2007-01-01
Roč. 43, č. 596 (2007), s. 46-51 ISSN 0321-0499 R&D Projects: GA ČR(CZ) GA102/07/0496 Institutional research plan: CEZ:AV0Z20570509 Keywords : chaotic behavior * low-dimensional chaotic systems * Rikitake dynamo Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering
Talebi, A.
2008-01-01
Key words: Hillslope geometry, Hillslope hydrology, Hillslope stability, Complex hillslopes, Modeling shallow landslides, HSB model, HSB-SM model.
The hydrologic response of a hillslope to rainfall involves a complex, transient saturated-unsaturated interaction that usually leads to a
Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M
2017-10-01
Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal
Low-dimensional molecular metals
Toyota, Naoki; Muller, Jens
2007-01-01
Assimilating research in the field of low-dimensional metals, this monograph provides an overview of the status of research on quasi-one- and two-dimensional molecular metals, describing normal-state properties, magnetic field effects, superconductivity, and the phenomena of interacting p and d electrons.
Moisik, Scott R.; Esling, John H.
2014-01-01
Purpose: Physiological and phonetic studies suggest that, at moderate levels of epilaryngeal stricture, the ventricular folds impinge upon the vocal folds and influence their dynamical behavior, which is thought to be responsible for constricted laryngeal sounds. In this work, the authors examine this hypothesis through biomechanical modeling.…
Learning Low-Dimensional Metrics
Jain, Lalit; Mason, Blake; Nowak, Robert
2017-01-01
This paper investigates the theoretical foundations of metric learning, focused on three key questions that are not fully addressed in prior work: 1) we consider learning general low-dimensional (low-rank) metrics as well as sparse metrics; 2) we develop upper and lower (minimax)bounds on the generalization error; 3) we quantify the sample complexity of metric learning in terms of the dimension of the feature space and the dimension/rank of the underlying metric;4) we also bound the accuracy ...
Low-dimensional chaotic attractors in drift wave turbulence
International Nuclear Information System (INIS)
Persson, M.; Nordman, H.
1991-01-01
Simulation results of toroidal η i -mode turbulence are analyzed using mathematical tools of nonlinear dynamics. Low-dimensional chaotic attractors are found in the strongly nonlinear regime while in the weakly interacting regime the dynamics is high dimensional. In both regimes, the solutions are found to display sensitive dependence on initial conditions, characterized by a positive largest Liapunov exponent. (au)
CT Image Reconstruction in a Low Dimensional Manifold
Cong, Wenxiang; Wang, Ge; Yang, Qingsong; Hsieh, Jiang; Li, Jia; Lai, Rongjie
2017-01-01
Regularization methods are commonly used in X-ray CT image reconstruction. Different regularization methods reflect the characterization of different prior knowledge of images. In a recent work, a new regularization method called a low-dimensional manifold model (LDMM) is investigated to characterize the low-dimensional patch manifold structure of natural images, where the manifold dimensionality characterizes structural information of an image. In this paper, we propose a CT image reconstruc...
Optical properties of low-dimensional materials
Ogawa, T
1998-01-01
This book surveys recent theoretical and experimental studies of optical properties of low-dimensional materials. As an extended version of Optical Properties of Low-Dimensional Materials (Volume 1, published in 1995 by World Scientific), Volume 2 covers a wide range of interesting low-dimensional materials including both inorganic and organic systems, such as disordered polymers, deformable molecular crystals, dilute magnetic semiconductors, SiGe/Si short-period superlattices, GaAs quantum wires, semiconductor microcavities, and photonic crystals. There are excellent review articles by promis
Quantum Phenomena in Low-Dimensional Systems
Geller, Michael R.
2001-01-01
A brief summary of the physics of low-dimensional quantum systems is given. The material should be accessible to advanced physics undergraduate students. References to recent review articles and books are provided when possible.
Anticipatory synchronization via low-dimensional filters
International Nuclear Information System (INIS)
Pyragiene, T.; Pyragas, K.
2017-01-01
An anticipatory chaotic synchronization scheme based on a low-order all-pass filter is proposed. The filter is designed as a Padé approximation to the transfer function of an ideal delay line, which is used in a standard Voss scheme. We show that despite its simplicity, the filter works in an anticipatory scheme as well as an ideal delay line. It provides extremely small synchronization error in the whole interval of anticipation time where the anticipatory manifold is stable. The efficacy of our scheme is explained by an analytically solvable model of unidirectionally coupled unstable spirals and confirmed numerically by an example of unidirectionally coupled chaotic Rössler systems. - Highlights: • A new coupling scheme for anticipating chaotic synchronization is proposed. • The scheme consists of a drive system coupled to a low-dimensional filter. • Long-term anticipation is achieved without using time-delay terms. • An analytical treatment estimates the maximum anticipation time. • The method is verified for the Rössler system.
Anticipatory synchronization via low-dimensional filters
Energy Technology Data Exchange (ETDEWEB)
Pyragiene, T., E-mail: tatjana.pyragiene@ftmc.lt; Pyragas, K.
2017-06-15
An anticipatory chaotic synchronization scheme based on a low-order all-pass filter is proposed. The filter is designed as a Padé approximation to the transfer function of an ideal delay line, which is used in a standard Voss scheme. We show that despite its simplicity, the filter works in an anticipatory scheme as well as an ideal delay line. It provides extremely small synchronization error in the whole interval of anticipation time where the anticipatory manifold is stable. The efficacy of our scheme is explained by an analytically solvable model of unidirectionally coupled unstable spirals and confirmed numerically by an example of unidirectionally coupled chaotic Rössler systems. - Highlights: • A new coupling scheme for anticipating chaotic synchronization is proposed. • The scheme consists of a drive system coupled to a low-dimensional filter. • Long-term anticipation is achieved without using time-delay terms. • An analytical treatment estimates the maximum anticipation time. • The method is verified for the Rössler system.
Low Dimensionality Effects in Complex Magnetic Oxides
Kelley, Paula J. Lampen
, Ca)MnO3 we observe a disruption of the long-range glassy strains associated with the charge-ordered phase in the bulk, lowering the field and pressure threshold for charge-order melting and increasing the ferromagnetic volume fraction as particle size is decreased. The long-range charge-ordered phase becomes completely suppressed when the particle size falls below 100 nm. In contrast, low dimensionality in the geometrically frustrated pseudo-1D spin chain compound Ca3Co2O6 is intrinsic, arising from the crystal lattice. We establish a comprehensive phase diagram for this exotic system consistent with recent reports of an incommensurate ground state and identify new sub-features of the ferrimagnetic phase. When defects in the form of grain boundaries are incorporated into the system the low-temperature slow-dynamic state is weakened, and new crossover phenomena emerge in the spin relaxation behavior along with an increased distribution of relaxation times. The presence of both disorder and randomness leads to a spin-glass-like state, as observed in gammaFe2O3 hollow nanoparticles, where freezing of surface spins at low temperature generates an irreversible magnetization component and an associated exchange-biasing effect. Our results point to distinct dynamic behaviors on the inner and outer surfaces of the hollow structures. Overall, these studies yield new physical insights into the role of dimensionality and disorder in these complex oxide systems and highlight the sensitivity of their manifested magnetic ground states to extrinsic factors, leading in many cases to crossover behaviors where the balance between competing phases is altered, or to the emergence of entirely new magnetic phenomena.
Magnetic resonance of low dimensional magnetic solids
Energy Technology Data Exchange (ETDEWEB)
Gatteschi, D.; Ferraro, F.; Sessoli, R. (Florence Univ. (Italy))
1994-06-01
The utility of EPR and NMR in the study of low-dimensional magnetic solids is shown. A short summary of the basis of magnetic resonance in these systems is reported, and the importance of spin-diffusion and magnetic anisotropy evidenced. Some results from experiments on metal-radical chains and clusters are presented. (authors). 37 refs., 7 figs.
Magnetic resonance of low dimensional magnetic solids
International Nuclear Information System (INIS)
Gatteschi, D.; Ferraro, F.; Sessoli, R.
1994-01-01
The utility of EPR and NMR in the study of low-dimensional magnetic solids is shown. A short summary of the basis of magnetic resonance in these systems is reported, and the importance of spin-diffusion and magnetic anisotropy evidenced. Some results from experiments on metal-radical chains and clusters are presented. (authors). 37 refs., 7 figs
Sharma, Ati S; Moarref, Rashad; McKeon, Beverley J; Park, Jae Sung; Graham, Michael D; Willis, Ashley P
2016-02-01
We report that many exact invariant solutions of the Navier-Stokes equations for both pipe and channel flows are well represented by just a few modes of the model of McKeon and Sharma [J. Fluid Mech. 658, 336 (2010)]. This model provides modes that act as a basis to decompose the velocity field, ordered by their amplitude of response to forcing arising from the interaction between scales. The model was originally derived from the Navier-Stokes equations to represent turbulent flows and has been used to explain coherent structure and to predict turbulent statistics. This establishes a surprising new link between the two distinct approaches to understanding turbulence.
Dazard, Jean-Eudes; Ishwaran, Hemant; Mehlotra, Rajeev; Weinberg, Aaron; Zimmerman, Peter
2018-01-01
Unraveling interactions among variables such as genetic, clinical, demographic and environmental factors is essential to understand the development of common and complex diseases. To increase the power to detect such variables interactions associated with clinical time-to-events outcomes, we borrowed established concepts from random survival forest (RSF) models. We introduce a novel RSF-based pairwise interaction estimator and derive a randomization method with bootstrap confidence intervals for inferring interaction significance. Using various linear and nonlinear time-to-events survival models in simulation studies, we first show the efficiency of our approach: true pairwise interaction-effects between variables are uncovered, while they may not be accompanied with their corresponding main-effects, and may not be detected by standard semi-parametric regression modeling and test statistics used in survival analysis. Moreover, using a RSF-based cross-validation scheme for generating prediction estimators, we show that informative predictors may be inferred. We applied our approach to an HIV cohort study recording key host gene polymorphisms and their association with HIV change of tropism or AIDS progression. Altogether, this shows how linear or nonlinear pairwise statistical interactions of variables may be efficiently detected with a predictive value in observational studies with time-to-event outcomes. PMID:29453930
Physics of low-dimensional systems
International Nuclear Information System (INIS)
Anon.
1989-01-01
The physics of low-dimensional systems has developed in a remarkable way over the last decade and has accelerated over the last few years, in particular because of the discovery of the new high temperature superconductors. The new developments started more than fifteen years ago with the discovery of the unexpected quasi-one-dimensional character of the TTF-TCNQ. Since then the field of conducting quasi-one-dimensional organic system have been rapidly growing. Parallel to the experimental work there has been an important theoretical development of great conceptual importance, such as charge density waves, soliton-like excitations, fractional charges, new symmetry properties etc. A new field of fundamental importance was the discovery of the Quantum Hall Effect in 1980. This field is still expanding with new experimental and theoretical discoveries. In 1986, then, came the totally unexpected discovery of high temperature superconductivity which started an explosive development. The three areas just mentioned formed the main themes of the Symposium. They do not in any way exhaust the progress in low-dimensional physics. We should mention the recent important development with both two-dimensional and one-dimensional and even zero-dimensional structures (quantum dots). The physics of mesoscopic systems is another important area where the low dimensionality is a key feature. Because of the small format of this Symposium we could unfortunately not cover these areas
Ghanem, Bernard; Ahuja, Narendra
2013-01-01
This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal
Dynamic Latent Classification Model
DEFF Research Database (Denmark)
Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre
as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...
Molenaar, Peter C M
2017-01-01
Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.
Low-dimensionality and predictability of solar wind and global magnetosphere during magnetic storms
Zivkovic, Tatjana; Rypdal, Kristoffer
2011-01-01
This article is part of Tatjana Živkovics' doctoral thesis. Available in Munin at http://hdl.handle.net/10037/3231 The storm index SYM-H, the solar wind velocity v, and interplanetary magnetic field Bz show no signatures of low-dimensional dynamics in quiet periods, but tests for determinism in the time series indicate that SYM-H exhibits a significant low-dimensional component during storm time, suggesting that self-organization takes place during magnetic storms. Even though our analysis...
Quantum Fluctuations of Low Dimensional Bose-Einstein ...
African Journals Online (AJOL)
A system of low dimensional condensed ultracold atomic gases inside a field of a laser-driven optical cavity exhibits dispersive optical bistability. During such a process the system also shows quantum fluctuations. Condensate fluctuations are highly manifested particularly in low dimensional systems. In this paper we have ...
Low dimensional neutron moderators for enhanced source brightness
DEFF Research Database (Denmark)
Mezei, Ferenc; Zanini, Luca; Takibayev, Alan
2014-01-01
In a recent numerical optimization study we have found that liquid para-hydrogen coupled cold neutron moderators deliver 3–5 times higher cold neutron brightness at a spallation neutron source if they take the form of a flat, quasi 2-dimensional disc, in contrast to the conventional more voluminous...... for cold neutrons. This model leads to the conclusions that the optimal shape for high brightness para-hydrogen neutron moderators is the quasi 1-dimensional tube and these low dimensional moderators can also deliver much enhanced cold neutron brightness in fission reactor neutron sources, compared...... to the much more voluminous liquid D2 or H2 moderators currently used. Neutronic simulation calculations confirm both of these theoretical conclusions....
Xiao, Hang
In the past several decades, low-dimensional materials (0D materials, 1D materials and 2D materials) have attracted much interest from both the experimental and theoretical points of view. Because of the quantum confinement effect, low-dimensional materials have exhibited a kaleidoscope of fascinating phenomena and unusual physical and chemical properties, shedding light on many novel applications. Despite the enormous success has been achieved in the research of low-dimensional materials, there are three fundamental challenges of research in low-dimensional materials: 1) Develop new computational tools to accurately describe the properties of low-dimensional materials with low computational cost. 2) Predict and synthesize new low-dimensional materials with novel properties. 3) Reveal new phenomenon induced by the interaction between low-dimensional materials and the surrounding environment. In this thesis, atomistic modelling tools have been applied to address these challenges. We first developed ReaxFF parameters for phosphorus and hydrogen to give an accurate description of the chemical and mechanical properties of pristine and defected black phosphorene. ReaxFF for P/H is transferable to a wide range of phosphorus and hydrogen containing systems including bulk black phosphorus, blue phosphorene, edge-hydrogenated phosphorene, phosphorus clusters and phosphorus hydride molecules. The potential parameters were obtained by conducting global optimization with respect to a set of reference data generated by extensive ab initio calculations. We extended ReaxFF by adding a 60° correction term which significantly improved the description of phosphorus clusters. Emphasis was placed on the mechanical response of black phosphorene with different types of defects. Compared to the nonreactive SW potential of phosphorene, ReaxFF for P/H systems provides a significant improvement in describing the mechanical properties of the pristine and defected black phosphorene, as well
Phonons in low-dimensional systems
International Nuclear Information System (INIS)
Mayer, A P; Bonart, D; Strauch, D
2004-01-01
An introduction is given to the dynamical properties of crystalline systems having lattice-translational symmetry in less than three dimensions. These include surfaces of and interfaces between crystals, layered structures (2D lattice periodicity), bars and wires (1D lattice periodicity), as well as crystallites and clusters that have no lattice translational symmetry at all. In addition, superlattices are covered as artificial materials, giving rise to interesting dynamical effects. Crystal surfaces and crystalline bars are considered in some detail. For these systems, changes of the atomic equilibrium positions in comparison to the corresponding bulk crystals are also discussed since they frequently affect the dynamical properties
Models for Dynamic Applications
DEFF Research Database (Denmark)
Sales-Cruz, Mauricio; Morales Rodriguez, Ricardo; Heitzig, Martina
2011-01-01
This chapter covers aspects of the dynamic modelling and simulation of several complex operations that include a controlled blending tank, a direct methanol fuel cell that incorporates a multiscale model, a fluidised bed reactor, a standard chemical reactor and finally a polymerisation reactor...... be applied to formulate, analyse and solve these dynamic problems and how in the case of the fuel cell problem the model consists of coupledmeso and micro scale models. It is shown how data flows are handled between the models and how the solution is obtained within the modelling environment....
Mechanical properties of low dimensional materials
Saini, Deepika
Recent advances in low dimensional materials (LDMs) have paved the way for unprecedented technological advancements. The drive to reduce the dimensions of electronics has compelled researchers to devise newer techniques to not only synthesize novel materials, but also tailor their properties. Although micro and nanomaterials have shown phenomenal electronic properties, their mechanical robustness and a thorough understanding of their structure-property relationship are critical for their use in practical applications. However, the challenges in probing these mechanical properties dramatically increase as their dimensions shrink, rendering the commonly used techniques inadequate. This dissertation focuses on developing techniques for accurate determination of elastic modulus of LDMs and their mechanical responses under tensile and shear stresses. Fibers with micron-sized diameters continuously undergo tensile and shear deformations through many phases of their processing and applications. Significant attention has been given to their tensile response and their structure-tensile properties relations are well understood, but the same cannot be said about their shear responses or the structure-shear properties. This is partly due to the lack of appropriate instruments that are capable of performing direct shear measurements. In an attempt to fill this void, this dissertation describes the design of an inexpensive tabletop instrument, referred to as the twister, which can measure the shear modulus (G) and other longitudinal shear properties of micron-sized individual fibers. An automated system applies a pre-determined twist to the fiber sample and measures the resulting torque using a sensitive optical detector. The accuracy of the instrument was verified by measuring G for high purity copper and tungsten fibers. Two industrially important fibers, IM7 carbon fiber and KevlarRTM 119, were found to have G = 17 and 2.4 GPa, respectively. In addition to measuring the shear
DEFF Research Database (Denmark)
Andreasen, Martin Møller; Meldrum, Andrew
This paper studies whether dynamic term structure models for US nominal bond yields should enforce the zero lower bound by a quadratic policy rate or a shadow rate specification. We address the question by estimating quadratic term structure models (QTSMs) and shadow rate models with at most four...
Low-Dimensional Network Formation in Molten Sodium Carbonate.
Wilding, Martin C; Wilson, Mark; Alderman, Oliver L G; Benmore, Chris; Weber, J K R; Parise, John B; Tamalonis, Anthony; Skinner, Lawrie
2016-04-15
Molten carbonates are highly inviscid liquids characterized by low melting points and high solubility of rare earth elements and volatile molecules. An understanding of the structure and related properties of these intriguing liquids has been limited to date. We report the results of a study of molten sodium carbonate (Na2CO3) which combines high energy X-ray diffraction, containerless techniques and computer simulation to provide insight into the liquid structure. Total structure factors (F(x)(Q)) are collected on the laser-heated carbonate spheres suspended in flowing gases of varying composition in an aerodynamic levitation furnace. The respective partial structure factor contributions to F(x)(Q) are obtained by performing molecular dynamics simulations treating the carbonate anions as flexible entities. The carbonate liquid structure is found to be heavily temperature-dependent. At low temperatures a low-dimensional carbonate chain network forms, at T = 1100 K for example ~55% of the C atoms form part of a chain. The mean chain lengths decrease as temperature is increased and as the chains become shorter the rotation of the carbonate anions becomes more rapid enhancing the diffusion of Na(+) ions.
Quantum Fluctuations of Low Dimensional Bose-Einstein ...
African Journals Online (AJOL)
Tadesse
that low dimensional quantum gases exhibit not only highly fascinating .... 2009; Marquardt and Girvin, 2009; Law, 1995; Vitali et al., 2007). ... ideal playground to test correlations between light and mesoscopic objects, to understand the.
Common phase diagram for low-dimensional superconductors
International Nuclear Information System (INIS)
Michalak, Rudi
2003-01-01
A phenomenological phase diagram which has been derived for high-temperature superconductors from NMR Knight-shift measurements of the pseudogap is compared to the phase diagram that is obtained for organic superconductors and spin-ladder superconductors, both low-dimensional systems. This is contrasted to the phase diagram of some Heavy Fermion superconductors, i.e. superconductors not constrained to a low dimensionality
International Nuclear Information System (INIS)
Nishimura, Hiroshi.
1993-05-01
Object-Oriented Programming has been used extensively to model the LBL Advanced Light Source 1.5 GeV electron storage ring. This paper is on the present status of the class library construction with emphasis on a dynamic modeling
Bun, M.J.G.; Sarafidis, V.
2013-01-01
This Chapter reviews the recent literature on dynamic panel data models with a short time span and a large cross-section. Throughout the discussion we considerlinear models with additional endogenous covariates. First we give a broad overview of available inference methods placing emphasis on GMM.
Ghanem, Bernard
2013-01-01
This paper proposes the problem of modeling video sequences of dynamic swarms (DSs). We define a DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar in any small spatiotemporal neighborhood. Examples of DS abound in nature, e.g., herds of animals and flocks of birds. To capture the local spatiotemporal properties of the DS, we present a probabilistic model that learns both the spatial layout of swarm elements (based on low-level image segmentation) and their joint dynamics that are modeled as linear transformations. To this end, a spatiotemporal neighborhood is associated with each swarm element, in which local stationarity is enforced both spatially and temporally. We assume that the prior on the swarm dynamics is distributed according to an MRF in both space and time. Embedding this model in a MAP framework, we iterate between learning the spatial layout of the swarm and its dynamics. We learn the swarm transformations using ICM, which iterates between estimating these transformations and updating their distribution in the spatiotemporal neighborhoods. We demonstrate the validity of our method by conducting experiments on real and synthetic video sequences. Real sequences of birds, geese, robot swarms, and pedestrians evaluate the applicability of our model to real world data. © 2012 Elsevier Inc. All rights reserved.
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.
Dielectric spectroscopy studies of low-disorder and low-dimensional materials
Tripathi, Pragya
2016-01-01
In this thesis we employ dielectric spectroscopy (in different implementations) to study the dielectric properties of different materials ranging from completely disordered supercooled liquids to low-disorder solids with only ratcheting reorientational motions, to low-dimensional systems such as thin films or needle-like crystals. The probed material properties include the electrical conductivity, the space-charge processes due to sample heterogeneities, molecular dynamics, hydrogen-bond dyna...
Unraveling surface enabled magnetic phenomena in low dimensional systems
Baljozovic, Milos; Girovsky, Jan; Nowakowski, Jan; Ali, Md Ehesan; Rossmann, Harald; Nijs, Thomas; Aeby, Elise; Nowakowska, Sylwia; Siewert, Dorota; Srivastava, Gitika; WäCkerlin, Christian; Dreiser, Jan; Decurtins, Silvio; Liu, Shi-Xia; Oppeneer, Peter M.; Jung, Thomas A.; Ballav, Nirmalya
Molecular spin systems with controllable interactions are of both fundamental and applied importance. These systems help us to better understand the fundamental origins of the interactions involved in low dimensional magnetic systems and to put them in the framework of existing models towards their further development. Following our first observation of exchange induced magnetic ordering in paramagnetic porphyrins adsorbed on ferromagnetic Co surface we showed that magnetic properties of such molecules can be controllably altered upon exposure to chemical and physical stimuli. In our most recent work it was shown that a synthetically programmed co-assembly of Fe and Mn phthalocyanines can also be realized on diamagnetic Au(111) surfaces where it induces long-range 2D ferrimagnetic order, at first glance in conflict with the Mermin-Wagner theory. Here we provide evidence for the first direct observation of such ordering from STM/STS and XMCD data and from DFT +U calculations demonstrating key role of the Au(111) surface states in mediating AFM RKKY coupling of the Kondo underscreened magnetic moments.
Unexpected magnetism in low dimensional systems: the role of symmetry
International Nuclear Information System (INIS)
Munoz, MC; Chico, L; Lopez-Sancho, MP; Beltran, JI; Gallego, S; Cerda, J
2006-01-01
The symmetry underlying the geometric structure of materials determines most of their physical properties. In low dimensional systems the role of symmetry is enhanced and can give rise to new phenomena. Here, we report on unexpected magnetism in carbon nanotubes and O-rich surfaces of ionic oxides, to show how its existence is closely related to the symmetry conditions. First, based on tight-binding models, we demonstrate that chiral carbon nanotubes present spin splitting at the Fermi level in the absence of a magneticfield, whereas achiral tubes preserve spin degeneracy. These remarkably different behaviors of chiral and non-chiral nanotubes are due to the intrinsic symmetry dependence of the spin-orbit interaction. Second, the occurrence of spin-polarization at ZrO 2 , Al 2 O 3 and MgO surfaces is proved by means of abinitio calculations within the density functional theory. Large spin moments develop at O-ended polar terminations, transforming the non-magnetic insulator into a half-metal. The magnetic moments mainly reside in the surface oxygen atoms, and their origin is related to the existence of 2p holes of well-defined spin polarization at the valence band of the ionic oxide. The direct relation between magnetization and local loss of donor charge shows that at the origin of these phenomena is the reduced surface symmetry
Directory of Open Access Journals (Sweden)
Loktev Aleksey Alekseevich
2013-01-01
Full Text Available The authors present their findings associated with their modeling of a dynamic load damper. According to the authors, the damper is to be installed onto a structure or its element that may be exposed to impact, vibration or any other dynamic loading. The damper is composed of paralleled or consecutively connected viscous and elastic elements. The authors study the influence of viscosity and elasticity parameters of the damper produced onto the regular displacement of points of the structure to be protected and onto the regular acceleration transmitted immediately from the damper to the elements positioned below it.
Dynamic wake meandering modeling
Energy Technology Data Exchange (ETDEWEB)
Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)
2007-06-15
We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as
International Nuclear Information System (INIS)
Colanero, K.; Chu, M.-C.
2002-01-01
We study a dynamical chiral bag model, in which massless fermions are confined within an impenetrable but movable bag coupled to meson fields. The self-consistent motion of the bag is obtained by solving the equations of motion exactly assuming spherical symmetry. When the bag interacts with an external meson wave we find three different kinds of resonances: fermionic, geometric, and σ resonances. We discuss the phenomenological implications of our results
Model for macroevolutionary dynamics.
Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E
2013-07-02
The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.
International Nuclear Information System (INIS)
McFadden, J.H.; Paulsen, M.P.; Gose, G.C.
1981-01-01
Thermal-hydraulic codes in general use for system calculations are based on extensive analyses of loss-of-coolant accidents following the postulated rupture of a large coolant pipe. In this study, time-dependent equation for the slip velocity in a two-phase flow condition has been incorporated into the RETRAN-02 computer code. This model addition was undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. The dynamic slip equation was derived from a set of two-fluid conservation equations. 18 refs
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.
Quantum confinement effects in low-dimensional systems
Indian Academy of Sciences (India)
2015-06-03
Jun 3, 2015 ... Quantum confinement effects in low-dimensional systems. Figure 5. (a) Various cuts of the three-dimensional data showing energy vs. momen- tum dispersion relations for Ag film of 17 ML thickness on Ge(111). (b) Photo- emission intensity maps along ¯M– ¯ – ¯K direction. (c) Substrate bands replotted ...
Shape control synthesis of low-dimensional calcium sulfate
Indian Academy of Sciences (India)
Shape control synthesis of low-dimensional calcium sulfate .... C in mixed solvents of 50 mL ethanol and 30 mL water for different reaction times was characterized by .... Duan X, Huang Y, Cui Y, Wang J and Lieber C M 2001 Nature 409 66.
Confinement Effects in Low-Dimensional Lead Iodide Perovskite Hybrids
Kamminga, Machteld E.; Fang, Honghua; Filip, Marina R.; Giustino, Feliciano; Baas, Jacobus; Blake, Graeme R.; Loi, Maria Antonietta; Palstra, Thomas T. M.
2016-01-01
We use a layered solution crystal growth technique to synthesize high-quality single crystals of phenylalkylammonium lead iodide organic/inorganic hybrid compounds. Single-crystal X-ray diffraction reveals low-dimensional structures consisting of inorganic sheets separated by bilayers of the organic
Neutron scattering studies of low dimensional magnetic systems
DEFF Research Database (Denmark)
Hansen, Ursula Bengård
investigated at low temperaturesand in a longitudinal magnetic eld using neutron spectroscopy. Here we observe thehybridisation of the magnon bound states, inherent to the low dimensional nature ofCoCl2 · 2D2O.At higher temperature, signatures which can be attributed to Magnetic Bloch Oscillationsis observed...
Low-dimensional and Data Fusion Techniques Applied to a Rectangular Supersonic Multi-stream Jet
Berry, Matthew; Stack, Cory; Magstadt, Andrew; Ali, Mohd; Gaitonde, Datta; Glauser, Mark
2017-11-01
Low-dimensional models of experimental and simulation data for a complex supersonic jet were fused to reconstruct time-dependent proper orthogonal decomposition (POD) coefficients. The jet consists of a multi-stream rectangular single expansion ramp nozzle, containing a core stream operating at Mj , 1 = 1.6 , and bypass stream at Mj , 3 = 1.0 with an underlying deck. POD was applied to schlieren and PIV data to acquire the spatial basis functions. These eigenfunctions were projected onto their corresponding time-dependent large eddy simulation (LES) fields to reconstruct the temporal POD coefficients. This reconstruction was able to resolve spectral peaks that were previously aliased due to the slower sampling rates of the experiments. Additionally, dynamic mode decomposition (DMD) was applied to the experimental and LES datasets, and the spatio-temporal characteristics were compared to POD. The authors would like to acknowledge AFOSR, program manager Dr. Doug Smith, for funding this research, Grant No. FA9550-15-1-0435.
Observing and modeling nonlinear dynamics in an internal combustion engine
International Nuclear Information System (INIS)
Daw, C.S.; Kennel, M.B.; Finney, C.E.; Connolly, F.T.
1998-01-01
We propose a low-dimensional, physically motivated, nonlinear map as a model for cyclic combustion variation in spark-ignited internal combustion engines. A key feature is the interaction between stochastic, small-scale fluctuations in engine parameters and nonlinear deterministic coupling between successive engine cycles. Residual cylinder gas from each cycle alters the in-cylinder fuel-air ratio and thus the combustion efficiency in succeeding cycles. The model close-quote s simplicity allows rapid simulation of thousands of engine cycles, permitting statistical studies of cyclic-variation patterns and providing physical insight into this technologically important phenomenon. Using symbol statistics to characterize the noisy dynamics, we find good quantitative matches between our model and experimental time-series measurements. copyright 1998 The American Physical Society
New developments in the theoretical treatment of low dimensional strongly correlated systems.
James, Andrew J A; Konik, Robert M; Lecheminant, Philippe; Robinson, Neil; Tsvelik, Alexei M
2017-10-09
We review two important non-perturbative approaches for extracting the physics of low- dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of confor- mal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symme- tries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1+1D quantum chro- modynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics. © 2017 IOP Publishing Ltd.
Nonlinear dynamic mechanism of vocal tremor from voice analysis and model simulations
Zhang, Yu; Jiang, Jack J.
2008-09-01
Nonlinear dynamic analysis and model simulations are used to study the nonlinear dynamic characteristics of vocal folds with vocal tremor, which can typically be characterized by low-frequency modulation and aperiodicity. Tremor voices from patients with disorders such as paresis, Parkinson's disease, hyperfunction, and adductor spasmodic dysphonia show low-dimensional characteristics, differing from random noise. Correlation dimension analysis statistically distinguishes tremor voices from normal voices. Furthermore, a nonlinear tremor model is proposed to study the vibrations of the vocal folds with vocal tremor. Fractal dimensions and positive Lyapunov exponents demonstrate the evidence of chaos in the tremor model, where amplitude and frequency play important roles in governing vocal fold dynamics. Nonlinear dynamic voice analysis and vocal fold modeling may provide a useful set of tools for understanding the dynamic mechanism of vocal tremor in patients with laryngeal diseases.
DEFF Research Database (Denmark)
Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James
2016-01-01
Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...
Energy–pressure relation for low-dimensional gases
Directory of Open Access Journals (Sweden)
Francesco Mancarella
2014-10-01
Full Text Available A particularly simple relation of proportionality between internal energy and pressure holds for scale-invariant thermodynamic systems (with Hamiltonians homogeneous functions of the coordinates, including classical and quantum – Bose and Fermi – ideal gases. One can quantify the deviation from such a relation by introducing the internal energy shift as the difference between the internal energy of the system and the corresponding value for scale-invariant (including ideal gases. After discussing some general thermodynamic properties associated with the scale-invariance, we provide criteria for which the internal energy shift density of an imperfect (classical or quantum gas is a bounded function of temperature. We then study the internal energy shift and deviations from the energy–pressure proportionality in low-dimensional models of gases interpolating between the ideal Bose and the ideal Fermi gases, focusing on the Lieb–Liniger model in 1d and on the anyonic gas in 2d. In 1d the internal energy shift is determined from the thermodynamic Bethe ansatz integral equations and an explicit relation for it is given at high temperature. Our results show that the internal energy shift is positive, it vanishes in the two limits of zero and infinite coupling (respectively the ideal Bose and the Tonks–Girardeau gas and it has a maximum at a finite, temperature-depending, value of the coupling. Remarkably, at fixed coupling the energy shift density saturates to a finite value for infinite temperature. In 2d we consider systems of Abelian anyons and non-Abelian Chern–Simons particles: as it can be seen also directly from a study of the virial coefficients, in the usually considered hard-core limit the internal energy shift vanishes and the energy is just proportional to the pressure, with the proportionality constant being simply the area of the system. Soft-core boundary conditions at coincident points for the two-body wavefunction introduce
Energy–pressure relation for low-dimensional gases
International Nuclear Information System (INIS)
Mancarella, Francesco; Mussardo, Giuseppe; Trombettoni, Andrea
2014-01-01
A particularly simple relation of proportionality between internal energy and pressure holds for scale-invariant thermodynamic systems (with Hamiltonians homogeneous functions of the coordinates), including classical and quantum – Bose and Fermi – ideal gases. One can quantify the deviation from such a relation by introducing the internal energy shift as the difference between the internal energy of the system and the corresponding value for scale-invariant (including ideal) gases. After discussing some general thermodynamic properties associated with the scale-invariance, we provide criteria for which the internal energy shift density of an imperfect (classical or quantum) gas is a bounded function of temperature. We then study the internal energy shift and deviations from the energy–pressure proportionality in low-dimensional models of gases interpolating between the ideal Bose and the ideal Fermi gases, focusing on the Lieb–Liniger model in 1d and on the anyonic gas in 2d. In 1d the internal energy shift is determined from the thermodynamic Bethe ansatz integral equations and an explicit relation for it is given at high temperature. Our results show that the internal energy shift is positive, it vanishes in the two limits of zero and infinite coupling (respectively the ideal Bose and the Tonks–Girardeau gas) and it has a maximum at a finite, temperature-depending, value of the coupling. Remarkably, at fixed coupling the energy shift density saturates to a finite value for infinite temperature. In 2d we consider systems of Abelian anyons and non-Abelian Chern–Simons particles: as it can be seen also directly from a study of the virial coefficients, in the usually considered hard-core limit the internal energy shift vanishes and the energy is just proportional to the pressure, with the proportionality constant being simply the area of the system. Soft-core boundary conditions at coincident points for the two-body wavefunction introduce a length scale
Low-dimensional chaos in a hydrodynamic system
International Nuclear Information System (INIS)
Brandstater, A.; Swift, J.; Swinney, H.L.; Wolf, A.; Farmer, J.D.; Jen, E.; Crutchfield, J.P.
1983-01-01
Evidence is presented for low-dimensional strange attractors in Couette-Taylor flow data. Computations of the largest Lyapunov exponent and metric entropy show that the system displays sensitive dependence on initial conditions. Although the phase space is very high dimensional, analysis of experimental data shows that motion is restricted to an attractor of dimension less than 5 for Reynolds numbers up to 30% above the onset of chaos. The Lyapunov exponent, entropy, and dimension all generally increase with Reynolds number
Campagnoli, Patrizia; Petris, Giovanni
2009-01-01
State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package.
GIS and dynamic phenomena modeling
Czech Academy of Sciences Publication Activity Database
Klimešová, Dana
2006-01-01
Roč. 4, č. 4 (2006), s. 11-15 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : dynamic modelling * temporal analysis * dynamics evaluation * temporal space Subject RIV: BC - Control Systems Theory
Quantum Effects in the Thermoelectric Power Factor of Low-Dimensional Semiconductors.
Hung, Nguyen T; Hasdeo, Eddwi H; Nugraha, Ahmad R T; Dresselhaus, Mildred S; Saito, Riichiro
2016-07-15
We theoretically investigate the interplay between the confinement length L and the thermal de Broglie wavelength Λ to optimize the thermoelectric power factor of semiconducting materials. An analytical formula for the power factor is derived based on the one-band model assuming nondegenerate semiconductors to describe quantum effects on the power factor of the low-dimensional semiconductors. The power factor is enhanced for one- and two-dimensional semiconductors when L is smaller than Λ of the semiconductors. In this case, the low-dimensional semiconductors having L smaller than their Λ will give a better thermoelectric performance compared to their bulk counterpart. On the other hand, when L is larger than Λ, bulk semiconductors may give a higher power factor compared to the lower dimensional ones.
Modelling dynamic roughness during floods
Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.
2007-01-01
In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most
Low-dimensional filiform Lie algebras over finite fields
Falcón Ganfornina, Óscar Jesús; Núñez Valdés, Juan; Pacheco Martínez, Ana María; Villar Liñán, María Trinidad; Vasek, Vladimir (Coordinador); Shmaliy, Yuriy S. (Coordinador); Trcek, Denis (Coordinador); Kobayashi, Nobuhiko P. (Coordinador); Choras, Ryszard S. (Coordinador); Klos, Zbigniew (Coordinador)
2011-01-01
In this paper we use some objects of Graph Theory to classify low-dimensional filiform Lie algebras over finite fields. The idea lies in the representation of each Lie algebra by a certain type of graphs. Then, some properties on Graph Theory make easier to classify the algebras. As results, which can be applied in several branches of Physics or Engineering, for instance, we find out that there exist, up to isomorphism, six 6-dimensional filiform Lie algebras over Z/pZ, for p = 2, 3, 5. Pl...
Magnetometry of low-dimensional electron and hole systems
Energy Technology Data Exchange (ETDEWEB)
Usher, A [School of Physics, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Elliott, M [School of Physics and Astronomy, Cardiff University, Queens Buildings, Cardiff CF24 3AA (United Kingdom)], E-mail: a.usher@exeter.ac.uk, E-mail: elliottm@cf.ac.uk
2009-03-11
The high-magnetic-field, low-temperature magnetic properties of low-dimensional electron and hole systems reveal a wealth of fundamental information. Quantum oscillations of the thermodynamic equilibrium magnetization yield the total density of states, a central quantity in understanding the quantum Hall effect in 2D systems. The magnetization arising from non-equilibrium circulating currents reveals details, not accessible with traditional measurements, of the vanishingly small longitudinal resistance in the quantum Hall regime. We review how the technique of magnetometry has been applied to these systems, the most important discoveries that have been made, and their theoretical significance. (topical review)
Hybrid dynamics for currency modeling
Theodosopoulos, Ted; Trifunovic, Alex
2006-01-01
We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. im...
Low dimensional field theories and condensed matter physics
International Nuclear Information System (INIS)
Nagaoka, Yosuke
1992-01-01
This issue is devoted to the Proceedings of the Fourth Yukawa International Seminar (YKIS '91) on Low Dimensional Field Theories and Condensed Matter Physics, which was held on July 28 to August 3 in Kyoto. In recent years there have been great experimental discoveries in the field of condensed matter physics: the quantum Hall effect and the high temperature superconductivity. Theoretical effort to clarify mechanisms of these phenomena revealed that they are deeply related to the basic problem of many-body systems with strong correlation. On the other hand, there have been important developments in field theory in low dimensions: the conformal field theory, the Chern-Simons gauge theory, etc. It was found that these theories work as a powerful method of approach to the problems in condensed matter physics. YKIS '91 was devoted to the study of common problems in low dimensional field theories and condensed matter physics. The 17 of the presented papers are collected in this issue. (J.P.N.)
Future device applications of low-dimensional carbon superlattice structures
Bhattacharyya, Somnath
2005-03-01
We observe superior transport properties in low-dimensional amorphous carbon (a-C) and superlattice structures fabricated by a number of different techniques. Low temperature conductivity of these materials is explained using argument based on the crossover of dimensionality of weak localization and electron-electron interactions along with a change of sign of the magneto-resistance. These trends are significantly different from many other well characterized ordered or oriented carbon structures, and, show direct evidence of high correlation length, mobility and an effect of the dimensionality in low-dimensional a-C films. We show routes to prepare bespoke features by tuning the phase relaxation time in order to make high-speed devices over large areas. The artificially grown multi-layer superlattice structures of diamond-like amorphous carbon films show high-frequency resonance and quantum conductance suggesting sufficiently high values of phase coherence length in the present disordered a-C system that could lead to fast switching multi-valued logic.
Characterization and Low-Dimensional Modeling of Urban Fluid Flow
2014-10-06
pollutant dispersion characteristics in urban street canyons . Journal of Applied... pollutant dispersion in an urban street canyon . Journal of Wind Engineering and Industrial Aerodynamics, 91:309–329, 2003. J. Kim and J. Baik. A numerical...J. Wang, and Z. Xie. The impact of solar radiation and street layout on pollutant dispersion in street canyon . Building and environment,
Computer Modelling of Dynamic Processes
Directory of Open Access Journals (Sweden)
B. Rybakin
2000-10-01
Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.
Low-dimensional geometry from euclidean surfaces to hyperbolic knots
Bonahon, Francis
2009-01-01
The study of 3-dimensional spaces brings together elements from several areas of mathematics. The most notable are topology and geometry, but elements of number theory and analysis also make appearances. In the past 30 years, there have been striking developments in the mathematics of 3-dimensional manifolds. This book aims to introduce undergraduate students to some of these important developments. Low-Dimensional Geometry starts at a relatively elementary level, and its early chapters can be used as a brief introduction to hyperbolic geometry. However, the ultimate goal is to describe the very recently completed geometrization program for 3-dimensional manifolds. The journey to reach this goal emphasizes examples and concrete constructions as an introduction to more general statements. This includes the tessellations associated to the process of gluing together the sides of a polygon. Bending some of these tessellations provides a natural introduction to 3-dimensional hyperbolic geometry and to the theory o...
Fluctuation-Response Relation and modeling in systems with fast and slow dynamics
Directory of Open Access Journals (Sweden)
G. Lacorata
2007-10-01
Full Text Available We show how a general formulation of the Fluctuation-Response Relation is able to describe in detail the connection between response properties to external perturbations and spontaneous fluctuations in systems with fast and slow variables. The method is tested by using the 360-variable Lorenz-96 model, where slow and fast variables are coupled to one another with reciprocal feedback, and a simplified low dimensional system. In the Fluctuation-Response context, the influence of the fast dynamics on the slow dynamics relies in a non trivial behavior of a suitable quadratic response function. This has important consequences for the modeling of the slow dynamics in terms of a Langevin equation: beyond a certain intrinsic time interval even the optimal model can give just statistical prediction.
Heat transport in low-dimensional materials: A review and perspective
Directory of Open Access Journals (Sweden)
Zhiping Xu
2016-05-01
Full Text Available Heat transport is a key energetic process in materials and devices. The reduced sample size, low dimension of the problem and the rich spectrum of material imperfections introduce fruitful phenomena at nanoscale. In this review, we summarize recent progresses in the understanding of heat transport process in low-dimensional materials, with focus on the roles of defects, disorder, interfaces, and the quantum-mechanical effect. New physics uncovered from computational simulations, experimental studies, and predictable models will be reviewed, followed by a perspective on open challenges.
Characteristics of exciton photoluminescence kinetics in low-dimensional silicon structures
Sachenko, A V; Manojlov, E G; Svechnikov, S V
2001-01-01
The time-resolved visible photoluminescence of porous nanocrystalline silicon films obtained by laser ablation have been measured within the temperature range 90-300 K. A study has been made of the interrelationship between photoluminescence characteristics (intensity, emission spectra, relaxation times, their temperature dependencies and structural and dielectric properties (size and shapes of Si nanocrystals, oxide phase of nanocrystal coating, porosity). A photoluminescence model is proposed that describes photon absorption and emission occurring in quantum-size Si nanocrystals while coupled subsystems of electron-hole pairs and excitons take part in the recombination. Possible excitonic Auger recombination mechanism in low-dimensional silicon structures is considered
Structural dynamic modifications via models
Indian Academy of Sciences (India)
The study shows that as many as half of the matrix ... the dynamicist's analytical modelling skill which would appear both in the numerator as. Figure 2. ..... Brandon J A 1990 Strategies for structural dynamic modification (New York: John Wiley).
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
Dynamical models of the Galaxy
Directory of Open Access Journals (Sweden)
McMillan P.J.
2012-02-01
Full Text Available I discuss the importance of dynamical models for exploiting survey data, focusing on the advantages of “torus” models. I summarize a number of applications of these models to the study of the Milky Way, including the determination of the peculiar Solar velocity and investigation of the Hyades moving group.
Thermal conduction in classical low-dimensional lattices
International Nuclear Information System (INIS)
Lepri, Stefano; Livi, Roberto; Politi, Antonio
2003-01-01
Deriving macroscopic phenomenological laws of irreversible thermodynamics from simple microscopic models is one of the tasks of non-equilibrium statistical mechanics. We consider stationary energy transport in crystals with reference to simple mathematical models consisting of coupled oscillators on a lattice. The role of lattice dimensionality on the breakdown of the Fourier's law is discussed and some universal quantitative aspects are emphasized: the divergence of the finite-size thermal conductivity is characterized by universal laws in one and two dimensions. Equilibrium and non-equilibrium molecular dynamics methods are presented along with a critical survey of previous numerical results. Analytical results for the non-equilibrium dynamics can be obtained in the harmonic chain where the role of disorder and localization can be also understood. The traditional kinetic approach, based on the Boltzmann-Peierls equation is also briefly sketched with reference to one-dimensional chains. Simple toy models can be defined in which the conductivity is finite. Anomalous transport in integrable non-linear systems is briefly discussed. Finally, possible future research themes are outlined
Shah, A A; Xing, W W; Triantafyllidis, V
2017-04-01
In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.
International Nuclear Information System (INIS)
McFadden, J.H.; Paulsen, M.P.; Gose, G.C.
1981-01-01
A time dependent equation for the slip velocity in a two-phase flow condition has been incorporated into a developmental version of the RETRAN computer code. This model addition has been undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. In this paper, the development of the slip model is summarized and the corresponding constitutive equations are discussed. Comparisons of RETRAN analyses with steady-state void fraction data and data from the Semiscale S-02-6 small break test are also presented
Modeling Propellant Tank Dynamics
National Aeronautics and Space Administration — The main objective of my work will be to develop accurate models of self-pressurizing propellant tanks for use in designing hybrid rockets. The first key goal is to...
Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity
International Nuclear Information System (INIS)
Vassiliadis, D.
1992-01-01
The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms
Modelling group dynamic animal movement
DEFF Research Database (Denmark)
Langrock, Roland; Hopcraft, J. Grant C.; Blackwell, Paul G.
2014-01-01
makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias......, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual......Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However...
Modeling Internet Topology Dynamics
Haddadi, H.; Uhlig, S.; Moore, A.; Mortier, R.; Rio, M.
Despite the large number of papers on network topology modeling and inference, there still exists ambiguity about the real nature of the Internet AS and router level topology. While recent findings have illustrated the inaccuracies in maps inferred from BGP peering and traceroute measurements,
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...
Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification.
Song, Yang; Li, Qing; Huang, Heng; Feng, Dagan; Chen, Mei; Cai, Weidong
2017-08-01
Microscopy image classification is important in various biomedical applications, such as cancer subtype identification, and protein localization for high content screening. To achieve automated and effective microscopy image classification, the representative and discriminative capability of image feature descriptors is essential. To this end, in this paper, we propose a new feature representation algorithm to facilitate automated microscopy image classification. In particular, we incorporate Fisher vector (FV) encoding with multiple types of local features that are handcrafted or learned, and we design a separation-guided dimension reduction method to reduce the descriptor dimension while increasing its discriminative capability. Our method is evaluated on four publicly available microscopy image data sets of different imaging types and applications, including the UCSB breast cancer data set, MICCAI 2015 CBTC challenge data set, and IICBU malignant lymphoma, and RNAi data sets. Our experimental results demonstrate the advantage of the proposed low-dimensional FV representation, showing consistent performance improvement over the existing state of the art and the commonly used dimension reduction techniques.
Electronic properties and phase transitions in low-dimensional semiconductors
International Nuclear Information System (INIS)
Panich, A M
2008-01-01
We present the first review of the current state of the literature on electronic properties and phase transitions in TlX and TlMX 2 (M = Ga, In; X = Se, S, Te) compounds. These chalcogenides belong to a family of the low-dimensional semiconductors possessing chain or layered structure. They are of significant interest because of their highly anisotropic properties, semi- and photoconductivity, nonlinear effects in their I-V characteristics (including a region of negative differential resistance), switching and memory effects, second harmonic optical generation, relaxor behavior and potential applications for optoelectronic devices. We review the crystal structure of TlX and TlMX 2 compounds, their transport properties under ambient conditions, experimental and theoretical studies of the electronic structure, transport properties and semiconductor-metal phase transitions under high pressure, and sequences of temperature-induced structural phase transitions with intermediate incommensurate states. The electronic nature of the ferroelectric phase transitions in the above-mentioned compounds, as well as relaxor behavior, nanodomains and possible occurrence of quantum dots in doped and irradiated crystals is discussed. (topical review)
Low-Dimensional Feature Representation for Instrument Identification
Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin
For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.
Thermoelectric properties of low-dimensional clathrates from first principles
Kasinathan, Deepa; Rosner, Helge
2011-03-01
Type-I inorganic clathrates are host-guest structures with the guest atoms trapped in the framework of the host structure. From a thermoelectric point of view, they are interesting because they are semiconductors with adjustable bandgaps. Investigations in the past decade have shown that type-I clathrates X8 Ga 16 Ge 30 (X = Ba, Sr, Eu) may have the unusual property of ``phonon glass-electron crystal'' for good thermoelectric materials. Among the known clathrates, Ba 8 Ga 16 Ge 30 has the highest figure of merit (ZT~1). To enable a more widespread usage of thermoelectric technology power generation and heating/cooling applications, ZT of at least 2-3 is required. Two different research approaches have been proposed for developing next generation thermoelectric materials: one investigating new families of advanced bulk materials, and the other studying low-dimensional materials. In our work, we concentrate on understanding the thermoelectric properties of the nanostructured Ba-based clathrates. We use semi-classical Boltzmann transport equations to calculate the various thermoelectric properties as a function of reduced dimensions. We observe that there exists a delicate balance between the electrical conductivity and the electronic part of the thermal conductivity in reduced dimensions. Insights from these results can directly be used to control particle size in nanostructuring experiments.
Proton tunneling in low dimensional cesium silicate LDS-1
Matsui, Hiroshi; Iwamoto, Kei; Mochizuki, Dai; Osada, Shimon; Asakura, Yusuke; Kuroda, Kazuyuki
2015-07-01
In low dimensional cesium silicate LDS-1 (monoclinic phase of CsHSi2O5), anomalous infrared absorption bands observed at 93, 155, 1210, and 1220 cm-1 are assigned to the vibrational mode of protons, which contribute to the strong hydrogen bonding between terminal oxygen atoms of silicate chain (O-O distance = 2.45 Å). The integrated absorbance (oscillator strength) for those modes is drastically enhanced at low temperatures. The analysis of integrated absorbance employing two different anharmonic double-minimum potentials makes clear that proton tunneling through the potential barrier yields an energy splitting of the ground state. The absorption bands at 93 and 155 cm-1, which correspond to the different vibrational modes of protons, are attributed to the optical transition between the splitting levels (excitation from the ground state (n = 0) to the first excited state (n = 1)). Moreover, the absorption bands at 1210 and 1220 cm-1 are identified as the optical transition from the ground state (n = 0) to the third excited state (n = 3). Weak Coulomb interactions in between the adjacent protons generate two types of vibrational modes: symmetric mode (93 and 1210 cm-1) and asymmetric mode (155 and 1220 cm-1). The broad absorption at 100-600 cm-1 reveals an emergence of collective mode due to the vibration of silicate chain coupled not only with the local oscillation of Cs+ but also with the proton oscillation relevant to the second excited state (n = 2).
Energy Technology Data Exchange (ETDEWEB)
Goettel, Stefan
2015-05-22
In this thesis, we study two recently developed methods to tackle low-dimensional correlated quantum systems. In the first part, we benchmark the extension of the functional renormalization group to spin-systems. We apply it to the two-dimensional XXZ model and reproduce the prediction for the phase transition from planar to axial ordering at the isotropic point. The interpretation of the critical scale (where the flow of the susceptibility diverges) as the critical temperature of the system can be questioned, since it yields only good results in the Ising limit. Especially near the isotropic point, this interpretation becomes unsatisfactory as the Mermin-Wagner theorem is violated. We discuss several problems of the method and conclude that it should only be used to explore phase diagrams. In the second part, we extend previous works to two-level quantum dots in the Coulomb blockade regime with special hopping matrices in nonequilibrium, e.g., the Kondo model, to the generic form, including ferromagnetic leads, spin-orbit interactions etc. The dot and the transport observables are determined completely by the hybridization matrix, leading to one of our major results that all these models can be mapped to the Anderson impurity model with ferromagnetic leads. We investigate this model with a well-controlled real-time renormalization group approach and justify the results of a poor man's scaling analysis. By using a singular value decomposition of the tunneling matrix we can rotate the model to the anisotropic Kondo model in the high-energy regime to solve the flow equations analytically. With this, we calculate the stationary dot magnetization and the current. The minimum of the magnetization is found to be an ellipsoid as function of the magnetic field, where the stretching factor determines the distance to the scaling limit. Afterwards, we consider the special case of two external reservoirs and the system being in the scaling limit and discuss the golden
Electron-hole liquid in semiconductors and low-dimensional structures
Sibeldin, N. N.
2017-11-01
The condensation of excitons into an electron-hole liquid (EHL) and the main EHL properties in bulk semiconductors and low-dimensional structures are considered. The EHL properties in bulk materials are discussed primarily in qualitative terms based on the experimental results obtained for germanium and silicon. Some of the experiments in which the main EHL thermodynamic parameters (density and binding energy) have been obtained are described and the basic factors that determine these parameters are considered. Topics covered include the effect of external perturbations (uniaxial strain and magnetic field) on EHL stability; phase diagrams for a nonequilibrium exciton-gas-EHL system; information on the size and concentration of electron-hole drops (EHDs) under various experimental conditions; the kinetics of exciton condensation and of recombination in the exciton-gas-EHD system; dynamic EHD properties and the motion of EHDs under the action of external forces; the properties of giant EHDs that form in potential wells produced by applying an inhomogeneous strain to the crystal; and effects associated with the drag of EHDs by nonequilibrium phonons (phonon wind), including the dynamics and formation of an anisotropic spatial structure of the EHD cloud. In discussing EHLs in low-dimensional structures, a number of studies are reviewed on the observation and experimental investigation of phenomena such as spatially indirect (dipolar) electron-hole and exciton (dielectric) liquids in GaAs/AlGaAs structures with double quantum wells (QWs), EHDs containing only a few electron-hole pairs (dropletons), EHLs in type-I silicon QWs, and spatially direct and dipolar EHLs in type-II silicon-germanium heterostructures.
Vehicle dynamics modeling and simulation
Schramm, Dieter; Bardini, Roberto
2014-01-01
The authors examine in detail the fundamentals and mathematical descriptions of the dynamics of automobiles. In this context different levels of complexity will be presented, starting with basic single-track models up to complex three-dimensional multi-body models. A particular focus is on the process of establishing mathematical models on the basis of real cars and the validation of simulation results. The methods presented are explained in detail by means of selected application scenarios.
Containing Terrorism: A Dynamic Model
Directory of Open Access Journals (Sweden)
Giti Zahedzadeh
2017-06-01
Full Text Available The strategic interplay between counterterror measures and terror activity is complex. Herein, we propose a dynamic model to depict this interaction. The model generates stylized prognoses: (i under conditions of inefficient counterterror measures, terror groups enjoy longer period of activity but only if recruitment into terror groups remains low; high recruitment shortens the period of terror activity (ii highly efficient counterterror measures effectively contain terror activity, but only if recruitment remains low. Thus, highly efficient counterterror measures can effectively contain terrorism if recruitment remains restrained. We conclude that the trajectory of the dynamics between counterterror measures and terror activity is heavily altered by recruitment.
A dynamical model of terrorism
Directory of Open Access Journals (Sweden)
Firdaus Udwadia
2006-01-01
Full Text Available This paper develops a dynamical model of terrorism. We consider the population in a given region as being made up of three primary components: terrorists, those susceptible to both terrorist and pacifist propaganda, and nonsusceptibles, or pacifists. The dynamical behavior of these three populations is studied using a model that incorporates the effects of both direct military/police intervention to reduce the terrorist population, and nonviolent, persuasive intervention to influence the susceptibles to become pacifists. The paper proposes a new paradigm for studying terrorism, and looks at the long-term dynamical evolution in time of these three population components when such interventions are carried out. Many important features—some intuitive, others not nearly so—of the nature of terrorism emerge from the dynamical model proposed, and they lead to several important policy implications for the management of terrorism. The different circumstances in which nonviolent intervention and/or military/police intervention may be beneficial, and the specific conditions under which each mode of intervention, or a combination of both, may be useful, are obtained. The novelty of the model presented herein is that it deals with the time evolution of terrorist activity. It appears to be one of the few models that can be tested, evaluated, and improved upon, through the use of actual field data.
Nonlinear transport behavior of low dimensional electron systems
Zhang, Jingqiao
The nonlinear behavior of low-dimensional electron systems attracts a great deal of attention for its fundamental interest as well as for potentially important applications in nanoelectronics. In response to microwave radiation and dc bias, strongly nonlinear electron transport that gives rise to unusual electron states has been reported in two-dimensional systems of electrons in high magnetic fields. There has also been great interest in the nonlinear response of quantum ballistic constrictions, where the effects of quantum interference, spatial dispersion and electron-electron interactions play crucial roles. In this thesis, experimental results of the research of low dimensional electron gas systems are presented. The first nonlinear phenomena were observed in samples of highly mobile two dimensional electrons in GaAs heavily doped quantum wells at different magnitudes of DC and AC (10 KHz to 20 GHz) excitations. We found that in the DC excitation regime the differential resistance oscillates with the DC current and external magnetic field, similar behavior was observed earlier in AlGaAs/GaAs heterostructures [C.L. Yang et al. ]. At external AC excitations the resistance is found to be also oscillating as a function of the magnetic field. However the form of the oscillations is considerably different from the DC case. We show that at frequencies below 100 KHz the difference is a result of a specific average of the DC differential resistance during the period of the external AC excitations. Secondly, in similar samples, strong suppression of the resistance by the electric field is observed in magnetic fields at which the Landau quantization of electron motion occurs. The phenomenon survives at high temperatures at which the Shubnikov de Haas oscillations are absent. The scale of the electric fields essential for the effect, is found to be proportional to temperature in the low temperature limit. We suggest that the strong reduction of the longitudinal resistance
INTRODUCTION: Physics of Low-dimensional Systems: Nobel Symposium 73
Lundqvist, Stig
1989-01-01
The physics of low-dimensional systems has developed in a remarkable way over the last decade and has accelerated over the last few years, in particular because of the discovery of the new high temperature superconductors. The new developments started more than fifteen years ago with the discovery of the unexpected quasi-one-dimensional character of the TTF-TCNQ. Since then the field of conducting quasi-one-dimensional organic systems have been rapidly growing. Parallel to the experimental work there has been an important theoretical development of great conceptual importance, such as charge density waves, soliton-like excitations, fractional charges, new symmetry properties etc. A new field of fundamental importance was the discovery of the Quantum Hall Effect in 1980. This field is still expanding with new experimental and theoretical discoveries. In 1986, then, came the totally unexpected discovery of high temperature superconductivity which started an explosive development. The three areas just mentioned formed the main themes of the Symposium. They do not in any way exhaust the progress in low-dimensional physics. We should mention the recent important development with both two-dimensional and one-dimensional and even zero-dimensional structures (quantum dots). The physics of mesoscopic systems is another important area where the low dimensionality is a key feature. Because of the small format of this Symposium we could unfortunately not cover these areas. A Nobel Symposium provides an excellent opportunity to bring together a group of prominent scientists for a stimulating exchange of new ideas and results. The Nobel Symposia are very small meetings by invitation only and the number of key international participants is typically in the range 25-40. These Symposia are arranged through a special Nobel Symposium Committee after proposal from individuals. This Symposium was sponsored by the Nobel Foundation through its Nobel Symposium Fund with grants from The
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
Classical and quantum phases of low-dimensional dipolar systems
Energy Technology Data Exchange (ETDEWEB)
Cartarius, Florian
2016-09-22
In this thesis we present a detailed study of the phase diagram of ultracold bosonic atoms confined along a tight atomic wave guide, along which they experience an optical lattice potential. In this quasi-one dimensional model we analyse the interplay between interactions and quantum fluctuations in (i) determining the non-equilibrium steady state after a quench and (ii) giving rise to novel equilibrium phases, when the interactions combine the s-wave contact interaction and the anisotropic long range dipole-dipole interactions. In detail, in the first part of the thesis we study the depinning of a gas of impenetrable bosons following the sudden switch of of the optical lattice. By means of a Bose-Fermi mapping we infer the exact quantum dynamical evolution and show that in the thermodynamic limit the system is in a non-equilibrium steady state without quasi-long range order. In the second part of the thesis, we study the effect of quantum fluctuations on the linear-zigzag instability in the ground state of ultracold dipolar bosons, as a function of the strength of the transverse confinement. We first analyse the linear-zigzag instability in the classical regime, and then use our results to develop a multi-mode Bose-Hubbard model for the system. We then develop several numerical methods, to determine the ground state.
Experimental Modeling of Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten Haack
2006-01-01
An engineering course, Simulation and Experimental Modeling, has been developed that is based on a method for direct estimation of physical parameters in dynamic systems. Compared with classical system identification, the method appears to be easier to understand, apply, and combine with physical...
Business model dynamics and innovation
DEFF Research Database (Denmark)
Cavalcante, Sergio Andre; Kesting, Peter; Ulhøi, John Parm
2011-01-01
the impact of specific changes to a firm's business model. Such a tool would be particularly useful in identifying path dependencies and resistance at the process level, and would therefore allow a firm's management to take focused action on this in advance. Originality/value – The paper makes two main...... and specifies four different types of business model change: business model creation, extension, revision, and termination. Each type of business model change is associated with specific challenges. Practical implications – The proposed typology can serve as a basis for developing a management tool to evaluate......Purpose – This paper aims to discuss the need to dynamize the existing conceptualization of business model, and proposes a new typology to distinguish different types of business model change. Design/methodology/approach – The paper integrates basic insights of innovation, business process...
Low-dimensional morphospace of topological motifs in human fMRI brain networks
Directory of Open Access Journals (Sweden)
Sarah E. Morgan
2018-06-01
Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.
On whole Abelian model dynamics
Energy Technology Data Exchange (ETDEWEB)
Chauca, J.; Doria, R. [CBPF, Rio de Janeiro (Brazil); Aprendanet, Petropolis, 25600 (Brazil)
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.
Relating structure and dynamics in organisation models
Jonkers, C.M.; Treur, J.
2002-01-01
To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems,
Modelling MIZ dynamics in a global model
Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto
2016-04-01
Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.
Hung, Nguyen T.; Nugraha, Ahmad R. T.; Saito, Riichiro
2018-02-01
This paper is a contribution to the Physical Review Applied collection in memory of Mildred S. Dresselhaus. Analytical formulas for thermoelectric figures of merit and power factors are derived based on the one-band model. We find that there is a direct relationship between the optimum figures of merit and the optimum power factors of semiconductors despite of the fact that the two quantities are generally given by different values of chemical potentials. By introducing a dimensionless parameter consisting of the optimum power factor and lattice thermal conductivity (without electronic thermal conductivity), it is possible to unify optimum figures of merit of both bulk and low-dimensional semiconductors into a single universal curve that covers many materials with different dimensionalities.
A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions
Ghommem, Mehdi; Akhtar, Imran; Hajj, M. R.
2013-01-01
We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson's equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.
Social Dynamics Modeling and Inference
2018-03-29
the experiment(s)/ theory and equipment or analyses. Development of innovative theoretical model and methodologies with experimental verifications...information. The methodology based on communication and information theory (thanks to leave at MIT supported by this research) is described in [J1], [C2...a dynamic system [C1] and as a social learning mechanism in details [J4]. Furthermore, by incentive seeding and rewiring connections, information
Nonlinear effects in low-dimensional magnetism: Solitons and vortices
International Nuclear Information System (INIS)
Bishop, A.R.; Kawabata, C.; Mertens, F.G.; Wysin, G.M.
1987-07-01
The report outlines recent results on the dynamics of easy-plane classical ferromagnetic spin in two spatial dimensions emphasising possible signatures of unbound vortices above the Kosterlitz-Thouless topological phase transition. 18 refs, 1 fig
Stability and electronic properties of low-dimensional nanostructures
Guan, Jie
As the devices used in daily life become smaller and more concentrated, traditional three-dimensional (3D) bulk materials have reached their limit in size. Low-dimensional nanomaterials have been attracting more attention in research and getting widely applied in many industrial fields because of their atomic-level size, unique advanced properties, and varied nanostructures. In this thesis, I have studied the stability and mechanical and electronic properties of zero-dimensional (0D) structures including carbon fullerenes, nanotori, metallofullerenes and phosphorus fullerenes, one-dimensional (1D) structures including carbon nanotubes and phosphorus nanotubes, as well as two-dimensional (2D) structures including layered transition metal dichalcogenides (TMDs), phosphorene and phosphorus carbide (PC). I first briefly introduce the scientific background and the motivation of all the work in this thesis. Then the computational techniques, mainly density functional theory (DFT), are reviewed in Chapter 2. In Chapter 3, I investigate the stability and electronic structure of endohedral rare-earth metallofullerene La C60 and the trifluoromethylized La C60(CF3)n with n ≤ 5. Odd n is preferred due to the closed-shell electronic configuration or large HOMO-LUMO gap, which is also meaningful for the separation of C 60-based metallofullerenes. Mechanical and electronic properties of layered materials including TMDs and black phosphorus are studied in Chapter 4 and 5. In Chapter 4, a metallic NbSe2/semiconducting WSe2 bilayer is investigated and besides a rigid band shift associated with charge transfer, the presence of NbSe2 does not modify the electronic structure of WSe2. Structural similarity and small lattice mismatch results in the heterojunction being capable of efficiently transferring charge acrossthe interface. In Chapter 5, I investigate the dependence of stability and electronic band structure on the in-layer strain in bulk black phosphorus. In Chapters 6, 7 and
Low-dimensional chiral physics. Gross-Neveu universality and magnetic catalysis
Energy Technology Data Exchange (ETDEWEB)
Scherer, Daniel David
2012-09-27
In this thesis, we investigate the 3-dimensional, chirally symmetric Gross-Neveu model with functional renormalization group methods. This low-dimensional quantum field theory describes the continuum limit of the low-energy sector in certain lattice systems. The functional renormalization group allows to study in a nonperturbative way the physical properties of many-body systems and quantum field theories. The starting point is a formally exact flow equation with 1-loop structure for the generating functional of 1-particle irreducible vertices. Within a gradient expansion - tailor-made for extracting the infrared asymptotics of the momentum and frequency dependent vertices of the theory - we study the strong-coupling fixed point of the Gross-Neveu model even beyond the formal limit of infinite flavor number. This fixed point controls a 2nd order quantum phase transition from a massless phase to a phase with massive Dirac fermions. After a first analysis of the purely fermionic theory, a Hubbard-Stratonovich transformation is used to partially bosonize the theory. Within this bosonized description, we find universal critical exponents that are in excellent quantitative agreement with available results from 1/N{sub f}-expansions and Monte Carlo simulations and are expected to improve upon earlier results. The renormalization group flow allows us to gain insights into the global and local structure of the critical manifold within given truncations and better understanding of the relevant directions in the space of couplings, which in general do not coincide with the Gaussian classification. Within the framework of the so-called ''asymptotic safety''-scenario relevant for the construction of proper field theories, the fixed-point theory could be determined exactly in the limit of infinite flavor number. Here, the Gross-Neveu model yields a simple and intuitive example for how to define a nonperturbatively renormalizable quantum field theory. Going
Low-dimensional chiral physics. Gross-Neveu universality and magnetic catalysis
International Nuclear Information System (INIS)
Scherer, Daniel David
2012-01-01
In this thesis, we investigate the 3-dimensional, chirally symmetric Gross-Neveu model with functional renormalization group methods. This low-dimensional quantum field theory describes the continuum limit of the low-energy sector in certain lattice systems. The functional renormalization group allows to study in a nonperturbative way the physical properties of many-body systems and quantum field theories. The starting point is a formally exact flow equation with 1-loop structure for the generating functional of 1-particle irreducible vertices. Within a gradient expansion - tailor-made for extracting the infrared asymptotics of the momentum and frequency dependent vertices of the theory - we study the strong-coupling fixed point of the Gross-Neveu model even beyond the formal limit of infinite flavor number. This fixed point controls a 2nd order quantum phase transition from a massless phase to a phase with massive Dirac fermions. After a first analysis of the purely fermionic theory, a Hubbard-Stratonovich transformation is used to partially bosonize the theory. Within this bosonized description, we find universal critical exponents that are in excellent quantitative agreement with available results from 1/N f -expansions and Monte Carlo simulations and are expected to improve upon earlier results. The renormalization group flow allows us to gain insights into the global and local structure of the critical manifold within given truncations and better understanding of the relevant directions in the space of couplings, which in general do not coincide with the Gaussian classification. Within the framework of the so-called ''asymptotic safety''-scenario relevant for the construction of proper field theories, the fixed-point theory could be determined exactly in the limit of infinite flavor number. Here, the Gross-Neveu model yields a simple and intuitive example for how to define a nonperturbatively renormalizable quantum field theory. Going beyond the determination
Yip, K.-P.; Marsh, D. J.; Holstein-Rathlou, N.-H.
1995-01-01
We applied a surrogate data technique to test for nonlinear structure in spontaneous fluctuations of hydrostatic pressure in renal tubules of hypertensive rats. Tubular pressure oscillates at 0.03-0.05 Hz in animals with normal blood pressure, but the fluctuations become irregular with chronic hypertension. Using time series from rats with hypertension we produced surrogate data sets to test whether they represent linearly correlated noise or ‘static’ nonlinear transforms of a linear stochastic process. The correlation dimension and the forecasting error were used as discriminating statistics to compare surrogate with experimental data. The results show that the original experimental time series can be distinguished from both linearly and static nonlinearly correlated noise, indicating that the nonlinear behavior is due to the intrinsic dynamics of the system. Together with other evidence this strongly suggests that a low dimensional chaotic attractor governs renal hemodynamics in hypertension. This appears to be the first demonstration of a transition to chaotic dynamics in an integrated physiological control system occurring in association with a pathological condition.
Dynamic transitions in a model of the hypothalamic-pituitary-adrenal axis
Čupić, Željko; Marković, Vladimir M.; Maćešić, Stevan; Stanojević, Ana; Damjanović, Svetozar; Vukojević, Vladana; Kolar-Anić, Ljiljana
2016-03-01
Dynamic properties of a nonlinear five-dimensional stoichiometric model of the hypothalamic-pituitary-adrenal (HPA) axis were systematically investigated. Conditions under which qualitative transitions between dynamic states occur are determined by independently varying the rate constants of all reactions that constitute the model. Bifurcation types were further characterized using continuation algorithms and scale factor methods. Regions of bistability and transitions through supercritical Andronov-Hopf and saddle loop bifurcations were identified. Dynamic state analysis predicts that the HPA axis operates under basal (healthy) physiological conditions close to an Andronov-Hopf bifurcation. Dynamic properties of the stress-control axis have not been characterized experimentally, but modelling suggests that the proximity to a supercritical Andronov-Hopf bifurcation can give the HPA axis both, flexibility to respond to external stimuli and adjust to new conditions and stability, i.e., the capacity to return to the original dynamic state afterwards, which is essential for maintaining homeostasis. The analysis presented here reflects the properties of a low-dimensional model that succinctly describes neurochemical transformations underlying the HPA axis. However, the model accounts correctly for a number of experimentally observed properties of the stress-response axis. We therefore regard that the presented analysis is meaningful, showing how in silico investigations can be used to guide the experimentalists in understanding how the HPA axis activity changes under chronic disease and/or specific pharmacological manipulations.
Multiscale modeling of pedestrian dynamics
Cristiani, Emiliano; Tosin, Andrea
2014-01-01
This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.
Low-Dimensional Materials for Optoelectronic and Bioelectronic Applications
Hong, Tu
In this thesis, we first discuss the fundamentals of ab initio electronic structure theory and density functional theory (DFT). We also discuss statistics related to computing thermodynamic averages of molecular dynamics (MD). We then use this theory to analyze and compare the structural, dynamical, and electronic properties of liquid water next to prototypical metals including platinum, graphite, and graphene. Our results are built on Born-Oppenheimer molecular dynamics (BOMD) generated using density functional theory (DFT) which explicitly include van der Waals (vdW) interactions within a first principles approach. All calculations reported use large simulation cells, allowing for an accurate treatment of the water-electrode interfaces. We have included vdW interactions through the use of the optB86b-vdW exchange correlation functional. Comparisons with the Perdew-Burke-Ernzerhof (PBE) exchange correlation functional are also shown. We find an initial peak, due to chemisorption, in the density profile of the liquid water-Pt interface not seen in the liquid water-graphite interface, liquid watergraphene interface, nor interfaces studied previously. To further investigate this chemisorption peak, we also report differences in the electronic structure of single water molecules on both Pt and graphite surfaces. We find that a covalent bond forms between the single water molecule and the platinum surface, but not between the single water molecule and the graphite surface. We also discuss the effects that defects and dopants in the graphite and graphene surfaces have on the structure and dynamics of liquid water. Lastly, we introduce artificial neural networks (ANNs), and demonstrate how they can be used to machine learn electronic structure calculations. As a proof of principle, we show the success of an ANN potential energy surfaces for a dimer molecule with a Lennard-Jones potential.
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
MATHEMATICAL MODEL FOR RIVERBOAT DYNAMICS
Directory of Open Access Journals (Sweden)
Aleksander Grm
2017-01-01
Full Text Available Present work describes a simple dynamical model for riverboat motion based on the square drag law. Air and water interactions with the boat are determined from aerodynamic coefficients. CFX simulations were performed with fully developed turbulent flow to determine boat aerodynamic coefficients for an arbitrary angle of attack for the air and water portions separately. The effect of wave resistance is negligible compared to other forces. Boat movement analysis considers only two-dimensional motion, therefore only six aerodynamics coefficients are required. The proposed model is solved and used to determine the critical environmental parameters (wind and current under which river navigation can be conducted safely. Boat simulator was tested in a single area on the Ljubljanica river and estimated critical wind velocity.
Energy Technology Data Exchange (ETDEWEB)
Cipiti, Benjamin B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-03-01
The Co-Decontamination (CoDCon) Demonstration project is designed to test the separation of a mixed U and Pu product from dissolved spent nuclear fuel. The primary purpose of the project is to quantify the accuracy and precision to which a U/Pu mass ratio can be achieved without removing a pure Pu product. The system includes an on-line monitoring system using spectroscopy to monitor the ratios throughout the process. A dynamic model of the CoDCon flowsheet and on-line monitoring system was developed in order to expand the range of scenarios that can be examined for process control and determine overall measurement uncertainty. The model development and initial results are presented here.
Modeling the dynamics of choice.
Baum, William M; Davison, Michael
2009-06-01
A simple linear-operator model both describes and predicts the dynamics of choice that may underlie the matching relation. We measured inter-food choice within components of a schedule that presented seven different pairs of concurrent variable-interval schedules for 12 food deliveries each with no signals indicating which pair was in force. This measure of local choice was accurately described and predicted as obtained reinforcer sequences shifted it to favor one alternative or the other. The effect of a changeover delay was reflected in one parameter, the asymptote, whereas the effect of a difference in overall rate of food delivery was reflected in the other parameter, rate of approach to the asymptote. The model takes choice as a primary dependent variable, not derived by comparison between alternatives-an approach that agrees with the molar view of behaviour.
Dynamical modeling of tidal streams
International Nuclear Information System (INIS)
Bovy, Jo
2014-01-01
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.
International Nuclear Information System (INIS)
Ruan, Dan; Keall, Paul
2010-01-01
Accurate real-time prediction of respiratory motion is desirable for effective motion management in radiotherapy for lung tumor targets. Recently, nonparametric methods have been developed and their efficacy in predicting one-dimensional respiratory-type motion has been demonstrated. To exploit the correlation among various coordinates of the moving target, it is natural to extend the 1D method to multidimensional processing. However, the amount of learning data required for such extension grows exponentially with the dimensionality of the problem, a phenomenon known as the 'curse of dimensionality'. In this study, we investigate a multidimensional prediction scheme based on kernel density estimation (KDE) in an augmented covariate-response space. To alleviate the 'curse of dimensionality', we explore the intrinsic lower dimensional manifold structure and utilize principal component analysis (PCA) to construct a proper low-dimensional feature space, where kernel density estimation is feasible with the limited training data. Interestingly, the construction of this lower dimensional representation reveals a useful decomposition of the variations in respiratory motion into the contribution from semiperiodic dynamics and that from the random noise, as it is only sensible to perform prediction with respect to the former. The dimension reduction idea proposed in this work is closely related to feature extraction used in machine learning, particularly support vector machines. This work points out a pathway in processing high-dimensional data with limited training instances, and this principle applies well beyond the problem of target-coordinate-based respiratory-based prediction. A natural extension is prediction based on image intensity directly, which we will investigate in the continuation of this work. We used 159 lung target motion traces obtained with a Synchrony respiratory tracking system. Prediction performance of the low-dimensional feature learning
Workshop on low-dimensional quantum field theory and its applications
International Nuclear Information System (INIS)
Yamamoto, Hisashi
1990-02-01
The workshop on 'Low-Dimensional Quantum Field Theory and its Applications' was held at INS on December 18 - 20, 1989 with about seventy participants. Some pedagogical reviews and the latest results were delivered on the recent topics related to both solid-state and particle physics. Among them are quantum Hall effect, high T c superconductivity and related topics in low-dimensional quantum field theory. Many active discussions were made on these issues. (J.P.N.)
Fabrication, Characterization, Properties, and Applications of Low-Dimensional BiFeO3 Nanostructures
Directory of Open Access Journals (Sweden)
Heng Wu
2014-01-01
Full Text Available Low-dimensional BiFeO3 nanostructures (e.g., nanocrystals, nanowires, nanotubes, and nanoislands have received considerable attention due to their novel size-dependent properties and outstanding multiferroic properties at room temperature. In recent years, much progress has been made both in fabrications and (microstructural, electrical, and magnetic in characterizations of BiFeO3 low-dimensional nanostructures. An overview of the state of art in BiFeO3 low-dimensional nanostructures is presented. First, we review the fabrications of high-quality BiFeO3 low-dimensional nanostructures via a variety of techniques, and then the structural characterizations and physical properties of the BiFeO3 low-dimensional nanostructures are summarized. Their potential applications in the next-generation magnetoelectric random access memories and photovoltaic devices are also discussed. Finally, we conclude this review by providing our perspectives to the future researches of BiFeO3 low-dimensional nanostructures and some key problems are also outlined.
System Dynamics Modelling for a Balanced Scorecard
DEFF Research Database (Denmark)
Nielsen, Steen; Nielsen, Erland Hejn
2008-01-01
/methodology/approach - We use a case study model to develop time or dynamic dimensions by using a System Dynamics modelling (SDM) approach. The model includes five perspectives and a number of financial and non-financial measures. All indicators are defined and related to a coherent number of different cause...... have a major influence on other indicators and profit and may be impossible to predict without using a dynamic model. Practical implications - The model may be used as the first step in quantifying the cause-and-effect relationships of an integrated BSC model. Using the System Dynamics model provides......Purpose - To construct a dynamic model/framework inspired by a case study based on an international company. As described by the theory, one of the main difficulties of BSC is to foresee the time lag dimension of different types of indicators and their combined dynamic effects. Design...
Optoelectronic and nonlinear optical processes in low dimensional ...
Indian Academy of Sciences (India)
Optoelectronic process; nonlinear optical process; semiconductor. Quest for ever faster and intelligent information processing technologies has sparked ..... Schematic energy level diagram for the proposed 4-level model. States other than the.
Expressive body movement responses to music are coherent, consistent, and low dimensional.
Amelynck, Denis; Maes, Pieter-Jan; Martens, Jean Pierre; Leman, Marc
2014-12-01
Embodied music cognition stresses the role of the human body as mediator for the encoding and decoding of musical expression. In this paper, we set up a low dimensional functional model that accounts for 70% of the variability in the expressive body movement responses to music. With the functional principal component analysis, we modeled individual body movements as a linear combination of a group average and a number of eigenfunctions. The group average and the eigenfunctions are common to all subjects and make up what we call the commonalities. An individual performance is then characterized by a set of scores (the individualities), one score per eigenfunction. The model is based on experimental data which finds high levels of coherence/consistency between participants when grouped according to musical education. This shows an ontogenetic effect. Participants without formal musical education focus on the torso for the expression of basic musical structure (tempo). Musically trained participants decode additional structural elements in the music and focus on body parts having more degrees of freedom (such as the hands). Our results confirm earlier studies that different body parts move differently along with the music.
Low-dimensional analysis, using POD, for two mixing layer-wake interactions
International Nuclear Information System (INIS)
Braud, Caroline; Heitz, Dominique; Arroyo, Georges; Perret, Laurent; Delville, Joeel; Bonnet, Jean-Paul
2004-01-01
The mixing layer-wake interaction is studied experimentally in the framework of two flow configurations. For the first one, the initial conditions of the mixing layer are modified by using a thick trailing edge, a wake effect is therefore superimposed to the mixing layer from its beginning (blunt trailing edge). In the second flow configuration, a canonical mixing layer is perturbed in its asymptotic region by the wake of a cylinder arranged perpendicular to the plane of the mixing layer. These interactions are analyzed mainly by using two-point velocity correlations and the proper orthogonal decomposition (POD). These two flow configurations differ by the degree of complexity they involve: the former is mainly 2D while the latter is highly 3D. The blunt trailing edge configuration is analyzed by using rakes of hot wire probes. This flow configuration is found to be considerably different when compared to a conventional mixing layer. It appears in particular that the scale of the large structures depends only on the trailing edge thickness and does not grow in its downstream evolution. A criterion, based on POD, is proposed in order to separate wake-mixing layer dominant areas of the downstream evolution of the flow. The complex 3D dynamical behaviour resulting from the interaction between the canonical plane mixing layer and the wake of a cylinder is investigated using data arising from particle image velocimetry measurements. An analysis of the velocity correlations shows different length scales in the regions dominated by wake like structures and shear layer type structures. In order to characterize the particular organization in the plane of symmetry, a POD-Galerkin projection of the Navier-Stokes equations is performed in this plane. This leads to a low-dimensional dynamical system that allows the analysis of the relationship between the dominant frequencies to be performed. A reconstruction of the dominant periodic motion suspected from previous studies is
Electronic Structure of Low-Dimensional Carbon Π-Systems
DEFF Research Database (Denmark)
García Lastra, Juan Maria; Boukahil, Idris; Qiao, Ruimin
2016-01-01
, and the electron hole interaction. For the latter, we develop a simple model that accurately represents a full Delta-self-consistent field (ΔSCF) calculation. The distortion of the LUMO because of its interaction with the C is hole is investigated. These results illustrate the electronic states of prototypical Π...
International Nuclear Information System (INIS)
Shin, Seung Ki; Seong, Poong Hyun
2008-01-01
Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing Reliability Graph with General Gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables
Investigation of advanced materials based on low-dimensional systems
Energy Technology Data Exchange (ETDEWEB)
Babenkov, Sergey
2016-11-15
In the framework of this thesis, a new end-station dedicated for dynamic-XPS measurements is created. The end-station is based on a new hemispherical electron spectrometer Argus which is equipped with a high speed detection system. In combination with the high brilliance XUV beamline P04 at PETRA III it provides users a unique tool for fast (down to 0.1 s/spectrum) and detailed investigations compared to existing XPS devices at other synchrotrons. This end-station is integrated into beamline P04 and available for users. During this research work it was widely used for fabrication of samples (Ar{sup +} sputtering, sample heating, film growth etc) and investigation of their properties by means of dynamic-XPS. Using several methods, the atomic and electronic structure of graphene grown on technically relevant substrates of cubic-SiC(001)/Si(001) (''on-axis'' and ''vicinal'') was investigated. We have shown a way to control the number of graphene layers by real-time photoemission measurements during preparation procedure. Using this approach, we have synthesized several samples with different numbers of graphene layers. Consequent atomically resolved STM studies prove the synthesis of a uniform, millimeter-scale graphene overlayer. At the same time, the graphene overlayer possesses rippled morphology and consists of large amount of domain boundaries. Directions of domain boundaries coincide with the directions of carbon atomic chains which were fabricated prior to graphene synthesis on the SiC(001)-c(2 x 2) surface reconstruction. Further, using vicinal-SiC, we synthesized Bernal-stacked trilayer graphene with self-aligned periodic nanodomain boundaries. We proposed a simple method to achieve a current On-Off ratio of 104 by opening a transport gap in Bernal-stacked trilayer graphene. Our low-temperature transport measurements clearly demonstrate that the self-aligned periodic NBs can induce a charge transport gap greater than 1
Investigation of advanced materials based on low-dimensional systems
International Nuclear Information System (INIS)
Babenkov, Sergey
2016-11-01
In the framework of this thesis, a new end-station dedicated for dynamic-XPS measurements is created. The end-station is based on a new hemispherical electron spectrometer Argus which is equipped with a high speed detection system. In combination with the high brilliance XUV beamline P04 at PETRA III it provides users a unique tool for fast (down to 0.1 s/spectrum) and detailed investigations compared to existing XPS devices at other synchrotrons. This end-station is integrated into beamline P04 and available for users. During this research work it was widely used for fabrication of samples (Ar"+ sputtering, sample heating, film growth etc) and investigation of their properties by means of dynamic-XPS. Using several methods, the atomic and electronic structure of graphene grown on technically relevant substrates of cubic-SiC(001)/Si(001) (''on-axis'' and ''vicinal'') was investigated. We have shown a way to control the number of graphene layers by real-time photoemission measurements during preparation procedure. Using this approach, we have synthesized several samples with different numbers of graphene layers. Consequent atomically resolved STM studies prove the synthesis of a uniform, millimeter-scale graphene overlayer. At the same time, the graphene overlayer possesses rippled morphology and consists of large amount of domain boundaries. Directions of domain boundaries coincide with the directions of carbon atomic chains which were fabricated prior to graphene synthesis on the SiC(001)-c(2 x 2) surface reconstruction. Further, using vicinal-SiC, we synthesized Bernal-stacked trilayer graphene with self-aligned periodic nanodomain boundaries. We proposed a simple method to achieve a current On-Off ratio of 104 by opening a transport gap in Bernal-stacked trilayer graphene. Our low-temperature transport measurements clearly demonstrate that the self-aligned periodic NBs can induce a charge transport gap greater than 1.3 eV. More remarkably, the transport gap of
Using postural synergies to animate a low-dimensional hand avatar in haptic simulation.
Mulatto, Sara; Formaglio, Alessandro; Malvezzi, Monica; Prattichizzo, Domenico
2013-01-01
A technique to animate a realistic hand avatar with 20 DoFs based on the biomechanics of the human hand is presented. The animation does not use any sensor glove or advanced tracker with markers. The proposed approach is based on the knowledge of a set of kinematic constraints on the model of the hand, referred to as postural synergies, which allows to represent the hand posture using a number of variables lower than the number of joints of the hand model. This low-dimensional set of parameters is estimated from direct measurement of the motion of thumb and index finger tracked using two haptic devices. A kinematic inversion algorithm has been developed, which takes synergies into account and estimates the kinematic configuration of the whole hand, i.e., also of the fingers whose end tips are not directly tracked by the two haptic devices. The hand skin is deformable and its deformation is computed using a linear vertex blending technique. The proposed synergy-based animation of the hand avatar involves only algebraic computations and is suitable for real-time implementation as required in haptics.
Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.
Xia, Youshen; Wang, Jun
2015-07-01
This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.
Radiative heat transfer in low-dimensional systems -- microscopic mode
Woods, Lilia; Phan, Anh; Drosdoff, David
2013-03-01
Radiative heat transfer between objects can increase dramatically at sub-wavelength scales. Exploring ways to modulate such transport between nano-systems is a key issue from fundamental and applied points of view. We advance the theoretical understanding of radiative heat transfer between nano-objects by introducing a microscopic model, which takes into account the individual atoms and their atomic polarizabilities. This approach is especially useful to investigate nano-objects with various geometries and give a detailed description of the heat transfer distribution. We employ this model to study the heat exchange in graphene nanoribbon/substrate systems. Our results for the distance separations, substrates, and presence of extended or localized defects enable making predictions for tailoring the radiative heat transfer at the nanoscale. Financial support from the Department of Energy under Contract No. DE-FG02-06ER46297 is acknowledged.
Low dimensional physics and gauge principles : Matinyan Festschrift
Klümper, Andreas; Sedrakyan, A G
2013-01-01
This is a collection of articles on fundamental physical principles and methods, the topics ranging from matrix models, random surfaces, quantum dots and rings, to black holes, cosmology and testing of the tiny effects predicted by General Relativity. Among the authors are Sir Roger Penrose and other well-known experts and the articles are addressed to graduate students and researchers. The volume is a Festschrift to a noted physicist and mentor Sergei Matinyan.
Characterizing and modeling citation dynamics.
Directory of Open Access Journals (Sweden)
Young-Ho Eom
Full Text Available Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.
Supply based on demand dynamical model
Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.
2018-04-01
We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.
Opinion dynamics model based on quantum formalism
Energy Technology Data Exchange (ETDEWEB)
Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)
2016-03-11
Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.
Experimental investigation of new low-dimensional spin systems in vanadium oxides
International Nuclear Information System (INIS)
Kaul, E.E.
2005-01-01
In this dissertation we reported our experimental investigation of the magnetic properties of nine low-dimensional vanadium compounds. Two of these materials are completely new (Pb 2 V 5 O 12 and Pb 2 VO(PO 4 ) 2 ) and were found during our search for new low-dimensional vanadium oxides. Among the other seven vanadium compounds studied, three were physically investigated for the first time (Sr 2 VO(PO 4 ) 2 , BaZnVO(PO 4 ) 2 and SrZnVO(PO 4 ) 2 ). Two had hitherto only preliminary, and wrongly interpreted, susceptibility measurements reported in the literature (Sr 2 V 3 O 9 and Ba 2 V 3 O 9 ) while the remaining two (Li 2 VOSiO 4 and Li 2 VOGeO 4 ) were previously investigated in some detail but the interpretation of the data was controversial. We investigated the magnetic properties of these materials by means of magnetic susceptibility and specific heat (C p (T)) measurements (as well as single crystal ESR measurements in the case of Sr 2 V 3 O 9 ). We synthesized the samples necessary for our physical studies. That required a search of the optimal synthesis conditions for obtaining pure, high quality, polycrystalline samples. Single crystals of Sr 2 V 3 O 9 and Pb 2 VO(PO 4 ) 2 were also successfully grown. Pb 2 VO(PO 4 ) 2 , BaZnVO(PO 4 ) 2 , SrZnVO(PO 4 ) 2 , Li 2 VOSiO 4 and Li 2 VOGeO 4 were found to be experimental examples of frustrated square-lattice systems which are described by theJ 1 -J 2 model. We found that Li 2 VOSiO 4 and Li 2 VOGeO 4 posses a weakly frustrated antiferromagnetic square lattice while Pb 2 VO(PO 4 ) 2 , BaZnVO(PO 4 ) 2 and SrZnVO(PO 4 ) 2 form a more strongly frustrated ferromagnetic square lattice. Pb 2 V 5 O 12 is structurally and compositionally related to the two dimensional A 2+ V 4+ n O 2n+1 vanadates. Its structure consists of layers formed by edge- and corner-shared square VO 5 pyramids. The basic structural units are plaquettes consisting of six corner-shared pyramids pointing in the same direction, which form a spin
Muon studies of low-dimensional solid state systems
International Nuclear Information System (INIS)
Jestaedt, T.
1999-04-01
of this spin-gap on the magnetic properties are investigated here. I also describe results of measurements on a material with even more reduced dimensionality, polybutadiene (PB). This is a non-conducting polymer without side-chains. Muons in this system can either be in a paramagnetic or a diamagnetic state (with a polymer radical state produced by reaction of muonium with a polymer bond). The nature of these states has been examined with a variety of μSR, techniques, and the influence of the polymer dynamics and the glass transition in PB is discussed. (author)
A study of low-dimensional inhomogeneous systems
International Nuclear Information System (INIS)
Arredondo Leon, Yesenia
2009-01-01
While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K c , which characterizes its decay at large distances. (orig.)
A study of low-dimensional inhomogeneous systems
Energy Technology Data Exchange (ETDEWEB)
Arredondo Leon, Yesenia
2009-01-15
While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K{sub c}, which characterizes its decay at large distances. (orig.)
Relating structure and dynamics in organisation models
Jonker, C.M.; Treur, J.
2003-01-01
To understand how an organisational structure relates to dynamics is an interesting fundamental challenge in the area of social modelling. Specifications of organisational structure usually have a diagrammatic form that abstracts from more detailed dynamics. Dynamic properties of agent systems, on
A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions
Ghommem, Mehdi
2013-01-01
We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson\\'s equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.
Low-Dimensional Organic-Inorganic Halide Perovskite: Structure, Properties, and Applications.
Misra, Ravi K; Cohen, Bat-El; Iagher, Lior; Etgar, Lioz
2017-10-09
Three-dimensional (3 D) perovskite has attracted a lot of attention owing to its success in photovoltaic (PV) solar cells. However, one of its major crucial issues lies in its stability, which has limited its commercialization. An important property of organic-inorganic perovskite is the possibility of forming a layered material by using long organic cations that do not fit into the octahedral cage. These long organic cations act as a "barrier" that "caps" 3 D perovskite to form the layered material. Controlling the number of perovskite layers could provide a confined structure with chemical and physical properties that are different from those of 3 D perovskite. This opens up a whole new batch of interesting materials with huge potential for optoelectronic applications. This Minireview presents the synthesis, properties, and structural orientation of low-dimensional perovskite. It also discusses the progress of low-dimensional perovskite in PV solar cells, which, to date, have performance comparable to that of 3 D perovskite but with enhanced stability. Finally, the use of low-dimensional perovskite in light-emitting diodes (LEDs) and photodetectors is discussed. The low-dimensional perovskites are promising candidates for LED devices, mainly because of their high radiative recombination as a result of the confined low-dimensional quantum well. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Computer simulation of phase separation and ordering processes in low-dimensional systems
DEFF Research Database (Denmark)
Mouritsen, O.G.; Shah, P.J.; Vitting Andersen, J.
1991-01-01
An account is given of recent activity in the field of dynamics of phase separation and ordering processes in two-dimensional statistical mechanical models. The fundamental questions of the dynamics involve the form of the growth law, the value of the growth exponent, the dynamical scaling...... properties, and a possible universal classification of the late-stage dynamics. Evidence from kinetic lattice model calculations using computer-simulation techniques is presented in favor of a universal description of the dynamics in terms of algebraic growth laws with exponents which only depend...
Experimental study on the spin-orbit coupling property in low-dimensional semiconductor structures
International Nuclear Information System (INIS)
Zhao, Hongming
2010-01-01
The spin-orbit coupling and optical properties have been studied in several low-dimensional semiconductor structures. First, the spin dynamics in (001) GaAs/AlGaAs two-dimensional electron gas was investigated by time resolved Kerr rotation technique under a transverse magnetic field. The in-plane spin lifetime is found to be anisotropic. The results show that the electron density in two-dimensional electron gas channel strongly affects the Rashba spin-orbit coupling. Then, a large anisotropy of the magnitude of in-plane conduction electron g factor in asymmetric (001) GaAs/AlGaAs QWs was observed and its tendency of temperature dependence was studied. Second, the experimental study of the in-plane-orientation dependent spin splitting in the C(0001) GaN/AlGaN two-dimensional electron gas at room temperature was reported. The measurement of circular photo-galvanic effect current clearly shows the isotropic in-plane spin splitting in this system for the first time. Third, the first measurement of conduction electron g factor in GaAsN at room temperature was done by using time resolved Kerr rotation technique. It demonstrates that the g factor can be modified drastically by introducing a small amount of nitrogen in GaAs bulk. Finally, the optical characteristic of indirect type II transition in a series of size and shape-controlled linear CdTe/CdSe/CdTe heterostructure nano-rods was studied by steady-state and time resolved photoluminescence. Results show the steady transfer from the direct optical transition (type I) within CdSe to the indirect transition (type II) between CdSe/CdTe as the length of the nano-rods increases. (author)
Dynamic modelling of nuclear steam generators
International Nuclear Information System (INIS)
Kerlin, T.W.; Katz, E.M.; Freels, J.; Thakkar, J.
1980-01-01
Moving boundary, nodal models with dynamic energy balances, dynamic mass balances, quasi-static momentum balances, and an equivalent single channel approach have been developed for steam generators used in nuclear power plants. The model for the U-tube recirculation type steam generator is described and comparisons are made of responses from models of different complexity; non-linear versus linear, high-order versus low order, detailed modeling of the control system versus a simple control assumption. The results of dynamic tests on nuclear power systems show that when this steam generator model is included in a system simulation there is good agreement with actual plant performance. (author)
Dynamic Airspace Managment - Models and Algorithms
Cheng, Peng; Geng, Rui
2010-01-01
This chapter investigates the models and algorithms for implementing the concept of Dynamic Airspace Management. Three models are discussed. First two models are about how to use or adjust air route dynamically in order to speed up air trafï¬c ï¬‚ow and reduce delay. The third model gives a way to dynamically generate the optimal sector conï¬guration for an air trafï¬c control center to both balance the controllerâ€™s workload and save control resources. The ï¬rst model, called the Dynami...
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
System dynamics modelling of situation awareness
CSIR Research Space (South Africa)
Oosthuizen, R
2015-11-01
Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...
An Agent Model Integrating an Adaptive Model for Environmental Dynamics
Treur, J.; Umair, M.
2011-01-01
The environments in which agents are used often may be described by dynamical models, e.g., in the form of a set of differential equations. In this paper, an agent model is proposed that can perform model-based reasoning about the environment, based on a numerical (dynamical system) model of the
Data-Driven Modeling of Complex Systems by means of a Dynamical ANN
Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.
2017-12-01
The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).
Hydration dynamics near a model protein surface
International Nuclear Information System (INIS)
Russo, Daniela; Hura, Greg; Head-Gordon, Teresa
2003-01-01
The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces
A New Generation of Luminescent Materials Based on Low-Dimensional Perovskites
Pan, Jun
2017-06-02
Low-dimensional perovskites with high luminescence properties are promising materials for optoelectronic applications. In this article, properties of two emerging types of low-dimensional perovskites are discussed, including perovskite quantum dots CsPbX3 (X = Cl, Br or I) and zero-dimensional perovskite Cs4PbBr6. Moreover, their application for light down conversion in LCD backlighting systems and in visible light communication are also presented. With their superior optical properties, we believe that further development of these materials will potentially open more prospective applications, especially for optoelectronics devices.
Lack of evidence for low-dimensional chaos in heart rate variability
DEFF Research Database (Denmark)
Kanters, J K; Holstein-Rathlou, N H; Agner, E
1994-01-01
INTRODUCTION: The term chaos is used to describe erratic or apparently random time-dependent behavior in deterministic systems. It has been suggested that the variability observed in the normal heart rate may be due to chaos, but this question has not been settled. METHODS AND RESULTS: Heart rate...... in the experimental data, but the prediction error as a function of the prediction length increased at a slower rate than characteristic of a low-dimensional chaotic system. CONCLUSION: There is no evidence for low-dimensional chaos in the time series of RR intervals from healthy human subjects. However, nonlinear...
Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection
DEFF Research Database (Denmark)
Bork, Lasse; Møller, Stig Vinther
2015-01-01
We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...
Adaptive numerical modeling of dynamic crack propagation
International Nuclear Information System (INIS)
Adouani, H.; Tie, B.; Berdin, C.; Aubry, D.
2006-01-01
We propose an adaptive numerical strategy that aims at developing reliable and efficient numerical tools to model dynamic crack propagation and crack arrest. We use the cohesive zone theory as behavior of interface-type elements to model crack. Since the crack path is generally unknown beforehand, adaptive meshing is proposed to model the dynamic crack propagation. The dynamic study requires the development of specific solvers for time integration. As both geometry and finite element mesh of the studied structure evolve in time during transient analysis, the stability behavior of dynamic solver becomes a major concern. For this purpose, we use the space-time discontinuous Galerkin finite element method, well-known to provide a natural framework to manage meshes that evolve in time. As an important result, we prove that the space-time discontinuous Galerkin solver is unconditionally stable, when the dynamic crack propagation is modeled by the cohesive zone theory, which is highly non-linear. (authors)
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Directory of Open Access Journals (Sweden)
Zhong Yi Wan
Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis
2018-01-01
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in
Modeling Gas Dynamics in California Sea Lions
2015-09-30
W. and Fahlman, A. (2009). Could beaked whales get the bends?. Effect of diving behaviour and physiology on modelled gas exchange for three species...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Modeling Gas Dynamics in California Sea Lions Andreas...to update a current gas dynamics model with recently acquired data for respiratory compliance (P-V), and body compartment size estimates in
A Dynamic Model of Sustainment Investment
2015-02-01
Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect
Modeling the Dynamic Digestive System Microbiome†
Estes, Anne M.
2015-01-01
“Modeling the Dynamic Digestive System Microbiome” is a hands-on activity designed to demonstrate the dynamics of microbiome ecology using dried pasta and beans to model disturbance events in the human digestive system microbiome. This exercise demonstrates how microbiome diversity is influenced by: 1) niche availability and habitat space and 2) a major disturbance event, such as antibiotic use. Students use a pictorial key to examine prepared models of digestive system microbiomes to determi...
Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Ternovsky, V. B.; Serga, I. N.; Bykowszczenko, N.
2017-10-01
Results of analysis and modelling the air pollutant (dioxide of nitrogen) concentration temporal dynamics in atmosphere of the industrial city Odessa are presented for the first time and based on computing by nonlinear methods of the chaos and dynamical systems theories. A chaotic behaviour is discovered and investigated. To reconstruct the corresponding strange chaotic attractor, the time delay and embedding dimension are computed. The former is determined by the methods of autocorrelation function and average mutual information, and the latter is calculated by means of correlation dimension method and algorithm of false nearest neighbours. It is shown that low-dimensional chaos exists in the nitrogen dioxide concentration time series under investigation. Further, the Lyapunov’s exponents spectrum, Kaplan-Yorke dimension and Kolmogorov entropy are computed.
ICTP Summer Course on Low-Dimensional Quantum Field Theories for Condensed Matter Physicists
Morandi, G; Lu, Y
1995-01-01
This volume contains a set of pedagogical reviews covering the most recent applications of low-dimensional quantum field theory in condensed matter physics, written by experts who have made major contributions to this rapidly developing field of research. The main purpose is to introduce active young researchers to new ideas and new techniques which are not covered by the standard textbooks.
Near-Integrability of Low-Dimensional Periodic Klein-Gordon Lattices
Directory of Open Access Journals (Sweden)
Ognyan Christov
2018-01-01
Full Text Available The low-dimensional periodic Klein-Gordon lattices are studied for integrability. We prove that the periodic lattice with two particles and certain nonlinear potential is nonintegrable. However, in the cases of up to six particles, we prove that their Birkhoff-Gustavson normal forms are integrable, which allows us to apply KAM theory in most cases.
Statistical mechanics of low-dimensional Ginzburg-Landau fields. Some new results
International Nuclear Information System (INIS)
Barsan, V.
1987-08-01
The Ginzburg-Landau theory for low-dimensional systems is approached using the transfer matrix method. Analitical formulae for the thermodynamical quantities of interest are obtained in the one-dimensional case. An exact expression for the free energy of of a planar array of linear chains is deduced. A good agrement with numerical and experimental data is found.(authors)
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. Published by Elsevier Inc.
Nonlinear dynamic phenomena in the beer model
DEFF Research Database (Denmark)
Mosekilde, Erik; Laugesen, Jakob Lund
2007-01-01
The production-distribution system or "beer game" is one of the most well-known system dynamics models. Notorious for the complex dynamics it produces, the beer game has been used for nearly five decades to illustrate how structure generates behavior and to explore human decision making. Here we...
Phone Routing using the Dynamic Memory Model
DEFF Research Database (Denmark)
Bendtsen, Claus Nicolaj; Krink, Thiemo
2002-01-01
In earlier studies a genetic algorithm (GA) extended with the dynamic memory model has shown remarkable performance on real-world-like problems. In this paper we experiment with routing in communication networks and show that the dynamic memory GA performs remarkable well compared to ant colony...
Dynamic queuing transmission model for dynamic network loading
DEFF Research Database (Denmark)
Raovic, Nevena; Nielsen, Otto Anker; Prato, Carlo Giacomo
2017-01-01
and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared...
Some dynamical aspects of interacting quintessence model
Indian Academy of Sciences (India)
Binayak S Choudhury
2018-03-16
Mar 16, 2018 ... Accelerated expansion of the Universe; quintessence; dynamical system; Friedmann–Lemaitre–. Robertson–Walker ... accepted theoretical model. One of the .... Thus, quintessence loses its self-strength and gives dark matter.
Modeling of truck's braking dynamics with ABS
Directory of Open Access Journals (Sweden)
Maxym DYACHUK
2014-09-01
Full Text Available In the article some questions of ABS simulation on the basis of plane vehicle's dynamics and automatic modeling are considered. The author's algorithm of ABS modulators control is presented.
Quantum theory of the electronic and optical properties of low-dimensional semiconductor systems
Lau, Wayne Heung
This thesis examines the electronic and optical properties of low-dimensional semiconductor systems. A theory is developed to study the electron-hole generation-recombination process of type-II semimetallic semiconductor heterojunctions based on a 3 x 3 k·p matrix Hamiltonian (three-band model) and an 8 x 8 k·p matrix Hamiltonian (eight-band model). A novel electron-hole generation and recombination process, which is called activationless generation-recombination process, is predicted. It is demonstrated that the current through the type-II semimetallic semiconductor heterojunctions is governed by the activationless electron-hole generation-recombination process at the heterointerfaces, and that the current-voltage characteristics are essentially linear. A qualitative agreement between theory and experiments is observed. The numerical results of the eight-band model are compared with those of the threeband model. Based on a lattice gas model, a theory is developed to study the influence of a random potential on the ionization equilibrium conditions for bound electron-hole pairs (excitons) in III--V semiconductor heterostructures. It is demonstrated that ionization equilibrium conditions for bound electron-hole pairs change drastically in the presence of strong disorder. It is predicted that strong disorder promotes dissociation of excitons in III--V semiconductor heterostructures. A theory of polariton (photon dressed by phonon) spontaneous emission in a III--V semiconductor doped with semiconductor quantum dots (QDs) or quantum wells (QWs) is developed. For the first time, superradiant and subradiant polariton spontaneous emission phenomena in a polariton-QD (QW) coupled system are predicted when the resonance energies of the two identical QDs (QWs) lie outside the polaritonic energy gap. It is also predicted that when the resonance energies of the two identical QDs (QWs) lie inside the polaritonic energy gap, spontaneous emission of polariton in the polariton
Dynamic Models of Insurgent Activity
2014-05-19
one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a “fear...more realistic model of human locomotion. The movement of the criminal agents follows a biased Levy flight with step sizes distributed according to a...power-law distribution. The biased Brownian motion of the original model is then derived as a special case. Starting with an agent-based model, we
Nonlinear dynamics of the magnetosphere and space weather
Sharma, A. Surjalal
1996-01-01
The solar wind-magnetosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity on the dynamics. The observational time series data were used together with phase space reconstruction techniques to analyze the magnetospheric dynamics. Analysis of the solar wind, auroral electrojet and Dst indices showed low dimensionality of the dynamics and accurate prediction can be made with an input/output model. The predictability of the magnetosphere in spite of the apparent complexity arises from its dynamical synchronism with the solar wind. The electrodynamic coupling between different regions of the magnetosphere yields its coherent, low dimensional behavior. The data from multiple satellites and ground stations can be used to develop a spatio-temporal model that identifies the coupling between different regions. These nonlinear dynamical models provide space weather forecasting capabilities.
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...
Bond graph modeling of nuclear reactor dynamics
International Nuclear Information System (INIS)
Tylee, J.L.
1981-01-01
A tenth-order linear model of a pressurized water reactor (PWR) is developed using bond graph techniques. The model describes the nuclear heat generation process and the transfer of this heat to the reactor coolant. Comparisons between the calculated model response and test data from a small-scale PWR show the model to be an adequate representation of the actual plant dynamics. Possible application of the model in an advanced plant diagnostic system is discussed
James, Andrew J A; Konik, Robert M; Lecheminant, Philippe; Robinson, Neil J; Tsvelik, Alexei M
2018-02-26
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symmetries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1 + 1D quantum chromodynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.
James, Andrew J. A.; Konik, Robert M.; Lecheminant, Philippe; Robinson, Neil J.; Tsvelik, Alexei M.
2018-04-01
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symmetries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb–Liniger model, 1 + 1D quantum chromodynamics, as well as Landau–Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.
Swarm Intelligence for Urban Dynamics Modelling
International Nuclear Information System (INIS)
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.
2009-01-01
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Swarm Intelligence for Urban Dynamics Modelling
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.
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
Kalidindi, Surya R; Gomberg, Joshua A; Trautt, Zachary T; Becker, Chandler A
2015-08-28
Structure quantification is key to successful mining and extraction of core materials knowledge from both multiscale simulations as well as multiscale experiments. The main challenge stems from the need to transform the inherently high dimensional representations demanded by the rich hierarchical material structure into useful, high value, low dimensional representations. In this paper, we develop and demonstrate the merits of a data-driven approach for addressing this challenge at the atomic scale. The approach presented here is built on prior successes demonstrated for mesoscale representations of material internal structure, and involves three main steps: (i) digital representation of the material structure, (ii) extraction of a comprehensive set of structure measures using the framework of n-point spatial correlations, and (iii) identification of data-driven low dimensional measures using principal component analyses. These novel protocols, applied on an ensemble of structure datasets output from molecular dynamics (MD) simulations, have successfully classified the datasets based on several model input parameters such as the interatomic potential and the temperature used in the MD simulations.
International Nuclear Information System (INIS)
Kalidindi, Surya R; Gomberg, Joshua A; Trautt, Zachary T; Becker, Chandler A
2015-01-01
Structure quantification is key to successful mining and extraction of core materials knowledge from both multiscale simulations as well as multiscale experiments. The main challenge stems from the need to transform the inherently high dimensional representations demanded by the rich hierarchical material structure into useful, high value, low dimensional representations. In this paper, we develop and demonstrate the merits of a data-driven approach for addressing this challenge at the atomic scale. The approach presented here is built on prior successes demonstrated for mesoscale representations of material internal structure, and involves three main steps: (i) digital representation of the material structure, (ii) extraction of a comprehensive set of structure measures using the framework of n-point spatial correlations, and (iii) identification of data-driven low dimensional measures using principal component analyses. These novel protocols, applied on an ensemble of structure datasets output from molecular dynamics (MD) simulations, have successfully classified the datasets based on several model input parameters such as the interatomic potential and the temperature used in the MD simulations. (paper)
Dynamical models of spiral galaxies
International Nuclear Information System (INIS)
Grosbol, P.
1990-01-01
The effects of changing the basic parameters of rotation curve steepness, amount of bulge, and pitch angle of the imposed spiral pattern in the galactic model of Contoupolos and Grosbel (1986) are investigated. The general conclusions of the model are confirmed and shown to be insensitive to the specific choice of parameters for the galactic potential. The exact amplitude at which the nonlinear effects at the 4:1 resonance become important do, however, depend on the model
Energy Balance Models and Planetary Dynamics
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.
Stirling Engine Dynamic System Modeling
Nakis, Christopher G.
2004-01-01
The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.
Brand Equity Evolution: a System Dynamics Model
Directory of Open Access Journals (Sweden)
Edson Crescitelli
2009-04-01
Full Text Available One of the greatest challenges in brand management lies in monitoring brand equity over time. This paper aimsto present a simulation model able to represent this evolution. The model was drawn on brand equity concepts developed by Aaker and Joachimsthaler (2000, using the system dynamics methodology. The use ofcomputational dynamic models aims to create new sources of information able to sensitize academics and managers alike to the dynamic implications of their brand management. As a result, an easily implementable model was generated, capable of executing continuous scenario simulations by surveying casual relations among the variables that explain brand equity. Moreover, the existence of a number of system modeling tools will allow extensive application of the concepts used in this study in practical situations, both in professional and educational settings
Discrete dynamic modeling of cellular signaling networks.
Albert, Réka; Wang, Rui-Sheng
2009-01-01
Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.
Dynamic Modelling with "MLE-Energy Dynamic" for Primary School
Giliberti, Enrico; Corni, Federico
During the recent years simulation and modelling are growing instances in science education. In primary school, however, the main use of software is the simulation, due to the lack of modelling software tools specially designed to fit/accomplish the needs of primary education. In particular primary school teachers need to use simulation in a framework that is both consistent and simple enough to be understandable by children [2]. One of the possible area to approach modelling is about the construction of the concept of energy, in particular for what concerns the relations among substance, potential, power [3]. Following the previous initial research results with this approach [2], and with the static version of the software MLE Energy [1], we suggest the design and the experimentation of a dynamic modelling software—MLE dynamic-capable to represent dynamically the relations occurring when two substance-like quantities exchange energy, modifying their potential. By means of this software the user can graphically choose the dependent and independent variables and leave the other parameters fixed. The software has been initially evaluated, during a course of science education with a group of primary school teachers-to-be, to test the ability of the software to improve teachers' way of thinking in terms of substance-like quantities and their effects (graphical representation of the extensive, intensive variables and their mutual relations); moreover, the software has been tested with a group of primary school teachers, asking their opinion about the software didactical relevance in the class work.
Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis.
Noh, Yung-Kyun; Hamm, Jihun; Park, Frank Chongwoo; Zhang, Byoung-Tak; Lee, Daniel D
2018-01-01
Classical discriminant analysis attempts to discover a low-dimensional subspace where class label information is maximally preserved under projection. Canonical methods for estimating the subspace optimize an information-theoretic criterion that measures the separation between the class-conditional distributions. Unfortunately, direct optimization of the information-theoretic criteria is generally non-convex and intractable in high-dimensional spaces. In this work, we propose a novel, tractable algorithm for discriminant analysis that considers the class-conditional densities as interacting fluids in the high-dimensional embedding space. We use the Bhattacharyya criterion as a potential function that generates forces between the interacting fluids, and derive a computationally tractable method for finding the low-dimensional subspace that optimally constrains the resulting fluid flow. We show that this model properly reduces to the optimal solution for homoscedastic data as well as for heteroscedastic Gaussian distributions with equal means. We also extend this model to discover optimal filters for discriminating Gaussian processes and provide experimental results and comparisons on a number of datasets.
Dynamics of the standard model
Donoghue, John F; Holstein, Barry R
2014-01-01
Describing the fundamental theory of particle physics and its applications, this book provides a detailed account of the Standard Model, focusing on techniques that can produce information about real observed phenomena. The book begins with a pedagogic account of the Standard Model, introducing essential techniques such as effective field theory and path integral methods. It then focuses on the use of the Standard Model in the calculation of physical properties of particles. Rigorous methods are emphasized, but other useful models are also described. This second edition has been updated to include recent theoretical and experimental advances, such as the discovery of the Higgs boson. A new chapter is devoted to the theoretical and experimental understanding of neutrinos, and major advances in CP violation and electroweak physics have been given a modern treatment. This book is valuable to graduate students and researchers in particle physics, nuclear physics and related fields.
Forecasting with Dynamic Regression Models
Pankratz, Alan
2012-01-01
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.
Detecting low-dimensional chaos by the “noise titration” technique: Possible problems and remedies
International Nuclear Information System (INIS)
Gao Jianbo; Hu Jing; Mao Xiang; Tung Wenwen
2012-01-01
Highlights: ► Distinguishing low-dimensional chaos from noise is an important issue. ► Noise titration technique is one of the main approaches on the issue. ► Problems of noise titration technique are systematically discussed. ► Solutions to the problems of noise titration technique are provided. - Abstract: Distinguishing low-dimensional chaos from noise is an important issue in time series analysis. Among the many methods proposed for this purpose is the noise titration technique, which quantifies the amount of noise that needs to be added to the signal to fully destroy its nonlinearity. Two groups of researchers recently have questioned the validity of the technique. In this paper, we report a broad range of situations where the noise titration technique fails, and offer solutions to fix the problems identified.
Dynamic Modelling Of A SCARA Robot
Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez
1987-10-01
This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.
Dynamic modeling of IGCC power plants
International Nuclear Information System (INIS)
Casella, F.; Colonna, P.
2012-01-01
Integrated Gasification Combined Cycle (IGCC) power plants are an effective option to reduce emissions and implement carbon-dioxide sequestration. The combination of a very complex fuel-processing plant and a combined cycle power station leads to challenging problems as far as dynamic operation is concerned. Dynamic performance is extremely relevant because recent developments in the electricity market push toward an ever more flexible and varying operation of power plants. A dynamic model of the entire system and models of its sub-systems are indispensable tools in order to perform computer simulations aimed at process and control design. This paper presents the development of the lumped-parameters dynamic model of an entrained-flow gasifier, with special emphasis on the modeling approach. The model is implemented into software by means of the Modelica language and validated by comparison with one set of data related to the steady operation of the gasifier of the Buggenum power station in the Netherlands. Furthermore, in order to demonstrate the potential of the proposed modeling approach and the use of simulation for control design purposes, a complete model of an exemplary IGCC power plant, including its control system, has been developed, by re-using existing models of combined cycle plant components; the results of a load dispatch ramp simulation are presented and shortly discussed. - Highlights: ► The acausal dynamic model of an entrained gasifier has been developed. ► The model can be used to perform system optimization and control studies. ► The model has been validated using field data. ► Model use is illustrated with an example showing the transient of an IGCC plant.
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan
Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.
Structure and dynamics in low-dimensional guest-host systems
Energy Technology Data Exchange (ETDEWEB)
John E. Fischer
2000-05-01
This is the final report of the fourth of four three year grants of the same title. The program evolved from an earlier DOE grant on graphite intercalation compounds. Since its inception eight years ago, the focus evolved continuously from conjugated polymers to fullerenes, disordered carbons for Li-ion battery applications, and most recently carbon nanotubes, with side excursion back to GIC's to exploit a recent advance in synthesis of a potentially exciting new phase. The unifying themes are the versatility of carbon in forming novel solids, and the flexibility of intercalation chemistry to provide new materials with potentially useful properties.
Reply to "Comment on 'Nonparametric forecasting of low-dimensional dynamical systems' ".
Berry, Tyrus; Giannakis, Dimitrios; Harlim, John
2016-03-01
In this Reply we provide additional results which allow a better comparison of the diffusion forecast and the "past-noise" forecasting (PNF) approach for the El Niño index. We remark on some qualitative differences between the diffusion forecast and PNF, and we suggest an alternative use of the diffusion forecast for the purposes of forecasting the probabilities of extreme events.
Coupled iterated map models of action potential dynamics in a one-dimensional cable of cardiac cells
International Nuclear Information System (INIS)
Wang Shihong; Xie Yuanfang; Qu Zhilin
2008-01-01
Low-dimensional iterated map models have been widely used to study action potential dynamics in isolated cardiac cells. Coupled iterated map models have also been widely used to investigate action potential propagation dynamics in one-dimensional (1D) coupled cardiac cells, however, these models are usually empirical and not carefully validated. In this study, we first developed two coupled iterated map models which are the standard forms of diffusively coupled maps and overcome the limitations of the previous models. We then determined the coupling strength and space constant by quantitatively comparing the 1D action potential duration profile from the coupled cardiac cell model described by differential equations with that of the coupled iterated map models. To further validate the coupled iterated map models, we compared the stability conditions of the spatially uniform state of the coupled iterated maps and those of the 1D ionic model and showed that the coupled iterated map model could well recapitulate the stability conditions, i.e. the spatially uniform state is stable unless the state is chaotic. Finally, we combined conduction into the developed coupled iterated map model to study the effects of coupling strength on wave stabilities and showed that the diffusive coupling between cardiac cells tends to suppress instabilities during reentry in a 1D ring and the onset of discordant alternans in a periodically paced 1D cable
Online Learning of Industrial Manipulators' Dynamics Models
DEFF Research Database (Denmark)
Polydoros, Athanasios
2017-01-01
, it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated. In this thesis, is presented, a novel online machine learning approach which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...
Dynamic optimization deterministic and stochastic models
Hinderer, Karl; Stieglitz, Michael
2016-01-01
This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Dynamic modeling of the INAPRO aquaponic system
Karimanzira, Divas; Keesman, Karel J.; Kloas, Werner; Baganz, Daniela; Rauschenbach, Thomas
2016-01-01
The use of modeling techniques to analyze aquaponics systems is demonstrated with an example of dynamic modeling for the production of Nile tilapia (Oreochromis niloticus) and tomatoes (Solanum lycopersicon) using the innovative double recirculating aquaponic system ASTAF-PRO. For the management
Dynamic spatial panels : models, methods, and inferences
Elhorst, J. Paul
This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent
A Discrete Dynamical Model of Signed Partitions
Directory of Open Access Journals (Sweden)
G. Chiaselotti
2013-01-01
Full Text Available We use a discrete dynamical model with three evolution rules in order to analyze the structure of a partially ordered set of signed integer partitions whose main properties are actually not known. This model is related to the study of some extremal combinatorial sum problems.
Dynamic Factor Models for the Volatility Surface
DEFF Research Database (Denmark)
van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van
The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...
Derouane, Eric; Hölderich, Wolfgang
1990-01-01
Low dimensionality is a multifarious concept which applies to very diversified materials. Thus, examples of low-dimensional systems are structures with one or several layers, single lines or patterns of lines, and small clusters isolated or dispersed in solid systems. Such low dimensional features can be produced in a wide variety of materials systems with a broad spectrum of scientific and practical interests. These features, in turn, induce specific properties and, particularly, specific transport properties. In the case of zeolites, low dimensionality appears in the network of small-diameter pores of molecular size, extending in one, two or three di mensions, that these solids exhibit as a characteristic feature and which explains the term of "molecular sieves" currently used to name these ma terials. Indeed, a large number of industrial processes for separation of gases and liquids, and for catalysis are based upon the use of this low dimensional feature in zeolites. For instance, zeolites constit...
Detection of Defect-Induced Magnetism in Low-Dimensional ZnO Structures by Magnetophotocurrent.
Lorite, Israel; Kumar, Yogesh; Esquinazi, Pablo; Zandalazini, Carlos; de Heluani, Silvia Perez
2015-09-09
The detection of defect-induced magnetic order in single low-dimensional oxide structures is in general difficult because of the relatively small yield of magnetically ordered regions. In this work, the effect of an external magnetic field on the transient photocurrent measured after light irradiation on different ZnO samples at room temperature is studied. It has been found that a magnetic field produces a change in the relaxation rate of the transient photocurrent only in magnetically ordered ZnO samples. This rate can decrease or increase with field, depending on whether the magnetically ordered region is in the bulk or only at the surface of the ZnO sample. The phenomenon reported here is of importance for the development of magneto-optical low-dimensional oxides devices and provides a new guideline for the detection of magnetic order in low-dimensional magnetic semiconductors. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Dynamical modeling of surface tension
International Nuclear Information System (INIS)
Brackbill, J.U.; Kothe, D.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 might be made more useful. Specifically, we consider a derivation of the CSF equations from a minimization of surface energy as outlined by Jacqmin. 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 are discussed
Session 6: Dynamic Modeling and Systems Analysis
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
Mesoscale Models of Fluid Dynamics
Boghosian, Bruce M.; Hadjiconstantinou, Nicolas G.
During the last half century, enormous progress has been made in the field of computational materials modeling, to the extent that in many cases computational approaches are used in a predictive fashion. Despite this progress, modeling of general hydrodynamic behavior remains a challenging task. One of the main challenges stems from the fact that hydrodynamics manifests itself over a very wide range of length and time scales. On one end of the spectrum, one finds the fluid's "internal" scale characteristic of its molecular structure (in the absence of quantum effects, which we omit in this chapter). On the other end, the "outer" scale is set by the characteristic sizes of the problem's domain. The resulting scale separation or lack thereof as well as the existence of intermediate scales are key to determining the optimal approach. Successful treatments require a judicious choice of the level of description which is a delicate balancing act between the conflicting requirements of fidelity and manageable computational cost: a coarse description typically requires models for underlying processes occuring at smaller length and time scales; on the other hand, a fine-scale model will incur a significantly larger computational cost.
Modelling biased human trust dynamics
Hoogendoorn, M.; Jaffry, S.W.; Maanen, P.P. van; Treur, J.
2013-01-01
Abstract. Within human trust related behaviour, according to the literature from the domains of Psychology and Social Sciences often non-rational behaviour can be observed. Current trust models that have been developed typically do not incorporate non-rational elements in the trust formation
Dynamic model for a boiling water reactor
International Nuclear Information System (INIS)
Muscettola, M.
1963-07-01
A theoretical formulation is derived for the dynamics of a boiling water reactor of the pressure tube and forced circulation type. Attention is concentrated on neutron kinetics, fuel element heat transfer dynamics, and the primary circuit - that is the boiling channel, riser, steam drum, downcomer and recirculating pump of a conventional La Mont loop. Models for the steam and feedwater plant are not derived. (author)
A dynamical model for multifragmentation
International Nuclear Information System (INIS)
Ngo, H.; Ighezou, F.Z.; Ngo, C.
1999-01-01
The surface multifragmentation of highly excited (compression and thermal excitation) 208 Pb is investigated with a finite temperature spherical TDHF approximation coupled to a restructured aggregation model. This approach is discussed in terms of the data available from ALADIN collaboration at GSI on gold ion induced reactions on C, Al and Cu targets at 600 MeV/u excitation energy. The calculation showed that the slowest fragments originate in the nuclear volume while the smaller, faster fragments are emitted from surface
Nonlinear Dynamic Models in Advanced Life Support
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.
System Dynamics Modeling of Multipurpose Reservoir Operation
Directory of Open Access Journals (Sweden)
Ebrahim Momeni
2006-03-01
Full Text Available System dynamics, a feedback – based object – oriented simulation approach, not only represents complex dynamic systemic systems in a realistic way but also allows the involvement of end users in model development to increase their confidence in modeling process. The increased speed of model development, the possibility of group model development, the effective communication of model results, and the trust developed in the model due to user participation are the main strengths of this approach. The ease of model modification in response to changes in the system and the ability to perform sensitivity analysis make this approach more attractive compared with systems analysis techniques for modeling water management systems. In this study, a system dynamics model was developed for the Zayandehrud basin in central Iran. This model contains river basin, dam reservoir, plains, irrigation systems, and groundwater. Current operation rule is conjunctive use of ground and surface water. Allocation factor for each irrigation system is computed based on the feedback from groundwater storage in its zone. Deficit water is extracted from groundwater.The results show that applying better rules can not only satisfy all demands such as Gawkhuni swamp environmental demand, but it can also prevent groundwater level drawdown in future.
Modeling and identification in structural dynamics
Jayakumar, Paramsothy
1987-01-01
Analytical modeling of structures subjected to ground motions is an important aspect of fully dynamic earthquake-resistant design. In general, linear models are only sufficient to represent structural responses resulting from earthquake motions of small amplitudes. However, the response of structures during strong ground motions is highly nonlinear and hysteretic. System identification is an effective tool for developing analytical models from experimental data. Testing of full-scale prot...
Feature Extraction for Structural Dynamics Model Validation
Energy Technology Data Exchange (ETDEWEB)
Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield
2016-01-13
As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.
Record Dynamics and the Parking Lot Model for granular dynamics
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.
Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander
2016-04-01
We suggest a method for empirical forecast of climate dynamics basing on the reconstruction of reduced dynamical models in a form of random dynamical systems [1,2] derived from observational time series. The construction of proper embedding - the set of variables determining the phase space the model works in - is no doubt the most important step in such a modeling, but this task is non-trivial due to huge dimension of time series of typical climatic fields. Actually, an appropriate expansion of observational time series is needed yielding the number of principal components considered as phase variables, which are to be efficient for the construction of low-dimensional evolution operator. We emphasize two main features the reduced models should have for capturing the main dynamical properties of the system: (i) taking into account time-lagged teleconnections in the atmosphere-ocean system and (ii) reflecting the nonlinear nature of these teleconnections. In accordance to these principles, in this report we present the methodology which includes the combination of a new way for the construction of an embedding by the spatio-temporal data expansion and nonlinear model construction on the basis of artificial neural networks. The methodology is aplied to NCEP/NCAR reanalysis data including fields of sea level pressure, geopotential height, and wind speed, covering Northern Hemisphere. Its efficiency for the interannual forecast of various climate phenomena including ENSO, PDO, NAO and strong blocking event condition over the mid latitudes, is demonstrated. Also, we investigate the ability of the models to reproduce and predict the evolution of qualitative features of the dynamics, such as spectral peaks, critical transitions and statistics of extremes. This research was supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS) [1] Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, "Random
Modeling the dynamics of dissent
Lee, Eun; Holme, Petter; Lee, Sang Hoon
2017-11-01
We investigate the formation of opinion against authority in an authoritarian society composed of agents with different levels of authority. We explore a ;dissenting; opinion, held by lower-ranking, obedient, or less authoritative people, spreading in an environment of an ;affirmative; opinion held by authoritative leaders. A real-world example would be a corrupt society where people revolt against such leaders, but it can be applied to more general situations. In our model, agents can change their opinion depending on their authority relative to their neighbors and their own confidence level. In addition, with a certain probability, agents can override the affirmative opinion to take the dissenting opinion of a neighbor. Based on analytic derivation and numerical simulations, we observe that both the network structure and heterogeneity in authority, and their correlation, significantly affect the possibility of the dissenting opinion to spread through the population. In particular, the dissenting opinion is suppressed when the authority distribution is very heterogeneous and there exists a positive correlation between the authority and the number of neighbors of people (degree). Except for such an extreme case, though, spreading of the dissenting opinion takes place when people have the tendency to override the authority to hold the dissenting opinion, but the dissenting opinion can take a long time to spread to the entire society, depending on the model parameters. We argue that the internal social structure of agents sets the scale of the time to reach consensus, based on the analysis of the underlying structural properties of opinion spreading.
Modeling Dynamic Regulatory Processes in Stroke
McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio
2012-01-01
The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432
Coupling population dynamics with earth system models: the POPEM model.
Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J
2017-09-16
Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.
Dynamical properties of the Rabi model
International Nuclear Information System (INIS)
Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin
2017-01-01
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. (paper)
Energy Technology Data Exchange (ETDEWEB)
Moore, Joel; Rabe, Karin; Nayak, Chetan; Troyer, Matthias
2012-05-01
Aspen Center for Physics Project Summary DOE Budget Period: 10/1/2011 to 9/30/2012 Contract # DE-SC0007479 New Paradigms for Low-Dimensional Electronic Materials The 2012 Aspen Winter Conference on Condensed Matter Physics was held at the Aspen Center for Physics from February 5 to 10, 2012. Seventy-four participants from seven countries, and several universities and national labs attended the workshop titled, New Paradigms for Low-Dimensional Electronic Materials. There were 34 formal talks, and a number of informal discussions held during the week. Talks covered a variety of topics related to DOE BES priorities, including, for example, advanced photon techniques (Hasan, Abbamonte, Orenstein, Shen, Ghosh) and predictive theoretical modeling of materials properties (Rappe, Pickett, Balents, Zhang, Vanderbilt); the full conference schedule is provided with this report. The week's events included a public lecture (Quantum Matters given by Chetan Nayak from Microsoft Research) and attended by 234 members of the public, and a physics caf© geared for high schoolers that is a discussion with physicists conducted by Kathryn Moler (Stanford University) and Andrew M. Rappe (University of Pennsylvania) and attended by 67 locals and visitors. While there were no published proceedings, some of the talks are posted online and can be Googled. The workshop was organized by Joel Moore (University of California Berkeley), Chetan Nayak (Microsoft Research), Karin Rabe (Rutgers University), and Matthias Troyer (ETH Zurich). Two organizers who did not attend the conference were Gabriel Aeppli (University College London & London Centre for Nanotechnology) and Andrea Cavalleri (Oxford University & Max Planck Hamburg).
Dynamic Modeling of ThermoFluid Systems
DEFF Research Database (Denmark)
Jensen, Jakob Munch
2003-01-01
The objective of the present study has been to developed dynamic models for two-phase flow in pipes (evaporation and condensation). Special attention has been given to modeling evaporators for refrigeration plant particular dry-expansion evaporators. Models of different complexity have been...... formulated. The different models deviate with respect to the detail¿s included and calculation time in connection with simulation. The models have been implemented in a new library named ThermoTwoPhase to the programming language Modelica. A test rig has been built with an evaporator instrumented in a way...
Research on nonlinear stochastic dynamical price model
International Nuclear Information System (INIS)
Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng
2008-01-01
In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies
Modelling environmental dynamics. Advances in goematic solutions
Energy Technology Data Exchange (ETDEWEB)
Paegelow, Martin [Toulouse-2 Univ., 31 (France). GEODE UMR 5602 CNRS; Camacho Olmedo, Maria Teresa (eds.) [Granada Univ (Spain). Dpto. de Analisis Geografico Regional y Geografia Fisica
2008-07-01
Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management. The first chapter introduces terminology and provides an overview of methodological modelling approaches which may be applied to environmental and complex dynamics. Based on this introduction this book illustrates various models applied to a large variety of themes: deforestation in tropical regions, fire risk, natural reforestation in European mountains, agriculture, biodiversity, urbanism, climate change and land management for decision support, etc. These case studies, provided by a large international spectrum of researchers and presented in a uniform structure, focus particularly on methods and model validation so that this book is not only aimed at researchers and graduates but also at professionals. (orig.)
Modeling emotional dynamics : currency versus field.
Energy Technology Data Exchange (ETDEWEB)
Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago
2008-08-01
Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.
Modeling initial contact dynamics during ambulation with dynamic simulation.
Meyer, Andrew R; Wang, Mei; Smith, Peter A; Harris, Gerald F
2007-04-01
Ankle-foot orthoses are frequently used interventions to correct pathological gait. Their effects on the kinematics and kinetics of the proximal joints are of great interest when prescribing ankle-foot orthoses to specific patient groups. Mathematical Dynamic Model (MADYMO) is developed to simulate motor vehicle crash situations and analyze tissue injuries of the occupants based multibody dynamic theories. Joint kinetics output from an inverse model were perturbed and input to the forward model to examine the effects of changes in the internal sagittal ankle moment on knee and hip kinematics following heel strike. Increasing the internal ankle moment (augmentation, equivalent to gastroc-soleus contraction) produced less pronounced changes in kinematic results at the hip, knee and ankle than decreasing the moment (attenuation, equivalent to gastroc-soleus relaxation). Altering the internal ankle moment produced two distinctly different kinematic curve morphologies at the hip. Decreased internal ankle moments increased hip flexion, peaking at roughly 8% of the gait cycle. Increasing internal ankle moments decreased hip flexion to a lesser degree, and approached normal at the same point in the gait cycle. Increasing the internal ankle moment produced relatively small, well-behaved extension-biased kinematic results at the knee. Decreasing the internal ankle moment produced more substantial changes in knee kinematics towards flexion that increased with perturbation magnitude. Curve morphologies were similar to those at the hip. Immediately following heel strike, kinematic results at the ankle showed movement in the direction of the internal moment perturbation. Increased internal moments resulted in kinematic patterns that rapidly approach normal after initial differences. When the internal ankle moment was decreased, differences from normal were much greater and did not rapidly decrease. This study shows that MADYMO can be successfully applied to accomplish forward
A Stochastic Model for Malaria Transmission Dynamics
Directory of Open Access Journals (Sweden)
Rachel Waema Mbogo
2018-01-01
Full Text Available Malaria is one of the three most dangerous infectious diseases worldwide (along with HIV/AIDS and tuberculosis. In this paper we compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in malaria transmission dynamics. Relationships between the basic reproduction number for malaria transmission dynamics between humans and mosquitoes and the extinction thresholds of corresponding continuous-time Markov chain models are derived under certain assumptions. The stochastic model is formulated using the continuous-time discrete state Galton-Watson branching process (CTDSGWbp. The reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or die out. Thresholds for disease extinction from stochastic models contribute crucial knowledge on disease control and elimination and mitigation of infectious diseases. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that malaria outbreak is more likely if the disease is introduced by infected mosquitoes as opposed to infected humans. These insights demonstrate the importance of a policy or intervention focusing on controlling the infected mosquito population if the control of malaria is to be realized.
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.
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
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.
On the mathematical modeling of soccer dynamics
Machado, J. A. Tenreiro; Lopes, António M.
2017-12-01
This paper addresses the modeling and dynamical analysis of soccer teams. Two modeling perspectives based on the concepts of fractional calculus are adopted. In the first, the power law behavior and fractional-order integration are explored. In the second, a league season is interpreted in the light of a system where the teams are represented by objects (particles) that evolve in time and interact (collide) at successive rounds with dynamics driven by the outcomes of the matches. The two proposed models embed implicitly details of players and coaches, or strategical and tactical maneuvers during the matches. Therefore, the scale of observation focuses on the teams behavior in the scope of the observed variables. Data characterizing two European soccer leagues in the season 2015-2016 are adopted and processed. The model leads to the emergence of patterns that are analyzed and interpreted.
BWR stability using a reducing dynamical model
International Nuclear Information System (INIS)
Ballestrin Bolea, J. M.; Blazquez Martinez, J. B.
1990-01-01
BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical structure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations is non-linear. Simple parametric calculation of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author)
Modelling the Dynamics of Emotional Awareness
Thilakarathne, D.J.; Treur, J.; Schaub, T.
2014-01-01
In this paper, based on literature from Cognitive and Affective Neuroscience, a computational agent model is introduced incorporating the role of emotional awareness states in the dynamics of action generation. More specifically, it covers both automatic, unconscious (bottom-up) and more cognitive
Object Oriented Modelling and Dynamical Simulation
DEFF Research Database (Denmark)
Wagner, Falko Jens; Poulsen, Mikael Zebbelin
1998-01-01
This report with appendix describes the work done in master project at DTU.The goal of the project was to develop a concept for simulation of dynamical systems based on object oriented methods.The result was a library of C++-classes, for use when both building componentbased models and when...
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...
CFTSIM-ITER dynamic fuel cycle model
International Nuclear Information System (INIS)
Busigin, A.; Gierszewski, P.
1998-01-01
Dynamic system models have been developed for specific tritium systems with considerable detail and for integrated fuel cycles with lesser detail (e.g. D. Holland, B. Merrill, Analysis of tritium migration and deposition in fusion reactor systems, Proceedings of the Ninth Symposium Eng. Problems of Fusion Research (1981); M.A. Abdou, E. Vold, C. Gung, M. Youssef, K. Shin, DT fuel self-sufficiency in fusion reactors, Fusion Technol. (1986); G. Spannagel, P. Gierszewski, Dynamic tritium inventory of a NET/ITER fuel cycle with lithium salt solution blanket, Fusion Eng. Des. (1991); W. Kuan, M.A. Abdou, R.S. Willms, Dynamic simulation of a proposed ITER tritium processing system, Fusion Technol. (1995)). In order to provide a tool to understand and optimize the behavior of the ITER fuel cycle, a dynamic fuel cycle model called CFTSIM is under development. The CFTSIM code incorporates more detailed ITER models, specifically for the important isotope separation system, and also has an easier-to-use graphical interface. This paper provides an overview of CFTSIM Version 1.0. The models included are those with significant and varying tritium inventories over a test campaign: fueling, plasma and first wall, pumping, fuel cleanup, isotope separation and storage. An illustration of the results is shown. (orig.)
The quantum Rabi model: solution and dynamics
International Nuclear Information System (INIS)
Xie, Qiongtao; Zhong, Honghua; Lee, Chaohong; Batchelor, Murray T
2017-01-01
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. (topical review)
A complete dynamic model of primary sedimentation.
Paraskevas, P; Kolokithas, G; Lekkas, T
1993-11-01
A dynamic mathematical model for the primary clarifier of a wastewater treatment plant is described, which is represented by a general tanks-in-series model, to simulate insufficient mixing. The model quantifies successfully the diurnal response of both the suspended and dissolved species. It is general enough, so that the values of the parameters can be replaced with those applicable to a specific case. The model was verified through data from the Biological Centre of Metamorfosi, in Athens, Greece, and can be used to assist in the design of new plants or in the analysis and output predictions of existing ones.
Dynamic Modeling of CDS Index Tranche Spreads
DEFF Research Database (Denmark)
Dorn, Jochen
This paper provides a Market Model which implies a dynamics for standardized CDS index tranche spreads, i.e. tranches which securitise CDS index series and dispose of predefined subordination. This model is useful for pricing options on tranches with future Issue Dates as well as for modeling...... options on structured credit derivatives. With the upcoming regulation of the CDS market in perspective, the model presented here is also an attempt to face the effects on pricing approaches provoked by an eventual Clearing Chamber . It becomes also possible to calibrate Index Tranche Options with bespoke...... tenors/tranche subordination to market data obtained by more liquid Index Tranche Options with standard characteristics....
Uncertainty and its propagation in dynamics models
International Nuclear Information System (INIS)
Devooght, J.
1994-01-01
The purpose of this paper is to bring together some characteristics due to uncertainty when we deal with dynamic models and therefore to propagation of uncertainty. The respective role of uncertainty and inaccuracy is examined. A mathematical formalism based on Chapman-Kolmogorov equation allows to define a open-quotes subdynamicsclose quotes where the evolution equation takes the uncertainty into account. The problem of choosing or combining models is examined through a loss function associated to a decision
Dynamic multibody modeling for tethered space elevators
Williams, Paul
2009-08-01
This paper presents a fundamental modeling strategy for dealing with powered and propelled bodies moving along space tethers. The tether is divided into a large number of discrete masses, which are connected by viscoelastic springs. The tether is subject to the full range of forces expected in Earth orbit in a relatively simple manner. Two different models of the elevator dynamics are presented. In order to capture the effect of the elevator moving along the tether, the elevator dynamics are included as a separate body in both models. One model treats the elevator's motion dynamically, where propulsive and friction forces are applied to the elevator body. The second model treats the elevator's motion kinematically, where the distance along the tether is determined by adjusting the lengths of tether on either side of the elevator. The tether model is used to determine optimal configurations for the space elevator. A modal analysis of two different configurations is presented which show that the fundamental mode of oscillation is a pendular one around the anchor point with a period on the order of 160 h for the in-plane motion, and 24 h for the out-of-plane motion. Numerical simulation results of the effects of the elevator moving along the cable are presented for different travel velocities and different elevator masses.
Sepsis progression and outcome: a dynamical model
Directory of Open Access Journals (Sweden)
Gessler Damian DG
2006-02-01
Full Text Available Abstract 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.
Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof
2018-01-01
We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.
Mineral vein dynamics modeling (FRACS). Phase 1
Energy Technology Data Exchange (ETDEWEB)
Urai, J.; Virgo, S.; Arndt, M. [RWTH Aachen (Germany). Geologie-Endogene Dynamik] [and others
2013-07-15
The Mineral Vein Dynamics Modeling group ''FRACS'' is a team of 7 research groups from the Universities of Mainz, Aachen, Tuebingen, Karlsruhe, Bayreuth, ETH Zuerich and Glasgow working on an understanding of the dynamic development of fracturing, fluid flow and fracture sealing. World-class field laboratories, especially carbonate sequences from the Oman Mountains are studied and classified. State of the art numerical programs are written, expanded and used to simulate the dynamic interaction of fracturing, flow and resealing and the results are compared with the natural examples. Newest analytical technologies including laser scanning, high resolution X-ray microtomography, fluid inclusion and isotope analysis are performed to understand and compare the results of simulations with natural examples. A new statistical program was developed to classify the natural fracture and vein systems and compare them with dynamic numerical simulations and analytical models. The results of the first project phase are extremely promising. Most of the numerical models have been developed up to the stage where they can be used to simulate the natural examples. The models allow a definition of the first proxies for high fluid pressure and tectonic stresses. It was found out that the Oman Mountains are a complex and very dynamic system that constantly fractures and reseals from the scale of small veins up to the scale of large normal and strike slip faults. The numerical simulations also indicate that the permeability of such systems is not a constant but that the system adjusts to the driving force, for ex-ample high fluid pressure. When the system reseals fast a fluctuating behavior can be observed in the models where the system constantly fractures and reseals, which is in accordance with the observation of the natural laboratory.
Activation of zero-error classical capacity in low-dimensional quantum systems
Park, Jeonghoon; Heo, Jun
2018-06-01
Channel capacities of quantum channels can be nonadditive even if one of two quantum channels has no channel capacity. We call this phenomenon activation of the channel capacity. In this paper, we show that when we use a quantum channel on a qubit system, only a noiseless qubit channel can generate the activation of the zero-error classical capacity. In particular, we show that the zero-error classical capacity of two quantum channels on qubit systems cannot be activated. Furthermore, we present a class of examples showing the activation of the zero-error classical capacity in low-dimensional systems.
How to measure the cooper pair mass using plasmons in low-dimensional superconductor structures
International Nuclear Information System (INIS)
Mishonov, T.M.
1990-06-01
The creation of the Cooper pair mass-spectroscopy is suggested. The plasmons in low-dimensional superconductor structures (layers or wires in dielectric background) are theoretically considered to that purpose. The Cooper pair mass m * can be determined by measurements of the Doppler shift of the plasmon frequency when a direct current is applied through the superconductor. The plasmons with frequency ω lower than the superconducting gap 2 Δ can be detected by the same fare-infrared (FIR) absorption technique and grating couplings used previously for investigation of two-dimension (2D) plasmons in semiconductor microstructures. (author). 17 refs, 2 figs
Low-Dimensional Nanomaterials as Active Layer Components in Thin-Film Photovoltaics
Shastry, Tejas Attreya
Thin-film photovoltaics offer the promise of cost-effective and scalable solar energy conversion, particularly for applications of semi-transparent solar cells where the poor absorption of commercially-available silicon is inadequate. Applications ranging from roof coatings that capture solar energy to semi-transparent windows that harvest the immense amount of incident sunlight on buildings could be realized with efficient and stable thin-film solar cells. However, the lifetime and efficiency of thin-film solar cells continue to trail their inorganic silicon counterparts. Low-dimensional nanomaterials, such as carbon nanotubes and two-dimensional metal dichalcogenides, have recently been explored as materials in thin-film solar cells due to their exceptional optoelectronic properties, solution-processability, and chemical inertness. Thus far, issues with the processing of these materials has held back their implementation in efficient photovoltaics. This dissertation reports processing advances that enable demonstrations of low-dimensional nanomaterials in thin-film solar cells. These low-dimensional photovoltaics show enhanced photovoltaic efficiency and environmental stability in comparison to previous devices, with a focus on semiconducting single-walled carbon nanotubes as an active layer component. The introduction summarizes recent advances in the processing of carbon nanotubes and their implementation through the thin-film photovoltaic architecture, as well as the use of two-dimensional metal dichalcogenides in photovoltaic applications and potential future directions for all-nanomaterial solar cells. The following chapter reports a study of the interaction between carbon nanotubes and surfactants that enables them to be sorted by electronic type via density gradient ultracentrifugation. These insights are utilized to construct of a broad distribution of carbon nanotubes that absorb throughout the solar spectrum. This polychiral distribution is then shown
Direct modeling for computational fluid dynamics
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
New concepts for dynamic plant uptake models
DEFF Research Database (Denmark)
Rein, Arno; Legind, Charlotte Nielsen; Trapp, Stefan
2011-01-01
Models for the prediction of chemical uptake into plants are widely applied tools for human and wildlife exposure assessment, pesticide design and for environmental biotechnology such as phytoremediation. Steady-state considerations are often applied, because they are simple and have a small data...... need. However, often the emission pattern is non-steady. Examples are pesticide spraying, or the application of manure and sewage sludge on agricultural fields. In these scenarios, steady-state solutions are not valid, and dynamic simulation is required. We compared different approaches for dynamic...
Statistical models of petrol engines vehicles dynamics
Ilie, C. O.; Marinescu, M.; Alexa, O.; Vilău, R.; Grosu, D.
2017-10-01
This paper focuses on studying statistical models of vehicles dynamics. It was design and perform a one year testing program. There were used many same type cars with gasoline engines and different mileage. Experimental data were collected of onboard sensors and those on the engine test stand. A database containing data of 64th tests was created. Several mathematical modelling were developed using database and the system identification method. Each modelling is a SISO or a MISO linear predictive ARMAX (AutoRegressive-Moving-Average with eXogenous inputs) model. It represents a differential equation with constant coefficients. It were made 64th equations for each dependency like engine torque as output and engine’s load and intake manifold pressure, as inputs. There were obtained strings with 64 values for each type of model. The final models were obtained using average values of the coefficients. The accuracy of models was assessed.
Indonesia’s Electricity Demand Dynamic Modelling
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.
Friction modelling of preloaded tube contact dynamics
International Nuclear Information System (INIS)
Hassan, M.A.; Rogers, R.J.
2004-01-01
Many loosely supported components are subjected to flow-induced vibration leading to localized wear. Life prediction depends on robust and accurate modelling of the nonlinear dynamics as the components interact with their supports. The output of such analysis is the component dynamic response and impact forces, including friction forces during stick-slip motions. Such results are used to determine the normal work rates, which are utilized to predict fretting wear damage. Accurate estimates of these parameters are essential. This paper presents simulations of a loosely supported fuel-channel tube subject to turbulence excitation. The effects of tube/support clearance and preload are investigated. Several friction models, including velocity-limited, spring-damper, and force-balance are utilized. A comparison of these models is carried out to investigate their accuracy. The results show good agreement with experimental work rates when a simple iterative procedure to update the friction forces is used. (authors)
Dynamic Circuit Model for Spintronic Devices
Alawein, Meshal
2017-01-09
In this work we propose a finite-difference scheme based circuit model of a general spintronic device and benchmark it with other models proposed for spintronic switching devices. Our model is based on the four-component spin circuit theory and utilizes the widely used coupled stochastic magnetization dynamics/spin transport framework. In addition to the steady-state analysis, this work offers a transient analysis of carrier transport. By discretizing the temporal and spatial derivatives to generate a linear system of equations, we derive new and simple finite-difference conductance matrices that can, to the first order, capture both static and dynamic behaviors of a spintronic device. We also discuss an extension of the spin modified nodal analysis (SMNA) for time-dependent situations based on the proposed scheme.
Dynamic Circuit Model for Spintronic Devices
Alawein, Meshal; Fariborzi, Hossein
2017-01-01
In this work we propose a finite-difference scheme based circuit model of a general spintronic device and benchmark it with other models proposed for spintronic switching devices. Our model is based on the four-component spin circuit theory and utilizes the widely used coupled stochastic magnetization dynamics/spin transport framework. In addition to the steady-state analysis, this work offers a transient analysis of carrier transport. By discretizing the temporal and spatial derivatives to generate a linear system of equations, we derive new and simple finite-difference conductance matrices that can, to the first order, capture both static and dynamic behaviors of a spintronic device. We also discuss an extension of the spin modified nodal analysis (SMNA) for time-dependent situations based on the proposed scheme.
Dynamic Intellectual Capital Model in a Company
Directory of Open Access Journals (Sweden)
Vladimir Shatrevich
2015-06-01
Full Text Available The aim of this paper is to indicate the relations between company’s value added (VA and intangible assets. Authors declare that Intellectual capital (IC is one of the most relevant intangibles for a company, and the concept with measurement, and the relation with value creation is necessary for modern markets. Since relationship between IC elements and VA are complicated, this paper is aimed to create a usable dynamic model for building company’s value added through intellectual capital. The model is incorporating that outputs from IC elements are not homogeneously received and made some contributions to dynamic nature of IC relation and VA. Variables that will help companies to evaluate contribution of each element of IC are added to the model. This paper emphasizes the importance of a company’s IC and the positive interaction between them in generating profits for company.
Friction modelling of preloaded tube contact dynamics
International Nuclear Information System (INIS)
Hassan, M.A.; Rogers, R.J.
2005-01-01
Many loosely supported components are subjected to flow-induced vibration leading to localized wear. Life prediction depends on robust and accurate modelling of the nonlinear dynamics as the components interact with their supports. The output of such analysis is the component dynamic response and impact forces, including friction forces during stick-slip motions. Such results are used to determine the normal work rates, which are utilized to predict fretting wear damage. Accurate estimates of these parameters are essential. This paper presents simulations of a loosely supported fuel-channel tube subject to turbulence excitation. The effects of tube/support clearance and preload are investigated. Several friction models, including velocity-limited, spring-damper and force-balance are utilized. A comparison of these models is carried out to investigate their accuracy. The results show good agreement with experimental work rates when a simple iterative procedure to update the friction forces is used
Traffic flow dynamics data, models and simulation
Treiber, Martin
2013-01-01
This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on ...
Complex networks under dynamic repair model
Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao
2018-01-01
Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
Collisional model for granular impact dynamics.
Clark, Abram H; Petersen, Alec J; Behringer, Robert P
2014-01-01
When an intruder strikes a granular material from above, the grains exert a stopping force which decelerates and stops the intruder. Many previous studies have used a macroscopic force law, including a drag force which is quadratic in velocity, to characterize the decelerating force on the intruder. However, the microscopic origins of the force-law terms are still a subject of debate. Here, drawing from previous experiments with photoelastic particles, we present a model which describes the velocity-squared force in terms of repeated collisions with clusters of grains. From our high speed photoelastic data, we infer that "clusters" correspond to segments of the strong force network that are excited by the advancing intruder. The model predicts a scaling relation for the velocity-squared drag force that accounts for the intruder shape. Additionally, we show that the collisional model predicts an instability to rotations, which depends on the intruder shape. To test this model, we perform a comprehensive experimental study of the dynamics of two-dimensional granular impacts on beds of photoelastic disks, with different profiles for the leading edge of the intruder. We particularly focus on a simple and useful case for testing shape effects by using triangular-nosed intruders. We show that the collisional model effectively captures the dynamics of intruder deceleration and rotation; i.e., these two dynamical effects can be described as two different manifestations of the same grain-scale physical processes.
Next Generation Carbon-Nitrogen Dynamics Model
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
Analysing the temporal dynamics of model performance for hydrological models
Reusser, D.E.; Blume, T.; Schaefli, B.; Zehe, E.
2009-01-01
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
An introduction to modeling neuronal dynamics
Börgers, Christoph
2017-01-01
This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book. .
Five challenges in modelling interacting strain dynamics
Directory of Open Access Journals (Sweden)
Paul S. Wikramaratna
2015-03-01
Full Text Available Population epidemiological models where hosts can be infected sequentially by different strains have the potential to help us understand many important diseases. Researchers have in recent years started to develop and use such models, but the extra layer of complexity from multiple strains brings with it many technical challenges. It is therefore hard to build models which have realistic assumptions yet are tractable. Here we outline some of the main challenges in this area. First we begin with the fundamental question of how to translate from complex small-scale dynamics within a host to useful population models. Next we consider the nature of so-called “strain space”. We describe two key types of host heterogeneities, and explain how models could help generate a better understanding of their effects. Finally, for diseases with many strains, we consider the challenge of modelling how immunity accumulates over multiple exposures.
Structural system identification: Structural dynamics model validation
Energy Technology Data Exchange (ETDEWEB)
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.
Low-dimensional carbon and MXene-based electrochemical capacitor electrodes.
Yoon, Yeoheung; Lee, Keunsik; Lee, Hyoyoung
2016-04-29
Due to their unique structure and outstanding intrinsic physical properties such as extraordinarily high electrical conductivity, large surface area, and various chemical functionalities, low-dimension-based materials exhibit great potential for application in electrochemical capacitors (ECs). The electrical properties of electrochemical capacitors are determined by the electrode materials. Because energy charge storage is a surface process, the surface properties of the electrode materials greatly influence the electrochemical performance of the cell. Recently, graphene, a single layer of sp(2)-bonded carbon atoms arrayed into two-dimensional carbon nanomaterial, has attracted wide interest as an electrode material for electrochemical capacitor applications due to its unique properties, including a high electrical conductivity and large surface area. Several low-dimensional materials with large surface areas and high conductivity such as onion-like carbons (OLCs), carbide-derived carbons (CDCs), carbon nanotubes (CNTs), graphene, metal hydroxide, transition metal dichalcogenides (TMDs), and most recently MXene, have been developed for electrochemical capacitors. Therefore, it is useful to understand the current issues of low-dimensional materials and their device applications.
Synthesis, Properties, and Applications of Low-Dimensional Carbon-Related Nano materials
International Nuclear Information System (INIS)
Mostofizadeh, A.; Li, Y.; Song, B.; Huang, Y.; Mostofizadeh, A.
2011-01-01
In recent years, many theoretical and experimental studies have been carried out to develop one of the most interesting aspects of the science and nano technology which is called carbon-related nano materials. The goal of this paper is to provide a review of some of the most exciting and important developments in the synthesis, properties, and applications of low-dimensional carbon nano materials. Carbon nano materials are formed in various structural features using several different processing methods. The synthesis techniques used to produce specific kinds of low-dimensional carbon nano materials such as zero-dimensional carbon nano materials (including fullerene, carbon-encapsulated metal nanoparticles, nano diamond, and onion-like carbons), one-dimensional carbon nano materials (including carbon nano fibers and carbon nano tubes), and two-dimensional carbon nano materials (including graphene and carbon nano walls) are discussed in this paper. Subsequently, the paper deals with an overview of the properties of the mainly important products as well as some important applications and the future outlooks of these advanced nano materials.
Directory of Open Access Journals (Sweden)
Chenchen Jiang
2017-01-01
Full Text Available In the past decades, in situ scanning electron microscopy (SEM has become a powerful technique for the experimental study of low-dimensional (1D/2D nanomaterials, since it can provide unprecedented details for individual nanostructures upon mechanical and electrical stimulus and thus uncover the fundamental deformation and failure mechanisms for their device applications. In this overview, we summarized recent developments on in situ SEM-based mechanical and electrical characterization techniques including tensile, compression, bending, and electrical property probing on individual nanostructures, as well as the state-of-the-art electromechanical coupling analysis. In addition, the advantages and disadvantages of in situ SEM tests were also discussed with some possible solutions to address the challenges. Furthermore, critical challenges were also discussed for the development and design of robust in situ SEM characterization platform with higher resolution and wider range of samples. These experimental efforts have offered in-depth understanding on the mechanical and electrical properties of low-dimensional nanomaterial components and given guidelines for their further structural and functional applications.
Synthesis, Properties, and Applications of Low-Dimensional Carbon-Related Nanomaterials
Directory of Open Access Journals (Sweden)
Ali Mostofizadeh
2011-01-01
Full Text Available In recent years, many theoretical and experimental studies have been carried out to develop one of the most interesting aspects of the science and nanotechnology which is called carbon-related nanomaterials. The goal of this paper is to provide a review of some of the most exciting and important developments in the synthesis, properties, and applications of low-dimensional carbon nanomaterials. Carbon nanomaterials are formed in various structural features using several different processing methods. The synthesis techniques used to produce specific kinds of low-dimensional carbon nanomaterials such as zero-dimensional carbon nanomaterials (including fullerene, carbon-encapsulated metal nanoparticles, nanodiamond, and onion-like carbons, one-dimensional carbon nanomaterials (including carbon nanofibers and carbon nanotubes, and two-dimensional carbon nanomaterials (including graphene and carbon nanowalls are discussed in this paper. Subsequently, the paper deals with an overview of the properties of the mainly important products as well as some important applications and the future outlooks of these advanced nanomaterials.
Low-dimensional carbon and MXene-based electrochemical capacitor electrodes
International Nuclear Information System (INIS)
Yoon, Yeoheung; Lee, Hyoyoung; Lee, Keunsik
2016-01-01
Due to their unique structure and outstanding intrinsic physical properties such as extraordinarily high electrical conductivity, large surface area, and various chemical functionalities, low-dimension-based materials exhibit great potential for application in electrochemical capacitors (ECs). The electrical properties of electrochemical capacitors are determined by the electrode materials. Because energy charge storage is a surface process, the surface properties of the electrode materials greatly influence the electrochemical performance of the cell. Recently, graphene, a single layer of sp 2 -bonded carbon atoms arrayed into two-dimensional carbon nanomaterial, has attracted wide interest as an electrode material for electrochemical capacitor applications due to its unique properties, including a high electrical conductivity and large surface area. Several low-dimensional materials with large surface areas and high conductivity such as onion-like carbons (OLCs), carbide-derived carbons (CDCs), carbon nanotubes (CNTs), graphene, metal hydroxide, transition metal dichalcogenides (TMDs), and most recently MXene, have been developed for electrochemical capacitors. Therefore, it is useful to understand the current issues of low-dimensional materials and their device applications. (topical review)
Jiang, Chenchen; Lu, Haojian; Zhang, Hongti; Shen, Yajing; Lu, Yang
2017-01-01
In the past decades, in situ scanning electron microscopy (SEM) has become a powerful technique for the experimental study of low-dimensional (1D/2D) nanomaterials, since it can provide unprecedented details for individual nanostructures upon mechanical and electrical stimulus and thus uncover the fundamental deformation and failure mechanisms for their device applications. In this overview, we summarized recent developments on in situ SEM-based mechanical and electrical characterization techniques including tensile, compression, bending, and electrical property probing on individual nanostructures, as well as the state-of-the-art electromechanical coupling analysis. In addition, the advantages and disadvantages of in situ SEM tests were also discussed with some possible solutions to address the challenges. Furthermore, critical challenges were also discussed for the development and design of robust in situ SEM characterization platform with higher resolution and wider range of samples. These experimental efforts have offered in-depth understanding on the mechanical and electrical properties of low-dimensional nanomaterial components and given guidelines for their further structural and functional applications.
Modeling the dynamic characteristics of pneumatic muscle.
Reynolds, D B; Repperger, D W; Phillips, C A; Bandry, G
2003-03-01
A pneumatic muscle (PM) system was studied to determine whether a three-element model could describe its dynamics. As far as the authors are aware, this model has not been used to describe the dynamics of PM. A new phenomenological model consists of a contractile (force-generating) element, spring element, and damping element in parallel. The PM system was investigated using an apparatus that allowed precise and accurate actuation pressure (P) control by a linear servo-valve. Length change of the PM was measured by a linear potentiometer. Spring and damping element functions of P were determined by a static perturbation method at several constant P values. These results indicate that at constant P, PM behaves as a spring and damper in parallel. The contractile element function of P was determined by the response to a step input in P, using values of spring and damping elements from the perturbation study. The study showed that the resulting coefficient functions of the three-element model describe the dynamic response to the step input of P accurately, indicating that the static perturbation results can be applied to the dynamic case. This model is further validated by accurately predicting the contraction response to a triangular P waveform. All three elements have pressure-dependent coefficients for pressure P in the range 207 < or = P < or = 621 kPa (30 < or = P < or = 90 psi). Studies with a step decrease in P (relaxation of the PM) indicate that the damping element coefficient is smaller during relaxation than contraction.
ITER Dynamic Tritium Inventory Modeling Code
International Nuclear Information System (INIS)
Cristescu, Ioana-R.; Doerr, L.; Busigin, A.; Murdoch, D.
2005-01-01
A tool for tritium inventory evaluation within each sub-system of the Fuel Cycle of ITER is vital, with respect to both the process of licensing ITER and also for operation. It is very likely that measurements of total tritium inventories may not be possible for all sub-systems, however tritium accounting may be achieved by modeling its hold-up within each sub-system and by validating these models in real-time against the monitored flows and tritium streams between the systems. To get reliable results, an accurate dynamic modeling of the tritium content in each sub-system is necessary. In order to optimize the configuration and operation of the ITER fuel cycle, a dynamic fuel cycle model was developed progressively in the decade up to 2000-2001. As the design for some sub-systems from the fuel cycle (i.e. Vacuum pumping, Neutral Beam Injectors (NBI)) have substantially progressed meanwhile, a new code developed under a different platform to incorporate these modifications has been developed. The new code is taking over the models and algorithms for some subsystems, such as Isotope Separation System (ISS); where simplified models have been previously considered, more detailed have been introduced, as for the Water Detritiation System (WDS). To reflect all these changes, the new code developed inside EU participating team was nominated TRIMO (Tritium Inventory Modeling), to emphasize the use of the code on assessing the tritium inventory within ITER
Simple mathematical models of gene regulatory dynamics
Mackey, Michael C; Tyran-Kamińska, Marta; Zeron, Eduardo S
2016-01-01
This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduat...
Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models
Ting, Chee-Ming
2017-12-06
We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.
Modeling of Dynamic Responses in Building Insulation
Directory of Open Access Journals (Sweden)
Anna Antonyová
2015-10-01
Full Text Available In this research a measurement systemwas developedfor monitoring humidity and temperature in the cavity between the wall and the insulating material in the building envelope. This new technology does not disturb the insulating material during testing. The measurement system can also be applied to insulation fixed ten or twenty years earlier and sufficiently reveals the quality of the insulation. A mathematical model is proposed to characterize the dynamic responses in the cavity between the wall and the building insulation as influenced by weather conditions.These dynamic responses are manifested as a delay of both humidity and temperature changes in the cavity when compared with the changes in the ambient surrounding of the building. The process is then modeled through numerical methods and statistical analysis of the experimental data obtained using the new system of measurement.
Dynamic energy-demand models. A comparison
International Nuclear Information System (INIS)
Yi, Feng
2000-01-01
This paper compares two second-generation dynamic energy demand models, a translog (TL) and a general Leontief (GL), in the study of price elasticities and factor substitutions of nine Swedish manufacturing industries: food, textiles, wood, paper, printing, chemicals, non-metallic minerals, base metals and machinery. Several model specifications are tested with likelihood ratio test. There is a disagreement on short-run adjustments; the TL model accepts putty-putty production technology of immediate adjustments, implying equal short- and long-run price elasticities of factors, while the GL model rejects immediate adjustments, giving out short-run elasticities quite different from the long-run. The two models also disagree in substitutability in many cases. 21 refs
The dynamic radiation environment assimilation model (DREAM)
International Nuclear Information System (INIS)
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.
Molecular dynamics modeling of polymer flammability
International Nuclear Information System (INIS)
Nyden, M.R.; Brown, J.E.; Lomakin, S.M.
1992-01-01
Molecular dynamic simulations were used to identify factors which promote char formation during the thermal degradation of polymers. Computer movies based on these simulations, indicate that cross-linked model polymers tend to undergo further cross-linking when burned, eventually forming a high molecular weight, thermally stable char. This paper reports that the prediction was confirmed by char yield measurements made on γ and e - -irradiated polyethylene and chemically cross-linked poly(methyl methacrylate)
Dynamical chaos and beam-beam models
International Nuclear Information System (INIS)
Izrailev, F.M.
1990-01-01
Some aspects of the nonlinear dynamics of beam-beam interaction for simple one-dimensional and two-dimensional models of round and flat beams are discussed. The main attention is paid to the stochasticity threshold due to the overlapping of nonlinear resonances. The peculiarities of a round beam are investigated in view of using the round beams in storage rings to get high luminosity. 16 refs.; 7 figs
Dynamical Model for Indoor Radon Concentration Monitoring
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Jílek, K.
2009-01-01
Roč. 20, č. 6 (2009), s. 718-729 ISSN 1180-4009. [TIES 2007. Annual Meeting of the International Environmental Society /18./. Mikulov, 16.08.2007-20.08.2007] Institutional research plan: CEZ:AV0Z10300504 Keywords : non-parametric regression * dynamic modeling * time-varying coefficients Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.000, year: 2009
Dynamical symmetries of the shell model
International Nuclear Information System (INIS)
Van Isacker, P.
2000-01-01
The applications of spectrum generating algebras and of dynamical symmetries in the nuclear shell model are many and varied. They stretch back to Wigner's early work on the supermultiplet model and encompass important landmarks in our understanding of the structure of the atomic nucleus such as Racah's SU(2) pairing model and Elliot's SU(3) rotational model. One of the aims of this contribution has been to show the historical importance of the idea of dynamical symmetry in nuclear physics. Another has been to indicate that, in spite of being old, this idea continues to inspire developments that are at the forefront of today's research in nuclear physics. It has been argued in this contribution that the main driving features of nuclear structure can be represented algebraically but at the same time the limitations of the symmetry approach must be recognised. It should be clear that such approach can only account for gross properties and that any detailed description requires more involved numerical calculations of which we have seen many fine examples during this symposium. In this way symmetry techniques can be used as an appropriate starting point for detailed calculations. A noteworthy example of this approach is the pseudo-SU(3) model which starting from its initial symmetry Ansatz has grown into an adequate and powerful description of the nucleus in terms of a truncated shell model. (author)
A model for nuclear research reactor dynamics
Energy Technology Data Exchange (ETDEWEB)
Barati, Ramin, E-mail: Barati.ramin@aut.ac.ir; Setayeshi, Saeed, E-mail: setayesh@aut.ac.ir
2013-09-15
Highlights: • A thirty-fourth order model is used to simulate the dynamics of a research reactor. • We consider delayed neutrons fraction as a function of time. • Variable fuel and temperature reactivity coefficients are used. • WIMS, BORGES and CITVAP codes are used for initial condition calculations. • Results are in agreement with experimental data rather than common codes. -- Abstract: In this paper, a useful thirty-fourth order model is presented to simulate the kinetics and dynamics of a research reactor core. The model considers relevant physical phenomena that govern the core such as reactor kinetics, reactivity feedbacks due to coolant and fuel temperatures (Doppler effects) with variable reactivity coefficients, xenon, samarium, boron concentration, fuel burn up and thermal hydraulics. WIMS and CITVAP codes are used to extract neutron cross sections and calculate the initial neuron flux respectively. The purpose is to present a model with results similar to reality as much as possible with reducing common simplifications in reactor modeling to be used in different analyses such as reactor control, functional reliability and safety. The model predictions are qualified by comparing with experimental data, detailed simulations of reactivity insertion transients, and steady state for Tehran research reactor reported in the literature and satisfactory results have been obtained.
New method dynamically models hydrocarbon fractionation
Energy Technology Data Exchange (ETDEWEB)
Kesler, M.G.; Weissbrod, J.M.; Sheth, B.V. [Kesler Engineering, East Brunswick, NJ (United States)
1995-10-01
A new method for calculating distillation column dynamics can be used to model time-dependent effects of independent disturbances for a range of hydrocarbon fractionation. It can model crude atmospheric and vacuum columns, with relatively few equilibrium stages and a large number of components, to C{sub 3} splitters, with few components and up to 300 equilibrium stages. Simulation results are useful for operations analysis, process-control applications and closed-loop control in petroleum, petrochemical and gas processing plants. The method is based on an implicit approach, where the time-dependent variations of inventory, temperatures, liquid and vapor flows and compositions are superimposed at each time step on the steady-state solution. Newton-Raphson (N-R) techniques are then used to simultaneously solve the resulting finite-difference equations of material, equilibrium and enthalpy balances that characterize distillation dynamics. The important innovation is component-aggregation and tray-aggregation to contract the equations without compromising accuracy. This contraction increases the N-R calculations` stability. It also significantly increases calculational speed, which is particularly important in dynamic simulations. This method provides a sound basis for closed-loop, supervisory control of distillation--directly or via multivariable controllers--based on a rigorous, phenomenological column model.
Dynamic analysis of a parasite population model
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.
Simple Models for the Dynamic Modeling of Rotating Tires
Directory of Open Access Journals (Sweden)
J.C. Delamotte
2008-01-01
Full Text Available Large Finite Element (FE models of tires are currently used to predict low frequency behavior and to obtain dynamic model coefficients used in multi-body models for riding and comfort. However, to predict higher frequency behavior, which may explain irregular wear, critical rotating speeds and noise radiation, FE models are not practical. Detailed FE models are not adequate for optimization and uncertainty predictions either, as in such applications the dynamic solution must be computed a number of times. Therefore, there is a need for simpler models that can capture the physics of the tire and be used to compute the dynamic response with a low computational cost. In this paper, the spectral (or continuous element approach is used to derive such a model. A circular beam spectral element that takes into account the string effect is derived, and a method to simulate the response to a rotating force is implemented in the frequency domain. The behavior of a circular ring under different internal pressures is investigated using modal and frequency/wavenumber representations. Experimental results obtained with a real untreaded truck tire are presented and qualitatively compared with the simple model predictions with good agreement. No attempt is made to obtain equivalent parameters for the simple model from the real tire results. On the other hand, the simple model fails to represent the correct variation of the quotient of the natural frequency by the number of circumferential wavelengths with the mode count. Nevertheless, some important features of the real tire dynamic behavior, such as the generation of standing waves and part of the frequency/wavenumber behavior, can be investigated using the proposed simplified model.
Dynamical model of birdsong maintenance and control
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.
Nonparametric modeling of dynamic functional connectivity in fmri data
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus
2015-01-01
dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a nonparametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted...
Chancroid transmission dynamics: a mathematical modeling approach.
Bhunu, C P; Mushayabasa, S
2011-12-01
Mathematical models have long been used to better understand disease transmission dynamics and how to effectively control them. Here, a chancroid infection model is presented and analyzed. The disease-free equilibrium is shown to be globally asymptotically stable when the reproduction number is less than unity. High levels of treatment are shown to reduce the reproduction number suggesting that treatment has the potential to control chancroid infections in any given community. This result is also supported by numerical simulations which show a decline in chancroid cases whenever the reproduction number is less than unity.
Population Model with a Dynamic Food Supply
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.
Conceptual Model of Dynamic Geographic Environment
Directory of Open Access Journals (Sweden)
Martínez-Rosales Miguel Alejandro
2014-04-01
Full Text Available In geographic environments, there are many and different types of geographic entities such as automobiles, trees, persons, buildings, storms, hurricanes, etc. These entities can be classified into two groups: geographic objects and geographic phenomena. By its nature, a geographic environment is dynamic, thus, it’s static modeling is not sufficient. Considering the dynamics of geographic environment, a new type of geographic entity called event is introduced. The primary target is a modeling of geographic environment as an event sequence, because in this case the semantic relations are much richer than in the case of static modeling. In this work, the conceptualization of this model is proposed. It is based on the idea to process each entity apart instead of processing the environment as a whole. After that, the so called history of each entity and its spatial relations to other entities are defined to describe the whole environment. The main goal is to model systems at a conceptual level that make use of spatial and temporal information, so that later it can serve as the semantic engine for such systems.
Modeling the Dynamic Digestive System Microbiome
Directory of Open Access Journals (Sweden)
Anne M. Estes
2015-08-01
Full Text Available “Modeling the Dynamic Digestive System Microbiome” is a hands-on activity designed to demonstrate the dynamics of microbiome ecology using dried pasta and beans to model disturbance events in the human digestive system microbiome. This exercise demonstrates how microbiome diversity is influenced by: 1 niche availability and habitat space and 2 a major disturbance event, such as antibiotic use. Students use a pictorial key to examine prepared models of digestive system microbiomes to determine what the person with the microbiome “ate.” Students then model the effect of taking antibiotics by removing certain “antibiotic sensitive” pasta. Finally, they add in “environmental microbes” or “native microbes” to recolonize the digestive system, determine how resilient their model microbome community is to disturbance, and discuss the implications. Throughout the exercise, students discuss differences in the habitat space available and microbiome community diversity. This exercise can be modified to discuss changes in the microbiome due to diet shifts and the emergence of antibiotic resistance in more depth.
Quadratic tracer dynamical models tobacco growth
International Nuclear Information System (INIS)
Qiang Jiyi; Hua Cuncai; Wang Shaohua
2011-01-01
In order to study the non-uniformly transferring process of some tracer dosages, we assume that the absorption of some tracer by tobacco is a quadratic function of the tracer quantity of the tracer in the case of fast absorption, whereas the exclusion of the tracer from tobacco is a linear function of the tracer quantity in the case of slow exclusion, after the tracer is introduced into tobacco once at zero time. A single-compartment quadratic dynamical model of Logistic type is established for the leaves of tobacco. Then, a two-compartment quadratic dynamical model is established for leaves and calms of the tobacco. Qualitative analysis of the models shows that the tracer applied to the leaves of the tobacco is excluded finally; however, the tracer stays at the tobacco for finite time. Two methods are also given for computing the parameters in the models. Finally, the results of the models are verified by the 32 P experiment for the absorption of tobacco. (authors)
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.
A Multiscale Model for Virus Capsid Dynamics
Directory of Open Access Journals (Sweden)
Changjun Chen
2010-01-01
Full Text Available 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.
AFDM: An Advanced Fluid-Dynamics Model
International Nuclear Information System (INIS)
Bohl, W.R.; Parker, F.R.; Wilhelm, D.; Goutagny, L.; Ninokata, H.
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
Mathematical modeling and applications in nonlinear dynamics
Merdan, Hüseyin
2016-01-01
The book covers nonlinear physical problems and mathematical modeling, including molecular biology, genetics, neurosciences, artificial intelligence with classical problems in mechanics and astronomy and physics. The chapters present nonlinear mathematical modeling in life science and physics through nonlinear differential equations, nonlinear discrete equations and hybrid equations. Such modeling can be effectively applied to the wide spectrum of nonlinear physical problems, including the KAM (Kolmogorov-Arnold-Moser (KAM)) theory, singular differential equations, impulsive dichotomous linear systems, analytical bifurcation trees of periodic motions, and almost or pseudo- almost periodic solutions in nonlinear dynamical systems. Provides methods for mathematical models with switching, thresholds, and impulses, each of particular importance for discontinuous processes Includes qualitative analysis of behaviors on Tumor-Immune Systems and methods of analysis for DNA, neural networks and epidemiology Introduces...
Dynamical models of happiness with fractional order
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.
Modeling Computer Virus and Its Dynamics
Directory of Open Access Journals (Sweden)
Mei Peng
2013-01-01
Full Text Available Based on that the computer will be infected by infected computer and exposed computer, and some of the computers which are in suscepitible status and exposed status can get immunity by antivirus ability, a novel coumputer virus model is established. The dynamic behaviors of this model are investigated. First, the basic reproduction number R0, which is a threshold of the computer virus spreading in internet, is determined. Second, this model has a virus-free equilibrium P0, which means that the infected part of the computer disappears, and the virus dies out, and P0 is a globally asymptotically stable equilibrium if R01 then this model has only one viral equilibrium P*, which means that the computer persists at a constant endemic level, and P* is also globally asymptotically stable. Finally, some numerical examples are given to demonstrate the analytical results.
Continuous Time Dynamic Contraflow Models and Algorithms
Directory of Open Access Journals (Sweden)
Urmila Pyakurel
2016-01-01
Full Text Available The research on evacuation planning problem is promoted by the very challenging emergency issues due to large scale natural or man-created disasters. It is the process of shifting the maximum number of evacuees from the disastrous areas to the safe destinations as quickly and efficiently as possible. Contraflow is a widely accepted model for good solution of evacuation planning problem. It increases the outbound road capacity by reversing the direction of roads towards the safe destination. The continuous dynamic contraflow problem sends the maximum number of flow as a flow rate from the source to the sink in every moment of time unit. We propose the mathematical model for the continuous dynamic contraflow problem. We present efficient algorithms to solve the maximum continuous dynamic contraflow and quickest continuous contraflow problems on single source single sink arbitrary networks and continuous earliest arrival contraflow problem on single source single sink series-parallel networks with undefined supply and demand. We also introduce an approximation solution for continuous earliest arrival contraflow problem on two-terminal arbitrary networks.
Advances in dynamic network modeling in complex transportation systems
Ukkusuri, Satish V
2013-01-01
This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.
Inelastic light scattering by low-lying excitations of electrons in low-dimensional semiconductors
Energy Technology Data Exchange (ETDEWEB)
Pellegrini, V. [NEST CNR-INFM and Scuola Normale Superiore, Pisa (Italy); Pinczuk, A. [Department of Physics, Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027 (United States); Bell Laboratories, Lucent Technologies, Murray Hill, New Jersey (United States)
2006-11-15
The low-dimensional electron systems that reside in artificial semiconductor heterostructures of great perfection are a contemporary materials base for explorations of collective phenomena. Studies of low-lying elementary excitations by inelastic light scattering offer insights on properties such energetics, interactions and spin magnetization. We review here recent light scattering results obtained from two-dimensional (2D) quantum fluids in semiconductor heterostructures under extreme conditions of low temperature and large magnetic field, where the quantum Hall phases are archetypes of novel behaviors. We also consider recent light scattering experiments that have probed the excitation spectra of few-electron states in semiconductor quantum dots. (copyright 2006 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
A Review on the Low-Dimensional and Hybridized Nanostructured Diamond Films
Directory of Open Access Journals (Sweden)
Hongdong Li
2015-01-01
Full Text Available In the last decade, besides the breakthrough of high-rate growth of chemical vapor deposited single-crystal diamonds, numerous nanostructured diamond films have been rapidly developed in the research fields of the diamond-based sciences and industrial applications. The low-dimensional diamonds of two-dimensional atomic-thick nanofilms and nanostructural diamond on the surface of bulk diamond films have been theoretically and experimentally investigated. In addition, the diamond-related hybrid nanostructures of n-type oxide/p-type diamond and n-type nitride/p-type diamond, having high performance physical and chemical properties, are proposed for further applications. In this review, we first briefly introduce the three categories of diamond nanostructures and then outline the current advances in these topics, including their design, fabrication, characterization, and properties. Finally, we address the remaining challenges in the research field and the future activities.
NATO Advanced Research Workshop on Optical Switching in Low-Dimensional Systems
Bányai, L
1989-01-01
This book contains all the papers presented at the NATO workshop on "Optical Switching in Low Dimensional Systems" held in Marbella, Spain from October 6th to 8th, 1988. Optical switching is a basic function for optical data processing, which is of technological interest because of its potential parallelism and its potential speed. Semiconductors which exhibit resonance enhanced optical nonlinearities in the frequency range close to the band edge are the most intensively studied materials for optical bistability and fast gate operation. Modern crystal growth techniques, particularly molecular beam epitaxy, allow the manufacture of semiconductor microstructures such as quantum wells, quantum wires and quantum dots in which the electrons are only free to move in two, one or zero dimensions, of the optically excited electron-hole pairs in these low respectively. The spatial confinement dimensional structures gives rise to an enhancement of the excitonic nonlinearities. Furthermore, the variations of the microstr...
Evolution of structure with Fe layer thickness in low dimensional Fe/Tb multilayered structures
International Nuclear Information System (INIS)
Harris, V.G.; Aylesworth, K.D.; Elam, W.T.; Koon, N.C.; Coehoorn, R.; Hoving, W.
1992-01-01
This paper reports on the atomic structure of a series of low-dimensional Fe/Tb multilayered structures which has been explored using a conversion-electron, extended x-ray absorption fine structure (EXAFS) technique. A structural transition from a close-packed amorphous structure to a body-centered crystalline structure is detected to occur over an Fe layer thickness range of 12.5 Angstrom to 15.0 Angstrom (Tb thickness is held constant at 4.5 Angstrom). Magnetic properties, specifically, magnetization, anisotropy field, and Kerr rotation angle, are measured and found to change significantly in response to this transition. Exploitation of the polarization properties of synchrotron radiation allowed for the description of the atomic structure both perpendicular and parallel to the sample plane
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.
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.
Directory of Open Access Journals (Sweden)
C Brandon Ogbunugafor
Full Text Available 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.
Dynamic modeling of gearbox faults: A review
Liang, Xihui; Zuo, Ming J.; Feng, Zhipeng
2018-01-01
Gearbox is widely used in industrial and military applications. Due to high service load, harsh operating conditions or inevitable fatigue, faults may develop in gears. If the gear faults cannot be detected early, the health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Early fault detection and diagnosis allows properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher cost reduction. Recently, many studies have been done to develop gearbox dynamic models with faults aiming to understand gear fault generation mechanism and then develop effective fault detection and diagnosis methods. This paper focuses on dynamics based gearbox fault modeling, detection and diagnosis. State-of-art and challenges are reviewed and discussed. This detailed literature review limits research results to the following fundamental yet key aspects: gear mesh stiffness evaluation, gearbox damage modeling and fault diagnosis techniques, gearbox transmission path modeling and method validation. In the end, a summary and some research prospects are presented.
Yi, Zheng; Lindner, Benjamin; Prinz, Jan-Hendrik; Noé, Frank; Smith, Jeremy C
2013-11-07
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.
A simple dynamic energy capacity model
International Nuclear Information System (INIS)
Gander, James P.
2012-01-01
I develop a simple dynamic model showing how total energy capacity is allocated to two different uses and how these uses and their corresponding energy flows are related and behave through time. The control variable of the model determines the allocation. All the variables of the model are in terms of a composite energy equivalent measured in BTU's. A key focus is on the shadow price of energy capacity and its behavior through time. Another key focus is on the behavior of the control variable that determines the allocation of overall energy capacity. The matching or linking of the model's variables to real world U.S. energy data is undertaken. In spite of some limitations of the data, the model and its behavior fit the data fairly well. Some energy policy implications are discussed. - Highlights: ► The model shows how energy capacity is allocated to current output production versus added energy capacity production. ► Two variables in the allocation are the shadow price of capacity and the control variable that determines the allocation. ► The model was linked to U.S. historical energy data and fit the data quite well. ► In particular, the policy control variable was cyclical and consistent with the model. ► Policy implications relevant to the allocation of energy capacity are discussed briefly.
Dynamic modelling of Industrial Heavy Water Plant
International Nuclear Information System (INIS)
Teruel, F.E.
1997-01-01
The dynamic behavior of the isotopic enrichment unites of the Industrial Heavy Water Plant, located in Arroyito, Neuquen, Argentina, was modeled and simulated in the present work. Dynamic models of the chemical and isotopic interchange processes existent in the plant, were developed. This served as a base to obtain representative models of the different unit and control systems. The developed models were represented in a modular code for each unit. Each simulator consists of approximately one hundred non-linear-first-order differential equations and some other algebraic equation, which are time resolved by the code. The different simulators allow to change a big number of boundary conditions and the control systems set point for each simulation, so that the program become very versatile. The output of the code allows to see the evolution through time of the variables of interest. An interface which facilitates the use of the first enrichment stage simulator was developed. This interface allows an easy access to generate wished events during the simulation and includes the possibility to plot evolution of the variables involved. The obtained results agree with the expected tendencies. The calculated nominal steady state matches by the manufacturer. The different steady states obtained, agree with previous works. The times and tendencies involved in the transients generated by the program, are in good agreement with the experience obtained at the plant. Based in the obtained results, it is concluded that the characteristic times of the plant are determined by the masses involved in the process. Different characteristics in the system dynamic behavior were generated with the different simulators, and were validated by plant personnel. This work allowed to understand the different process involved in the heavy water manufacture, and to develop a very useful tool for the personnel of the plant. (author). 14 refs., figs., tabs. plant. (author). 14 refs., figs., tabs
Modeling dynamic functional connectivity using a wishart mixture model
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2017-01-01
framework provides model selection by quantifying models generalization to new data. We use this to quantify the number of states within a prespecified window length. We further propose a heuristic procedure for choosing the window length based on contrasting for each window length the predictive...... together whereas short windows are more unstable and influenced by noise and we find that our heuristic correctly identifies an adequate level of complexity. On single subject resting state fMRI data we find that dynamic models generally outperform static models and using the proposed heuristic points...
Adaptive-network models of collective dynamics
Zschaler, G.
2012-09-01
Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge
Modelling forest dynamics along climate gradients in Bolivia
Seiler, C.; Hutjes, R.W.A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V.K.; Melton, J.R.; Hickler, T.; Kabat, P.
2014-01-01
Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model
Modelling Market Dynamics with a "Market Game"
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.
Dynamics of a Stochastic Intraguild Predation Model
Directory of Open Access Journals (Sweden)
Zejing Xing
2016-04-01
Full Text Available Intraguild predation (IGP is a widespread ecological phenomenon which occurs when one predator species attacks another predator species with which it competes for a shared prey species. The objective of this paper is to study the dynamical properties of a stochastic intraguild predation model. We analyze stochastic persistence and extinction of the stochastic IGP model containing five cases and establish the sufficient criteria for global asymptotic stability of the positive solutions. This study shows that it is possible for the coexistence of three species under the influence of environmental noise, and that the noise may have a positive effect for IGP species. A stationary distribution of the stochastic IGP model is established and it has the ergodic property, suggesting that the time average of population size with the development of time is equal to the stationary distribution in space. Finally, we show that our results may be extended to two well-known biological systems: food chains and exploitative competition.
Agent-based modeling and network dynamics
Namatame, Akira
2016-01-01
The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...
Flight Dynamic Model Exchange using XML
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.
Traffic flow dynamics. Data, models and simulation
Energy Technology Data Exchange (ETDEWEB)
Treiber, Martin [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Kesting, Arne [TomTom Development Germany GmbH, Berlin (Germany)
2013-07-01
First comprehensive textbook of this fascinating interdisciplinary topic which explains advances in a way that it is easily accessible to engineering, physics and math students. Presents practical applications of traffic theory such as driving behavior, stability analysis, stop-and-go waves, and travel time estimation. Presents the topic in a novel and systematic way by addressing both microscopic and macroscopic models with a focus on traffic instabilities. Revised and extended edition of the German textbook ''Verkehrsdynamik und -simulation''. This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.
Mineral vein dynamics modelling (FRACS II)
International Nuclear Information System (INIS)
Urai, J.; Virgo, S.; Arndt, M.
2016-08-01
The Mineral Vein Dynamics Modeling group ''FRACS'' started out as a team of 7 research groups in its first phase and continued with a team of 5 research groups at the Universities of Aachen, Tuebingen, Karlsruhe, Mainz and Glasgow during its second phase ''FRACS 11''. The aim of the group was to develop an advanced understanding of the interplay between fracturing, fluid flow and fracture healing with a special emphasis on the comparison of field data and numerical models. Field areas comprised the Oman mountains in Oman (which where already studied in detail in the first phase), a siliciclastic sequence in the Internal Ligurian Units in Italy (closed to Sestri Levante) and cores of Zechstein carbonates from a Lean Gas reservoir in Northern Germany. Numerical models of fracturing, sealing and interaction with fluid that were developed in phase I where expanded in phase 11. They were used to model small scale fracture healing by crystal growth and the resulting influence on flow, medium scale fracture healing and its influence on successive fracturing and healing, as well as large scale dynamic fluid flow through opening and closing fractures and channels as a function of fluid overpressure. The numerical models were compared with structures in the field and we were able to identify first proxies for mechanical vein-hostrock properties and fluid overpressures versus tectonic stresses. Finally we propose a new classification of stylolites based on numerical models and observations in the Zechstein cores and continued to develop a new stress inversion tool to use stylolites to estimate depth of their formation.
Mineral vein dynamics modelling (FRACS II)
Energy Technology Data Exchange (ETDEWEB)
Urai, J.; Virgo, S.; Arndt, M. [RWTH Aachen (Germany); and others
2016-08-15
The Mineral Vein Dynamics Modeling group ''FRACS'' started out as a team of 7 research groups in its first phase and continued with a team of 5 research groups at the Universities of Aachen, Tuebingen, Karlsruhe, Mainz and Glasgow during its second phase ''FRACS 11''. The aim of the group was to develop an advanced understanding of the interplay between fracturing, fluid flow and fracture healing with a special emphasis on the comparison of field data and numerical models. Field areas comprised the Oman mountains in Oman (which where already studied in detail in the first phase), a siliciclastic sequence in the Internal Ligurian Units in Italy (closed to Sestri Levante) and cores of Zechstein carbonates from a Lean Gas reservoir in Northern Germany. Numerical models of fracturing, sealing and interaction with fluid that were developed in phase I where expanded in phase 11. They were used to model small scale fracture healing by crystal growth and the resulting influence on flow, medium scale fracture healing and its influence on successive fracturing and healing, as well as large scale dynamic fluid flow through opening and closing fractures and channels as a function of fluid overpressure. The numerical models were compared with structures in the field and we were able to identify first proxies for mechanical vein-hostrock properties and fluid overpressures versus tectonic stresses. Finally we propose a new classification of stylolites based on numerical models and observations in the Zechstein cores and continued to develop a new stress inversion tool to use stylolites to estimate depth of their formation.
MODELS AND THE DYNAMICS OF THEORIES
Directory of Open Access Journals (Sweden)
Paulo Abrantes
2007-12-01
Full Text Available Abstract: This paper gives a historical overview of the ways various trends in the philosophy of science dealt with models and their relationship with the topics of heuristics and theoretical dynamics. First of all, N. Campbell’s account of analogies as components of scientific theories is presented. Next, the notion of ‘model’ in the reconstruction of the structure of scientific theories proposed by logical empiricists is examined. This overview finishes with M. Hesse’s attempts to develop Campbell’s early ideas in terms of an analogical inference. The final part of the paper points to contemporary developments on these issues which adopt a cognitivist perspective. It is indicated how discussions in the cognitive sciences might help to flesh out some of the insights philosophers of science had concerning the role models and analogies play in actual scientific theorizing. Key words: models, analogical reasoning, metaphors in science, the structure of scientific theories, theoretical dynamics, heuristics, scientific discovery.
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
Numerical modeling of bubble dynamics in magmas
Huber, Christian; Su, Yanqing; Parmigiani, Andrea
2014-05-01
Understanding the complex non-linear physics that governs volcanic eruptions is contingent on our ability to characterize the dynamics of bubbles and its effect on the ascending magma. The exsolution and migration of bubbles has also a great impact on the heat and mass transport in and out of magma bodies stored at shallow depths in the crust. Multiphase systems like magmas are by definition heterogeneous at small scales. Although mixture theory or homogenization methods are convenient to represent multiphase systems as a homogeneous equivalent media, these approaches do not inform us on possible feedbacks at the pore-scale and can be significantly misleading. In this presentation, we discuss the development and application of bubble-scale multiphase flow modeling to address the following questions : How do bubbles impact heat and mass transport in magma chambers ? How efficient are chemical exchanges between the melt and bubbles during magma decompression? What is the role of hydrodynamic interactions on the deformation of bubbles while the magma is sheared? Addressing these questions requires powerful numerical methods that accurately model the balance between viscous, capillary and pressure stresses. We discuss how these bubble-scale models can provide important constraints on the dynamics of magmas stored at shallow depth or ascending to the surface during an eruption.
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.
Dynamical Vertex Approximation for the Hubbard Model
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.
A dynamic model of the wormhole and the Multiverse model
International Nuclear Information System (INIS)
Shatskii, A A; Kardashev, N S; Novikov, I D
2008-01-01
An analytic solution methodology for general relativity (GR) equations describing the hypothetical phenomenon of wormholes is presented and the analysis of wormholes in terms of their physical properties is discussed. An analytic solution of the GR equations for static and dynamic spherically symmetric wormholes is given. The dynamic solution generally describes a 'traversable' wormhole, i.e., one allowing matter, energy, and information to pass through it. It is shown how the energy-momentum tensor of matter in a wormhole can be represented in a form allowing the GR equations to be solved analytically, which has a crucial methodological importance for analyzing the properties of the solution obtained. The energy-momentum tensor of wormhole matter is represented as a superposition of a spherically symmetric magnetic (or electric) field and negative-density dust matter, serving as exotic matter necessary for a 'traversable' wormhole to exist. The dynamics of the model are investigated. A similar model is considered (and analyzed in terms of inflation) for the Einstein equations with a Λ term. Superposing enough dust matter, a magnetic field, and a Λ term can produce a static solution, which turns out to be a spherical Multiverse model with an infinite number of wormhole-connected spherical universes. This Multiverse can have its total energy positive everywhere in space, and in addition can be out of equilibrium (i.e., dynamic). (methodological notes)
A dynamic model of the wormhole and the Multiverse model
Energy Technology Data Exchange (ETDEWEB)
Shatskii, A A; Kardashev, N S [Astro-Space Centre of the P. N. Lebedev Physics Institute, Russian Academy of Sciences, Moscow (Russian Federation); Novikov, I D [Russian Research Centre ' Kurchatov Institute' , Moscow (Russian Federation)
2008-05-31
An analytic solution methodology for general relativity (GR) equations describing the hypothetical phenomenon of wormholes is presented and the analysis of wormholes in terms of their physical properties is discussed. An analytic solution of the GR equations for static and dynamic spherically symmetric wormholes is given. The dynamic solution generally describes a 'traversable' wormhole, i.e., one allowing matter, energy, and information to pass through it. It is shown how the energy-momentum tensor of matter in a wormhole can be represented in a form allowing the GR equations to be solved analytically, which has a crucial methodological importance for analyzing the properties of the solution obtained. The energy-momentum tensor of wormhole matter is represented as a superposition of a spherically symmetric magnetic (or electric) field and negative-density dust matter, serving as exotic matter necessary for a 'traversable' wormhole to exist. The dynamics of the model are investigated. A similar model is considered (and analyzed in terms of inflation) for the Einstein equations with a {lambda} term. Superposing enough dust matter, a magnetic field, and a {lambda} term can produce a static solution, which turns out to be a spherical Multiverse model with an infinite number of wormhole-connected spherical universes. This Multiverse can have its total energy positive everywhere in space, and in addition can be out of equilibrium (i.e., dynamic). (methodological notes)
Development of Dynamic Environmental Effect Calculation Model
International Nuclear Information System (INIS)
Jeong, Chang Joon; Ko, Won Il
2010-01-01
The short-term, long-term decay heat, and radioactivity are considered as main environmental parameters of SF and HLA. In this study, the dynamic calculation models for radioactivity, short-term decay heat, and long-term heat load of the SF are developed and incorporated into the Doneness code. The spent fuel accumulation has become a major issue for sustainable operation of nuclear power plants. If a once-through fuel cycle is selected, the SF will be disposed into the repository. Otherwise, in case of fast reactor or reuse cycle, the SF will be reprocessed and the high level waste will be disposed
Zealotry effects on opinion dynamics in the adaptive voter model
Klamser, Pascal P.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.
2017-11-01
The adaptive voter model has been widely studied as a conceptual model for opinion formation processes on time-evolving social networks. Past studies on the effect of zealots, i.e., nodes aiming to spread their fixed opinion throughout the system, only considered the voter model on a static network. Here we extend the study of zealotry to the case of an adaptive network topology co-evolving with the state of the nodes and investigate opinion spreading induced by zealots depending on their initial density and connectedness. Numerical simulations reveal that below the fragmentation threshold a low density of zealots is sufficient to spread their opinion to the whole network. Beyond the transition point, zealots must exhibit an increased degree as compared to ordinary nodes for an efficient spreading of their opinion. We verify the numerical findings using a mean-field approximation of the model yielding a low-dimensional set of coupled ordinary differential equations. Our results imply that the spreading of the zealots' opinion in the adaptive voter model is strongly dependent on the link rewiring probability and the average degree of normal nodes in comparison with that of the zealots. In order to avoid a complete dominance of the zealots' opinion, there are two possible strategies for the remaining nodes: adjusting the probability of rewiring and/or the number of connections with other nodes, respectively.
Trophic dynamics of a simple model ecosystem.
Bell, Graham; Fortier-Dubois, Étienne
2017-09-13
We have constructed a model of community dynamics that is simple enough to enumerate all possible food webs, yet complex enough to represent a wide range of ecological processes. We use the transition matrix to predict the outcome of succession and then investigate how the transition probabilities are governed by resource supply and immigration. Low-input regimes lead to simple communities whereas trophically complex communities develop when there is an adequate supply of both resources and immigrants. Our interpretation of trophic dynamics in complex communities hinges on a new principle of mutual replenishment, defined as the reciprocal alternation of state in a pair of communities linked by the invasion and extinction of a shared species. Such neutral couples are the outcome of succession under local dispersal and imply that food webs will often be made up of suites of trophically equivalent species. When immigrants arrive from an external pool of fixed composition a similar principle predicts a dynamic core of webs constituting a neutral interchange network, although communities may express an extensive range of other webs whose membership is only in part predictable. The food web is not in general predictable from whole-community properties such as productivity or stability, although it may profoundly influence these properties. © 2017 The Author(s).
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. Published by the BMJ Publishing Group Limited. For permission
A Mathematical Model of Cardiovascular Response to Dynamic Exercise
National Research Council Canada - National Science Library
Magosso, E
2001-01-01
A mathematical model of cardiovascular response to dynamic exercise is presented, The model includes the pulsating heart, the systemic and pulmonary, circulation, a functional description of muscle...
Testing substellar models with dynamical mass measurements
Directory of Open Access Journals (Sweden)
Liu M.C.
2011-07-01
Full Text Available We have been using Keck laser guide star adaptive optics to monitor the orbits of ultracool binaries, providing dynamical masses at lower luminosities and temperatures than previously available and enabling strong tests of theoretical models. We have identified three specific problems with theory: (1 We find that model color–magnitude diagrams cannot be reliably used to infer masses as they do not accurately reproduce the colors of ultracool dwarfs of known mass. (2 Effective temperatures inferred from evolutionary model radii are typically inconsistent with temperatures derived from fitting atmospheric models to observed spectra by 100–300 K. (3 For the only known pair of field brown dwarfs with a precise mass (3% and age determination (≈25%, the measured luminosities are ~2–3× higher than predicted by model cooling rates (i.e., masses inferred from Lbol and age are 20–30% larger than measured. To make progress in understanding the observed discrepancies, more mass measurements spanning a wide range of luminosity, temperature, and age are needed, along with more accurate age determinations (e.g., via asteroseismology for primary stars with brown dwarf binary companions. Also, resolved optical and infrared spectroscopy are needed to measure lithium depletion and to characterize the atmospheres of binary components in order to better assess model deficiencies.
Computational social dynamic modeling of group recruitment.
Energy Technology Data Exchange (ETDEWEB)
Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken (Sandia National Laboratories, Albuquerque, NM); Smrcka, Julianne D. (Sandia National Laboratories, Albuquerque, NM); Ko, Teresa H.; Moy, Timothy David (Sandia National Laboratories, Albuquerque, NM); 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.
AFDM: An advanced fluid-dynamics model
International Nuclear Information System (INIS)
Henneges, G.; Kleinheins, S.
1994-01-01
This volume of the Advanced Fluid-Dynamics Model (AFDM) documents the modeling of the equation of state (EOS) in the code. The authors present an overview of the basic concepts underlying the thermodynamics modeling and resulting EOS, which is a set of relations between the thermodynamic properties of materials. The AFDM code allows for multiphase-multimaterial systems, which they explore in three phase models: two-material solid, two-material liquid, and three-material vapor. They describe and compare two ways of specifying the EOS of materials: (1) as simplified analytic expressions, or (2) as tables that precisely describe the properties of materials and their interactions for mechanical equilibrium. Either of the two EOS models implemented in AFDM can be selected by specifying the option when preprocessing the source code for compilation. Last, the authors determine thermophysical properties such as surface tension, thermal conductivities, and viscosities in the model for the intracell exchanges of AFDM. Specific notations, routines, EOS data, plots, test results, and corrections to the code are available in the appendices
Dynamic models for distributed generation resources
Energy Technology Data Exchange (ETDEWEB)
Morched, A.S. [BPR Energie, Sherbrooke, PQ (Canada)
2010-07-01
Distributed resources can impact the performance of host power systems during both normal and abnormal system conditions. This PowerPoint presentation discussed the use of dynamic models for identifying potential interaction problems between interconnected systems. The models were designed to simulate steady state behaviour as well as transient responses to system disturbances. The distributed generators included directly coupled and electronically coupled generators. The directly coupled generator was driven by wind turbines. Simplified models of grid-side inverters, electronically coupled wind generators and doubly-fed induction generators (DFIGs) were presented. The responses of DFIGs to wind variations were evaluated. Synchronous machine and electronically coupled generator responses were compared. The system model components included load models, generators, protection systems, and system equivalents. Frequency responses to islanding events were reviewed. The study demonstrated that accurate simulations are needed to predict the impact of distributed generation resources on the performance of host systems. Advances in distributed generation technology have outpaced the development of models needed for integration studies. tabs., figs.
AFDM: An Advanced Fluid-Dynamics Model
International Nuclear Information System (INIS)
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
Graphical models for inferring single molecule dynamics
Directory of Open Access Journals (Sweden)
Gonzalez Ruben L
2010-10-01
Full Text Available Abstract 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.
Forward and backward dynamics in implicitly defined overlapping generations models
Gardini, L.; Hommes, C.; Tramontana, F.; de Vilder, R.
2009-01-01
In dynamic economic models derived from optimization principles, the forward equilibrium dynamics may not be uniquely defined, while the backward dynamics is well defined. We derive properties of the global forward equilibrium paths based on properties of the backward dynamics. We propose the
Constructing Dynamic Event Trees from Markov Models
International Nuclear Information System (INIS)
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-01-01
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
Nonsmooth mechanics models, dynamics and control
Brogliato, Bernard
2016-01-01
Now in its third edition, this standard reference is a comprehensive treatment of nonsmooth mechanical systems refocused to give more prominence to control and modelling. It covers Lagrangian and Newton–Euler systems, detailing mathematical tools such as convex analysis and complementarity theory. The ways in which nonsmooth mechanics influence and are influenced by well-posedness analysis, numerical analysis and simulation, modelling and control are explained. Contact/impact laws, stability theory and trajectory-tracking control are given in-depth exposition connected by a framework formed from complementarity systems and measure-differential inclusions. Links are established with electrical circuits with set-valued nonsmooth elements and with other nonsmooth dynamical systems like impulsive and piecewise linear systems. Nonsmooth Mechanics (third edition) has been substantially rewritten, edited and updated to account for the significant body of results that have emerged in the twenty-first century—incl...
Driven dynamics of simplified tribological models
Energy Technology Data Exchange (ETDEWEB)
Vanossi, A [CNR-INFM National Research Center S3 and Department of Physics, University of Modena and Reggio Emilia, Via Campi 213/A, 41100 Modena (Italy); Braun, O M [Institute of Physics, National Academy of Sciences of Ukraine, 03028 Kiev (Ukraine)
2007-08-01
Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena.
Dynamic modeling and control of CFSTF
International Nuclear Information System (INIS)
Danesh, Y.; Jalali Farahani, F.
2001-01-01
This paper deals with the modeling and control of a continuous-flow fermentation process for the production of alcohol: The dynamic behavior of ferment ors has been developed from mass balance and leads to nonlinear differential equations. Based on the proposed model, two computer algorithms are provided to control output alcohol concentration at the desired value by input flow rate manipulation. The first algorithm is based on a conventional Proportional-Integral-Derivative, in which its parameters are determined in a trial and error procedure. The second algorithm is based on optimal controllers. In this way, the difference between output alcohol concentration and desired value is minimized by flow rate manipulation. Minimization (optimization) is done based on the MARQYARDT procedure. The advantages of this method over the conventional Proportional-Integral-Derivative controller are its higher speed and lack of overshoot
Driven dynamics of simplified tribological models
International Nuclear Information System (INIS)
Vanossi, A; Braun, O M
2007-01-01
Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena
Organic production in a dynamic CGE model
DEFF Research Database (Denmark)
Jacobsen, Lars Bo
2004-01-01
for conventional production into land for organic production, a period of two years must pass before the land being transformed can be used for organic production. During that time, the land is counted as land of the organic industry, but it can only produce the conventional product. To handle this rule, we make......Concerns about the impact of modern agriculture on the environment have in recent years led to an interest in supporting the development of organic farming. In addition to environmental benefits, the aim is to encourage the provision of other “multifunctional” properties of organic farming...... such as rural amenities and rural development that are spillover benefit additional to the supply of food. In this paper we further develop an existing dynamic general equilibrium model of the Danish economy to specifically incorporate organic farming. In the model and input-output data each primary...
BWR stability using a reduced dynamical model
International Nuclear Information System (INIS)
Ballestrin Bolea, J.M.; Blazquez, J.B.
1990-01-01
BWR stability can be treated with reduced order dynamical models. When the parameters of the model came from experimental data, the predictions are accurate. In this work an alternative derivation for the void fraction equation is made, but remarking the physical struct-ure of the parameters. As the poles of power/reactivity transfer function are related with the parameters, the measurement of the poles by other techniques such as noise analysis will lead to the parameters, but the system of equations in non-linear. Simple parametric calculat-ion of decay ratio are performed, showing why BWRs become unstable when they are operated at low flow and high power. (Author). 7 refs
Dynamical relaxation in 2HDM models
Lalak, Zygmunt; Markiewicz, Adam
2018-03-01
Dynamical relaxation provides an interesting solution to the hierarchy problem in face of the missing signatures of any new physics in recent experiments. Through a dynamical process taking place in the inflationary phase of the Universe it manages to achieve a small electroweak scale without introducing new states observable in current experiments. Appropriate approximation makes it possible to derive an explicit formula for the final vevs in the double-scanning scenario extended to a model with two Higgs doublets (2HDM). Analysis of the relaxation in the 2HDM confirms that in a general case it is impossible to keep vevs of both scalars small, unless fine-tuning is present or additional symmetries are cast upon the Lagrangian. Within the slightly constrained variant of the 2HDM, where odd powers of the fields’ expectation values are not present (which can be easily enforced by requiring that the doublets have different gauge transformations or by imposing a global symmetry) it is shown that the difference between the vevs of two scalars tends to be proportional to the cutoff. The analysis of the relaxation in 2HDM indicates that in a general case the relaxation would be stopped by the first doublet that gains a vev, with the other one remaining vevless with a mass of the order of the cutoff. This happens to conform with the inert doublet model.
Dynamical Model about Rumor Spreading with Medium
Directory of Open Access Journals (Sweden)
Xiaxia Zhao
2013-01-01
Full Text Available Rumor is a kind of social remark, that is untrue, and not be confirmed, and spreads on a large scale in a short time. Usually, it can induce a cloud of pressure, anxiety, and panic. Traditionally, it is propagated by word of mouth. Nowadays, with the emergence of the internet, rumors can be spread by instant messengers, emails, or publishing. With this new pattern of spreading, an ISRW dynamical model considering the medium as a subclass is established. Beside the dynamical analysis of the model, we mainly explore the mechanism of spreading of individuals-to-individuals and medium-to-individual. By numerical simulation, we find that if we want to control the rumor spreading, it will not only need to control the rate of change of the spreader subclass, but also need to control the change of the information about rumor in medium which has larger influence. Moreover, to control the effusion of rumor is more important than deleting existing information about rumor. On the one hand, government should enhance the management of internet. On the other hand, relevant legal institutions for punishing the rumor creator and spreader on internet who can be tracked should be established. Using this way, involved authorities can propose efficient measures to control the rumor spreading to keep the stabilization of society and development of economy.
A Model of Project and Organisational Dynamics
Directory of Open Access Journals (Sweden)
Jenny Leonard
2012-04-01
Full Text Available The strategic, transformational nature of many information systems projects is now widely understood. Large-scale implementations of systems are known to require significant management of organisational change in order to be successful. Moreover, projects are rarely executed in isolation – most organisations have a large programme of projects being implemented at any one time. However, project and value management methodologies provide ad hoc definitions of the relationship between a project and its environment. This limits the ability of an organisation to manage the larger dynamics between projects and organisations, over time, and between projects. The contribution of this paper, therefore, is to use literature on organisational theory to provide a more systematic understanding of this area. The organisational facilitators required to obtain value from a project are categorised, and the processes required to develop those facilitators are defined. This formalisation facilitates generalisation between projects and highlights any time and path dependencies required in developing organisational facilitators. The model therefore has the potential to contribute to the development of IS project management theory within dynamic organisational contexts. Six cases illustrate how this model could be used.
Microscopic to Macroscopic Dynamical Models of Sociality
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).
Modeling Insurgent Network Structure and Dynamics
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.
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
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
Dynamic Causal Models and Autopoietic Systems
Directory of Open Access Journals (Sweden)
OLIVIER DAVID
2007-01-01
Full Text Available Dynamic Causal Modelling (DCM and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated
Coordinated supply chain dynamic production planning model
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.
DYNAMIC MODELLING OF VIBRATIONS ASSISTED DRILLING
Directory of Open Access Journals (Sweden)
Mathieu LADONNE
2015-05-01
Full Text Available The number of multi-materials staking configurations for aeronautical structures is increasing, with the evolution of composite and metallic materials. For drilling the fastening holes, the processes of Vibration Assisted Drilling (VAD expand rapidly, as it permits to improve reliability of drilling operations on multilayer structures. Among these processes of VAD, the solution with forced vibrations added to conventional feed to create a discontinuous cutting is the more developed in industry. The back and forth movement allows to improve the evacuation of chips by breaking it. This technology introduces two new operating parameters, the frequency and the amplitude of the oscillation. To optimize the process, the choice of those parameters requires first to model precisely the operation cutting and dynamics. In this paper, a kinematic modelling of the process is firstly proposed. The limits of the model are analysed through comparison between simulations and measurements. The proposed model is used to develop a cutting force model that allows foreseeing the operating conditions which ensure good chips breaking and tool life improvement.
LDMS: A Low-Dimensional Modeling System for Hillslope, Catchment and River-Basin Runoff
National Research Council Canada - National Science Library
Duffy, Christopher
2000-01-01
.... The approach assumes that soil moisture and saturated groundwater storage serve as essential state variables in the rainfall-runoff process and that natural variations in topography, drainage area...
Fish Pectoral Fin Hydrodynamics; Part III: Low Dimensional Models via POD Analysis
Bozkurttas, M.; Madden, P.
2005-11-01
The highly complex kinematics of the pectoral fin and the resulting hydrodynamics does not lend itself easily to analysis based on simple notions of pitching/heaving/paddling kinematics or lift/drag based propulsive mechanisms. A more inventive approach is needed to dissect the fin gait and gain insight into the hydrodynamic performance of the pectoral fin. The focus of the current work is on the hydrodynamics of the pectoral fin of a bluegill sunfish in steady forward motion. The 3D, time-dependent fin kinematics is obtained via a stereo-videographic technique. We employ proper orthogonal decomposition to extract the essential features of the fin gait and then use CFD to examine the hydrodynamics of simplified gaits synthesized from the POD modes. The POD spectrum shows that the first two, three and five POD modes capture 55%, 67%, and 80% of the motion respectively. The first three modes are in particular highly distinct: Mode-1 is a ``cupping'' motion where the fin cups forward as it is abducted; Mode-2 is an ``expansion'' motion where the fin expands to present a larger area during adduction and finally Mode-3 involves a ``spanwise flick'' of the dorsal edge of the fin. Numerical simulation of flow past fin gaits synthesized from these modes lead to insights into the mechanisms of thrust production; these are discussed in detail.
Computational modeling of intraocular gas dynamics
International Nuclear Information System (INIS)
Noohi, P; Abdekhodaie, M J; Cheng, Y L
2015-01-01
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. SF_6 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 SF_6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF_6 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 SF_6 is 1.4 times more than that of using diluted SF_6 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. (paper)
Dynamic complexities in a parasitoid-host-parasitoid ecological model
International Nuclear Information System (INIS)
Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili
2009-01-01
Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model
Dynamic complexities in a parasitoid-host-parasitoid ecological model
Energy Technology Data Exchange (ETDEWEB)
Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)
2009-01-15
Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.
Prediction Models for Dynamic Demand Response
Energy Technology Data Exchange (ETDEWEB)
Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.
2015-11-02
As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D^{2}R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D^{2}R, which we address in this paper. Our first contribution is the formal definition of D^{2}R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D^{2}R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D^{2}R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D^{2}R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D^{2}R. Also, prediction models require just few days’ worth of data indicating that small amounts of
Analytical dynamic modeling of fast trilayer polypyrrole bending actuators
International Nuclear Information System (INIS)
Amiri Moghadam, Amir Ali; Moavenian, Majid; Tahani, Masoud; Torabi, Keivan
2011-01-01
Analytical modeling of conjugated polymer actuators with complicated electro-chemo-mechanical dynamics is an interesting area for research, due to the wide range of applications including biomimetic robots and biomedical devices. Although there have been extensive reports on modeling the electrochemical dynamics of polypyrrole (PPy) bending actuators, mechanical dynamics modeling of the actuators remains unexplored. PPy actuators can operate with low voltage while producing large displacement in comparison to robotic joints, they do not have friction or backlash, but they suffer from some disadvantages such as creep and hysteresis. In this paper, a complete analytical dynamic model for fast trilayer polypyrrole bending actuators has been proposed and named the analytical multi-domain dynamic actuator (AMDDA) model. First an electrical admittance model of the actuator will be obtained based on a distributed RC line; subsequently a proper mechanical dynamic model will be derived, based on Hamilton's principle. The purposed modeling approach will be validated based on recently published experimental results
e-Commerce and supply chains: Modelling of dynamics through ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
The dynamics associated with two production planning and control policies are modelled, viz. .... Hence, there is a strong need to design a dynamic knowledge inference system .... sell a variety of components to the subassembly manufacturer.
Immersive visualization of dynamic CFD model results
International Nuclear Information System (INIS)
Comparato, J.R.; Ringel, K.L.; Heath, D.J.
2004-01-01
With immersive visualization the engineer has the means for vividly understanding problem causes and discovering opportunities to improve design. Software can generate an interactive world in which collaborators experience the results of complex mathematical simulations such as computational fluid dynamic (CFD) modeling. Such software, while providing unique benefits over traditional visualization techniques, presents special development challenges. The visualization of large quantities of data interactively requires both significant computational power and shrewd data management. On the computational front, commodity hardware is outperforming large workstations in graphical quality and frame rates. Also, 64-bit commodity computing shows promise in enabling interactive visualization of large datasets. Initial interactive transient visualization methods and examples are presented, as well as development trends in commodity hardware and clustering. Interactive, immersive visualization relies on relevant data being stored in active memory for fast response to user requests. For large or transient datasets, data management becomes a key issue. Techniques for dynamic data loading and data reduction are presented as means to increase visualization performance. (author)
Modelling of the PELE fragmentation dynamics
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.
Modelling of the PELE fragmentation dynamics
International Nuclear Information System (INIS)
Verreault, J
2014-01-01
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.
Models of dynamical R-parity violation
Energy Technology Data Exchange (ETDEWEB)
Csáki, Csaba; Kuflik, Eric [Department of Physics, LEPP, Cornell University, Ithaca, NY 14853 (United States); Slone, Oren; Volansky, Tomer [Raymond and Beverly Sackler School of Physics and Astronomy, Tel-Aviv University, Tel-Aviv 69978 (Israel)
2015-06-08
The presence of R-parity violating interactions may relieve the tension between existing LHC constraints and natural supersymmetry. In this paper we lay down the theoretical framework and explore models of dynamical R-parity violation in which the breaking of R-parity is communicated to the visible sector by heavy messenger fields. We find that R-parity violation is often dominated by non-holomorphic operators that have so far been largely ignored, and might require a modification of the existing searches at the LHC. The dynamical origin implies that the effects of such operators are suppressed by the ratio of either the light fermion masses or the supersymmetry breaking scale to the mediation scale, thereby providing a natural explanation for the smallness of R-parity violation. We consider various scenarios, classified by whether R-parity violation, flavor breaking and/or supersymmetry breaking are mediated by the same messenger fields. The most compact case, corresponding to a deformation of the so called flavor mediation scenario, allows for the mediation of supersymmetry breaking, R-parity breaking, and flavor symmetry breaking in a unified manner.
Dynamical Models for Computer Viruses Propagation
Directory of Open Access Journals (Sweden)
José R. C. Piqueira
2008-01-01
Full Text Available Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network.
Photochemical modification of magnetic properties in organic low-dimensional conductors
International Nuclear Information System (INIS)
Naito, Toshio; Kakizaki, Akihiro; Wakeshima, Makoto; Hinatsu, Yukio; Inabe, Tamotsu
2009-01-01
Magnetic properties of organic charge transfer salts Ag(DX) 2 (DX=2,5-dihalogeno-N,N'-dicyanoquinonediimine; X=Cl, Br, I) were modified by UV irradiation from paramagnetism to diamagnetism in an irreversible way. The temperature dependence of susceptibility revealed that such change in magnetic behavior could be continuously controlled by the duration of irradiation. The observation with scanning electron microprobe revealed that the original appearance of samples, e.g. black well-defined needle-shaped shiny single crystals, remained after irradiation irrespective of the irradiation conditions and the duration. Thermochemical analysis and X-ray diffraction study demonstrated that the change in the physical properties were due to (partial) decomposition of Ag(DX) 2 to AgX, which was incorporated in the original Ag(DX) 2 lattices. Because the physical properties of low-dimensional organic conductors are very sensitive to lattice defects, even a small amount of AgX could effectively modify the electronic properties of Ag(DX) 2 without making the original crystalline appearance collapse. - Graphical abstract: By UV irradiation with appropriate masks, a part of single crystal of organic conductors irreversibly turned diamagnetic retaining their original crystalline shapes.
Low-dimensional organization of angular momentum during walking on a narrow beam.
Chiovetto, Enrico; Huber, Meghan E; Sternad, Dagmar; Giese, Martin A
2018-01-08
Walking on a beam is a challenging motor skill that requires the regulation of upright balance and stability. The difficulty in beam walking results from the reduced base of support compared to that afforded by flat ground. One strategy to maintain stability and hence avoid falling off the beam is to rotate the limb segments to control the body's angular momentum. The aim of this study was to examine the coordination of the angular momentum variations during beam walking. We recorded movement kinematics of participants walking on a narrow beam and computed the angular momentum contributions of the body segments with respect to three different axes. Results showed that, despite considerable variability in the movement kinematics, the angular momentum was characterized by a low-dimensional organization based on a small number of segmental coordination patterns. When the angular momentum was computed with respect to the beam axis, the largest fraction of its variation was accounted for by the trunk segment. This simple organization was robust and invariant across all participants. These findings support the hypothesis that control strategies for complex balancing tasks might be easier to understand by investigating angular momentum instead of the segmental kinematics.
Low-Dimensional-Networked Metal Halide Perovskites: The Next Big Thing
Saidaminov, Makhsud I.
2017-03-03
Low-dimensional-networked (low-DN) perovskite derivatives are bulk quantum materials in which charge carriers are localized within ordered metal halide sheets, rods, or clusters that are separated by cationic lattices. After two decades of hibernation, this class of semiconductors reemerged in the past two years, largely catalyzed by the interest in alternative, more stable absorbers to CH3NH3PbI3-type perovskites in photovoltaics. Whether low-DN perovskites will surpass other photovoltaic technologies remains to be seen, but their impressively high photo- and electroluminescence yields have already set new benchmarks in light emission applications. Here we offer our perspective on the most exciting advances in materials design of low-DN perovskites for energy- and optoelectronic-related applications. The next few years will usher in an explosive growth in this tribe of quantum materials, as only a few members have been synthesized, while the potential library of compositions and structures is believed to be much larger and is yet to be discovered.
Directory of Open Access Journals (Sweden)
Weixun Zhou
2017-05-01
Full Text Available Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs for high-resolution remote sensing image retrieval (HRRSIR. To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.
NATO Advanced Research Workshop on Thin Film Growth Techniques for Low-Dimensional Structures
Parkin, S; Dobson, P; Neave, J; Arrott, A
1987-01-01
This work represents the account of a NATO Advanced Research Workshop on "Thin Film Growth Techniques for Low Dimensional Structures", held at the University of Sussex, Brighton, England from 15-19 Sept. 1986. The objective of the workshop was to review the problems of the growth and characterisation of thin semiconductor and metal layers. Recent advances in deposition techniques have made it possible to design new material which is based on ultra-thin layers and this is now posing challenges for scientists, technologists and engineers in the assessment and utilisation of such new material. Molecular beam epitaxy (MBE) has become well established as a method for growing thin single crystal layers of semiconductors. Until recently, MBE was confined to the growth of III-V compounds and alloys, but now it is being used for group IV semiconductors and II-VI compounds. Examples of such work are given in this volume. MBE has one major advantage over other crystal growth techniques in that the structure of the growi...
Emerging Low-Dimensional Materials for Nonlinear Optics and Ultrafast Photonics.
Liu, Xiaofeng; Guo, Qiangbing; Qiu, Jianrong
2017-04-01
Low-dimensional (LD) materials demonstrate intriguing optical properties, which lead to applications in diverse fields, such as photonics, biomedicine and energy. Due to modulation of electronic structure by the reduced structural dimensionality, LD versions of metal, semiconductor and topological insulators (TIs) at the same time bear distinct nonlinear optical (NLO) properties as compared with their bulk counterparts. Their interaction with short pulse laser excitation exhibits a strong nonlinear character manifested by NLO absorption, giving rise to optical limiting or saturated absorption associated with excited state absorption and Pauli blocking in different materials. In particular, the saturable absorption of these emerging LD materials including two-dimensional semiconductors as well as colloidal TI nanoparticles has recently been utilized for Q-switching and mode-locking ultra-short pulse generation across the visible, near infrared and middle infrared wavelength regions. Beside the large operation bandwidth, these ultrafast photonics applications are especially benefit from the high recovery rate as well as the facile processibility of these LD materials. The prominent NLO response of these LD materials have also provided new avenues for the development of novel NLO and photonics devices for all-optical control as well as optical circuits beyond ultrafast lasers. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Low-Dimensional Organic Tin Bromide Perovskites and Their Photoinduced Structural Transformation.
Zhou, Chenkun; Tian, Yu; Wang, Mingchao; Rose, Alyssa; Besara, Tiglet; Doyle, Nicholas K; Yuan, Zhao; Wang, Jamie C; Clark, Ronald; Hu, Yanyan; Siegrist, Theo; Lin, Shangchao; Ma, Biwu
2017-07-24
Hybrid organic-inorganic metal halide perovskites possess exceptional structural tunability, with three- (3D), two- (2D), one- (1D), and zero-dimensional (0D) structures on the molecular level all possible. While remarkable progress has been realized in perovskite research in recent years, the focus has been mainly on 3D and 2D structures, with 1D and 0D structures significantly underexplored. The synthesis and characterization of a series of low-dimensional organic tin bromide perovskites with 1D and 0D structures is reported. Using the same organic and inorganic components, but at different ratios and reaction conditions, both 1D (C 4 N 2 H 14 )SnBr 4 and 0D (C 4 N 2 H 14 Br) 4 SnBr 6 can be prepared in high yields. Moreover, photoinduced structural transformation from 1D to 0D was investigated experimentally and theoretically in which photodissociation of 1D metal halide chains followed by structural reorganization leads to the formation of a more thermodynamically stable 0D structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Towards room-temperature superconductivity in low-dimensional C60 nanoarrays: An ab initio study
Erbahar, Dogan; Liu, Dan; Berber, Savas; Tománek, David
2018-04-01
We propose to raise the critical temperature Tc for superconductivity in doped C60 molecular crystals by increasing the electronic density of states at the Fermi level N (EF) and thus the electron-phonon coupling constant in low-dimensional C60 nanoarrays. We consider both electron and hole dopings and present numerical results for N (EF) , which increases with the decreasing bandwidth of the partly filled hu- and t1 u-derived frontier bands with the decreasing coordination number of C60. Whereas a significant increase in N (EF) occurs in two-dimensional (2D) arrays of doped C60 intercalated in-between graphene layers, we propose that the highest-Tc values approaching room temperature may occur in bundles of nanotubes filled by one-dimensional (1D) arrays of externally doped C60 or La @C60 or in diluted three-dimensional (3D) crystals where quasi-1D arrangements of C60 form percolation paths.
Meng, Fanke
Photocatalytic hydrogen generation by water splitting is a promising technique to produce clean and renewable solar fuel. The development of effective semiconductor photocatalysts to obtain efficient photocatalytic activity is the key objective. However, two critical reasons prevent wide applications of semiconductor photocatalysts: low light usage efficiency and high rates of charge recombination. In this dissertation, several low-dimensional semiconductors were synthesized with hydrothermal, hydrolysis, and chemical impregnation methods. The band structures of the low-dimensional semiconductor materials were engineered to overcome the above mentioned two shortcomings. In addition, the correlation between the photocatalytic activity of the low-dimensional semiconductor materials and their band structures were studied. First, we studied the effect of oxygen vacancies on the photocatalytic activity of one-dimensional anatase TiO2 nanobelts. Given that the oxygen vacancy plays a significant role in band structure and photocatalytic performance of semiconductors, oxygen vacancies were introduced into the anatase TiO2 nanobelts during reduction in H2 at high temperature. The oxygen vacancies of the TiO2 nanobelts boosted visible-light-responsive photocatalytic activity but weakened ultraviolet-light-responsive photocatalytic activity. As oxygen vacancies are commonly introduced by dopants, these results give insight into why doping is not always beneficial to the overall photocatalytic performance despite increases in absorption. Second, we improved the photocatalytic performance of two-dimensional lanthanum titanate (La2Ti2 O7) nanosheets, which are widely studied as an efficient photocatalyst due to the unique layered crystal structure. Nitrogen was doped into the La2Ti2O7 nanosheets and then Pt nanoparticles were loaded onto the La2Ti2O7 nanosheets. Doping nitrogen narrowed the band gap of the La2Ti 2O7 nanosheets by introducing a continuum of states by the valence
Modular assembly of low-dimensional coordination architectures on metal surfaces
International Nuclear Information System (INIS)
Stepanow, Sebastian; Lin, Nian; Barth, Johannes V
2008-01-01
The engineering of highly organized molecular architectures has attracted strong interest because of its potential for novel materials and functional nanoscopic devices. An important factor in the development, integration, and exploitation of such systems is the capability to prepare them on surfaces or in nanostructured environments. Recent advances in supramolecular design on metal substrates provide atomistic insight into the underlying self-assembly processes, mainly by scanning tunneling microscopy observations. This review summarizes progress in noncovalent synthesis strategies under ultra-high vacuum conditions employing metal ions as coordination centers directing the molecular organization. The realized metallosupramolecular compounds and arrays combine the properties of their constituent metal ions and organic ligands, and present several attractive features: their redox, magnetic and spin-state transitions. The presented exemplary molecular level studies elucidate the arrangement of organic adsorbates on metal surfaces, demonstrating the interplay between intermolecular and molecule-substrate interactions that needs to be controlled for the fabrication of low-dimensional structures. The understanding of metallosupramolecular organization and metal-ligand interactions on solid surfaces is important for the control of structure and concomitant function
A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)
Weber, Michael
2004-01-01
The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...
Bio-Inspired Neural Model for Learning Dynamic Models
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.
R-process nucleosynthesis: a dynamical model
Energy Technology Data Exchange (ETDEWEB)
Hillebrandt, W; Takahashi, K [Technische Hochschule Darmstadt (Germany, F.R.). Inst. fuer Kernphysik; Kodama, T [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro
1976-10-01
The synthesis of heavy and neutron-rich elements (with the mass number A > approximately 70) is reconsidered in the framework of a dynamical supernova model. The synthesis equation for the rapid neutron-capture (or, the r-) process and the hydrodynamical equations for the supernova explosion are solved simultaneously. Improved systematics of nuclear parameters are used, and the energy release due to ..beta..-decays as well as the energy loss due to neutrinos is taken into account. It is shown that the observed solar-system abundance curve can be reproduced fairly well by assuming only one supernova event on a time-scale of the order of 1 s. However there are still some discrepancies which may be explained by uncertainties in the nuclear data used.
Dynamical system analysis of interacting models
Carneiro, S.; Borges, H. A.
2018-01-01
We perform a dynamical system analysis of a cosmological model with linear dependence between the vacuum density and the Hubble parameter, with constant-rate creation of dark matter. We show that the de Sitter spacetime is an asymptotically stable critical point, future limit of any expanding solution. Our analysis also shows that the Minkowski spacetime is an unstable critical point, which eventually collapses to a singularity. In this way, such a prescription for the vacuum decay not only predicts the correct future de Sitter limit, but also forbids the existence of a stable Minkowski universe. We also study the effect of matter creation on the growth of structures and their peculiar velocities, showing that it is inside the current errors of redshift space distortions observations.
Analysis of A Virus Dynamics Model
Zhang, Baolin; Li, Jianquan; Li, Jia; Zhao, Xin
2018-03-01
In order to more accurately characterize the virus infection in the host, a virus dynamics model with latency and virulence is established and analyzed in this paper. The positivity and boundedness of the solution are proved. After obtaining the basic reproduction number and the existence of infected equilibrium, the Lyapunov method and the LaSalle invariance principle are used to determine the stability of the uninfected equilibrium and infected equilibrium by constructing appropriate Lyapunov functions. We prove that, when the basic reproduction number does not exceed 1, the uninfected equilibrium is globally stable, the virus can be cleared eventually; when the basic reproduction number is more than 1, the infected equilibrium is globally stable, the virus will persist in the host at a certain level. The effect of virulence and latency on infection is also discussed.
Coarsening dynamics in the Vicsek model
Dey, Supravat; Katyal, Nisha; Das, Dibyendu; Puri, Sanjay
We numerically study the flocking model introduced by Vicsek et al. (1995) in the coarsening regime. At standard self-propulsion speeds, we find two distinct growth laws for the coupled density and velocity fields. The characteristic length scale of the density domains grows as Lρ (t) t 1 / 4 , while the velocity length scale grows much faster, viz . , Lv (t) t 5 / 6 . The spatial fluctuations in the density and velocity ordering are studied by calculating the two-point correlation function and the structure factor, which show deviations from the well-known Porod's law. This is a natural consequence of scattering from irregular morphologies that dynamically arise in the system. In contrast, at lower self-propulsion speeds, the morphology is distinct, and as a result a new set of scaling exponents emerge. Most strikingly, the velocity order follows the density order with Lρ (t) Lv (t) t 1 / 4 .
Relativistic dynamical reduction models and nonlocality
International Nuclear Information System (INIS)
Ghirardi, G.C.; Grassi, R.
1990-09-01
We discuss some features of continuous dynamical models yielding state vector reduction and we briefly sketch some recent attempts to get a relativistic generalization of them. Within the relativistic context we analyze in detail the local an nonlocal features of the reduction mechanism and we investigate critically the possibility of attributing objective properties to individual systems in the micro and macroscopic cases. At the nonrelativistic level, two physically equivalent versions of continuous reduction mechanisms have been presented. However, only one of them can be taken as a starting point for the above considered relativistic generalization. By resorting to counterfactual arguments we show that the reason for this lies in the fact that the stochasticity involved in the two approaches has different conceptual implications. (author). 7 refs, 4 figs
A dynamical theory for the Rishon model
International Nuclear Information System (INIS)
Harari, H.; Seiberg, N.
1980-09-01
We propose a composite model for quarks and leptons based on an exact SU(3)sub(C)xSU(3)sub(H) gauge theory and two fundamental J=1/2 fermions: a charged T-rishon and a neutral V-rishon. Quarks, leptons and W-bosons are SU(3)sub(H)-singlet composites of rishons. A dynamically broken effective SU(3)sub(C)xSU(2)sub(L)xSU(2)sub(R)xU(1)sub(B-L) gauge theory emerges at the composite level. The theory is ''natural'', anomaly-free, has no fundamental scalar particles, and describes at least three generations of quarks and leptons. Several ''technicolor'' mechanisms are automatically present. (Author)
Dynamic modeling and simulation of wind turbines
International Nuclear Information System (INIS)
Ghafari Seadat, M.H.; Kheradmand Keysami, M.; Lari, H.R.
2002-01-01
Using wind energy for generating electricity in wind turbines is a good way for using renewable energies. It can also help to protect the environment. The main objective of this paper is dynamic modeling by energy method and simulation of a wind turbine aided by computer. In this paper, the equations of motion are extracted for simulating the system of wind turbine and then the behavior of the system become obvious by solving the equations. The turbine is considered with three blade rotor in wind direction, induced generator that is connected to the network and constant revolution for simulation of wind turbine. Every part of the wind turbine should be simulated for simulation of wind turbine. The main parts are blades, gearbox, shafts and generator
Modelling the Congo basin ecosystems with a dynamic vegetation model
Dury, Marie; Hambuckers, Alain; Trolliet, Franck; Huynen, Marie-Claude; Haineaux, Damien; Fontaine, Corentin M.; Fayolle, Adeline; François, Louis
2014-05-01
The scarcity of field observations in some parts of the world makes difficult a deep understanding of some ecosystems such as humid tropical forests in Central Africa. Therefore, modelling tools are interesting alternatives to study those regions even if the lack of data often prevents sharp calibration and validation of the model projections. Dynamic vegetation models (DVMs) are process-based models that simulate shifts in potential vegetation and its associated biogeochemical and hydrological cycles in response to climate. Initially run at the global scale, DVMs can be run at any spatial scale provided that climate and soil data are available. In the framework of the BIOSERF project ("Sustainability of tropical forest biodiversity and services under climate and human pressure"), we use and adapt the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) to study the Congo basin vegetation dynamics. The field campaigns have notably allowed the refinement of the vegetation representation from plant functional types (PFTs) to individual species through the collection of parameters such as the specific leaf area or the leaf C:N ratio of common tropical tree species and the location of their present-day occurrences from literature and available database. Here, we test the model ability to reproduce the present spatial and temporal variations of carbon stocks (e.g. biomass, soil carbon) and fluxes (e.g. gross and net primary productivities (GPP and NPP), net ecosystem production (NEP)) as well as the observed distribution of the studied species over the Congo basin. In the lack of abundant and long-term measurements, we compare model results with time series of remote sensing products (e.g. vegetation leaf area index (LAI), GPP and NPP). Several sensitivity tests are presented: we assess consecutively the impacts of the level at which the vegetation is simulated (PFTs or species), the spatial resolution and the initial land
Projecting surgeon supply using a dynamic model.
Fraher, Erin P; Knapton, Andy; Sheldon, George F; Meyer, Anthony; Ricketts, Thomas C
2013-05-01
To develop a projection model to forecast the head count and full-time equivalent supply of surgeons by age, sex, and specialty in the United States from 2009 to 2028. The search for the optimal number and specialty mix of surgeons to care for the United States population has taken on increased urgency under health care reform. Expanded insurance coverage and an aging population will increase demand for surgical and other medical services. Accurate forecasts of surgical service capacity are crucial to inform the federal government, training institutions, professional associations, and others charged with improving access to health care. The study uses a dynamic stock and flow model that simulates future changes in numbers and specialty type by factoring in changes in surgeon demographics and policy factors. : Forecasts show that overall surgeon supply will decrease 18% during the period form 2009 to 2028 with declines in all specialties except colorectal, pediatric, neurological surgery, and vascular surgery. Model simulations suggest that none of the proposed changes to increase graduate medical education currently under consideration will be sufficient to offset declines. The length of time it takes to train surgeons, the anticipated decrease in hours worked by surgeons in younger generations, and the potential decreases in graduate medical education funding suggest that there may be an insufficient surgeon workforce to meet population needs. Existing maldistribution patterns are likely to be exacerbated, leading to delayed or lost access to time-sensitive surgical procedures, particularly in rural areas.
Persistent agents in Axelrod's social dynamics model
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.
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. PsycINFO Database Record (c) 2016 APA, all rights reserved.
CFD modeling of the IRIS pressurizer dynamic
International Nuclear Information System (INIS)
Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R.; Bezerra, Jair L.; Lira, Carlos A.B. Oliveira
2015-01-01
Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)
CFD modeling of the IRIS pressurizer dynamic
Energy Technology Data Exchange (ETDEWEB)
Sanz, Ronny R.; Montesinos, Maria E.; Garcia, Carlos; Bueno, Elizabeth D.; Mazaira, Leorlen R., E-mail: rsanz@instec.cu, E-mail: mmontesi@instec.cu, E-mail: cgh@instec.cu, E-mail: leored1984@gmail.com [Instituto Superior de Tecnologias y Ciencias Aplicadas (InSTEC), La Habana (Cuba); Bezerra, Jair L.; Lira, Carlos A.B. Oliveira, E-mail: jair.lima@ufpe.br, E-mail: cabol@ufpe.br [Universida Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear
2015-07-01
Integral layout of nuclear reactor IRIS makes possible the elimination of the spray system, which is usually used to mitigate in-surge transient and also help to Boron homogenization. The study of transients with deficiencies in the Boron homogenization in this technology is very important, because they can cause disturbances in the reactor power and insert a strong reactivity in the core. The detailed knowledge of the behavior of multiphase multicomponent flows is challenging due to the complex phenomena and interactions at the interface. In this context, the CFD modeling is employed in the design of equipment in the nuclear industry as it allows predicting accidents or predicting their performance in dissimilar applications. The aim of the present research is to model the IRIS pressurizer's dynamic using the commercial CFD code CFX. A symmetric tri dimensional model equivalent to 1/8 of the total geometry was adopted to reduce mesh size and minimize processing time. The model considers the coexistence of four phases and also takes into account the heat losses. The relationships for interfacial mass, energy, and momentum transport are programmed and incorporated into CFX. Moreover, two subdomains and several additional variables are defined to monitoring the boron dilution sequences and condensation-evaporation rates in different control volumes. For transient states a non - equilibrium stratification in the pressurizer is considered. This paper discusses the model developed and the behavior of the system for representative transients sequences. The results of analyzed transients of IRIS can be applied to the design of pressurizer internal structures and components. (author)
A eural etwork Model for Dynamics Simulation
African Journals Online (AJOL)
Nafiisah
Results 5 - 18 ... situations, such as a dynamic environment (e.g., a molecular dynamics (MD) simulation whereby an atom constantly changes its local environment and number ..... of systems including both small clusters and bulk structures. 7.
International Nuclear Information System (INIS)
Allen, J. W.
2003-01-01
This report summarizes a 12-year program of various kinds of synchrotron spectroscopies directed at the electronic structures of narrow band and low-dimensional materials that display correlated electron behaviors such as metal-insulator transitions, mixed valence, superconductivity, Kondo moment quenching, heavy Fermions, and non-Fermi liquid properties
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
2017-07-01
Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.
Progress towards Continental River Dynamics modeling
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.
Supercomputer modeling of volcanic eruption dynamics
Energy Technology Data Exchange (ETDEWEB)
Kieffer, S.W. [Arizona State Univ., Tempe, AZ (United States); Valentine, G.A. [Los Alamos National Lab., NM (United States); Woo, Mahn-Ling [Arizona State Univ., Tempe, AZ (United States)
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.
A dynamic model of Venus's gravity field
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.
Improving Bioenergy Crops through Dynamic Metabolic Modeling
Directory of Open Access Journals (Sweden)
Mojdeh Faraji
2017-10-01
Full Text Available Enormous advances in genetics and metabolic engineering have made it possible, in principle, to create new plants and crops with improved yield through targeted molecular alterations. However, while the potential is beyond doubt, the actual implementation of envisioned new strains is often difficult, due to the diverse and complex nature of plants. Indeed, the intrinsic complexity of plants makes intuitive predictions difficult and often unreliable. The hope for overcoming this challenge is that methods of data mining and computational systems biology may become powerful enough that they could serve as beneficial tools for guiding future experimentation. In the first part of this article, we review the complexities of plants, as well as some of the mathematical and computational methods that have been used in the recent past to deepen our understanding of crops and their potential yield improvements. In the second part, we present a specific case study that indicates how robust models may be employed for crop improvements. This case study focuses on the biosynthesis of lignin in switchgrass (Panicum virgatum. Switchgrass is considered one of the most promising candidates for the second generation of bioenergy production, which does not use edible plant parts. Lignin is important in this context, because it impedes the use of cellulose in such inedible plant materials. The dynamic model offers a platform for investigating the pathway behavior in transgenic lines. In particular, it allows predictions of lignin content and composition in numerous genetic perturbation scenarios.
Modelling Ebola virus dynamics: Implications for therapy.
Martyushev, Alexey; Nakaoka, Shinji; Sato, Kei; Noda, Takeshi; Iwami, Shingo
2016-11-01
Ebola virus (EBOV) causes a severe, often fatal Ebola virus disease (EVD), for which no approved antivirals exist. Recently, some promising anti-EBOV drugs, which are experimentally potent in animal models, have been developed. However, because the quantitative dynamics of EBOV replication in humans is uncertain, it remains unclear how much antiviral suppression of viral replication affects EVD outcome in patients. Here, we developed a novel mathematical model to quantitatively analyse human viral load data obtained during the 2000/01 Uganda EBOV outbreak and evaluated the effects of different antivirals. We found that nucleoside analogue- and siRNA-based therapies are effective if a therapy with a >50% inhibition rate is initiated within a few days post-symptom-onset. In contrast, antibody-based therapy requires not only a higher inhibition rate but also an earlier administration, especially for otherwise fatal cases. Our results demonstrate that an appropriate choice of EBOV-specific drugs is required for effective EVD treatment. Copyright © 2016 Elsevier B.V. All rights reserved.
Quantum Dynamics in the HMF Model
Plestid, Ryan; O'Dell, Duncan
2017-04-01
The Hamiltonian Mean Field (HMF) model represents a paradigm in the study of long-range interactions but has never been realized in a lab. Recently Shutz and Morigi (PRL 113) have come close but ultimately fallen short. Their proposal relied on cavity-induced interactions between atoms. If a design using cold atoms is to be successful, an understanding of quantum effects is essential. I will outline the natural quantum generalization of the HMF assuming a BEC by using a generalized Gross-Pitaevskii equation (gGPE). I will show how quantum effects modify features which are well understood in the classical model. More specifically, by working in the semi-classical regime (strong interparticle interactions) we can identify the universal features predicted by catastrophe theory dressed with quantum interference effects. The stationary states of gGPE can be solved exactly and are found to be described by self-consistent Mathieu functions. Finally, I will discuss the connection between the classical description of the dynamics in terms of the Vlassov equation, and the gGPE. We would like to thank the Government of Ontario's OGS program, NSERC, and the Perimeter Institute of Theoretical Physics.
Dynamical reduction models with general gaussian noises
International Nuclear Information System (INIS)
Bassi, Angelo; Ghirardi, GianCarlo
2002-02-01
We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the statevector, white noise stochastic processes with non white ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view the most relevant motivation for the approach we propose here derives from the fact that in relativistic models the occurrence of white noises is the main responsible for the appearance of untractable divergences. Therefore, one can hope that resorting to non white noises one can overcome such a difficulty. We investigate stochastic equations with non white noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above mentioned subject but also for the general study of dissipative systems and decoherence. (author)
Dynamical reduction models with general Gaussian noises
International Nuclear Information System (INIS)
Bassi, Angelo; Ghirardi, GianCarlo
2002-01-01
We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the state vector, white-noise stochastic processes with nonwhite ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view, the most relevant motivation for the approach we propose here derives from the fact that in relativistic models intractable divergences appear as a consequence of the white nature of the noises. Therefore, one can hope that resorting to nonwhite noises, one can overcome such a difficulty. We investigate stochastic equations with nonwhite noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above-mentioned subject but also for the general study of dissipative systems and decoherence
Nonlinear dynamics new directions models and applications
Ugalde, Edgardo
2015-01-01
This book, along with its companion volume, Nonlinear Dynamics New Directions: Theoretical Aspects, covers topics ranging from fractal analysis to very specific applications of the theory of dynamical systems to biology. This second volume contains mostly new applications of the theory of dynamical systems to both engineering and biology. The first volume is devoted to fundamental aspects and includes a number of important new contributions as well as some review articles that emphasize new development prospects. The topics addressed in the two volumes include a rigorous treatment of fluctuations in dynamical systems, topics in fractal analysis, studies of the transient dynamics in biological networks, synchronization in lasers, and control of chaotic systems, among others. This book also: · Develops applications of nonlinear dynamics on a diversity of topics such as patterns of synchrony in neuronal networks, laser synchronization, control of chaotic systems, and the study of transient dynam...
Urban eco-efficiency and system dynamics modelling
Energy Technology Data Exchange (ETDEWEB)
Hradil, P., Email: petr.hradil@vtt.fi
2012-06-15
Assessment of urban development is generally based on static models of economic, social or environmental impacts. More advanced dynamic models have been used mostly for prediction of population and employment changes as well as for other macro-economic issues. This feasibility study was arranged to test the potential of system dynamic modelling in assessing eco-efficiency changes during urban development. (orig.)
Linking spatial and dynamic models for traffic maneuvers
DEFF Research Database (Denmark)
Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal
2015-01-01
For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...
Dynamics in Higher Education Politics: A Theoretical Model
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…
Maritime piracy situation modelling with dynamic Bayesian networks
CSIR Research Space (South Africa)
Dabrowski, James M
2015-05-01
Full Text Available A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a...
Agent Based Modeling on Organizational Dynamics of Terrorist Network
Bo Li; Duoyong Sun; Renqi Zhu; Ze Li
2015-01-01
Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...
Low Dimensional Embedding of Climate Data for Radio Astronomical Site Testing in the Colombian Andes
Chaparro Molano, Germán; Ramírez Suárez, Oscar Leonardo; Restrepo Gaitán, Oscar Alberto; Marcial Martínez Mercado, Alexander
2017-10-01
We set out to evaluate the potential of the Colombian Andes for millimeter-wave astronomical observations. Previous studies for astronomical site testing in this region have suggested that nighttime humidity and cloud cover conditions make most sites unsuitable for professional visible-light observations. Millimeter observations can be done during the day, but require that the precipitable water vapor column above a site stays below ˜10 mm. Due to a lack of direct radiometric or radiosonde measurements, we present a method for correlating climate data from weather stations to sites with a low precipitable water vapor column. We use unsupervised learning techniques to low dimensionally embed climate data (precipitation, rain days, relative humidity, and sunshine duration) in order to group together stations with similar long-term climate behavior. The data were taken over a period of 30 years by 2046 weather stations across the Colombian territory. We find six regions with unusually dry, clear-sky conditions, ranging in elevations from 2200 to 3800 masl. We evaluate the suitability of each region using a quality index derived from a Bayesian probabilistic analysis of the station type and elevation distributions. Two of these regions show a high probability of having an exceptionally low precipitable water vapor column. We compared our results with global precipitable water vapor maps and find a plausible geographical correlation with regions with low water vapor columns (˜10 mm) at an accuracy of ˜20 km. Our methods can be applied to similar data sets taken in other countries as a first step toward astronomical site evaluation.
MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL
Directory of Open Access Journals (Sweden)
Andrey Borisovich Nikolaev
2017-09-01
Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.
AIR INGRESS ANALYSIS: COMPUTATIONAL FLUID DYNAMIC MODELS
Energy Technology Data Exchange (ETDEWEB)
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.
A Dynamic Travel Time Estimation Model Based on Connected Vehicles
Directory of Open Access Journals (Sweden)
Daxin Tian
2015-01-01
Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
Fu, Chunjiang; Suzuki, Yasuyuki; Kiyono, Ken; Morasso, Pietro; Nomura, Taishin
2014-12-06
Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather
Modeling of ELM Dynamics in ITER
International Nuclear Information System (INIS)
Pankin, A.Y.; Bateman, G.; Kritz, A.H.; Brennan, D.P.; Snyder, P.B.; Kruger, S.
2007-01-01
Edge localized modes (ELMs) are large scale instabilities that alter the H-mode pedestal, reduce the total plasma stored energy, and can result in heat pulses to the divertor plates. These modes can be triggered by pressure driven ballooning modes or by current driven peeling instabilities. In this study, stability analyses are carried out for a series of ITER equilibria that are generated with the TEQ and TOQ equilibrium codes. The H-mode pedestal pressure and parallel component of plasma current density are varied in a systematic way in order to include the relevant parameter space for a specific ITER discharge. Ideal MHD stability codes, DCON, ELITE, and BALOO code, are employed to determine whether or not each ITER equilibrium profile is unstable to peeling or ballooning modes in the pedestal region. Several equilibria that are close to the marginal stability boundary for peeling and ballooning modes are tested with the NIMROD non-ideal MHD code. The effects of finite resistivity are studied in a series of linear NIMROD computations. It is found that the peeling-ballooning stability threshold is very sensitive to the resistivity and viscosity profiles, which vary dramatically over a wide range near the separatrix. Due to the effects of finite resistivity and viscosity, the peeling-ballooning stability threshold is shifted compared to the ideal threshold. A fundamental question in the integrated modeling of ELMy H-mode discharges concerning how much plasma and current density is removed during each ELM crash can be addressed with nonlinear non-ideal MHD simulations. In this study, the NIMROD computer simulations are continued into the nonlinear stage for several ITER equilibria that are marginally unstable to peeling or ballooning modes. The role of two-fluid and finite Larmor radius effects on the ELM dynamics in ITER geometry is examined. The formation of ELM filament structures, which are observed in many existing tokamak experiments, is demonstrated for ITER
Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto
2016-12-01
It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low-dimensional
Dynamic hysteretic sensing model of bending-mode Galfenol transducer
International Nuclear Information System (INIS)
Cao, Shuying; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei
2015-01-01
A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device
Dynamic hysteretic sensing model of bending-mode Galfenol transducer
Energy Technology Data Exchange (ETDEWEB)
Cao, Shuying, E-mail: shuying-cao@hebut.edu.cn; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei [Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin 300130 (China)
2015-05-07
A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.
System Dynamics Modeling for Supply Chain Information Sharing
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.
A comprehensive dynamic modeling approach for giant magnetostrictive material actuators
International Nuclear Information System (INIS)
Gu, Guo-Ying; Zhu, Li-Min; Li, Zhi; Su, Chun-Yi
2013-01-01
In this paper, a comprehensive modeling approach for a giant magnetostrictive material actuator (GMMA) is proposed based on the description of nonlinear electromagnetic behavior, the magnetostrictive effect and frequency response of the mechanical dynamics. It maps the relationships between current and magnetic flux at the electromagnetic part to force and displacement at the mechanical part in a lumped parameter form. Towards this modeling approach, the nonlinear hysteresis effect of the GMMA appearing only in the electrical part is separated from the linear dynamic plant in the mechanical part. Thus, a two-module dynamic model is developed to completely characterize the hysteresis nonlinearity and the dynamic behaviors of the GMMA. The first module is a static hysteresis model to describe the hysteresis nonlinearity, and the cascaded second module is a linear dynamic plant to represent the dynamic behavior. To validate the proposed dynamic model, an experimental platform is established. Then, the linear dynamic part and the nonlinear hysteresis part of the proposed model are identified in sequence. For the linear part, an approach based on axiomatic design theory is adopted. For the nonlinear part, a Prandtl–Ishlinskii model is introduced to describe the hysteresis nonlinearity and a constrained quadratic optimization method is utilized to identify its coefficients. Finally, experimental tests are conducted to demonstrate the effectiveness of the proposed dynamic model and the corresponding identification method. (paper)
Further Results on Dynamic Additive Hazard Rate Model
Directory of Open Access Journals (Sweden)
Zhengcheng Zhang
2014-01-01
Full Text Available In the past, the proportional and additive hazard rate models have been investigated in the works. Nanda and Das (2011 introduced and studied the dynamic proportional (reversed hazard rate model. In this paper we study the dynamic additive hazard rate model, and investigate its aging properties for different aging classes. The closure of the model under some stochastic orders has also been investigated. Some examples are also given to illustrate different aging properties and stochastic comparisons of the model.
Identification of a nuclear plant dynamics via ARMAX model
International Nuclear Information System (INIS)
Yamamoto, Shigeki; Otsuji, Tomoo; Muramatsu, Eiichi
2000-01-01
Dynamics of the reactor of nuclear ship 'Mutsu' is described by a linear time-invariant discrete-time model which is referred to as ARMAX (Auto-Regressive Moving Average eXogenious inputs) model. Applying system identification methods, parameters of the ARMAX model are determined from input-output data of the reactor. Accuracy of the model is examined in time and frequency domain. We show that the model can be a good approximation of the plant dynamics. (author)
Gweon, Gey-Hong
Using angle resolved photoemission spectroscopy (ARPES) as the main experimental tool and the single particle Green's function as the main theoretical tool, materials of various degrees of low dimensionality and different ground states are studied. The underlying theme of this thesis is that of one dimensional physics, which includes charge density waves (CDW's) and the Luttinger liquid (LL). The LL is the prime example of a lattice non-Fermi liquid (non-FL) and CDW fluctuations also give non-FL behaviors. Non-FL physics is an emerging paradigm of condensed matter physics. It is thought by some researchers that one dimensional LL behavior is a key element in solving the high temperature superconductivity problem. TiTe2 is a quasi-2 dimensional (quasi-2D) Fermi liquid (FL) material very well suited for ARPES lineshape studies. I report ARPES spectra at 300 K which show an unusual behavior of a peak moving through the Fermi energy (EF). I also report a good fit of the ARPES spectra at 25 K obtained by using a causal Green's function proposed by K. Matho. SmTe3 is a quasi-2D CDW material. The near EF ARPES spectra and intensity map reveal rich details of an anisotropic gap and imperfectly nested Fermi surface (FS) for a high temperature CDW. A simple model of imperfect nesting can be constructed from these data and predicts a CDW wavevector in very good agreement with the value known from electron diffraction. NaMo6O17 and KMo 6O17 are also quasi-2D CDW materials. The "hidden nesting" or "hidden 1 dimensionality" picture for the CDW is confirmed very well by our direct image of the FS. K0.3MoO3, the so-called "blue bronze," is a quasi-1 dimensional (quasi-1D) CDW material. Even in its metallic phase above the CDW transition temperature, its photoemission spectra show an anomalously weak intensity at EF and no clear metallic Fermi edge. I compare predictions of an LL model and a CDW fluctuation model regarding these aspects, and find that the LL scenario explains them
Modeling proteasome dynamics in Parkinson's disease
International Nuclear Information System (INIS)
Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H; Pigolotti, Simone; Otzen, Daniel
2009-01-01
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
Dynamics of the Random Field Ising Model
Xu, Jian
The Random Field Ising Model (RFIM) is a general tool to study disordered systems. Crackling noise is generated when disordered systems are driven by external forces, spanning a broad range of sizes. Systems with different microscopic structures such as disordered mag- nets and Earth's crust have been studied under the RFIM. In this thesis, we investigated the domain dynamics and critical behavior in two dipole-coupled Ising ferromagnets Nd2Fe14B and LiHoxY 1-xF4. With Tc well above room temperature, Nd2Fe14B has shown reversible disorder when exposed to an external transverse field and crosses between two universality classes in the strong and weak disorder limits. Besides tunable disorder, LiHoxY1-xF4 has shown quantum tunneling effects arising from quantum fluctuations, providing another mechanism for domain reversal. Universality within and beyond power law dependence on avalanche size and energy were studied in LiHo0.65Y0.35 F4.
Dynamical Models For Prices With Distributed Delays
Directory of Open Access Journals (Sweden)
Mircea Gabriela
2015-06-01
Full Text Available In the present paper we study some models for the price dynamics of a single commodity market. The quantities of supplied and demanded are regarded as a function of time. Nonlinearities in both supply and demand functions are considered. The inventory and the level of inventory are taken into consideration. Due to the fact that the consumer behavior affects commodity demand, and the behavior is influenced not only by the instantaneous price, but also by the weighted past prices, the distributed time delay is introduced. The following kernels are taken into consideration: demand price weak kernel and demand price Dirac kernel. Only one positive equilibrium point is found and its stability analysis is presented. When the demand price kernel is weak, under some conditions of the parameters, the equilibrium point is locally asymptotically stable. When the demand price kernel is Dirac, the existence of the local oscillations is investigated. A change in local stability of the equilibrium point, from stable to unstable, implies a Hopf bifurcation. A family of periodic orbits bifurcates from the positive equilibrium point when the time delay passes through a critical value. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.
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.
Modeling shockwave deformation via molecular dynamics
International Nuclear Information System (INIS)
Holian, B.L.
1987-01-01
Molecular dynamics (MD), where the equations of motion of up to thousands of interacting atoms are solved on the computer, has proven to be a powerful tool for investigating a wide variety of nonequilibrium processes from the atomistic viewpoint. Simulations of shock waves in three-dimensional (3D) solids and fluids have shown conclusively that shear-stress relaxation is achieved through atomic rearrangement. In the case of fluids, the transverse motion is viscous, and the constitutive model of Navier-Stokes hydrodynamics has been shown to be accurate - even on the time and distance scales of MD experiments. For strong shocks in solids, the plastic flow that leads to shear-stress relaxation in MD is highly localized near the shock front, involving a slippage along close-packed planes. For shocks of intermediate strength, MD calculations exhibit an elastic precursor running out in front of the steady plastic wave, where slippage similar in character to that in the very strong shocks leads to shear-stress relaxation. An interesting correlation between the maximum shear stress and the Hugoniot pressure jump is observed for both 3D and fluid shockwave calculations, which may have some utility in modeling applications. At low shock strengths, the MD simulations show only elastic compression, with no permanent transverse atomic strains. The result for perfect 3D crystals is also seen in calculations for 1D chains. It is speculated that, if it were practical, a very large MD system containing dislocations could be expected to exhibit more realistic plastic flow for weak shock waves, too
An individual-based model of Zebrafish population dynamics accounting for energy dynamics
DEFF Research Database (Denmark)
Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...
Optical/Far-Infrared Control of Low-Dimensional Semiconductor Structures
National Research Council Canada - National Science Library
Citrin, David
2003-01-01
.... The manipulation of the carrier and optical dynamics will be achieved by the use of specially tailored ultrafast optical pulses, multicolor laser fields, millimeter or submillimeter electromagnetic...
Development of plenoptic infrared camera using low dimensional material based photodetectors
Chen, Liangliang
Infrared (IR) sensor has extended imaging from submicron visible spectrum to tens of microns wavelength, which has been widely used for military and civilian application. The conventional bulk semiconductor materials based IR cameras suffer from low frame rate, low resolution, temperature dependent and highly cost, while the unusual Carbon Nanotube (CNT), low dimensional material based nanotechnology has been made much progress in research and industry. The unique properties of CNT lead to investigate CNT based IR photodetectors and imaging system, resolving the sensitivity, speed and cooling difficulties in state of the art IR imagings. The reliability and stability is critical to the transition from nano science to nano engineering especially for infrared sensing. It is not only for the fundamental understanding of CNT photoresponse induced processes, but also for the development of a novel infrared sensitive material with unique optical and electrical features. In the proposed research, the sandwich-structured sensor was fabricated within two polymer layers. The substrate polyimide provided sensor with isolation to background noise, and top parylene packing blocked humid environmental factors. At the same time, the fabrication process was optimized by real time electrical detection dielectrophoresis and multiple annealing to improve fabrication yield and sensor performance. The nanoscale infrared photodetector was characterized by digital microscopy and precise linear stage in order for fully understanding it. Besides, the low noise, high gain readout system was designed together with CNT photodetector to make the nano sensor IR camera available. To explore more of infrared light, we employ compressive sensing algorithm into light field sampling, 3-D camera and compressive video sensing. The redundant of whole light field, including angular images for light field, binocular images for 3-D camera and temporal information of video streams, are extracted and
A model of nematode dynamics in the Westerschelde estuary
Li, J.; Vincx, M.; Herman, P.M.J.
1996-01-01
We developed a time dynamic model to investigate the temporal dynamics of nematode community in the brackish zone of the Westerschelde Estuary. The biomass of four nematode feeding groups observed from March 1991 to February 1992 is used to calibrate the model. Using environmental data as the input,
Dynamic of exact perturbations in Bianchi IX type cosmological models
International Nuclear Information System (INIS)
Mello Neto, J.R.T. de.
1985-01-01
The dynamic of Bianchi IX type cosmological models is studied, after reducing Einstein equations to Hamiltonian system. Using the Melnikov method, the existence of chaos in the dynamic of these models is proved, and some numerical experiments are carried out. (M.C.K.) [pt
Dynamic root uptake model for neutral lipophilic organics
DEFF Research Database (Denmark)
Trapp, Stefan
2002-01-01
and output to stem with the transpiration stream plus first-order metabolism and dilution by exponential growth. For chemicals with low or intermediate lipophilicity (log Kow , 2), there was no relevant difference between dynamic model and equilibrium approach. For lipophilic compounds, the dynamic model...
Model for the dynamic study of AC contactors
Energy Technology Data Exchange (ETDEWEB)
Corcoles, F.; Pedra, J.; Garrido, J.P.; Baza, R. [Dep. d' Eng. Electrica ETSEIB. UPC, Barcelona (Spain)
2000-08-01
This paper proposes a model for the dynamic analysis of AC contactors. The calculation algorithm and implementation are discussed. The proposed model can be used to study the influence of the design parameters and the supply in their dynamic behaviour. The high calculation speed of the implemented algorithm allows extensive ranges of parameter variations to be analysed. (orig.)
Wind speed dynamical model in a wind farm
DEFF Research Database (Denmark)
Soleimanzadeh, Maryam; Wisniewski, Rafal
2010-01-01
, the dynamic model for wind flow will be established. The state space variables are determined based on a fine mesh defined for the farm. The end goal of this method is to assist the development of a dynamical model of a wind farm that can be engaged for better wind farm control strategies....
Accelerating transition dynamics in city regions: A qualitative modeling perspective
P.J. Valkering (Pieter); Yücel, G. (Gönenç); Gebetsroither-Geringer, E. (Ernst); Markvica, K. (Karin); Meynaerts, E. (Erika); N. Frantzeskaki (Niki)
2017-01-01
textabstractIn this article, we take stock of the findings from conceptual and empirical work on the role of transition initiatives for accelerating transitions as input for modeling acceleration dynamics. We applied the qualitative modeling approach of causal loop diagrams to capture the dynamics
Dynamic model based on Bayesian method for energy security assessment
International Nuclear Information System (INIS)
Augutis, Juozas; Krikštolaitis, Ričardas; Pečiulytė, Sigita; Žutautaitė, Inga
2015-01-01
Highlights: • Methodology for dynamic indicator model construction and forecasting of indicators. • Application of dynamic indicator model for energy system development scenarios. • Expert judgement involvement using Bayesian method. - Abstract: The methodology for the dynamic indicator model construction and forecasting of indicators for the assessment of energy security level is presented in this article. An indicator is a special index, which provides numerical values to important factors for the investigated area. In real life, models of different processes take into account various factors that are time-dependent and dependent on each other. Thus, it is advisable to construct a dynamic model in order to describe these dependences. The energy security indicators are used as factors in the dynamic model. Usually, the values of indicators are obtained from statistical data. The developed dynamic model enables to forecast indicators’ variation taking into account changes in system configuration. The energy system development is usually based on a new object construction. Since the parameters of changes of the new system are not exactly known, information about their influences on indicators could not be involved in the model by deterministic methods. Thus, dynamic indicators’ model based on historical data is adjusted by probabilistic model with the influence of new factors on indicators using the Bayesian method
A Comprehensive Method for Comparing Mental Models of Dynamic Systems
Schaffernicht, Martin; Grösser, Stefan N.
2011-01-01
Mental models are the basis on which managers make decisions even though external decision support systems may provide help. Research has demonstrated that more comprehensive and dynamic mental models seem to be at the foundation for improved policies and decisions. Eliciting and comparing such models can systematically explicate key variables and their main underlying structures. In addition, superior dynamic mental models can be identified. This paper reviews existing studies which measure ...
Dislocation climb models from atomistic scheme to dislocation dynamics
Niu, Xiaohua; Luo, Tao; Lu, Jianfeng; Xiang, Yang
2016-01-01
We develop a mesoscopic dislocation dynamics model for vacancy-assisted dislocation climb by upscalings from a stochastic model on the atomistic scale. Our models incorporate microscopic mechanisms of (i) bulk diffusion of vacancies, (ii) vacancy exchange dynamics between bulk and dislocation core, (iii) vacancy pipe diffusion along the dislocation core, and (iv) vacancy attachment-detachment kinetics at jogs leading to the motion of jogs. Our mesoscopic model consists of the vacancy bulk dif...
The Financial Accounting Model from a System Dynamics' Perspective
Melse, Eric
2006-01-01
This paper explores the foundation of the financial accounting model. We examine the properties of the accounting equation as the principal algorithm for the design and the development of a System Dynamics model. Key to the perspective is the foundational requirement that resolves the temporal conflict that resides in a stock and flow model. Through formal analysis the accounting equation is redefined as a cybernetic model by expressing the temporal and dynamic properties of its terms. Articu...
Directory of Open Access Journals (Sweden)
Xu Liu
2015-01-01
Full Text Available Unsteady aerodynamic system modeling is widely used to solve the dynamic stability problems encountering aircraft design. In this paper, single degree-of-freedom (SDF vibration model and forced simple harmonic motion (SHM model for dynamic derivative prediction are developed on the basis of modified Etkin model. In the light of the characteristics of SDF time domain solution, the free vibration identification methods for dynamic stability parameters are extended and applied to the time domain numerical simulation of blunted cone calibration model examples. The dynamic stability parameters by numerical identification are no more than 0.15% deviated from those by experimental simulation, confirming the correctness of SDF vibration model. The acceleration derivatives, rotary derivatives, and combination derivatives of Army-Navy Spinner Rocket are numerically identified by using unsteady N-S equation and solving different SHV patterns. Comparison with the experimental result of Army Ballistic Research Laboratories confirmed the correctness of the SHV model and dynamic derivative identification. The calculation result of forced SHM is better than that by the slender body theory of engineering approximation. SDF vibration model and SHM model for dynamic stability parameters provide a solution to the dynamic stability problem encountering aircraft design.
National Research Council Canada - National Science Library
Raftery, Adrian E; Karny, Miroslav; Andrysek, Josef; Ettler, Pavel
2007-01-01
... is. We develop a method called Dynamic Model Averaging (DMA) in which a state space model for the parameters of each model is combined with a Markov chain model for the correct model. This allows the (correct...
Dynamics of mathematical models in biology bringing mathematics to life
Zazzu, Valeria; Guarracino, Mario
2016-01-01
This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes in cells. Moreover, chapters i...
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
Stochastic dynamic programming model for optimal resource ...
Indian Academy of Sciences (India)
M Bhuvaneswari
2018-04-11
Apr 11, 2018 ... handover in VANET; because of high dynamics in net- work topology, collaboration ... containers, doctors, nurses, cash and stocks. Similarly, ... GTBA does not take the resource types and availability into consideration.
Induction generator models in dynamic simulation tools
DEFF Research Database (Denmark)
Knudsen, Hans; Akhmatov, Vladislav
1999-01-01
For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained...
Model reduction tools for nonlinear structural dynamics
Slaats, P.M.A.; Jongh, de J.; Sauren, A.A.H.J.
1995-01-01
Three mode types are proposed for reducing nonlinear dynamical system equations, resulting from finite element discretizations: tangent modes, modal derivatives, and newly added static modes. Tangent modes are obtained from an eigenvalue problem with a momentary tangent stiffness matrix. Their