NASA Astrophysics Data System (ADS)
Draper, Martin; Usera, Gabriel
2015-04-01
The Scale Dependent Dynamic Model (SDDM) has been widely validated in large-eddy simulations using pseudo-spectral codes [1][2][3]. The scale dependency, particularly the potential law, has been proved also in a priori studies [4][5]. To the authors' knowledge there have been only few attempts to use the SDDM in finite difference (FD) and finite volume (FV) codes [6][7], finding some improvements with the dynamic procedures (scale independent or scale dependent approach), but not showing the behavior of the scale-dependence parameter when using the SDDM. The aim of the present paper is to evaluate the SDDM in the open source code caffa3d.MBRi, an updated version of the code presented in [8]. caffa3d.MBRi is a FV code, second-order accurate, parallelized with MPI, in which the domain is divided in unstructured blocks of structured grids. To accomplish this, 2 cases are considered: flow between flat plates and flow over a rough surface with the presence of a model wind turbine, taking for this case the experimental data presented in [9]. In both cases the standard Smagorinsky Model (SM), the Scale Independent Dynamic Model (SIDM) and the SDDM are tested. As presented in [6][7] slight improvements are obtained with the SDDM. Nevertheless, the behavior of the scale-dependence parameter supports the generalization of the dynamic procedure proposed in the SDDM, particularly taking into account that no explicit filter is used (the implicit filter is unknown). [1] F. Porté-Agel, C. Meneveau, M.B. Parlange. "A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer". Journal of Fluid Mechanics, 2000, 415, 261-284. [2] E. Bou-Zeid, C. Meneveau, M. Parlante. "A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows". Physics of Fluids, 2005, 17, 025105 (18p). [3] R. Stoll, F. Porté-Agel. "Dynamic subgrid-scale models for momentum and scalar fluxes in large-eddy simulations of neutrally stratified atmospheric boundary layers over heterogeneous terrain". Water Resources Research, 2006, 42, WO1409 (18 p). [4] J. Keissl, M. Parlange, C. Meneveau. "Field experimental study of dynamic Smagorinsky models in the atmospheric surface layer". Journal of the Atmospheric Science, 2004, 61, 2296-2307. [5] E. Bou-Zeid, N. Vercauteren, M.B. Parlange, C. Meneveau. "Scale dependence of subgrid-scale model coefficients: An a priori study". Physics of Fluids, 2008, 20, 115106. [6] G. Kirkil, J. Mirocha, E. Bou-Zeid, F.K. Chow, B. Kosovic, "Implementation and evaluation of dynamic subfilter - scale stress models for large - eddy simulation using WRF". Monthly Weather Review, 2012, 140, 266-284. [7] S. Radhakrishnan, U. Piomelli. "Large-eddy simulation of oscillating boundary layers: model comparison and validation". Journal of Geophysical Research, 2008, 113, C02022. [8] G. Usera, A. Vernet, J.A. Ferré. "A parallel block-structured finite volume method for flows in complex geometry with sliding interfaces". Flow, Turbulence and Combustion, 2008, 81, 471-495. [9] Y-T. Wu, F. Porté-Agel. "Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations". BoundaryLayerMeteorology, 2011, 138, 345-366.
Multiscale functions, scale dynamics, and applications to partial differential equations
NASA Astrophysics Data System (ADS)
Cresson, Jacky; Pierret, Frédéric
2016-05-01
Modeling phenomena from experimental data always begins with a choice of hypothesis on the observed dynamics such as determinism, randomness, and differentiability. Depending on these choices, different behaviors can be observed. The natural question associated to the modeling problem is the following: "With a finite set of data concerning a phenomenon, can we recover its underlying nature? From this problem, we introduce in this paper the definition of multi-scale functions, scale calculus, and scale dynamics based on the time scale calculus [see Bohner, M. and Peterson, A., Dynamic Equations on Time Scales: An Introduction with Applications (Springer Science & Business Media, 2001)] which is used to introduce the notion of scale equations. These definitions will be illustrated on the multi-scale Okamoto's functions. Scale equations are analysed using scale regimes and the notion of asymptotic model for a scale equation under a particular scale regime. The introduced formalism explains why a single scale equation can produce distinct continuous models even if the equation is scale invariant. Typical examples of such equations are given by the scale Euler-Lagrange equation. We illustrate our results using the scale Newton's equation which gives rise to a non-linear diffusion equation or a non-linear Schrödinger equation as asymptotic continuous models depending on the particular fractional scale regime which is considered.
Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing
2016-11-01
Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.
Mejias, Jorge F.; Murray, John D.; Kennedy, Henry; Wang, Xiao-Jing
2016-01-01
Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions. PMID:28138530
Slope-scale dynamic states of rockfalls
NASA Astrophysics Data System (ADS)
Agliardi, F.; Crosta, G. B.
2009-04-01
Rockfalls are common earth surface phenomena characterised by complex dynamics at the slope scale, depending on local block kinematics and slope geometry. We investigated the nature of this slope-scale dynamics by parametric 3D numerical modelling of rockfalls over synthetic slopes with different inclination, roughness and spatial resolution. Simulations were performed through an original code specifically designed for rockfall modeling, incorporating kinematic and hybrid algorithms with different damping functions available to model local energy loss by impact and pure rolling. Modelling results in terms of average velocity profiles suggest that three dynamic regimes (i.e. decelerating, steady-state and accelerating), previously recognized in the literature through laboratory experiments on granular flows, can set up at the slope scale depending on slope average inclination and roughness. Sharp changes in rock fall kinematics, including motion type and lateral dispersion of trajectories, are associated to the transition among different regimes. Associated threshold conditions, portrayed in "phase diagrams" as slope-roughness critical lines, were analysed depending on block size, impact/rebound angles, velocity and energy, and model spatial resolution. Motion in regime B (i.e. steady state) is governed by a slope-scale "viscous friction" with average velocity linearly related to the sine of slope inclination. This suggest an analogy between rockfall motion in regime B and newtonian flow, whereas in regime C (i.e. accelerating) an analogy with a dilatant flow was observed. Thus, although local behavior of single falling blocks is well described by rigid body dynamics, the slope scale dynamics of rockfalls seem to statistically approach that of granular media. Possible outcomes of these findings include a discussion of the transition from rockfall to granular flow, the evaluation of the reliability of predictive models, and the implementation of criteria for a preliminary evaluation of hazard assessment and countermeasure planning.
NASA Astrophysics Data System (ADS)
Tseng, Yu-Heng; Meneveau, Charles; Parlange, Marc B.
2004-11-01
Large Eddy Simulations (LES) of atmospheric boundary-layer air movement in urban environments are especially challenging due to complex ground topography. Typically in such applications, fairly coarse grids must be used where the subgrid-scale (SGS) model is expected to play a crucial role. A LES code using pseudo-spectral discretization in horizontal planes and second-order differencing in the vertical is implemented in conjunction with the immersed boundary method to incorporate complex ground topography, with the classic equilibrium log-law boundary condition in the new-wall region, and with several versions of the eddy-viscosity model: (1) the constant-coefficient Smagorinsky model, (2) the dynamic, scale-invariant Lagrangian model, and (3) the dynamic, scale-dependent Lagrangian model. Other planar-averaged type dynamic models are not suitable because spatial averaging is not possible without directions of statistical homogeneity. These SGS models are tested in LES of flow around a square cylinder and of flow over surface-mounted cubes. Effects on the mean flow are documented and found not to be major. Dynamic Lagrangian models give a physically more realistic SGS viscosity field, and in general, the scale-dependent Lagrangian model produces larger Smagorinsky coefficient than the scale-invariant one, leading to reduced distributions of resolved rms velocities especially in the boundary layers near the bluff bodies.
Blob-Spring Model for the Dynamics of Ring Polymer in Obstacle Environment
NASA Astrophysics Data System (ADS)
Lele, Ashish K.; Iyer, Balaji V. S.; Juvekar, Vinay A.
2008-07-01
The dynamical behavior of cyclic macromolecules in a fixed obstacle (FO) environment is very different than the behavior of linear chains in the same topological environment; while the latter relax by a snake-like reptational motion from their chain ends the former can relax only by contour length fluctuations since they are endless. Duke, Obukhov and Rubinstein proposed a scaling model (the DOR model) to interpret the dynamical scaling exponents shown by Monte Carlo simulations of rings in a FO environment. We present a model (blob-spring model) to describe the dynamics of flexible and non-concatenated ring polymer in FO environment based on a theoretical formulation developed for the dynamics of an unentangled fractal polymer. We argue that the perpetual evolution of ring perimeter by the motion of contour segments results in an extra frictional load. Our model predicts self-similar dynamics with scaling exponents for the molecular weight dependence of diffusion coefficient and relaxation times that are in agreement with the scaling model proposed by Obukhov et al.
Disruption of sheet-like structures in Alfvénic turbulence by magnetic reconnection
NASA Astrophysics Data System (ADS)
Mallet, A.; Schekochihin, A. A.; Chandran, B. D. G.
2017-07-01
We propose a mechanism whereby the intense, sheet-like structures naturally formed by dynamically aligning Alfvénic turbulence are destroyed by magnetic reconnection at a scale \\hat{λ }_D, larger than the dissipation scale predicted by models of intermittent, dynamically aligning turbulence. The reconnection process proceeds in several stages: first, a linear tearing mode with N magnetic islands grows and saturates, and then the X-points between these islands collapse into secondary current sheets, which then reconnect until the original structure is destroyed. This effectively imposes an upper limit on the anisotropy of the structures within the perpendicular plane, which means that at scale \\hat{λ }_D the turbulent dynamics change: at scales larger than \\hat{λ }_D, the turbulence exhibits scale-dependent dynamic alignment and a spectral index approximately equal to -3/2, while at scales smaller than \\hat{λ }_D, the turbulent structures undergo a succession of disruptions due to reconnection, limiting dynamic alignment, steepening the effective spectral index and changing the final dissipation scale. The scaling of \\hat{λ }_D with the Lundquist (magnetic Reynolds) number S_{L_\\perp } depends on the order of the statistics being considered, and on the specific model of intermittency; the transition between the two regimes in the energy spectrum is predicted at approximately \\hat{λ }_D˜ S_{L_\\perp }^{-0.6}. The spectral index below \\hat{λ }_D is bounded between -5/3 and -2.3. The final dissipation scale is at \\hat{λ }_{η ,∞}˜ S_{L_\\perp }^{-3/4}, the same as the Kolmogorov scale arising in theories of turbulence that do not involve scale-dependent dynamic alignment.
Quantum critical point revisited by dynamical mean-field theory
NASA Astrophysics Data System (ADS)
Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.
2017-03-01
Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. We use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. By comparing with the calculations based on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.
Quantum critical point revisited by dynamical mean-field theory
Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.
2017-03-31
Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. We characterize the QCP by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. Here, we use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. Furthermore, by comparing with the calculations basedmore » on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.« less
Irreversible opinion spreading on scale-free networks
NASA Astrophysics Data System (ADS)
Candia, Julián
2007-02-01
We study the dynamical and critical behavior of a model for irreversible opinion spreading on Barabási-Albert (BA) scale-free networks by performing extensive Monte Carlo simulations. The opinion spreading within an inhomogeneous society is investigated by means of the magnetic Eden model, a nonequilibrium kinetic model for the growth of binary mixtures in contact with a thermal bath. The deposition dynamics, which is studied as a function of the degree of the occupied sites, shows evidence for the leading role played by hubs in the growth process. Systems of finite size grow either ordered or disordered, depending on the temperature. By means of standard finite-size scaling procedures, the effective order-disorder phase transitions are found to persist in the thermodynamic limit. This critical behavior, however, is absent in related equilibrium spin systems such as the Ising model on BA scale-free networks, which in the thermodynamic limit only displays a ferromagnetic phase. The dependence of these results on the degree exponent is also discussed for the case of uncorrelated scale-free networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei M.
Dynamical mean-field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. We characterize the QCP by a universal scaling form of the self-energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low-energy kink and the high-energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high-energy antiferromagnetic paramagnons. Here, we use the frequency-dependent four-point correlation function of spin operators to calculate the momentum-dependent correction to the electron self-energy. Furthermore, by comparing with the calculations basedmore » on the spin-fermion model, our results indicate the frequency dependence of the quasiparticle-paramagnon vertices is an important factor to capture the momentum dependence in quasiparticle scattering.« less
NASA Technical Reports Server (NTRS)
Ivanco, Thomas G.
2013-01-01
NASA Langley Research Center's Transonic Dynamics Tunnel (TDT) is the world's most capable aeroelastic test facility. Its large size, transonic speed range, variable pressure capability, and use of either air or R-134a heavy gas as a test medium enable unparalleled manipulation of flow-dependent scaling quantities. Matching these scaling quantities enables dynamic similitude of a full-scale vehicle with a sub-scale model, a requirement for proper characterization of any dynamic phenomenon, and many static elastic phenomena. Select scaling parameters are presented in order to quantify the scaling advantages of TDT and the consequence of testing in other facilities. In addition to dynamic testing, the TDT is uniquely well-suited for high risk testing or for those tests that require unusual model mount or support systems. Examples of recently conducted dynamic tests requiring unusual model support are presented. In addition to its unique dynamic test capabilities, the TDT is also evaluated in its capability to conduct aerodynamic performance tests as a result of its flow quality. Results of flow quality studies and a comparison to a many other transonic facilities are presented. Finally, the ability of the TDT to support future NASA research thrusts and likely vehicle designs is discussed.
Optogenetic stimulation of a meso-scale human cortical model
NASA Astrophysics Data System (ADS)
Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi
2015-03-01
Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.
Quantum Critical Point revisited by the Dynamical Mean Field Theory
NASA Astrophysics Data System (ADS)
Xu, Wenhu; Kotliar, Gabriel; Tsvelik, Alexei
Dynamical mean field theory is used to study the quantum critical point (QCP) in the doped Hubbard model on a square lattice. The QCP is characterized by a universal scaling form of the self energy and a spin density wave instability at an incommensurate wave vector. The scaling form unifies the low energy kink and the high energy waterfall feature in the spectral function, while the spin dynamics includes both the critical incommensurate and high energy antiferromagnetic paramagnons. We use the frequency dependent four-point correlation function of spin operators to calculate the momentum dependent correction to the electron self energy. Our results reveal a substantial difference with the calculations based on the Spin-Fermion model which indicates that the frequency dependence of the the quasiparitcle-paramagnon vertices is an important factor. The authors are supported by Center for Computational Design of Functional Strongly Correlated Materials and Theoretical Spectroscopy under DOE Grant DE-FOA-0001276.
Homogenization techniques for population dynamics in strongly heterogeneous landscapes.
Yurk, Brian P; Cobbold, Christina A
2018-12-01
An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.
Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D
2015-01-01
There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.
Hübel, Niklas; Dahlem, Markus A.
2014-01-01
The classical Hodgkin-Huxley (HH) model neglects the time-dependence of ion concentrations in spiking dynamics. The dynamics is therefore limited to a time scale of milliseconds, which is determined by the membrane capacitance multiplied by the resistance of the ion channels, and by the gating time constants. We study slow dynamics in an extended HH framework that includes time-dependent ion concentrations, pumps, and buffers. Fluxes across the neuronal membrane change intra- and extracellular ion concentrations, whereby the latter can also change through contact to reservoirs in the surroundings. Ion gain and loss of the system is identified as a bifurcation parameter whose essential importance was not realized in earlier studies. Our systematic study of the bifurcation structure and thus the phase space structure helps to understand activation and inhibition of a new excitability in ion homeostasis which emerges in such extended models. Also modulatory mechanisms that regulate the spiking rate can be explained by bifurcations. The dynamics on three distinct slow times scales is determined by the cell volume-to-surface-area ratio and the membrane permeability (seconds), the buffer time constants (tens of seconds), and the slower backward buffering (minutes to hours). The modulatory dynamics and the newly emerging excitable dynamics corresponds to pathological conditions observed in epileptiform burst activity, and spreading depression in migraine aura and stroke, respectively. PMID:25474648
In-medium effects via nuclear stopping in asymmetric colliding nuclei
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaur, Mandeep
2016-05-06
The nuclear stopping is studied using isospin-dependent quantum molecular dynamics (IQMD) model in asymmetric colliding nuclei by varying mass asymmetry. The calculations have been done at incident energies varying between 50 and 400 MeV/nucleon for different impact parameters. We investigate the relative role of constant scaled and density-dependent scaled cross-sections. Our study reveals that nuclear stopping depends on the mass asymmetry, incident energy and impact parameter, however, it is independent of the way of scaling the cross-section.
Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.
Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad
2010-03-01
We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.
The length and time scales of water's glass transitions
NASA Astrophysics Data System (ADS)
Limmer, David T.
2014-06-01
Using a general model for the equilibrium dynamics of supercooled liquids, I compute from molecular properties the emergent length and time scales that govern the nonequilibrium relaxation behavior of amorphous ice prepared by rapid cooling. Upon cooling, the liquid water falls out of equilibrium whereby the temperature dependence of its relaxation time is predicted to change from super-Arrhenius to Arrhenius. A consequence of this crossover is that the location of the apparent glass transition temperature depends logarithmically on cooling rate. Accompanying vitrification is the emergence of a dynamical length-scale, the size of which depends on the cooling rate and varies between angstroms and tens of nanometers. While this protocol dependence clarifies a number of previous experimental observations for amorphous ice, the arguments are general and can be extended to other glass forming liquids.
The length and time scales of water's glass transitions.
Limmer, David T
2014-06-07
Using a general model for the equilibrium dynamics of supercooled liquids, I compute from molecular properties the emergent length and time scales that govern the nonequilibrium relaxation behavior of amorphous ice prepared by rapid cooling. Upon cooling, the liquid water falls out of equilibrium whereby the temperature dependence of its relaxation time is predicted to change from super-Arrhenius to Arrhenius. A consequence of this crossover is that the location of the apparent glass transition temperature depends logarithmically on cooling rate. Accompanying vitrification is the emergence of a dynamical length-scale, the size of which depends on the cooling rate and varies between angstroms and tens of nanometers. While this protocol dependence clarifies a number of previous experimental observations for amorphous ice, the arguments are general and can be extended to other glass forming liquids.
Multi-scale simulations of droplets in generic time-dependent flows
NASA Astrophysics Data System (ADS)
Milan, Felix; Biferale, Luca; Sbragaglia, Mauro; Toschi, Federico
2017-11-01
We study the deformation and dynamics of droplets in time-dependent flows using a diffuse interface model for two immiscible fluids. The numerical simulations are at first benchmarked against analytical results of steady droplet deformation, and further extended to the more interesting case of time-dependent flows. The results of these time-dependent numerical simulations are compared against analytical models available in the literature, which assume the droplet shape to be an ellipsoid at all times, with time-dependent major and minor axis. In particular we investigate the time-dependent deformation of a confined droplet in an oscillating Couette flow for the entire capillary range until droplet break-up. In this way these multi component simulations prove to be a useful tool to establish from ``first principles'' the dynamics of droplets in complex flows involving multiple scales. European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No 642069. & European Research Council under the European Community's Seventh Framework Program, ERC Grant Agreement No 339032.
Wavepacket dynamics in one-dimensional system with long-range correlated disorder
NASA Astrophysics Data System (ADS)
Yamada, Hiroaki S.
2018-03-01
We numerically investigate dynamical property in the one-dimensional tight-binding model with long-range correlated disorder having power spectrum 1 /fα (α: spectrum exponent) generated by Fourier filtering method. For relatively small α <αc (=2) time-dependence of mean square displacement (MSD) of the initially localized wavepacket shows ballistic spread and localizes as time elapses. It is shown that α-dependence of the dynamical localization length determined by the MSD exhibits a simple scaling law in the localization regime for the relatively weak disorder strength W. Furthermore, scaled MSD by the dynamical localization length almost obeys an universal function from the ballistic to the localization regime in the various combinations of the parameters α and W.
On the scale dependence of earthquake stress drop
NASA Astrophysics Data System (ADS)
Cocco, Massimo; Tinti, Elisa; Cirella, Antonella
2016-10-01
We discuss the debated issue of scale dependence in earthquake source mechanics with the goal of providing supporting evidence to foster the adoption of a coherent interpretative framework. We examine the heterogeneous distribution of source and constitutive parameters during individual ruptures and their scaling with earthquake size. We discuss evidence that slip, slip-weakening distance and breakdown work scale with seismic moment and are interpreted as scale dependent parameters. We integrate our estimates of earthquake stress drop, computed through a pseudo-dynamic approach, with many others available in the literature for both point sources and finite fault models. We obtain a picture of the earthquake stress drop scaling with seismic moment over an exceptional broad range of earthquake sizes (-8 < MW < 9). Our results confirm that stress drop values are scattered over three order of magnitude and emphasize the lack of corroborating evidence that stress drop scales with seismic moment. We discuss these results in terms of scale invariance of stress drop with source dimension to analyse the interpretation of this outcome in terms of self-similarity. Geophysicists are presently unable to provide physical explanations of dynamic self-similarity relying on deterministic descriptions of micro-scale processes. We conclude that the interpretation of the self-similar behaviour of stress drop scaling is strongly model dependent. We emphasize that it relies on a geometric description of source heterogeneity through the statistical properties of initial stress or fault-surface topography, in which only the latter is constrained by observations.
Dynamic model including piping acoustics of a centrifugal compression system
NASA Astrophysics Data System (ADS)
van Helvoirt, Jan; de Jager, Bram
2007-04-01
This paper deals with low-frequency pulsation phenomena in full-scale centrifugal compression systems associated with compressor surge. The Greitzer lumped parameter model is applied to describe the dynamic behavior of an industrial compressor test rig and experimental evidence is provided for the presence of acoustic pulsations in the compression system under study. It is argued that these acoustic phenomena are common for full-scale compression systems where pipe system dynamics have a significant influence on the overall system behavior. The main objective of this paper is to extend the basic compressor model in order to include the relevant pipe system dynamics. For this purpose a pipeline model is proposed, based on previous developments for fluid transmission lines. The connection of this model to the lumped parameter model is accomplished via the selection of appropriate boundary conditions. Validation results will be presented, showing a good agreement between simulation and measurement data. The results indicate that the damping of piping transients depends on the nominal, time-varying pressure and flow velocity. Therefore, model parameters are made dependent on the momentary pressure and a switching nonlinearity is introduced into the model to vary the acoustic damping as a function of flow velocity. These modifications have limited success and the results indicate that a more sophisticated model is required to fully describe all (nonlinear) acoustic effects. However, the very good qualitative results show that the model adequately combines compressor and pipe system dynamics. Therefore, the proposed model forms a step forward in the analysis and modeling of surge in full-scale centrifugal compression systems and opens the path for further developments in this field.
Influence of viscoelastic nature on the intermittent peel-front dynamics of adhesive tape
NASA Astrophysics Data System (ADS)
Kumar, Jagadish; Ananthakrishna, G.
2010-07-01
We investigate the influence of viscoelastic nature of the adhesive on the intermittent peel front dynamics by extending a recently introduced model for peeling of an adhesive tape. As time and rate-dependent deformation of the adhesives are measured in stationary conditions, a crucial step in incorporating the viscoelastic effects applicable to unstable intermittent peel dynamics is the introduction of a dynamization scheme that eliminates the explicit time dependence in terms of dynamical variables. We find contrasting influences of viscoelastic contribution in different regions of tape mass, roller inertia, and pull velocity. As the model acoustic energy dissipated depends on the nature of the peel front and its dynamical evolution, the combined effect of the roller inertia and pull velocity makes the acoustic energy noisier for small tape mass and low-pull velocity while it is burstlike for low-tape mass, intermediate values of the roller inertia and high-pull velocity. The changes are quantified by calculating the largest Lyapunov exponent and analyzing the statistical distributions of the amplitudes and durations of the model acoustic energy signals. Both single and two stage power-law distributions are observed. Scaling relations between the exponents are derived which show that the exponents corresponding to large values of event sizes and durations are completely determined by those for small values. The scaling relations are found to be satisfied in all cases studied. Interestingly, we find only five types of model acoustic emission signals among multitude of possibilities of the peel front configurations.
NASA Astrophysics Data System (ADS)
Hansen, U.; Rodgers, S.; Jensen, K. F.
2000-07-01
A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.
Multiscale System for Environmentally-Driven Infectious Disease with Threshold Control Strategy
NASA Astrophysics Data System (ADS)
Sun, Xiaodan; Xiao, Yanni
A multiscale system for environmentally-driven infectious disease is proposed, in which control measures at three different scales are implemented when the number of infected hosts exceeds a certain threshold. Our coupled model successfully describes the feedback mechanisms of between-host dynamics on within-host dynamics by employing one-scale variable guided enhancement of interventions on other scales. The modeling approach provides a novel idea of how to link the large-scale dynamics to small-scale dynamics. The dynamic behaviors of the multiscale system on two time-scales, i.e. fast system and slow system, are investigated. The slow system is further simplified to a two-dimensional Filippov system. For the Filippov system, we study the dynamics of its two subsystems (i.e. free-system and control-system), the sliding mode dynamics, the boundary equilibrium bifurcations, as well as the global behaviors. We prove that both subsystems may undergo backward bifurcations and the sliding domain exists. Meanwhile, it is possible that the pseudo-equilibrium exists and is globally stable, or the pseudo-equilibrium, the disease-free equilibrium and the real equilibrium are tri-stable, or the pseudo-equilibrium and the real equilibrium are bi-stable, or the pseudo-equilibrium and disease-free equilibrium are bi-stable, which depends on the threshold value and other parameter values. The global stability of the pseudo-equilibrium reveals that we may maintain the number of infected hosts at a previously given value. Moreover, the bi-stability and tri-stability indicate that whether the number of infected individuals tends to zero or a previously given value or other positive values depends on the parameter values and the initial states of the system. These results highlight the challenges in the control of environmentally-driven infectious disease.
The family of anisotropically scaled equatorial waves
NASA Astrophysics Data System (ADS)
RamíRez GutiéRrez, Enver; da Silva Dias, Pedro Leite; Raupp, Carlos; Bonatti, Jose Paulo
2011-04-01
In the present work we introduce the family of anisotropic equatorial waves. This family corresponds to equatorial waves at intermediate states between the shallow water and the long wave approximation model. The new family is obtained by using anisotropic time/space scalings on the linearized, unforced and inviscid shallow water model. It is shown that the anisotropic equatorial waves tend to the solutions of the long wave model in one extreme and to the shallow water model solutions in the other extreme of the parameter dependency. Thus, the problem associated with the completeness of the long wave model solutions can be asymptotically addressed. The anisotropic dispersion relation is computed and, in addition to the typical dependency on the equivalent depth, meridional quantum number and zonal wavenumber, it also depends on the anisotropy between both zonal to meridional space and velocity scales as well as the fast to slow time scales ratio. For magnitudes of the scales compatible with those of the tropical region, both mixed Rossby-gravity and inertio-gravity waves are shifted to a moderately higher frequency and, consequently, not filtered out. This draws attention to the fact that, for completeness of the long wave like solutions, it is necessary to include both the anisotropic mixed Rossby-gravity and inertio-gravity waves. Furthermore, the connection of slow and fast manifolds (distinguishing feature of equatorial dynamics) is preserved, though modified for the equatorial anisotropy parameters used δ ∈ < 1]. New possibilities of horizontal and vertical scale nonlinear interactions are allowed. Thus, the anisotropic shallow water model is of fundamental importance for understanding multiscale atmosphere and ocean dynamics in the tropics.
Statistical Ensemble of Large Eddy Simulations
NASA Technical Reports Server (NTRS)
Carati, Daniele; Rogers, Michael M.; Wray, Alan A.; Mansour, Nagi N. (Technical Monitor)
2001-01-01
A statistical ensemble of large eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large scale velocity fields is used to propose an ensemble averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES's provides statistics of the large scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time developing plane wake. It is found that the results are almost independent of the number of LES's in the statistical ensemble provided that the ensemble contains at least 16 realizations.
NASA Astrophysics Data System (ADS)
Jing, R.; Lin, N.; Emanuel, K.; Vecchi, G. A.; Knutson, T. R.
2017-12-01
A Markov environment-dependent hurricane intensity model (MeHiM) is developed to simulate the climatology of hurricane intensity given the surrounding large-scale environment. The model considers three unobserved discrete states representing respectively storm's slow, moderate, and rapid intensification (and deintensification). Each state is associated with a probability distribution of intensity change. The storm's movement from one state to another, regarded as a Markov chain, is described by a transition probability matrix. The initial state is estimated with a Bayesian approach. All three model components (initial intensity, state transition, and intensity change) are dependent on environmental variables including potential intensity, vertical wind shear, midlevel relative humidity, and ocean mixing characteristics. This dependent Markov model of hurricane intensity shows a significant improvement over previous statistical models (e.g., linear, nonlinear, and finite mixture models) in estimating the distributions of 6-h and 24-h intensity change, lifetime maximum intensity, and landfall intensity, etc. Here we compare MeHiM with various dynamical models, including a global climate model [High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR)], a regional hurricane model (Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model), and a simplified hurricane dynamic model [Coupled Hurricane Intensity Prediction System (CHIPS)] and its newly developed fast simulator. The MeHiM developed based on the reanalysis data is applied to estimate the intensity of simulated storms to compare with the dynamical-model predictions under the current climate. The dependences of hurricanes on the environment under current and future projected climates in the various models will also be compared statistically.
Tropical precipitation extremes: Response to SST-induced warming in aquaplanet simulations
NASA Astrophysics Data System (ADS)
Bhattacharya, Ritthik; Bordoni, Simona; Teixeira, João.
2017-04-01
Scaling of tropical precipitation extremes in response to warming is studied in aquaplanet experiments using the global Weather Research and Forecasting (WRF) model. We show how the scaling of precipitation extremes is highly sensitive to spatial and temporal averaging: while instantaneous grid point extreme precipitation scales more strongly than the percentage increase (˜7% K-1) predicted by the Clausius-Clapeyron (CC) relationship, extremes for zonally and temporally averaged precipitation follow a slight sub-CC scaling, in agreement with results from Climate Model Intercomparison Project (CMIP) models. The scaling depends crucially on the employed convection parameterization. This is particularly true when grid point instantaneous extremes are considered. These results highlight how understanding the response of precipitation extremes to warming requires consideration of dynamic changes in addition to the thermodynamic response. Changes in grid-scale precipitation, unlike those in convective-scale precipitation, scale linearly with the resolved flow. Hence, dynamic changes include changes in both large-scale and convective-scale motions.
The Thick Level-Set model for dynamic fragmentation
Stershic, Andrew J.; Dolbow, John E.; Moës, Nicolas
2017-01-04
The Thick Level-Set (TLS) model is implemented to simulate brittle media undergoing dynamic fragmentation. This non-local model is discretized by the finite element method with damage represented as a continuous field over the domain. A level-set function defines the extent and severity of damage, and a length scale is introduced to limit the damage gradient. Numerical studies in one dimension demonstrate that the proposed method reproduces the rate-dependent energy dissipation and fragment length observations from analytical, numerical, and experimental approaches. In conclusion, additional studies emphasize the importance of appropriate bulk constitutive models and sufficient spatial resolution of the length scale.
The spatial scale for cisco recruitment dynamics in Lake Superior during 1978-2007
Rook, Benjamin J.; Hansen, Michael J.; Gorman, Owen T.
2012-01-01
The cisco Coregonus artedi was once the most abundant fish species in the Great Lakes, but currently cisco populations are greatly reduced and management agencies are attempting to restore the species throughout the basin. To increase understanding of the spatial scale at which density‐independent and density‐dependent factors influence cisco recruitment dynamics in the Great Lakes, we used a Ricker stock–recruitment model to identify and quantify the appropriate spatial scale for modeling age‐1 cisco recruitment dynamics in Lake Superior. We found that the recruitment variation of ciscoes in Lake Superior was best described by a five‐parameter regional model with separate stock–recruitment relationships for the western, southern, eastern, and northern regions. The spatial scale for modeling was about 260 km (range = 230–290 km). We also found that the density‐independent recruitment rate and the rate of compensatory density dependence varied among regions at different rates. The density‐independent recruitment rate was constant among regions (3.6 age‐1 recruits/spawner), whereas the rate of compensatory density dependence varied 16‐fold among regions (range = −0.2 to −2.9/spawner). Finally, we found that peak recruitment and the spawning stock size that produced peak recruitment varied among regions. Both peak recruitment (0.5–7.1 age‐1 recruits/ha) and the spawning stock size that produced peak recruitment (0.3–5.3 spawners/ha) varied 16‐fold among regions. Our findings support the hypothesis that the factors driving cisco recruitment operate within four different regions of Lake Superior, suggest that large‐scale abiotic factors are more important than small‐scale biotic factors in influencing cisco recruitment, and suggest that fishery managers throughout Lake Superior and the entire Great Lakes basin should address cisco restoration and management efforts on a regional scale in each lake.
NASA Astrophysics Data System (ADS)
Keys, Aaron
2013-03-01
Using molecular simulation and coarse-grained lattice models, we study the dynamics of glass-forming liquids above and below the glass transition temperature. In the supercooled regime, we study the structure, statistics, and dynamics of excitations responsible for structural relaxation for several atomistic models of glass-formers. Excitations (or soft spots) are detected in terms of persistent particle displacements. At supercooled conditions, we find that excitations are associated with correlated particle motions that are sparse and localized, and the statistics and dynamics of these excitations are facilitated and hierarchical. Excitations at one point in space facilitate the birth and death of excitations at neighboring locations, and space-time excitation structures are microcosms of heterogeneous dynamics at larger scales. Excitation-energy scales grow logarithmically with the characteristic size of the excitation, giving structural-relaxation times that can be predicted quantitatively from dynamics at short time scales. We demonstrate that these same physical principles govern the dynamics of glass-forming systems driven out-of-equilibrium by time-dependent protocols. For a system cooled and re-heated through the glass transition, non-equilibrium response functions, such as heat capacities, are notably asymmetric in time, and the response to melting a glass depends markedly on the cooling protocol by which the glass was formed. We introduce a quantitative description of this behavior based on the East model, with parameters determined from reversible transport data, that agrees well with irreversible differential scanning calorimetry. We find that the observed hysteresis and asymmetric response is a signature of an underlying dynamical transition between equilibrium melts with no trivial spatial correlations and non-equilibrium glasses with correlation lengths that are both large and dependent upon the rate at which the glass is prepared. The correlation length corresponds to the size of amorphous domains bounded by excitations that remain frozen on the observation time scale, thus forming stripes when viewed in space and time. We elucidate properties of the striped phase and show that glasses of this type, traditionally prepared through cooling, can be considered a finite-size realization of the inactive phase formed by the s-ensemble in the space-time thermodynamic limit.
Particle dynamics in a viscously decaying cat's eye: The effect of finite Schmidt numbers
NASA Astrophysics Data System (ADS)
Newton, P. K.; Meiburg, Eckart
1991-05-01
The dynamics and mixing of passive marker particles for the model problem of a decaying cat's eye flow is studied. The flow field corresponds to Stuart's one-parameter family of solutions [J. Fluid Mech. 29, 417 (1967)]. It is time dependent as a result of viscosity, which is modeled by allowing the free parameter to depend on time according to the self-similar solution of the Navier-Stokes equations for an isolated point vortex. Particle diffusion is numerically simulated by a random walk model. While earlier work had shown that, for small values of time over Reynolds number t/Re≪1, the interval length characterizing the formation of lobes of fluid escaping from the cat's eye scales as Re-1/2, the present study shows that, for the case of diffusive effects and t/Pe≪1, the scaling follows Pe-1/4. A simple argument, taking into account streamline convergence and divergence in different parts of the flow field, explains the Pe-1/4 scaling.
Large fluctuations in anti-coordination games on scale-free graphs
NASA Astrophysics Data System (ADS)
Sabsovich, Daniel; Mobilia, Mauro; Assaf, Michael
2017-05-01
We study the influence of the complex topology of scale-free graphs on the dynamics of anti-coordination games (e.g. snowdrift games). These reference models are characterized by the coexistence (evolutionary stable mixed strategy) of two competing species, say ‘cooperators’ and ‘defectors’, and, in finite systems, by metastability and large-fluctuation-driven fixation. In this work, we use extensive computer simulations and an effective diffusion approximation (in the weak selection limit) to determine under which circumstances, depending on the individual-based update rules, the topology drastically affects the long-time behavior of anti-coordination games. In particular, we compute the variance of the number of cooperators in the metastable state and the mean fixation time when the dynamics is implemented according to the voter model (death-first/birth-second process) and the link dynamics (birth/death or death/birth at random). For the voter update rule, we show that the scale-free topology effectively renormalizes the population size and as a result the statistics of observables depend on the network’s degree distribution. In contrast, such a renormalization does not occur with the link dynamics update rule and we recover the same behavior as on complete graphs.
Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.
Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha
2017-09-01
Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.
Non-local damage rheology and size effect
NASA Astrophysics Data System (ADS)
Lyakhovsky, V.
2011-12-01
We study scaling relations controlling the onset of transiently-accelerating fracturing and transition to dynamic rupture propagation in a non-local damage rheology model. The size effect is caused principally by growth of a fracture process zone, involving stress redistribution and energy release associated with a large fracture. This implies that rupture nucleation and transition to dynamic propagation are inherently scale-dependent processes. Linear elastic fracture mechanics (LEFM) and local damage mechanics are formulated in terms of dimensionless strain components and thus do not allow introducing any space scaling, except linear relations between fracture length and displacements. Generalization of Weibull theory provides scaling relations between stress and crack length at the onset of failure. A powerful extension of the LEFM formulation is the displacement-weakening model which postulates that yielding is complete when the crack wall displacement exceeds some critical value or slip-weakening distance Dc at which a transition to kinetic friction is complete. Scaling relations controlling the transition to dynamic rupture propagation in slip-weakening formulation are widely accepted in earthquake physics. Strong micro-crack interaction in a process zone may be accounted for by adopting either integral or gradient type non-local damage models. We formulate a gradient-type model with free energy depending on the scalar damage parameter and its spatial derivative. The damage-gradient term leads to structural stresses in the constitutive stress-strain relations and a damage diffusion term in the kinetic equation for damage evolution. The damage diffusion eliminates the singular localization predicted by local models. The finite width of the localization zone provides a fundamental length scale that allows numerical simulations with the model to achieve the continuum limit. A diffusive term in the damage evolution gives rise to additional damage diffusive time scale associated with the structural length scale. The ratio between two time scales associated with damage accumulation and diffusion, the damage diffusivity ratio, reflects the role of the diffusion-controlled delocalization. We demonstrate that localized fracturing occurs at the damage diffusivity ratio below certain critical value leading to a linear scaling between stress and crack length compatible with size effect for failures at crack initiation. A subseuqent quasi-static fracture growth is self-similar with increasing size of the process zone proportional to the fracture length. At a certain stage, controlled by dynamic weakening, the self-similarity breaks down and crack velocity significantly deviates from that predicted by the quasi-static regime, the size of the process zone decreases, and the rate of crack growth ceases to be controlled by the rate of damage increase. Furthermore, the crack speed approaches that predicted by the elasto-dynamic equation. The non-local damage rheology model predicts that the nucleation size of the dynamic fracture scales with fault zone thickness distance of the stress interraction.
Dynamics and Steady States in Excitable Mobile Agent Systems
NASA Astrophysics Data System (ADS)
Peruani, Fernando; Sibona, Gustavo J.
2008-04-01
We study the spreading of excitations in 2D systems of mobile agents where the excitation is transmitted when a quiescent agent keeps contact with an excited one during a nonvanishing time. We show that the steady states strongly depend on the spatial agent dynamics. Moreover, the coupling between exposition time (ω) and agent-agent contact rate (CR) becomes crucial to understand the excitation dynamics, which exhibits three regimes with CR: no excitation for low CR, an excited regime in which the number of quiescent agents (S) is inversely proportional to CR, and, for high CR, a novel third regime, model dependent, where S scales with an exponent ξ-1, with ξ being the scaling exponent of ω with CR.
Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.
Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo
2015-12-15
Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.
Nonequilibrium simulations of model ionomers in an oscillating electric field
Ting, Christina L.; Sorensen-Unruh, Karen E.; Stevens, Mark J.; ...
2016-07-25
Here, we perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understoodmore » by comparison with relevant time scales in the systems, obtained from independent calculations.« less
Nonequilibrium simulations of model ionomers in an oscillating electric field
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ting, Christina L.; Sorensen-Unruh, Karen E.; Stevens, Mark J.
Here, we perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understoodmore » by comparison with relevant time scales in the systems, obtained from independent calculations.« less
Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M
2007-09-15
Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.
Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation
Balaguer-Ballester, Emili; Clark, Nicholas R.; Coath, Martin; Krumbholz, Katrin; Denham, Susan L.
2009-01-01
Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing. PMID:19266015
Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.
Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C
2017-07-01
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Understory plant biomass dynamics of prescribed burned Pinus palustris stands
C.A. Gonzalez-Benecke; L.J. Samuelson; T.A. Stokes; W.P. Cropper Jr; T.A. Martin; K.H. Johnsen
2015-01-01
Longleaf pine (Pinus palustris Mill.) forests are characterized by unusually high understory plant species diversity, but models describing understory ground cover biomass, and hence fuel load dynamics, are scarce for this ï¬re-dependent ecosystem. Only coarse scale estimates, being restricted on accuracy and geographical extrapolation,...
Accelerating universe with time variation of G and Λ
NASA Astrophysics Data System (ADS)
Darabi, F.
2012-03-01
We study a gravitational model in which scale transformations play the key role in obtaining dynamical G and Λ. We take a non-scale invariant gravitational action with a cosmological constant and a gravitational coupling constant. Then, by a scale transformation, through a dilaton field, we obtain a new action containing cosmological and gravitational coupling terms which are dynamically dependent on the dilaton field with Higgs type potential. The vacuum expectation value of this dilaton field, through spontaneous symmetry breaking on the basis of anthropic principle, determines the time variations of G and Λ. The relevance of these time variations to the current acceleration of the universe, coincidence problem, Mach's cosmological coincidence and those problems of standard cosmology addressed by inflationary models, are discussed. The current acceleration of the universe is shown to be a result of phase transition from radiation toward matter dominated eras. No real coincidence problem between matter and vacuum energy densities exists in this model and this apparent coincidence together with Mach's cosmological coincidence are shown to be simple consequences of a new kind of scale factor dependence of the energy momentum density as ρ˜ a -4. This model also provides the possibility for a super fast expansion of the scale factor at very early universe by introducing exotic type matter like cosmic strings.
Neutron star dynamics under time-dependent external torques
NASA Astrophysics Data System (ADS)
Gügercinoǧlu, Erbil; Alpar, M. Ali
2017-11-01
The two-component model describes neutron star dynamics incorporating the response of the superfluid interior. Conventional solutions and applications involve constant external torques, as appropriate for radio pulsars on dynamical time-scales. We present the general solution of two-component dynamics under arbitrary time-dependent external torques, with internal torques that are linear in the rotation rates, or with the extremely non-linear internal torques due to vortex creep. The two-component model incorporating the response of linear or non-linear internal torques can now be applied not only to radio pulsars but also to magnetars and to neutron stars in binary systems, with strong observed variability and noise in the spin-down or spin-up rates. Our results allow the extraction of the time-dependent external torques from the observed spin-down (or spin-up) time series, \\dot{Ω }(t). Applications are discussed.
Coarse-graining to the meso and continuum scales with molecular-dynamics-like models
NASA Astrophysics Data System (ADS)
Plimpton, Steve
Many engineering-scale problems that industry or the national labs try to address with particle-based simulations occur at length and time scales well beyond the most optimistic hopes of traditional coarse-graining methods for molecular dynamics (MD), which typically start at the atomic scale and build upward. However classical MD can be viewed as an engine for simulating particles at literally any length or time scale, depending on the models used for individual particles and their interactions. To illustrate I'll highlight several coarse-grained (CG) materials models, some of which are likely familiar to molecular-scale modelers, but others probably not. These include models for water droplet freezing on surfaces, dissipative particle dynamics (DPD) models of explosives where particles have internal state, CG models of nano or colloidal particles in solution, models for aspherical particles, Peridynamics models for fracture, and models of granular materials at the scale of industrial processing. All of these can be implemented as MD-style models for either soft or hard materials; in fact they are all part of our LAMMPS MD package, added either by our group or contributed by collaborators. Unlike most all-atom MD simulations, CG simulations at these scales often involve highly non-uniform particle densities. So I'll also discuss a load-balancing method we've implemented for these kinds of models, which can improve parallel efficiencies. From the physics point-of-view, these models may be viewed as non-traditional or ad hoc. But because they are MD-style simulations, there's an opportunity for physicists to add statistical mechanics rigor to individual models. Or, in keeping with a theme of this session, to devise methods that more accurately bridge models from one scale to the next.
Robust control of combustion instabilities
NASA Astrophysics Data System (ADS)
Hong, Boe-Shong
Several interactive dynamical subsystems, each of which has its own time-scale and physical significance, are decomposed to build a feedback-controlled combustion- fluid robust dynamics. On the fast-time scale, the phenomenon of combustion instability is corresponding to the internal feedback of two subsystems: acoustic dynamics and flame dynamics, which are parametrically dependent on the slow-time-scale mean-flow dynamics controlled for global performance by a mean-flow controller. This dissertation constructs such a control system, through modeling, analysis and synthesis, to deal with model uncertainties, environmental noises and time- varying mean-flow operation. Conservation law is decomposed as fast-time acoustic dynamics and slow-time mean-flow dynamics, served for synthesizing LPV (linear parameter varying)- L2-gain robust control law, in which a robust observer is embedded for estimating and controlling the internal status, while achieving trade- offs among robustness, performances and operation. The robust controller is formulated as two LPV-type Linear Matrix Inequalities (LMIs), whose numerical solver is developed by finite-element method. Some important issues related to physical understanding and engineering application are discussed in simulated results of the control system.
The Resilience of Coral Reefs Across a Hierarchy of Spatial and Temporal scales
NASA Astrophysics Data System (ADS)
Mumby, P. J.
2016-02-01
Resilience is a dynamical property of ecosystems that integrates processes of recovery, disturbance and internal dynamics, including reinforcing feedbacks. As such, resilience is a useful framework to consider how ecosystems respond to multiple drivers occurring over multiple scales. Many insights have emerged recently including the way in which stressors can combine synergistically to deplete resilience. However, while recent advances have mapped resilience across seascapes, most studies have not captured emergent spatial dependencies and dynamics across the seascape (e.g., independent box models are run across the seascape in isolation). Here, we explore the dynamics that emerge when the seascape is `wired up' using data on larval dispersal, thereby giving a fully spatially-realistic model. We then consider how dynamics change across even larger, biogeographic scales, posing the question, `are there robust and global "rules of thumb" for the resilience of a single ecosystem?'. Answers to this question will help managers tailor their interventions and research needs for their own jurisdiction.
Double dynamic scaling in human communication dynamics
NASA Astrophysics Data System (ADS)
Wang, Shengfeng; Feng, Xin; Wu, Ye; Xiao, Jinhua
2017-05-01
In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.
Rate and state dependent processes in sea ice deformation
NASA Astrophysics Data System (ADS)
Sammonds, P. R.; Scourfield, S.; Lishman, B.
2014-12-01
Realistic models of sea ice processes and properties are needed to assess sea ice thickness, extent and concentration and, when run within GCMs, provide prediction of climate change. The deformation of sea ice is a key control on the Arctic Ocean dynamics. But the deformation of sea ice is dependent not only on the rate of the processes involved but also the state of the sea ice and particular in terms of its evolution with time and temperature. Shear deformation is a dominant mechanism from the scale of basin-scale shear lineaments, through floe-floe interaction to block sliding in ice ridges. The shear deformation will not only depend on the speed of movement of ice surfaces but also the degree that the surfaces have bonded during thermal consolidation and compaction. Frictional resistance to sliding can vary by more than two orders of magnitude depending on the state of the interface. But this in turn is dependent upon both imposed conditions and sea ice properties such as size distribution of interfacial broken ice, angularity, porosity, salinity, etc. We review experimental results in sea ice mechanics from mid-scale experiments, conducted in the Hamburg model ship ice tank, simulating sea ice floe motion and interaction and compare these with laboratory experiments on ice friction done in direct shear from which a rate and state constitutive relation for shear deformation is derived. Finally we apply this to field measurement of sea ice friction made during experiments in the Barents Sea to assess the other environmental factors, the state terms, that need to be modelled in order to up-scale to Arctic Ocean-scale dynamics.
Spreading dynamics of a SIQRS epidemic model on scale-free networks
NASA Astrophysics Data System (ADS)
Li, Tao; Wang, Yuanmei; Guan, Zhi-Hong
2014-03-01
In order to investigate the influence of heterogeneity of the underlying networks and quarantine strategy on epidemic spreading, a SIQRS epidemic model on the scale-free networks is presented. Using the mean field theory the spreading dynamics of the virus is analyzed. The spreading critical threshold and equilibria are derived. Theoretical results indicate that the critical threshold value is significantly dependent on the topology of the underlying networks and quarantine rate. The existence of equilibria is determined by threshold value. The stability of disease-free equilibrium and the permanence of the disease are proved. Numerical simulations confirmed the analytical results.
Prunescu, Remus Mihail; Sin, Gürkan
2013-12-01
The enzymatic hydrolysis process is one of the key steps in second generation biofuel production. After being thermally pretreated, the lignocellulosic material is liquefied by enzymes prior to fermentation. The scope of this paper is to evaluate a dynamic model of the hydrolysis process on a demonstration scale reactor. The following novel features are included: the application of the Convection-Diffusion-Reaction equation to a hydrolysis reactor to assess transport and mixing effects; the extension of a competitive kinetic model with enzymatic pH dependency and hemicellulose hydrolysis; a comprehensive pH model; and viscosity estimations during the course of reaction. The model is evaluated against real data extracted from a demonstration scale biorefinery throughout several days of operation. All measurements are within predictions uncertainty and, therefore, the model constitutes a valuable tool to support process optimization, performance monitoring, diagnosis and process control at full-scale studies. Copyright © 2013 Elsevier Ltd. All rights reserved.
Dynamics of a neural system with a multiscale architecture
Breakspear, Michael; Stam, Cornelis J
2005-01-01
The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448
Modeling fluvial incision and transient landscape evolution: Influence of dynamic channel adjustment
NASA Astrophysics Data System (ADS)
Attal, M.; Tucker, G. E.; Whittaker, A. C.; Cowie, P. A.; Roberts, G. P.
2008-09-01
Channel geometry exerts a fundamental control on fluvial processes. Recent work has shown that bedrock channel width depends on a number of parameters, including channel slope, and is not solely a function of drainage area as is commonly assumed. The present work represents the first attempt to investigate the consequences of dynamic, gradient-sensitive channel adjustment for drainage-basin evolution. We use the Channel-Hillslope Integrated Landscape Development (CHILD) model to analyze the response of a catchment to a given tectonic perturbation, using, as a template, the topography of a well-documented catchment in the footwall of an active normal fault in the Apennines (Italy) that is known to be undergoing a transient response to tectonic forcing. We show that the observed transient response can be reproduced to first order with a simple detachment-limited fluvial incision law. Transient landscape is characterized by gentler gradients and a shorter response time when dynamic channel adjustment is allowed. The differences in predicted channel geometry between the static case (width dependent solely on upstream area) and dynamic case (width dependent on both drainage area and channel slope) lead to contrasting landscape morphologies when integrated at the scale of a whole catchment, particularly in presence of strong tilting and/or pronounced slip-rate acceleration. Our results emphasize the importance of channel width in controlling fluvial processes and landscape evolution. They stress the need for using a dynamic hydraulic scaling law when modeling landscape evolution, particularly when the relative uplift field is nonuniform.
Entanglement dynamics following a sudden quench: An exact solution
NASA Astrophysics Data System (ADS)
Ghosh, Supriyo; Gupta, Kumar S.; Srivastava, Shashi C. L.
2017-12-01
We present an exact and fully analytical treatment of the entanglement dynamics for an isolated system of N coupled oscillators following a sudden quench of the system parameters. The system is analyzed using the solutions of the time-dependent Schrodinger's equation, which are obtained by solving the corresponding nonlinear Ermakov equations. The entanglement entropies exhibit a multi-oscillatory behaviour, where the number of dynamically generated time scales increases with N. The harmonic chains exhibit entanglement revival and for larger values of N (> 10), we find near-critical logarithmic scaling for the entanglement entropy, which is modulated by a time-dependent factor. The N = 2 case is equivalent to the two-site Bose-Hubbard model in the tunneling regime, which is amenable to empirical realization in cold-atom systems.
LONG-TERM PROJECTIONS OF EASTERN OYSTER POPULATIONS UNDER VARIOUS MANAGEMENT SCENARIOS
Time series of fishery-dependent and fishery-independent data were used to parameterize a model of oyster population dynamics for Maryland's Chesapeake Bay. Model parameters are (1) fishing mortality, estimated from differences between predicted and reported landings scaled to a ...
Range expansion through fragmented landscapes under a variable climate
Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J
2013-01-01
Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124
NASA Astrophysics Data System (ADS)
Tiwary, C. S.; Chakraborty, S.; Mahapatra, D. R.; Chattopadhyay, K.
2014-05-01
This paper attempts to gain an understanding of the effect of lamellar length scale on the mechanical properties of two-phase metal-intermetallic eutectic structure. We first develop a molecular dynamics model for the in-situ grown eutectic interface followed by a model of deformation of Al-Al2Cu lamellar eutectic. Leveraging the insights obtained from the simulation on the behaviour of dislocations at different length scales of the eutectic, we present and explain the experimental results on Al-Al2Cu eutectic with various different lamellar spacing. The physics behind the mechanism is further quantified with help of atomic level energy model for different length scale as well as different strain. An atomic level energy partitioning of the lamellae and the interface regions reveals that the energy of the lamellae core are accumulated more due to dislocations irrespective of the length-scale. Whereas the energy of the interface is accumulated more due to dislocations when the length-scale is smaller, but the trend is reversed when the length-scale is large beyond a critical size of about 80 nm.
Hyper-scaling relations in the conformal window from dynamic AdS/QCD
NASA Astrophysics Data System (ADS)
Evans, Nick; Scott, Marc
2014-09-01
Dynamic AdS/QCD is a holographic model of strongly coupled gauge theories with the dynamics included through the running anomalous dimension of the quark bilinear, γ. We apply it to describe the physics of massive quarks in the conformal window of SU(Nc) gauge theories with Nf fundamental flavors, assuming the perturbative two-loop running for γ. We show that to find regular, holographic renormalization group flows in the infrared, the decoupling of the quark flavors at the scale of the mass is important, and enact it through suitable boundary conditions when the flavors become on shell. We can then compute the quark condensate and the mesonic spectrum (Mρ,Mπ,Mσ) and decay constants. We compute their scaling dependence on the quark mass for a number of examples. The model matches perturbative expectations for large quark mass and naïve dimensional analysis (including the anomalous dimensions) for small quark mass. The model allows study of the intermediate regime where there is an additional scale from the running of the coupling, and we present results for the deviation of scalings from assuming only the single scale of the mass.
Effect of double layers on magnetosphere-ionosphere coupling
NASA Technical Reports Server (NTRS)
Lysak, Robert L.; Hudson, Mary K.
1987-01-01
The Earth's auroral zone contains dynamic processes occurring on scales from the length of an auroral zone field line which characterizes Alfven wave propagation to the scale of microscopic processes which occur over a few Debye lengths. These processes interact in a time-dependent fashion since the current carried by the Alfven waves can excite microscopic turbulence which can in turn provide dissipation of the Alfven wave energy. This review will first describe the dynamic aspects of auroral current structures with emphasis on consequences for models of microscopic turbulence. A number of models of microscopic turbulence will be introduced into a large-scale model of Alfven wave propagation to determine the effect of various models on the overall structure of auroral currents. In particular, the effects of a double layer electric field which scales with the plasma temperature and Debye length is compared with the effect of anomalous resistivity due to electrostatic ion cyclotron turbulence in which the electric field scales with the magnetic field strength. It is found that the double layer model is less diffusive than in the resistive model leading to the possibility of narrow, intense current structures.
Critical Fluctuations in Cortical Models Near Instability
Aburn, Matthew J.; Holmes, C. A.; Roberts, James A.; Boonstra, Tjeerd W.; Breakspear, Michael
2012-01-01
Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human electroencephalography (EEG), however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where non-linearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power law scaling, and bistable switching have been suggested as generic indicators of the approach to bifurcation in non-linear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen–Rit model) of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations. PMID:22952464
Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L
2017-08-15
The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.
SPM investigation of local aging effects in glassy polymers
NASA Astrophysics Data System (ADS)
Crider, Philip
2005-03-01
We investigate the cooperative and heterogeneous nature of glassy dynamics by nanometer-scale probing in a glassy polymer, Polyvinyl-Actetate (PVAc), with a Scanning Force Microscope (SFM). Using ultra-high-vacuum (UHV) Scanning Capacitive Force Microscopy techniques, nanometer-scale capacitive responses are probed. Dielectric relaxation near the glass transition is investigated, and scanning capabilities are utilized to analyze spatial response on a nanometer scale. The results of these studies may yield insight into the understanding of temperature-dependent cooperative length scales, local aging properties, and energy landscape properties of evolving dipole clusters on a mesoscopic scale. Results are used to test the validity and relevance of current models of glassy dynamics.
Size-density scaling in protists and the links between consumer-resource interaction parameters.
DeLong, John P; Vasseur, David A
2012-11-01
Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
The role of fanatics in consensus formation
NASA Astrophysics Data System (ADS)
Gündüç, Semra
2015-08-01
A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.
Beyond Darcy's law: The role of phase topology and ganglion dynamics for two-fluid flow
Armstrong, Ryan T.; McClure, James E.; Berrill, Mark A.; ...
2016-10-27
Relative permeability quantifies the ease at which immiscible phases flow through porous rock and is one of the most well known constitutive relationships for petroleum engineers. It however exhibits troubling dependencies on experimental conditions and is not a unique function of phase saturation as commonly accepted in industry practices. The problem lies in the multi-scale nature of the problem where underlying disequilibrium processes create anomalous macroscopic behavior. Here we show that relative permeability rate dependencies are explained by ganglion dynamic flow. We utilize fast X-ray micro-tomography and pore-scale simulations to identify unique flow regimes during the fractional flow of immisciblemore » phases and quantify the contribution of ganglion flux to the overall flux of non-wetting phase. We anticipate our approach to be the starting point for the development of sophisticated multi-scale flow models that directly link pore-scale parameters to macro-scale behavior. Such models will have a major impact on how we recover hydrocarbons from the subsurface, store sequestered CO 2 in geological formations, and remove non-aqueous environmental hazards from the vadose zone.« less
Active Brownian agents with concentration-dependent chemotactic sensitivity.
Meyer, Marcel; Schimansky-Geier, Lutz; Romanczuk, Pawel
2014-02-01
We study a biologically motivated model of overdamped, autochemotactic Brownian agents with concentration-dependent chemotactic sensitivity. The agents in our model move stochastically and produce a chemical ligand at their current position. The ligand concentration obeys a reaction-diffusion equation and acts as a chemoattractant for the agents, which bias their motion towards higher concentrations of the dynamically altered chemical field. We explore the impact of concentration-dependent response to chemoattractant gradients on large-scale pattern formation, by deriving a coarse-grained macroscopic description of the individual-based model, and compare the conditions for emergence of inhomogeneous solutions for different variants of the chemotactic sensitivity. We focus primarily on the so-called receptor-law sensitivity, which models a nonlinear decrease of chemotactic sensitivity with increasing ligand concentration. Our results reveal qualitative differences between the receptor law, the constant chemotactic response, and the so-called log law, with respect to stability of the homogeneous solution, as well as the emergence of different patterns (labyrinthine structures, clusters, and bubbles) via spinodal decomposition or nucleation. We discuss two limiting cases, where the model can be reduced to the dynamics of single species: (I) the agent density governed by a density-dependent effective diffusion coefficient and (II) the ligand field with an effective bistable, time-dependent reaction rate. In the end, we turn to single clusters of agents, studying domain growth and determining mean characteristics of the stationary inhomogeneous state. Analytical results are confirmed and extended by large-scale GPU simulations of the individual based model.
Reynolds, Sara A; Brassil, Chad E
2013-12-21
Single-species population models often include density-dependence phenomenologically in order to approximate higher order mechanisms. Here we consider the common scenario in which density-dependence acts via depletion of a renewed resource. When the response of the resource is very quick relative to that of the consumer, the consumer dynamics can be captured by a single-species, density-dependent model. Time scale separation is used to show analytically how the shape of the density-dependent relationship depends on the type of resource and the form of the functional response. Resource types of abiotic, biotic, and biotic with migration are considered, in combination with linear and saturating functional responses. In some cases, we derive familiar forms of single-species models, adding to the justification for their use. In other scenarios novel forms of density-dependence are derived, for example an abiotic resource and a saturating functional response can result in a nonlinear density-dependent relationship in the associated single-species model of the consumer. In this case, the per capita relationship has both concave-up and concave-down sections. © 2013 Published by Elsevier Ltd. All rights reserved.
Dynamic spectrin/ankyrin-G microdomains promote lateral membrane assembly by opposing endocytosis
Jenkins, Paul M.; He, Meng; Bennett, Vann
2015-01-01
Current physical models for plasma membranes emphasize dynamic 10- to 300-nm compartments at thermodynamic equilibrium but subject to thermal fluctuations. However, epithelial lateral membranes contain micrometer-sized domains defined by an underlying membrane skeleton composed of spectrin and its partner ankyrin-G. We demonstrate that these spectrin/ankyrin-G domains exhibit local microtubule-dependent movement on a time scale of minutes and encounter most of the lateral membranes within an hour. Spectrin/ankyrin-G domains exclude clathrin and clathrin-dependent cargo, and inhibit both receptor-mediated and bulk endocytosis. Moreover, inhibition of endocytosis fully restores lateral membrane height in spectrin- or ankyrin-G–depleted cells. These findings support a non-equilibrium cellular-scale model for epithelial lateral membranes, where spectrin/ankyrin-G domains actively patrol the plasma membrane, analogous to “window washers,” and promote columnar morphology by blocking membrane uptake. PMID:26523289
Theory of rumour spreading in complex social networks
NASA Astrophysics Data System (ADS)
Nekovee, M.; Moreno, Y.; Bianconi, G.; Marsili, M.
2007-01-01
We introduce a general stochastic model for the spread of rumours, and derive mean-field equations that describe the dynamics of the model on complex social networks (in particular, those mediated by the Internet). We use analytical and numerical solutions of these equations to examine the threshold behaviour and dynamics of the model on several models of such networks: random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumour spreading rate below which a rumour cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumour spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumour, however, depends on the interplay between network topology and the rumour spreading rate. Our results show that scale-free social networks are prone to the spreading of rumours, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale information dissemination algorithms on the Internet.
Spiking and bursting patterns of fractional-order Izhikevich model
NASA Astrophysics Data System (ADS)
Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha
2018-03-01
Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.
Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances.
Chekroun, Mickaël David; Neelin, J David; Kondrashov, Dmitri; McWilliams, James C; Ghil, Michael
2014-02-04
Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them--as filtered through an observable of the system--is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap--defined as the distance between the subdominant RP resonance and the unit circle--plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño-Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally.
Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances
Chekroun, Mickaël David; Neelin, J. David; Kondrashov, Dmitri; McWilliams, James C.; Ghil, Michael
2014-01-01
Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them—as filtered through an observable of the system—is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap—defined as the distance between the subdominant RP resonance and the unit circle—plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño–Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally. PMID:24443553
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tiwary, C. S., E-mail: cst.iisc@gmail.com; Chattopadhyay, K.; Chakraborty, S.
2014-05-28
This paper attempts to gain an understanding of the effect of lamellar length scale on the mechanical properties of two-phase metal-intermetallic eutectic structure. We first develop a molecular dynamics model for the in-situ grown eutectic interface followed by a model of deformation of Al-Al{sub 2}Cu lamellar eutectic. Leveraging the insights obtained from the simulation on the behaviour of dislocations at different length scales of the eutectic, we present and explain the experimental results on Al-Al{sub 2}Cu eutectic with various different lamellar spacing. The physics behind the mechanism is further quantified with help of atomic level energy model for different lengthmore » scale as well as different strain. An atomic level energy partitioning of the lamellae and the interface regions reveals that the energy of the lamellae core are accumulated more due to dislocations irrespective of the length-scale. Whereas the energy of the interface is accumulated more due to dislocations when the length-scale is smaller, but the trend is reversed when the length-scale is large beyond a critical size of about 80 nm.« less
The effects of wind disturbance on temperate rain forest structure and dynamics of southeast Alaska.
Gregory J. Nowacki; Marc G. Kramer
1998-01-01
Wind disturbance plays a fundamental role in shaping forest dynamics in southeast Alaska. Recent studies have increased our appreciation for the effects of wind at both large and small scales. Current thinking is that wind disturbance characteristics change over a continuum dependent on landscape features (e.g., exposure, landscape position, topography). Data modeling...
NASA Astrophysics Data System (ADS)
Huang, Libai
2015-03-01
The frontier in solar energy conversion now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. To address this new frontier, I will discuss our recent efforts on elucidating multi-scale energy transfer, migration, and dissipation processes with simultaneous femtosecond temporal resolution and nanometer spatial resolution. We have developed ultrafast microscopy that combines ultrafast spectroscopy with optical microscopy to map exciton dynamics and transport with simultaneous ultrafast time resolution and diffraction-limited spatial resolution. We have employed pump-probe transient absorption microscopy to elucidate morphology and structure dependent exciton dynamics and transport in single nanostructures and molecular assemblies. More specifically, (1) We have applied transient absorption microscopy (TAM) to probe environmental and structure dependent exciton relaxation pathways in sing-walled carbon nanotubes (SWNTs) by mapping dynamics in individual pristine SWNTs with known structures. (2) We have systematically measured and modeled the optical properties of the Frenkel excitons in self-assembled porphyrin tubular aggregates that represent an analog to natural photosynthetic antennae. Using a combination of ultrafast optical microscopy and stochastic exciton modeling, we address exciton transport and relaxation pathways, especially those related to disorder.
Zhu, Zhiwei; Zhou, Xiaoqin
2012-01-01
The main contribution of this paper is the development of a linearized model for describing the dynamic hysteresis behaviors of piezoelectrically actuated fast tool servo (FTS). A linearized hysteresis force model is proposed and mathematically described by a fractional order differential equation. Combining the dynamic modeling of the FTS mechanism, a linearized fractional order dynamic hysteresis (LFDH) model for the piezoelectrically actuated FTS is established. The unique features of the LFDH model could be summarized as follows: (a) It could well describe the rate-dependent hysteresis due to its intrinsic characteristics of frequency-dependent nonlinear phase shifts and amplitude modulations; (b) The linearization scheme of the LFDH model would make it easier to implement the inverse dynamic control on piezoelectrically actuated micro-systems. To verify the effectiveness of the proposed model, a series of experiments are conducted. The toolpaths of the FTS for creating two typical micro-functional surfaces involving various harmonic components with different frequencies and amplitudes are scaled and employed as command signals for the piezoelectric actuator. The modeling errors in the steady state are less than ±2.5% within the full span range which is much smaller than certain state-of-the-art modeling methods, demonstrating the efficiency and superiority of the proposed model for modeling dynamic hysteresis effects. Moreover, it indicates that the piezoelectrically actuated micro systems would be more suitably described as a fractional order dynamic system.
NASA Astrophysics Data System (ADS)
Rajni; Kumar, Suneel
2012-02-01
We have analyzed the role of interaction range on multifragmentation within the isospin-dependent quantum molecular dynamic (IQMD) model. We find that the effect of width of Gaussian wave packet associated with a nucleon depends on the mass of the colliding system. For a given set of input parameters, we find that width has a sizable effect. At the same time, we know that a different set of parameters can influence the reaction dynamics drastically. Hence, in our opinion it may not be possible to pin down the width to a very narrow level. A systematic study of mass effect ( 197Au, 124La, 124Sn, 107Sn in the breakup of a projectile spectator at intermediate energies has been performed. We also studied the disapperance of flow which demonstrates the effect of the scaled Gaussian width (SGW). Our studies shows that SGW influences the reaction dynamics.
Pattern formation in individual-based systems with time-varying parameters
NASA Astrophysics Data System (ADS)
Ashcroft, Peter; Galla, Tobias
2013-12-01
We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.
NASA Astrophysics Data System (ADS)
Zaug, Joseph M.; Austin, Ryan A.; Armstrong, Michael R.; Crowhurst, Jonathan C.; Goldman, Nir; Ferranti, Louis; Saw, Cheng K.; Swan, Raymond A.; Gross, Richard; Fried, Laurence E.
2018-05-01
We report experimental and computational studies of shock wave dynamics in single-crystal β-HMX on an ultrafast time scale. Here, a laser-based compression drive (˜1 ns in duration; stresses of up to ˜40 GPa) is used to propagate shock waves normal to the (110) and (010) lattice planes. Ultrafast time-domain interferometry measurements reveal distinct, time-dependent relationships between the shock wave velocity and particle velocity for each crystal orientation, which suggest evolving physical processes on a sub-nanosecond time scale. To help interpret the experimental data, elastic shock wave response was simulated using a finite-strain model of crystal thermoelasticity. At early propagation times (<500 ps), the model is in agreement with the data, which indicates that the mechanical response is dominated by thermoelastic deformation. The model agreement depends on the inclusion of nonlinear elastic effects in both the spherical and deviatoric stress-strain responses. This is achieved by employing an equation-of-state and a pressure-dependent stiffness tensor, which was computed via atomistic simulation. At later times (>500 ps), the crystal samples exhibit signatures of inelastic deformation, structural phase transformation, or chemical reaction, depending on the direction of wave propagation.
NASA Technical Reports Server (NTRS)
Grauer, Jared A.; Morelli, Eugene A.
2013-01-01
A nonlinear simulation of the NASA Generic Transport Model was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of dynamic models identified from flight data. Measurements from a typical system identification maneuver were systematically and progressively deteriorated and then used to estimate stability and control derivatives within a Monte Carlo analysis. Based on the results, recommendations were provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using other flight conditions, parameter estimation methods, and a full-scale F-16 nonlinear aircraft simulation were compared with these recommendations.
Roles of dark energy perturbations in dynamical dark energy models: can we ignore them?
Park, Chan-Gyung; Hwang, Jai-chan; Lee, Jae-heon; Noh, Hyerim
2009-10-09
We show the importance of properly including the perturbations of the dark energy component in the dynamical dark energy models based on a scalar field and modified gravity theories in order to meet with present and future observational precisions. Based on a simple scaling scalar field dark energy model, we show that observationally distinguishable substantial differences appear by ignoring the dark energy perturbation. By ignoring it the perturbed system of equations becomes inconsistent and deviations in (gauge-invariant) power spectra depend on the gauge choice.
A Stochastic Fractional Dynamics Model of Rainfall Statistics
NASA Astrophysics Data System (ADS)
Kundu, Prasun; Travis, James
2013-04-01
Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.
Extreme-volatility dynamics in crude oil markets
NASA Astrophysics Data System (ADS)
Jiang, Xiong-Fei; Zheng, Bo; Qiu, Tian; Ren, Fei
2017-02-01
Based on concepts and methods from statistical physics, we investigate extreme-volatility dynamics in the crude oil markets, using the high-frequency data from 2006 to 2010 and the daily data from 1986 to 2016. The dynamic relaxation of extreme volatilities is described by a power law, whose exponents usually depend on the magnitude of extreme volatilities. In particular, the relaxation before and after extreme volatilities is time-reversal symmetric at the high-frequency time scale, but time-reversal asymmetric at the daily time scale. This time-reversal asymmetry is mainly induced by exogenous events. However, the dynamic relaxation after exogenous events exhibits the same characteristics as that after endogenous events. An interacting herding model both with and without exogenous driving forces could qualitatively describe the extreme-volatility dynamics.
Spatial averaging of a dissipative particle dynamics model for active suspensions
NASA Astrophysics Data System (ADS)
Panchenko, Alexander; Hinz, Denis F.; Fried, Eliot
2018-03-01
Starting from a fine-scale dissipative particle dynamics (DPD) model of self-motile point particles, we derive meso-scale continuum equations by applying a spatial averaging version of the Irving-Kirkwood-Noll procedure. Since the method does not rely on kinetic theory, the derivation is valid for highly concentrated particle systems. Spatial averaging yields stochastic continuum equations similar to those of Toner and Tu. However, our theory also involves a constitutive equation for the average fluctuation force. According to this equation, both the strength and the probability distribution vary with time and position through the effective mass density. The statistics of the fluctuation force also depend on the fine scale dissipative force equation, the physical temperature, and two additional parameters which characterize fluctuation strengths. Although the self-propulsion force entering our DPD model contains no explicit mechanism for aligning the velocities of neighboring particles, our averaged coarse-scale equations include the commonly encountered cubically nonlinear (internal) body force density.
Vortex dynamics and Lagrangian statistics in a model for active turbulence.
James, Martin; Wilczek, Michael
2018-02-14
Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. (Proc. Natl. Acad. Sci. U.S.A. 109, 14308 (2012)), we model active turbulence by means of a generalized Navier-Stokes equation. Two-point velocity statistics of active turbulence, both in the Eulerian and the Lagrangian frame, is explored. We characterize the scale-dependent features of two-point statistics in this system. Furthermore, we extend this statistical study with measurements of vortex dynamics in this system. Our observations suggest that the large-scale statistics of active turbulence is close to Gaussian with sub-Gaussian tails.
A unified gas-kinetic scheme for continuum and rarefied flows IV: Full Boltzmann and model equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Chang, E-mail: cliuaa@ust.hk; Xu, Kun, E-mail: makxu@ust.hk; Sun, Quanhua, E-mail: qsun@imech.ac.cn
Fluid dynamic equations are valid in their respective modeling scales, such as the particle mean free path scale of the Boltzmann equation and the hydrodynamic scale of the Navier–Stokes (NS) equations. With a variation of the modeling scales, theoretically there should have a continuous spectrum of fluid dynamic equations. Even though the Boltzmann equation is claimed to be valid in all scales, many Boltzmann solvers, including direct simulation Monte Carlo method, require the cell resolution to the order of particle mean free path scale. Therefore, they are still single scale methods. In order to study multiscale flow evolution efficiently, themore » dynamics in the computational fluid has to be changed with the scales. A direct modeling of flow physics with a changeable scale may become an appropriate approach. The unified gas-kinetic scheme (UGKS) is a direct modeling method in the mesh size scale, and its underlying flow physics depends on the resolution of the cell size relative to the particle mean free path. The cell size of UGKS is not limited by the particle mean free path. With the variation of the ratio between the numerical cell size and local particle mean free path, the UGKS recovers the flow dynamics from the particle transport and collision in the kinetic scale to the wave propagation in the hydrodynamic scale. The previous UGKS is mostly constructed from the evolution solution of kinetic model equations. Even though the UGKS is very accurate and effective in the low transition and continuum flow regimes with the time step being much larger than the particle mean free time, it still has space to develop more accurate flow solver in the region, where the time step is comparable with the local particle mean free time. In such a scale, there is dynamic difference from the full Boltzmann collision term and the model equations. This work is about the further development of the UGKS with the implementation of the full Boltzmann collision term in the region where it is needed. The central ingredient of the UGKS is the coupled treatment of particle transport and collision in the flux evaluation across a cell interface, where a continuous flow dynamics from kinetic to hydrodynamic scales is modeled. The newly developed UGKS has the asymptotic preserving (AP) property of recovering the NS solutions in the continuum flow regime, and the full Boltzmann solution in the rarefied regime. In the mostly unexplored transition regime, the UGKS itself provides a valuable tool for the non-equilibrium flow study. The mathematical properties of the scheme, such as stability, accuracy, and the asymptotic preserving, will be analyzed in this paper as well.« less
On the origin of bursts and heavy tails in animal dynamics
NASA Astrophysics Data System (ADS)
Reynolds, A. M.
2011-01-01
Over recent years there has been an accumulation of evidence that many animal behaviours are characterised by common scale-invariant patterns of switching between two contrasting activities over a period of time. This is evidenced in mammalian wake-sleep patterns, in the intermittent stop-start locomotion of Drosophila fruit flies, and in the Lévy walk movement patterns of a diverse range of animals in which straight-line movements are punctuated by occasional turns. Here it is shown that these dynamics can be modelled by a stochastic variant of Barabási’s model [A.-L. Barabási, The origin of bursts and heavy tails in human dynamics, Nature 435 (2005) 207-211] for bursts and heavy tails in human dynamics. The new model captures a tension between two competing and conflicting activities. The durations of one type of activity are distributed according to an inverse-square power-law, mirroring the ubiquity of inverse-square power-law scaling seen in empirical data. The durations of the second type of activity follow exponential distributions with characteristic timescales that depend on species and metabolic rates. This again is a common feature of animal behaviour. Bursty human dynamics, on the other hand, are characterised by power-law distributions with scaling exponents close to -1 and -3/2.
NASA Astrophysics Data System (ADS)
He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong
2015-12-01
Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Yujie; Yang, Jinyan; Zhuang, Qianlai
Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less
He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong
2015-01-01
Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.
Electron-phonon interaction within classical molecular dynamics
Tamm, A.; Samolyuk, G.; Correa, A. A.; ...
2016-07-14
Here, we present a model for nonadiabatic classical molecular dynamics simulations that captures with high accuracy the wave-vector q dependence of the phonon lifetimes, in agreement with quantum mechanics calculations. It is based on a local view of the e-ph interaction where individual atom dynamics couples to electrons via a damping term that is obtained as the low-velocity limit of the stopping power of a moving ion in a host. The model is parameter free, as its components are derived from ab initio-type calculations, is readily extended to the case of alloys, and is adequate for large-scale molecular dynamics computermore » simulations. We also show how this model removes some oversimplifications of the traditional ionic damped dynamics commonly used to describe situations beyond the Born-Oppenheimer approximation.« less
Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco
2014-01-01
An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.
Scaling Behavior of Firm Growth
NASA Astrophysics Data System (ADS)
Stanley, Michael H. R.; Nunes Amaral, Luis A.; Buldyrev, Sergey V.; Havlin, Shlomo; Leschhorn, Heiko; Maass, Philipp; Salinger, Michael A.; Stanley, H. Eugene
1996-03-01
The theory of the firm is of considerable interest in economics. The standard microeconomic theory of the firm is largely a static model and has thus proved unsatisfactory for addressing inherently dynamic issues such as the growth of economies. In recent years, many have attempted to develop richer models that provide a more accurate representation of firm dynamics due to learning, innovative effort, and the development of organizational infrastructure. The validity of these new, inherently dynamic theories depends on their consistency with the statistical properties of firm growth, e.g. the relationship between growth rates and firm size. Using the Compustat database over the time period 1975-1991, we find: (i) the distribution of annual growth rates for firms with approximately the same sales displays an exponential form with the logarithm of growth rate, and (ii) the fluctuations in the growth rates --- measured by the width of this distribution --- scale as a power law with the firm sales. We place these findings of scaling behavior in the context of conventional economics by considering firm growth dynamics with temporal correlations and also, by considering a hierarchical organization of the departments of a firm.
Multiple Scales in Fluid Dynamics and Meteorology: The DFG Priority Programme 1276 MetStröm
NASA Astrophysics Data System (ADS)
von Larcher, Th; Klein, R.
2012-04-01
Geophysical fluid motions are characterized by a very wide range of length and time scales, and by a rich collection of varying physical phenomena. The mathematical description of these motions reflects this multitude of scales and mechanisms in that it involves strong non-linearities and various scale-dependent singular limit regimes. Considerable progress has been made in recent years in the mathematical modelling and numerical simulation of such flows in detailed process studies, numerical weather forecasting, and climate research. One task of outstanding importance in this context has been and will remain for the foreseeable future the subgrid scale parameterization of the net effects of non-resolved processes that take place on spacio-temporal scales not resolvable even by the largest most recent supercomputers. Since the advent of numerical weather forecasting some 60 years ago, one simple but efficient means to achieve improved forecasting skills has been increased spacio-temporal resolution. This seems quite consistent with the concept of convergence of numerical methods in Applied Mathematics and Computational Fluid Dynamics (CFD) at a first glance. Yet, the very notion of increased resolution in atmosphere-ocean science is very different from the one used in Applied Mathematics: For the mathematician, increased resolution provides the benefit of getting closer to the ideal of a converged solution of some given partial differential equations. On the other hand, the atmosphere-ocean scientist would naturally refine the computational grid and adjust his mathematical model, such that it better represents the relevant physical processes that occur at smaller scales. This conceptual contradiction remains largely irrelevant as long as geophysical flow models operate with fixed computational grids and time steps and with subgrid scale parameterizations being optimized accordingly. The picture changes fundamentally when modern techniques from CFD involving spacio-temporal grid adaptivity get invoked in order to further improve the net efficiency in exploiting the given computational resources. In the setting of geophysical flow simulation one must then employ subgrid scale parameterizations that dynamically adapt to the changing grid sizes and time steps, implement ways to judiciously control and steer the newly available flexibility of resolution, and invent novel ways of quantifying the remaining errors. The DFG priority program MetStröm covers the expertise of Meteorology, Fluid Dynamics, and Applied Mathematics to develop model- as well as grid-adaptive numerical simulation concepts in multidisciplinary projects. The goal of this priority programme is to provide simulation models which combine scale-dependent (mathematical) descriptions of key physical processes with adaptive flow discretization schemes. Deterministic continuous approaches and discrete and/or stochastic closures and their possible interplay are taken into consideration. Research focuses on the theory and methodology of multiscale meteorological-fluid mechanics modelling. Accompanying reference experiments support model validation.
Predicting viscous-range velocity gradient dynamics in large-eddy simulations of turbulence
NASA Astrophysics Data System (ADS)
Johnson, Perry; Meneveau, Charles
2017-11-01
The details of small-scale turbulence are not directly accessible in large-eddy simulations (LES), posing a modeling challenge because many important micro-physical processes depend strongly on the dynamics of turbulence in the viscous range. Here, we introduce a method for coupling existing stochastic models for the Lagrangian evolution of the velocity gradient tensor with LES to simulate unresolved dynamics. The proposed approach is implemented in LES of turbulent channel flow and detailed comparisons with DNS are carried out. An application to modeling the fate of deformable, small (sub-Kolmogorov) droplets at negligible Stokes number and low volume fraction with one-way coupling is carried out. These results illustrate the ability of the proposed model to predict the influence of small scale turbulence on droplet micro-physics in the context of LES. This research was made possible by a graduate Fellowship from the National Science Foundation and by a Grant from The Gulf of Mexico Research Initiative.
NASA Astrophysics Data System (ADS)
Berloff, P. S.
2016-12-01
This work aims at developing a framework for dynamically consistent parameterization of mesoscale eddy effects for use in non-eddy-resolving ocean circulation models. The proposed eddy parameterization framework is successfully tested on the classical, wind-driven double-gyre model, which is solved both with explicitly resolved vigorous eddy field and in the non-eddy-resolving configuration with the eddy parameterization replacing the eddy effects. The parameterization focuses on the effect of the stochastic part of the eddy forcing that backscatters and induces eastward jet extension of the western boundary currents and its adjacent recirculation zones. The parameterization locally approximates transient eddy flux divergence by spatially localized and temporally periodic forcing, referred to as the plunger, and focuses on the linear-dynamics flow solution induced by it. The nonlinear self-interaction of this solution, referred to as the footprint, characterizes and quantifies the induced eddy forcing exerted on the large-scale flow. We find that spatial pattern and amplitude of each footprint strongly depend on the underlying large-scale flow, and the corresponding relationships provide the basis for the eddy parameterization and its closure on the large-scale flow properties. Dependencies of the footprints on other important parameters of the problem are also systematically analyzed. The parameterization utilizes the local large-scale flow information, constructs and scales the corresponding footprints, and then sums them up over the gyres to produce the resulting eddy forcing field, which is interactively added to the model as an extra forcing. Thus, the assumed ensemble of plunger solutions can be viewed as a simple model for the cumulative effect of the stochastic eddy forcing. The parameterization framework is implemented in the simplest way, but it provides a systematic strategy for improving the implementation algorithm.
Wave models for turbulent free shear flows
NASA Technical Reports Server (NTRS)
Liou, W. W.; Morris, P. J.
1991-01-01
New predictive closure models for turbulent free shear flows are presented. They are based on an instability wave description of the dominant large scale structures in these flows using a quasi-linear theory. Three model were developed to study the structural dynamics of turbulent motions of different scales in free shear flows. The local characteristics of the large scale motions are described using linear theory. Their amplitude is determined from an energy integral analysis. The models were applied to the study of an incompressible free mixing layer. In all cases, predictions are made for the development of the mean flow field. In the last model, predictions of the time dependent motion of the large scale structure of the mixing region are made. The predictions show good agreement with experimental observations.
Temporal scaling and spatial statistical analyses of groundwater level fluctuations
NASA Astrophysics Data System (ADS)
Sun, H.; Yuan, L., Sr.; Zhang, Y.
2017-12-01
Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.
NASA Astrophysics Data System (ADS)
Dalguer, L. A.; Miyake, H.; Irikura, K.; Wu, H., Sr.
2016-12-01
Empirical scaling models of seismic moment and rupture area provide constraints to parameterize source parameters, such as stress drop, for numerical simulations of ground motion. There are several scaling models published in the literature. The effect of the finite width seismogenic zone and the free-surface have been attributed to cause the breaking of the well know self-similar scaling (e.g. Dalguer et al, 2008) given origin to the so called L and W models for large faults. These models imply the existence of three-stage scaling relationship between seismic moment and rupture area (e.g. Irikura and Miyake, 2011). In this paper we extend the work done by Dalguer et al 2008, in which these authors calibrated fault models that match the observations showing that the average stress drop is independent of earthquake size for buried earthquakes, but scale dependent for surface-rupturing earthquakes. Here we have developed additional sets of dynamic rupture models for vertical strike slip faults to evaluate the effect of the weak shallow layer (WSL) zone for the calibration of stress drop. Rupture in the WSL zone is expected to operate with enhanced energy absorption mechanism. The set of dynamic models consists of fault models with width 20km and fault length L=20km, 40km, 60km, 80km, 100km, 120km, 200km, 300km and 400km and average stress drop values of 2.0MPa, 2.5MPa, 3.0MPa, 3.5MPa, 5.0MPa and 7.5MPa. For models that break the free-surface, the WSL zone is modeled assuming a 2km width with stress drop 0.0MPa or -2.0 MPa. Our results show that depending on the characterization of the WSL zone, the average stress drop at the seismogenic zone that fit the empirical models changes. If WSL zone is not considered, that is, stress drop at SL zone is the same as the seismogenic zone, average stress drop is about 20% smaller than models with WSL zone. By introducing more energy absorption at the SL zone, that could be the case of large mature faults, the average stress drop in the seismogenic zone increases. Suggesting that large earthquakes need higher stress drop to break the fault than buried and moderate earthquakes. Therefore, the value of the average stress drop for large events that break the free-source depend on the definition of the WSL. Suggesting that the WSL plays an important role on the prediction of final slip and fault displacement.
The four fixed points of scale invariant single field cosmological models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xue, BingKan, E-mail: bxue@princeton.edu
2012-10-01
We introduce a new set of flow parameters to describe the time dependence of the equation of state and the speed of sound in single field cosmological models. A scale invariant power spectrum is produced if these flow parameters satisfy specific dynamical equations. We analyze the flow of these parameters and find four types of fixed points that encompass all known single field models. Moreover, near each fixed point we uncover new models where the scale invariance of the power spectrum relies on having simultaneously time varying speed of sound and equation of state. We describe several distinctive new modelsmore » and discuss constraints from strong coupling and superluminality.« less
NASA Astrophysics Data System (ADS)
Posnansky, Oleg P.
2018-05-01
The measuring of dynamic magnetic susceptibility by nuclear magnetic resonance is used for revealing information about the internal structure of various magnetoactive composites. The response of such material on the applied external static and time-varying magnetic fields encodes intrinsic dynamic correlations and depends on links between macroscopic effective susceptibility and structure on the microscopic scale. In the current work we carried out computational analysis of the frequency dependent dynamic magnetic susceptibility and demonstrated its dependence on the microscopic architectural elements while also considering Euclidean dimensionality. The proposed numerical method is efficient in the simulation of nuclear magnetic resonance experiments in two- and three-dimensional random magnetic media by choosing and modeling the influence of the concentration of components and internal hierarchical characteristics of physical parameters.
NASA Astrophysics Data System (ADS)
Schmengler, A. C.; Vlek, P. L. G.
2012-04-01
Modelling soil erosion requires a holistic understanding of the sediment dynamics in a complex environment. As most erosion models are scale-dependent and their parameterization is spatially limited, their application often requires special care, particularly in data-scarce environments. This study presents a hierarchical approach to overcome the limitations of a single model by using various quantitative methods and soil erosion models to cope with the issues of scale. At hillslope scale, the physically-based Water Erosion Prediction Project (WEPP)-model is used to simulate soil loss and deposition processes. Model simulations of soil loss vary between 5 to 50 t ha-1 yr-1 dependent on the spatial location on the hillslope and have only limited correspondence with the results of the 137Cs technique. These differences in absolute soil loss values could be either due to internal shortcomings of each approach or to external scale-related uncertainties. Pedo-geomorphological soil investigations along a catena confirm that estimations by the 137Cs technique are more appropriate in reflecting both the spatial extent and magnitude of soil erosion at hillslope scale. In order to account for sediment dynamics at a larger scale, the spatially-distributed WaTEM/SEDEM model is used to simulate soil erosion at catchment scale and to predict sediment delivery rates into a small water reservoir. Predicted sediment yield rates are compared with results gained from a bathymetric survey and sediment core analysis. Results show that specific sediment rates of 0.6 t ha-1 yr-1 by the model are in close agreement with observed sediment yield calculated from stratigraphical changes and downcore variations in 137Cs concentrations. Sediment erosion rates averaged over the entire catchment of 1 to 2 t ha-1 yr-1 are significantly lower than results obtained at hillslope scale confirming an inverse correlation between the magnitude of erosion rates and the spatial scale of the model. The study has shown that the use of multiple methods facilitates the calibration and validation of models and might provide a more accurate measure for soil erosion rates in ungauged catchments. Moreover, the approach could be used to identify the most appropriate working and operational scales for soil erosion modelling.
On the physics of electron ejection from laser-irradiated overdense plasmas
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thévenet, M.; Vincenti, H.; Faure, J.
2016-06-15
Using 1D and 2D PIC simulations, we describe and model the backward ejection of electron bunches when a laser pulse reflects off an overdense plasma with a short density gradient on its front side. The dependence on the laser intensity and gradient scale length is studied. It is found that during each laser period, the incident laser pulse generates a large charge-separation field, or plasma capacitor, which accelerates an attosecond bunch of electrons toward vacuum. This process is maximized for short gradient scale lengths and collapses when the gradient scale length is comparable to the laser wavelength. We develop amore » model that reproduces the electron dynamics and the dependence on laser intensity and gradient scale length. This process is shown to be strongly linked with high harmonic generation via the Relativistic Oscillating Mirror mechanism.« less
NASA Technical Reports Server (NTRS)
Lucchin, Francesco; Matarrese, Sabino; Melott, Adrian L.; Moscardini, Lauro
1994-01-01
We calculate reduced moments (xi bar)(sub q) of the matter density fluctuations, up to order q = 5, from counts in cells produced by particle-mesh numerical simulations with scale-free Gaussian initial conditions. We use power-law spectra P(k) proportional to k(exp n) with indices n = -3, -2, -1, 0, 1. Due to the supposed absence of characteristic times or scales in our models, all quantities are expected to depend on a single scaling variable. For each model, the moments at all times can be expressed in terms of the variance (xi bar)(sub 2), alone. We look for agreement with the hierarchical scaling ansatz, according to which ((xi bar)(sub q)) proportional to ((xi bar)(sub 2))(exp (q - 1)). For n less than or equal to -2 models, we find strong deviations from the hierarchy, which are mostly due to the presence of boundary problems in the simulations. A small, residual signal of deviation from the hierarchical scaling is however also found in n greater than or equal to -1 models. The wide range of spectra considered and the large dynamic range, with careful checks of scaling and shot-noise effects, allows us to reliably detect evolution away from the perturbation theory result.
Two-rate periodic protocol with dynamics driven through many cycles
NASA Astrophysics Data System (ADS)
Kar, Satyaki
2017-02-01
We study the long time dynamics in closed quantum systems periodically driven via time dependent parameters with two frequencies ω1 and ω2=r ω1 . Tuning of the ratio r there can unleash plenty of dynamical phenomena to occur. Our study includes integrable models like Ising and X Y models in d =1 and the Kitaev model in d =1 and 2 and can also be extended to Dirac fermions in graphene. We witness the wave-function overlap or dynamic freezing that occurs within some small/ intermediate frequency regimes in the (ω1,r ) plane (with r ≠0 ) when the ground state is evolved through a single cycle of driving. However, evolved states soon become steady with long driving, and the freezing scenario gets rarer. We extend the formalism of adiabatic-impulse approximation for many cycle driving within our two-rate protocol and show the near-exact comparisons at small frequencies. An extension of the rotating wave approximation is also developed to gather an analytical framework of the dynamics at high frequencies. Finally we compute the entanglement entropy in the stroboscopically evolved states within the gapped phases of the system and observe how it gets tuned with the ratio r in our protocol. The minimally entangled states are found to fall within the regime of dynamical freezing. In general, the results indicate that the entanglement entropy in our driven short-ranged integrable systems follow a genuine nonarea law of scaling and show a convergence (with a r dependent pace) towards volume scaling behavior as the driving is continued for a long time.
NASA Astrophysics Data System (ADS)
Scala, Antonio; Festa, Gaetano; Vilotte, Jean-Pierre
2017-04-01
Earthquake ruptures often develop along faults separating materials with dissimilar elastic properties. Due to the broken symmetry, the propagation of the rupture along the bimaterial interface is driven by the coupling between interfacial sliding and normal traction perturbations. We numerically investigate in-plane rupture growth along a planar interface, under slip weakening friction, separating two dissimilar isotropic linearly elastic half-spaces. We perform a parametric study of the classical Prakash-Clifton regularisation for different material contrasts. In particular mesh-dependence and regularisation-dependence of the numerical solutions are analysed in this parameter space. When regularisation involves a slip-rate dependent relaxation time, a characteristic sliding distance is identified below which numerical solutions no longer depend on the regularisation parameter, i.e. they are consistent solutions of the same physical problem. Such regularisation provides an adaptive high-frequency filter of the slip-induced normal traction perturbations, following the dynamic shrinking of the dissipation zone during the acceleration phase. In contrast, regularisation involving a constant relaxation time leads to numerical solutions that always depend on the regularisation parameter since it fails adapting to the shrinking of the process zone. Dynamic regularisation is further investigated using a non-local regularisation based on a relaxation time that depends on the dynamic length of the dissipation zone. Such reformulation is shown to provide similar results as the dynamic time scale regularisation proposed by Prakash-Clifton when slip rate is replaced by the maximum slip rate along the sliding interface. This leads to the identification of a dissipative length scale associated with the coupling between interfacial sliding and normal traction perturbations, together with a scaling law between the maximum slip rate and the dynamic size of the process zone during the rupture propagation. Dynamic time scale regularisation is show to provide mesh-independent and physically well-posed numerical solutions during the acceleration phase toward an asymptotic speed. When generalised Rayleigh wave does not exist, numerical solutions are shown to tend toward an asymptotic velocity higher than the slowest shear wave speed. When generalised Rayleigh wave speed exists, as numerical solutions tend toward this velocity, increasing spurious oscillations develop and solutions become unstable. In this regime regularisation dependent and unstable finite-size pulses may be generated. This instability is associated with the singular behaviour of the slip-induced normal traction perturbations, and of the slip rate at the rupture front, in relation with complete shrinking of the dissipation zone. This phase requires to be modelled either by more complex interface constitutive laws involving velocity-strengthening effects that may stabilize short wavelength interfacial propagating modes or by considering non-ideal interfaces that introduce a new length scale in the problem that may promote selection and stabilization of the slip pulses.
Time dependent turbulence modeling and analytical theories of turbulence
NASA Technical Reports Server (NTRS)
Rubinstein, R.
1993-01-01
By simplifying the direct interaction approximation (DIA) for turbulent shear flow, time dependent formulas are derived for the Reynolds stresses which can be included in two equation models. The Green's function is treated phenomenologically, however, following Smith and Yakhot, we insist on the short and long time limits required by DIA. For small strain rates, perturbative evaluation of the correlation function yields a time dependent theory which includes normal stress effects in simple shear flows. From this standpoint, the phenomenological Launder-Reece-Rodi model is obtained by replacing the Green's function by its long time limit. Eddy damping corrections to short time behavior initiate too quickly in this model; in contrast, the present theory exhibits strong suppression of eddy damping at short times. A time dependent theory for large strain rates is proposed in which large scales are governed by rapid distortion theory while small scales are governed by Kolmogorov inertial range dynamics. At short times and large strain rates, the theory closely matches rapid distortion theory, but at long times it relaxes to an eddy damping model.
Physically representative atomistic modeling of atomic-scale friction
NASA Astrophysics Data System (ADS)
Dong, Yalin
Nanotribology is a research field to study friction, adhesion, wear and lubrication occurred between two sliding interfaces at nano scale. This study is motivated by the demanding need of miniaturization mechanical components in Micro Electro Mechanical Systems (MEMS), improvement of durability in magnetic storage system, and other industrial applications. Overcoming tribological failure and finding ways to control friction at small scale have become keys to commercialize MEMS with sliding components as well as to stimulate the technological innovation associated with the development of MEMS. In addition to the industrial applications, such research is also scientifically fascinating because it opens a door to understand macroscopic friction from the most bottom atomic level, and therefore serves as a bridge between science and engineering. This thesis focuses on solid/solid atomic friction and its associated energy dissipation through theoretical analysis, atomistic simulation, transition state theory, and close collaboration with experimentalists. Reduced-order models have many advantages for its simplification and capacity to simulating long-time event. We will apply Prandtl-Tomlinson models and their extensions to interpret dry atomic-scale friction. We begin with the fundamental equations and build on them step-by-step from the simple quasistatic one-spring, one-mass model for predicting transitions between friction regimes to the two-dimensional and multi-atom models for describing the effect of contact area. Theoretical analysis, numerical implementation, and predicted physical phenomena are all discussed. In the process, we demonstrate the significant potential for this approach to yield new fundamental understanding of atomic-scale friction. Atomistic modeling can never be overemphasized in the investigation of atomic friction, in which each single atom could play a significant role, but is hard to be captured experimentally. In atomic friction, the interesting physical process is buried between the two contact interfaces, thus makes a direct measurement more difficult. Atomistic simulation is able to simulate the process with the dynamic information of each single atom, and therefore provides valuable interpretations for experiments. In this, we will systematically to apply Molecular Dynamics (MD) simulation to optimally model the Atomic Force Microscopy (AFM) measurement of atomic friction. Furthermore, we also employed molecular dynamics simulation to correlate the atomic dynamics with the friction behavior observed in experiments. For instance, ParRep dynamics (an accelerated molecular dynamic technique) is introduced to investigate velocity dependence of atomic friction; we also employ MD simulation to "see" how the reconstruction of gold surface modulates the friction, and the friction enhancement mechanism at a graphite step edge. Atomic stick-slip friction can be treated as a rate process. Instead of running a direction simulation of the process, we can apply transition state theory to predict its property. We will have a rigorous derivation of velocity and temperature dependence of friction based on the Prandtl-Tomlinson model as well as transition theory. A more accurate relation to prediction velocity and temperature dependence is obtained. Furthermore, we have included instrumental noise inherent in AFM measurement to interpret two discoveries in experiments, suppression of friction at low temperature and the attempt frequency discrepancy between AFM measurement and theoretical prediction. We also discuss the possibility to treat wear as a rate process.
Molecular dynamics at low time resolution.
Faccioli, P
2010-10-28
The internal dynamics of macromolecular systems is characterized by widely separated time scales, ranging from fraction of picoseconds to nanoseconds. In ordinary molecular dynamics simulations, the elementary time step Δt used to integrate the equation of motion needs to be chosen much smaller of the shortest time scale in order not to cut-off physical effects. We show that in systems obeying the overdamped Langevin equation, it is possible to systematically correct for such discretization errors. This is done by analytically averaging out the fast molecular dynamics which occurs at time scales smaller than Δt, using a renormalization group based technique. Such a procedure gives raise to a time-dependent calculable correction to the diffusion coefficient. The resulting effective Langevin equation describes by construction the same long-time dynamics, but has a lower time resolution power, hence it can be integrated using larger time steps Δt. We illustrate and validate this method by studying the diffusion of a point-particle in a one-dimensional toy model and the denaturation of a protein.
Fractal scaling analysis of groundwater dynamics in confined aquifers
NASA Astrophysics Data System (ADS)
Tu, Tongbi; Ercan, Ali; Kavvas, M. Levent
2017-10-01
Groundwater closely interacts with surface water and even climate systems in most hydroclimatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations in confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality, and multifractal detrended fluctuation analysis (MF-DFA) and multiscale multifractal analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics, which may be fitted by the Lévy stable distribution, or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation, is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes that can model both the long-memory behavior and the Brownian finite-memory behavior.
Assessing global vegetation activity using spatio-temporal Bayesian modelling
NASA Astrophysics Data System (ADS)
Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.
2016-04-01
This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.
Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems
NASA Astrophysics Data System (ADS)
Stanton, L. G.; Glosli, J. N.; Murillo, M. S.
2018-04-01
Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.
The impact of ARM on climate modeling
Randall, David A.; Del Genio, Anthony D.; Donner, Lee J.; ...
2016-07-15
Climate models are among humanity’s most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of Earth down to 100 km or smaller and implicitly include the effects of processes on even smaller scales down to a micron or so. In addition, themore » atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM).« less
NASA Astrophysics Data System (ADS)
Freytag, B.; Liljegren, S.; Höfner, S.
2017-04-01
Context. Observations of asymptotic giant branch (AGB) stars with increasing spatial resolution reveal new layers of complexity of atmospheric processes on a variety of scales. Aims: To analyze the physical mechanisms that cause asymmetries and surface structures in observed images, we use detailed 3D dynamical simulations of AGB stars; these simulations self-consistently describe convection and pulsations. Methods: We used the CO5BOLD radiation-hydrodynamics code to produce an exploratory grid of global "star-in-a-box" models of the outer convective envelope and the inner atmosphere of AGB stars to study convection, pulsations, and shock waves and their dependence on stellar and numerical parameters. Results: The model dynamics are governed by the interaction of long-lasting giant convection cells, short-lived surface granules, and strong, radial, fundamental-mode pulsations. Radial pulsations and shorter wavelength, traveling, acoustic waves induce shocks on various scales in the atmosphere. Convection, waves, and shocks all contribute to the dynamical pressure and, thus, to an increase of the stellar radius and to a levitation of material into layers where dust can form. Consequently, the resulting relation of pulsation period and stellar radius is shifted toward larger radii compared to that of non-linear 1D models. The dependence of pulsation period on luminosity agrees well with observed relations. The interaction of the pulsation mode with the non-stationary convective flow causes occasional amplitude changes and phase shifts. The regularity of the pulsations decreases with decreasing gravity as the relative size of convection cells increases. The model stars do not have a well-defined surface. Instead, the light is emitted from a very extended inhomogeneous atmosphere with a complex dynamic pattern of high-contrast features. Conclusions: Our models self-consistently describe convection, convectively generated acoustic noise, fundamental-mode radial pulsations, and atmospheric shocks of various scales, which give rise to complex changing structures in the atmospheres of AGB stars.
NASA Astrophysics Data System (ADS)
Uritskaya, Olga Y.
2005-05-01
Results of fractal stability analysis of daily exchange rate fluctuations of more than 30 floating currencies for a 10-year period are presented. It is shown for the first time that small- and large-scale dynamical instabilities of national monetary systems correlate with deviations of the detrended fluctuation analysis (DFA) exponent from the value 1.5 predicted by the efficient market hypothesis. The observed dependence is used for classification of long-term stability of floating exchange rates as well as for revealing various forms of distortion of stable currency dynamics prior to large-scale crises. A normal range of DFA exponents consistent with crisis-free long-term exchange rate fluctuations is determined, and several typical scenarios of unstable currency dynamics with DFA exponents fluctuating beyond the normal range are identified. It is shown that monetary crashes are usually preceded by prolonged periods of abnormal (decreased or increased) DFA exponent, with the after-crash exponent tending to the value 1.5 indicating a more reliable exchange rate dynamics. Statistically significant regression relations (R=0.99, p<0.01) between duration and magnitude of currency crises and the degree of distortion of monofractal patterns of exchange rate dynamics are found. It is demonstrated that the parameters of these relations characterizing small- and large-scale crises are nearly equal, which implies a common instability mechanism underlying these events. The obtained dependences have been used as a basic ingredient of a forecasting technique which provided correct in-sample predictions of monetary crisis magnitude and duration over various time scales. The developed technique can be recommended for real-time monitoring of dynamical stability of floating exchange rate systems and creating advanced early-warning-system models for currency crisis prevention.
Quadtree of TIN: a new algorithm of dynamic LOD
NASA Astrophysics Data System (ADS)
Zhang, Junfeng; Fei, Lifan; Chen, Zhen
2009-10-01
Currently, Real-time visualization of large-scale digital elevation model mainly employs the regular structure of GRID based on quadtree and triangle simplification methods based on irregular triangulated network (TIN). TIN is a refined means to express the terrain surface in the computer science, compared with GRID. However, the data structure of TIN model is complex, and is difficult to realize view-dependence representation of level of detail (LOD) quickly. GRID is a simple method to realize the LOD of terrain, but contains more triangle count. A new algorithm, which takes full advantage of the two methods' merit, is presented in this paper. This algorithm combines TIN with quadtree structure to realize the view-dependence LOD controlling over the irregular sampling point sets, and holds the details through the distance of viewpoint and the geometric error of terrain. Experiments indicate that this approach can generate an efficient quadtree triangulation hierarchy over any irregular sampling point sets and achieve dynamic and visual multi-resolution performance of large-scale terrain at real-time.
Filament velocity scaling laws for warm ions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Manz, P.; Max-Planck-Institut für Plasmaphysik, EURATOM Assoziation, Boltzmannstr. 2, 85748 Garching; Carralero, D.
2013-10-15
The dynamics of filaments or blobs in the scrape-off layer of magnetic fusion devices are studied by magnitude estimates of a comprehensive drift-interchange-Alfvén fluid model. The standard blob models are reproduced in the cold ion case. Even though usually neglected, in the scrape-off layer, the ion temperature can exceed the electron temperature by an order of magnitude. The ion pressure affects the dynamics of filaments amongst others by adding up to the interchange drive and the polarisation current. It is shown how both effects modify the scaling laws for filament velocity in dependence of its size. Simplifications for experimentally relevantmore » limit regimes are given. These are the sheath dissipation, collisional, and electromagnetic regime.« less
Spreading dynamics of an e-commerce preferential information model on scale-free networks
NASA Astrophysics Data System (ADS)
Wan, Chen; Li, Tao; Guan, Zhi-Hong; Wang, Yuanmei; Liu, Xiongding
2017-02-01
In order to study the influence of the preferential degree and the heterogeneity of underlying networks on the spread of preferential e-commerce information, we propose a novel susceptible-infected-beneficial model based on scale-free networks. The spreading dynamics of the preferential information are analyzed in detail using the mean-field theory. We determine the basic reproductive number and equilibria. The theoretical analysis indicates that the basic reproductive number depends mainly on the preferential degree and the topology of the underlying networks. We prove the global stability of the information-elimination equilibrium. The permanence of preferential information and the global attractivity of the information-prevailing equilibrium are also studied in detail. Some numerical simulations are presented to verify the theoretical results.
Theoretical approaches for dynamical ordering of biomolecular systems.
Okumura, Hisashi; Higashi, Masahiro; Yoshida, Yuichiro; Sato, Hirofumi; Akiyama, Ryo
2018-02-01
Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies. We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified. The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function. These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.
Thermodynamic scaling of dynamics in polymer melts: predictions from the generalized entropy theory.
Xu, Wen-Sheng; Freed, Karl F
2013-06-21
Many glass-forming fluids exhibit a remarkable thermodynamic scaling in which dynamic properties, such as the viscosity, the relaxation time, and the diffusion constant, can be described under different thermodynamic conditions in terms of a unique scaling function of the ratio ρ(γ)∕T, where ρ is the density, T is the temperature, and γ is a material dependent constant. Interest in the scaling is also heightened because the exponent γ enters prominently into considerations of the relative contributions to the dynamics from pressure effects (e.g., activation barriers) vs. volume effects (e.g., free volume). Although this scaling is clearly of great practical use, a molecular understanding of the scaling remains elusive. Providing this molecular understanding would greatly enhance the utility of the empirically observed scaling in assisting the rational design of materials by describing how controllable molecular factors, such as monomer structures, interactions, flexibility, etc., influence the scaling exponent γ and, hence, the dynamics. Given the successes of the generalized entropy theory in elucidating the influence of molecular details on the universal properties of glass-forming polymers, this theory is extended here to investigate the thermodynamic scaling in polymer melts. The predictions of theory are in accord with the appearance of thermodynamic scaling for pressures not in excess of ~50 MPa. (The failure at higher pressures arises due to inherent limitations of a lattice model.) In line with arguments relating the magnitude of γ to the steepness of the repulsive part of the intermolecular potential, the abrupt, square-well nature of the lattice model interactions lead, as expected, to much larger values of the scaling exponent. Nevertheless, the theory is employed to study how individual molecular parameters affect the scaling exponent in order to extract a molecular understanding of the information content contained in the exponent. The chain rigidity, cohesive energy, chain length, and the side group length are all found to significantly affect the magnitude of the scaling exponent, and the computed trends agree well with available experiments. The variations of γ with these molecular parameters are explained by establishing a correlation between the computed molecular dependence of the scaling exponent and the fragility. Thus, the efficiency of packing the polymers is established as the universal physical mechanism determining both the fragility and the scaling exponent γ.
Network simulations of optical illusions
NASA Astrophysics Data System (ADS)
Shinbrot, Troy; Lazo, Miguel Vivar; Siu, Theo
We examine a dynamical network model of visual processing that reproduces several aspects of a well-known optical illusion, including subtle dependencies on curvature and scale. The model uses a genetic algorithm to construct the percept of an image, and we show that this percept evolves dynamically so as to produce the illusions reported. We find that the perceived illusions are hardwired into the model architecture and we propose that this approach may serve as an archetype to distinguish behaviors that are due to nature (i.e. a fixed network architecture) from those subject to nurture (that can be plastically altered through learning).
NASA Astrophysics Data System (ADS)
Martinez, Luis; Meneveau, Charles
2014-11-01
Large Eddy Simulations (LES) of the flow past a single wind turbine with uniform inflow have been performed. A goal of the simulations is to compare two turbulence subgrid-scale models and their effects in predicting the initial breakdown, transition and evolution of the wake behind the turbine. Prior works have often observed negligible sensitivities to subgrid-scale models. The flow is modeled using an in-house LES with pseudo-spectral discretization in horizontal planes and centered finite differencing in the vertical direction. Turbines are represented using the actuator line model. We compare the standard constant-coefficient Smagorinsky subgrid-scale model with the Lagrangian Scale Dependent Dynamic model (LSDM). The LSDM model predicts faster transition to turbulence in the wake, whereas the standard Smagorinsky model predicts significantly delayed transition. The specified Smagorinsky coefficient is larger than the dynamic one on average, increasing diffusion thus delaying transition. A second goal is to compare the resulting near-blade properties such as local aerodynamic forces from the LES with Blade Element Momentum Theory. Results will also be compared with those of the SOWFA package, the wind energy CFD framework from NREL. This work is supported by NSF (IGERT and IIA-1243482) and computations use XSEDE resources, and has benefitted from interactions with Dr. M. Churchfield of NREL.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gustafson, William I.; Ma, Po-Lun; Xiao, Heng
2013-08-29
The ability to use multi-resolution dynamical cores for weather and climate modeling is pushing the atmospheric community towards developing scale aware or, more specifically, resolution aware parameterizations that will function properly across a range of grid spacings. Determining the resolution dependence of specific model parameterizations is difficult due to strong resolution dependencies in many pieces of the model. This study presents the Separate Physics and Dynamics Experiment (SPADE) framework that can be used to isolate the resolution dependent behavior of specific parameterizations without conflating resolution dependencies from other portions of the model. To demonstrate the SPADE framework, the resolution dependencemore » of the Morrison microphysics from the Weather Research and Forecasting model and the Morrison-Gettelman microphysics from the Community Atmosphere Model are compared for grid spacings spanning the cloud modeling gray zone. It is shown that the Morrison scheme has stronger resolution dependence than Morrison-Gettelman, and that the ability of Morrison-Gettelman to use partial cloud fractions is not the primary reason for this difference. This study also discusses how to frame the issue of resolution dependence, the meaning of which has often been assumed, but not clearly expressed in the atmospheric modeling community. It is proposed that parameterization resolution dependence can be expressed in terms of "resolution dependence of the first type," RA1, which implies that the parameterization behavior converges towards observations with increasing resolution, or as "resolution dependence of the second type," RA2, which requires that the parameterization reproduces the same behavior across a range of grid spacings when compared at a given coarser resolution. RA2 behavior is considered the ideal, but brings with it serious implications due to limitations of parameterizations to accurately estimate reality with coarse grid spacing. The type of resolution awareness developers should target in their development depends upon the particular modeler’s application.« less
Stoichiometric vs hydroclimatic controls on soil biogeochemical processes
NASA Astrophysics Data System (ADS)
Manzoni, Stefano; Porporato, Amilcare
2010-05-01
Soil nutrient cycles are controlled by both stoichiometric constraints (e.g., carbon to nutrient ratios) and hydroclimatic conditions (e.g., soil moisture and temperature). Both controls tend to act in a nonlinear manner and give rise to complex dynamics in soil biogeochemistry at different space-time scales. We first review the theoretical basis of soil biogeochemical models, looking for the general principles underlying these models across space-time scales and scientific disciplines. By comparing more than 250 models, we show that similar kinetic and stoichiometric laws, formulated to mechanistically represent the complex biochemical constraints to decomposition, are common to most models, providing a basis for their classification. Moreover, a historic analysis reveals that the complexity (e.g., phase space dimension, model architecture) and degree and number of nonlinearities generally increased with date, while they decreased with increasing spatial and temporal scale of interest. Soil biogeochmical dynamics may be suitable conceptualized using a number of compartments (e.g., decomposers, organic substrates, inorganic ions) interacting among each other at rates that depend (nonlinearly) on climatic drivers. As a consequence, hydroclimatic-induced fluctuations at the daily scale propagate through the various soil compartments leading to cascading effects ranging from short-term fluctuations in the smaller pools to long-lasting changes in the larger ones. Such cascading effects are known to occur in dryland ecosystems, and are increasingly being recongnized to control the long-term carbon and nutrient balances in more mesic ecosystems. We also show that separating biochemical from climatic impacts on organic matter decomposition results in universal curves describing data of plant residue decomposition and nutrient mineralization across the globe. Future extensions to larger spatial scales and managed ecosystems are also briefly outlined. It is critical that future modeling efforts carefully account for the scale-dependence of their mathematical formulations, especially when applied to a wide range of scales.
Investigating EMIC Wave Dynamics with RAM-SCB-E
NASA Astrophysics Data System (ADS)
Jordanova, V. K.; Fu, X.; Henderson, M. G.; Morley, S.; Welling, D. T.; Yu, Y.
2017-12-01
The distribution of ring current ions and electrons in the inner magnetosphere depends strongly on their transport in realistic electric (E) and magnetic (B) fields and concurrent energization or loss. To investigate the high variability of energetic particle (H+, He+, O+, and electron) fluxes during storms selected by the GEM Surface Charging Challenge, we use our kinetic ring current model (RAM) two-way coupled with a 3-D magnetic field code (SCB). This model was just extended to include electric field calculations, making it a unique, fully self-consistent, anisotropic ring current-atmosphere interactions model, RAM-SCB-E. Recently we investigated electromagnetic ion cyclotron (EMIC) instability in a local plasma using both linear theory and nonlinear hybrid simulations and derived a scaling formula that relates the saturation EMIC wave amplitude to initial plasma conditions. Global dynamic EMIC wave maps obtained with our RAM-SCB-E model using this scaling will be presented and compared with statistical models. These plasma waves can affect significantly both ion and electron precipitation into the atmosphere and the subsequent patterns of ionospheric conductance, as well as the global ring current dynamics.
The role of phase dynamics in a stochastic model of a passively advected scalar
NASA Astrophysics Data System (ADS)
Moradi, Sara; Anderson, Johan
2016-05-01
Collective synchronous motion of the phases is introduced in a model for the stochastic passive advection-diffusion of a scalar with external forcing. The model for the phase coupling dynamics follows the well known Kuramoto model paradigm of limit-cycle oscillators. The natural frequencies in the Kuramoto model are assumed to obey a given scale dependence through a dispersion relation of the drift-wave form -βk/1 +k2 , where β is a constant representing the typical strength of the gradient. The present aim is to study the importance of collective phase dynamics on the characteristic time evolution of the fluctuation energy and the formation of coherent structures. Our results show that the assumption of a fully stochastic phase state of turbulence is more relevant for high values of β, where we find that the energy spectrum follows a k-7 /2 scaling. Whereas for lower β there is a significant difference between a-synchronised and synchronised phase states, one could expect the formation of coherent modulations in the latter case.
Diffusive real-time dynamics of a particle with Berry curvature
NASA Astrophysics Data System (ADS)
Misaki, Kou; Miyashita, Seiji; Nagaosa, Naoto
2018-02-01
We study theoretically the influence of Berry phase on the real-time dynamics of the single particle focusing on the diffusive dynamics, i.e., the time dependence of the distribution function. Our model can be applied to the real-time dynamics of intraband relaxation and diffusion of optically excited excitons, trions, or particle-hole pair. We found that the dynamics at the early stage is deeply influenced by the Berry curvature in real space (B ), momentum space (Ω ), and also the crossed space between these two (C ). For example, it is found that Ω induces the rotation of the wave packet and causes the time dependence of the mean square displacement of the particle to be linear in time t at the initial stage; it is qualitatively different from the t3 dependence in the absence of the Berry curvature. It is also found that Ω and C modify the characteristic time scale of the thermal equilibration of momentum distribution. Moreover, the dynamics under various combinations of B ,Ω , and C shows singular behaviors such as the critical slowing down or speeding up of the momentum equilibration and the reversals of the direction of rotations. The relevance of our model for time-resolved experiments in transition metal dichalcogenides is also discussed.
The Dynamical Balance of the Brain at Rest
Deco, Gustavo; Corbetta, Maurizio
2014-01-01
We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530
DOE Office of Scientific and Technical Information (OSTI.GOV)
Preston, Benjamin L.; King, Anthony W.; Ernst, Kathleen M.
Human agency is an essential determinant of the dynamics of agroecosystems. However, the manner in which agency is represented within different approaches to agroecosystem modeling is largely contingent on the scales of analysis and the conceptualization of the system of interest. While appropriate at times, narrow conceptualizations of agroecosystems can preclude consideration for how agency manifests at different scales, thereby marginalizing processes, feedbacks, and constraints that would otherwise affect model results. Modifications to the existing modeling toolkit may therefore enable more holistic representations of human agency. Model integration can assist with the development of multi-scale agroecosystem modeling frameworks that capturemore » different aspects of agency. In addition, expanding the use of socioeconomic scenarios and stakeholder participation can assist in explicitly defining context-dependent elements of scale and agency. Finally, such approaches, however, should be accompanied by greater recognition of the meta agency of model users and the need for more critical evaluation of model selection and application.« less
Meta-ecosystem dynamics and functioning on finite spatial networks
Marleau, Justin N.; Guichard, Frédéric; Loreau, Michel
2014-01-01
The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory. PMID:24403323
Reaction Force of Micro-scale Liquid Droplets Constrained Between Parallel Plates through CFD
NASA Astrophysics Data System (ADS)
Free, Robert; Hekiri, Haider; Hawa, Takumi
2012-02-01
Micro-scale liquid droplets responding to depression between parallel plates are investigated analytically and numerically. The functional dependence of the reaction force accrued in such droplets on droplet size, surface tension, depression amount, and contact angle is explored. For both the 2D and 3D case, an analytical model is developed based on first principles. Computational fluid dynamics is then utilized to evaluate the validity of these models. The reaction force is highly nonlinear, initially increasing very slowly with increasing depression of the droplet, but eventually moving asymptotically to infinity. The force scales linearly with both the droplet free radius and surface tension of the liquid, but has a much more complicated dependence on the contact angle and depression. Explicit expressions for the reaction force have been determined, showing these dependencies. The 3D model has been largely supported by the CFD results. It very accurately predicts the reaction force on the upper plate as the droplet is crushed, accounting for the effect of contact angle, surface tension, and droplet size.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Qing; Leung, Lai-Yung R.; Rauscher, Sara
This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisturemore » transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the data aggregation effect in omega, thermodynamic changes become relatively significant in offsetting the effect of dynamics leading to reduce differences between the simulated and aggregated results. Compared to MPAS, the simulated stronger vertical motion with HOMME also results in larger resolution dependency. Compared to the simulation at fine resolution, the vertical motion during extremes is insufficiently resolved/parameterized at the coarser resolution even after accounting for the natural reduction in variability with coarser resolution, and this is more distinct in the simulation with HOMME. To reduce uncertainties in simulated precipitation extremes, future development in cloud parameterizations must address their sensitivity to spatial resolution as well as dynamical cores.« less
Evolution over time of the Milky Way's disc shape
NASA Astrophysics Data System (ADS)
Amôres, E. B.; Robin, A. C.; Reylé, C.
2017-06-01
Context. Galactic structure studies can be used as a path to constrain the scenario of formation and evolution of our Galaxy. The dependence with the age of stellar population parameters would be linked with the history of star formation and dynamical evolution. Aims: We aim to investigate the structures of the outer Galaxy, such as the scale length, disc truncation, warp and flare of the thin disc and study their dependence with age by using 2MASS data and a population synthesis model (the so-called Besançon Galaxy Model). Methods: We have used a genetic algorithm to adjust the parameters on the observed colour-magnitude diagrams at longitudes 80° ≤ ℓ ≤ 280° for | b | ≤ 5.5°. We explored parameter degeneracies and uncertainties. Results: We identify a clear dependence of the thin disc scale length, warp and flare shapes with age. The scale length is found to vary between 3.8 kpc for the youngest to about 2 kpc for the oldest. The warp shows a complex structure, clearly asymmetrical with a node angle changing with age from approximately 165° for old stars to 195° for young stars. The outer disc is also flaring with a scale height that varies by a factor of two between the solar neighbourhood and a Galactocentric distance of 12 kpc. Conclusions: We conclude that the thin disc scale length is in good agreement with the inside-out formation scenario and that the outer disc is not in dynamical equilibrium. The warp deformation with time may provide some clues to its origin.
NASA Astrophysics Data System (ADS)
Gross, Markus
2018-03-01
We consider a one-dimensional fluctuating interfacial profile governed by the Edwards–Wilkinson or the stochastic Mullins-Herring equation for periodic, standard Dirichlet and Dirichlet no-flux boundary conditions. The minimum action path of an interfacial fluctuation conditioned to reach a given maximum height M at a finite (first-passage) time T is calculated within the weak-noise approximation. Dynamic and static scaling functions for the profile shape are obtained in the transient and the equilibrium regime, i.e. for first-passage times T smaller or larger than the characteristic relaxation time, respectively. In both regimes, the profile approaches the maximum height M with a universal algebraic time dependence characterized solely by the dynamic exponent of the model. It is shown that, in the equilibrium regime, the spatial shape of the profile depends sensitively on boundary conditions and conservation laws, but it is essentially independent of them in the transient regime.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stershic, Andrew J.; Dolbow, John E.; Moës, Nicolas
The Thick Level-Set (TLS) model is implemented to simulate brittle media undergoing dynamic fragmentation. This non-local model is discretized by the finite element method with damage represented as a continuous field over the domain. A level-set function defines the extent and severity of damage, and a length scale is introduced to limit the damage gradient. Numerical studies in one dimension demonstrate that the proposed method reproduces the rate-dependent energy dissipation and fragment length observations from analytical, numerical, and experimental approaches. In conclusion, additional studies emphasize the importance of appropriate bulk constitutive models and sufficient spatial resolution of the length scale.
Tropical atmospheric circulations with humidity effects.
Hsia, Chun-Hsiung; Lin, Chang-Shou; Ma, Tian; Wang, Shouhong
2015-01-08
The main objective of this article is to study the effect of the moisture on the planetary scale atmospheric circulation over the tropics. The modelling we adopt is the Boussinesq equations coupled with a diffusive equation of humidity, and the humidity-dependent heat source is modelled by a linear approximation of the humidity. The rigorous mathematical analysis is carried out using the dynamic transition theory. In particular, we obtain mixed transitions, also known as random transitions, as described in Ma & Wang (2010 Discrete Contin. Dyn. Syst. 26 , 1399-1417. (doi:10.3934/dcds.2010.26.1399); 2011 Adv. Atmos. Sci. 28 , 612-622. (doi:10.1007/s00376-010-9089-0)). The analysis also indicates the need to include turbulent friction terms in the model to obtain correct convection scales for the large-scale tropical atmospheric circulations, leading in particular to the right critical temperature gradient and the length scale for the Walker circulation. In short, the analysis shows that the effect of moisture lowers the magnitude of the critical thermal Rayleigh number and does not change the essential characteristics of dynamical behaviour of the system.
Integrating deep Earth dynamics in paleogeographic reconstructions of Australia
NASA Astrophysics Data System (ADS)
Heine, Christian; Müller, R. Dietmar; Steinberger, Bernhard; DiCaprio, Lydia
2010-03-01
It is well documented that the Cenozoic progressive flooding of Australia, contemporaneous with a eustatic sea level fall, requires a downward tilting of the Australian Plate towards the SE Asian subduction system. Previously, this large-scale, mantle-convection driven dynamic topography effect has been approximated by computing the time-dependent vertical shifts and tilts of a plane, but the observed subsidence and uplift anomalies indicate a more complex interplay between time-dependent mantle convection and plate motion. We combine plate kinematics with a global mantle backward-advection model based on shear-wave mantle tomography, paleogeographic data, eustatic sea level estimates and basin stratigraphy to reconstruct the Australian flooding history for the last 70 Myrs on a continental scale. We compute time-dependent dynamic surface topography and continental inundation of a digital elevation model adjusted for sediment accumulation. Our model reveals two evolving dynamic topography lows, over which the Australian plate has progressively moved. We interpret the southern low to be caused by sinking slab material with an origin along the eastern Gondwana subduction zone in the Cretaceous, whereas the northern low, which first straddles northern Australia in the Oligocene, is mainly attributable to material subducted north and northeast of Australia. Our model accounts for the Paleogene exposure of the Gulf of Carpentaria region at a time when sea level was much higher than today, and explains anomalous Late Tertiary subsidence on Australia's northern, western and southern margins. The resolution of our model, which excludes short-wavelength mantle density anomalies and is restricted to depths larger than 220 km, is not sufficient to model the two well recorded episodes of major transgressions in South Australia in the Eocene and Miocene. However, the overall, long-wavelength spatio-temporal pattern of Australia's inundation record is well captured by combining our modelled dynamic topography with a recent eustatic sea level curve. We suggest that the apparent Late Cenozoic northward tilting of Australia was a stepwise function of South Australia first moving away northwards from the Gondwana subduction-related dynamic topography low in the Oligocene, now found under the Australian-Antarctic Discordance, followed by a drawing down of northern Australia as it overrode a slab burial ground now underlying much of the northern half of Australia, starting in the Miocene. Our model suggests that today's geography of Australia is strongly dependent on mantle forces. Without mantle convection, which draws Australia down by up to 300 m, nearly all of Australia's continental shelves would be exposed. We conclude that dissecting the interplay between eustasy and mantle-driven dynamic topography is critical for understanding hinterland uplift, basin subsidence, the formation and destruction of shallow epeiric seas and their facies distribution, but also for the evolution of petroleum systems.
Scale and the representation of human agency in the modeling of agroecosystems
Preston, Benjamin L.; King, Anthony W.; Ernst, Kathleen M.; ...
2015-07-17
Human agency is an essential determinant of the dynamics of agroecosystems. However, the manner in which agency is represented within different approaches to agroecosystem modeling is largely contingent on the scales of analysis and the conceptualization of the system of interest. While appropriate at times, narrow conceptualizations of agroecosystems can preclude consideration for how agency manifests at different scales, thereby marginalizing processes, feedbacks, and constraints that would otherwise affect model results. Modifications to the existing modeling toolkit may therefore enable more holistic representations of human agency. Model integration can assist with the development of multi-scale agroecosystem modeling frameworks that capturemore » different aspects of agency. In addition, expanding the use of socioeconomic scenarios and stakeholder participation can assist in explicitly defining context-dependent elements of scale and agency. Finally, such approaches, however, should be accompanied by greater recognition of the meta agency of model users and the need for more critical evaluation of model selection and application.« less
Translocation of polymers into crowded media with dynamic attractive nanoparticles.
Cao, Wei-Ping; Ren, Qing-Bao; Luo, Meng-Bo
2015-07-01
The translocation of polymers through a small pore into crowded media with dynamic attractive nanoparticles is simulated. Results show that the nanoparticles at the trans side can affect the translocation by influencing the free-energy landscape and the diffusion of polymers. Thus the translocation time τ is dependent on the polymer-nanoparticle attraction strength ɛ and the mobility of nanoparticles V. We observe a power-law relation of τ with V, but the exponent is dependent on ɛ and nanoparticle concentration. In addition, we find that the effect of attractive dynamic nanoparticles on the dynamics of polymers is dependent on the time scale. At a short time scale, subnormal diffusion is observed at strong attraction and the diffusion is slowed down by the dynamic nanoparticles. However, the diffusion of polymers is normal at a long time scale and the diffusion constant increases with the increase in V.
A fully dynamic magneto-rheological fluid damper model
NASA Astrophysics Data System (ADS)
Jiang, Z.; Christenson, R. E.
2012-06-01
Control devices can be used to dissipate the energy of a civil structure subjected to dynamic loading, thus reducing structural damage and preventing failure. Semiactive control devices have received significant attention in recent years. The magneto-rheological (MR) fluid damper is a promising type of semiactive device for civil structures due to its mechanical simplicity, inherent stability, high dynamic range, large temperature operating range, robust performance, and low power requirements. The MR damper is intrinsically nonlinear and rate-dependent, both as a function of the displacement across the MR damper and the command current being supplied to the MR damper. As such, to develop control algorithms that take maximum advantage of the unique features of the MR damper, accurate models must be developed to describe its behavior for both displacement and current. In this paper, a new MR damper model that includes a model of the pulse-width modulated (PWM) power amplifier providing current to the damper, a proposed model of the time varying inductance of the large-scale 200 kN MR dampers coils and surrounding MR fluid—a dynamic behavior that is not typically modeled—and a hyperbolic tangent model of the controllable force behavior of the MR damper is presented. Validation experimental tests are conducted with two 200 kN large-scale MR dampers located at the Smart Structures Technology Laboratory (SSTL) at the University of Illinois at Urbana-Champaign and the Lehigh University Network for Earthquake Engineering Simulation (NEES) facility. Comparison with experimental test results for both prescribed motion and current and real-time hybrid simulation of semiactive control of the MR damper shows that the proposed MR damper model can accurately predict the fully dynamic behavior of the large-scale 200 kN MR damper.
High Speed Dynamics in Brittle Materials
NASA Astrophysics Data System (ADS)
Hiermaier, Stefan
2015-06-01
Brittle Materials under High Speed and Shock loading provide a continuous challenge in experimental physics, analysis and numerical modelling, and consequently for engineering design. The dependence of damage and fracture processes on material-inherent length and time scales, the influence of defects, rate-dependent material properties and inertia effects on different scales make their understanding a true multi-scale problem. In addition, it is not uncommon that materials show a transition from ductile to brittle behavior when the loading rate is increased. A particular case is spallation, a brittle tensile failure induced by the interaction of stress waves leading to a sudden change from compressive to tensile loading states that can be invoked in various materials. This contribution highlights typical phenomena occurring when brittle materials are exposed to high loading rates in applications such as blast and impact on protective structures, or meteorite impact on geological materials. A short review on experimental methods that are used for dynamic characterization of brittle materials will be given. A close interaction of experimental analysis and numerical simulation has turned out to be very helpful in analyzing experimental results. For this purpose, adequate numerical methods are required. Cohesive zone models are one possible method for the analysis of brittle failure as long as some degree of tension is present. Their recent successful application for meso-mechanical simulations of concrete in Hopkinson-type spallation tests provides new insight into the dynamic failure process. Failure under compressive loading is a particular challenge for numerical simulations as it involves crushing of material which in turn influences stress states in other parts of a structure. On a continuum scale, it can be modeled using more or less complex plasticity models combined with failure surfaces, as will be demonstrated for ceramics. Models which take microstructural cracking directly into account may provide a more physics-based approach for compressive failure in the future.
The Effect of the Density Ratio on the Nonlinear Dynamics of the Unstable Fluid Interface
NASA Technical Reports Server (NTRS)
Abarzhi, S. I.
2003-01-01
Here we report multiple harmonic theoretical solutions for a complete system of conservation laws, which describe the large-scale coherent dynamics in RTI and RMI for fluids with a finite density ratio in the general three-dimensional case. The analysis yields new properties of the bubble front dynamics. In either RTI or RMI, the obtained dependencies of the bubble velocity and curvature on the density ratio differ qualitatively and quantitatively from those suggested by the models of Sharp (1984), Oron et al. (2001), and Goncharov (2002). We show explicitly that these models violate the conservation laws. For the first time, our theory reveals an important qualitative distinction between the dynamics of the RT and RM bubbles.
Aspects of extratropical synoptic-scale processes in opposing ENSO phases
NASA Astrophysics Data System (ADS)
Schwierz, C.; Wernli, H.; Hess, D.
2003-04-01
Energy and momentum provided by anomalous tropical heating/cooling affect the circulation on the global scale. Pacific Sea surface temperature anomalies strongly force local conditions in the equatorial Pacific, but are also known to change the climate in the extratropics, particularly over the American continent. The impact on more remote areas such as the Atlantic-European region is less clear. There the observed effects in both analyses and model studies show dependence on the resolution of the model/data, as well as on the time scales under consideration (Merkel and Latif, 2002; Compo et al., 2001). Most of the previous studies focus on larger-scale processes and seasonal time scales (or longer). Here we concentrate on the impact of opposing ENSO phases on extratropical synoptic-scale dynamics. The investigation is undertaken for the Niño/Niña events of 1972/3 and 1973/4 respectively, for 5 winter months (NDJFM) using ECMWF ERA40 data with 1o× 1o horizontal resolution and 60 vertical levels. The examination of the resulting differences in terms of standard dynamical fields (temperature, sea level pressure, precipitation, geopotential) is complemented with additional diagnostic fields (e.g. potential vorticity (PV), anti-/cyclone tracks and frequencies, PV streamers/cut-offs, blocking) in an attempt to gain more insight into aspects of extratropical synoptic-scale dynamical processes associated with ENSO SST anomalies.
Modeling the coupled return-spread high frequency dynamics of large tick assets
NASA Astrophysics Data System (ADS)
Curato, Gianbiagio; Lillo, Fabrizio
2015-01-01
Large tick assets, i.e. assets where one tick movement is a significant fraction of the price and bid-ask spread is almost always equal to one tick, display a dynamics in which price changes and spread are strongly coupled. We present an approach based on the hidden Markov model, also known in econometrics as the Markov switching model, for the dynamics of price changes, where the latent Markov process is described by the transitions between spreads. We then use a finite Markov mixture of logit regressions on past squared price changes to describe temporal dependencies in the dynamics of price changes. The model can thus be seen as a double chain Markov model. We show that the model describes the shape of the price change distribution at different time scales, volatility clustering, and the anomalous decrease of kurtosis. We calibrate our models based on Nasdaq stocks and we show that this model reproduces remarkably well the statistical properties of real data.
Multiscale modeling and simulation of microtubule-motor-protein assemblies
NASA Astrophysics Data System (ADS)
Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.
2015-12-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.
Multiscale modeling and simulation of microtubule-motor-protein assemblies.
Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J
2015-01-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.
Multiscale modeling and simulation of microtubule–motor-protein assemblies
Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.
2016-01-01
Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729
Molecular dynamics study of the isotropic-nematic quench.
Bradac, Z; Kralj, S; Zumer, S
2002-02-01
Effects of cylindrical and spherical confinement on the kinetics of the isotropic-nematic quench is studied numerically. The nematic liquid crystal structure was modeled by a modified induced-dipole--induced-dipole interaction. Molecules were allowed to wander around points of a hexagonal lattice. Brownian molecular dynamics was used in order to access macroscopic time scales. In the bulk we distinguish between the early, domain, and late stage regime. The early regime is characterized by the exponential growth of the nematic uniaxial order parameter. In the domain regime domains are clearly visible and the average nematic domain size xi(d) obeys the dynamical scaling law xi(d)-t(gamma). The late stage evolution is dominated by dynamics of individual defects. In a confined system the qualitative change of the scaling behavior appears when xi(d) becomes comparable to a typical linear dimension R of the confinement. In the confining regime (xi(d)>or=R) the scaling coefficient gamma depends on the details of the confinement and also the final equilibrium nematic structure. The domain growth is well described with the Kibble-Zurek mechanism.
NASA Astrophysics Data System (ADS)
Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Schneider, Tapio; Teixeira, João.
2018-03-01
Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection—such as that they adjust instantaneously to changes in resolved-scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass-flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.
Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Teixeira, João
2018-01-01
Abstract Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle. PMID:29780442
Helium segregation on surfaces of plasma-exposed tungsten
Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...
2016-01-21
Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less
Helium segregation on surfaces of plasma-exposed tungsten
NASA Astrophysics Data System (ADS)
Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.
2016-02-01
We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1 ⩽ n ⩽ 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.
An action potential-driven model of soleus muscle activation dynamics for locomotor-like movements
NASA Astrophysics Data System (ADS)
Kim, Hojeong; Sandercock, Thomas G.; Heckman, C. J.
2015-08-01
Objective. The goal of this study was to develop a physiologically plausible, computationally robust model for muscle activation dynamics (A(t)) under physiologically relevant excitation and movement. Approach. The interaction of excitation and movement on A(t) was investigated comparing the force production between a cat soleus muscle and its Hill-type model. For capturing A(t) under excitation and movement variation, a modular modeling framework was proposed comprising of three compartments: (1) spikes-to-[Ca2+]; (2) [Ca2+]-to-A; and (3) A-to-force transformation. The individual signal transformations were modeled based on physiological factors so that the parameter values could be separately determined for individual modules directly based on experimental data. Main results. The strong dependency of A(t) on excitation frequency and muscle length was found during both isometric and dynamically-moving contractions. The identified dependencies of A(t) under the static and dynamic conditions could be incorporated in the modular modeling framework by modulating the model parameters as a function of movement input. The new modeling approach was also applicable to cat soleus muscles producing waveforms independent of those used to set the model parameters. Significance. This study provides a modeling framework for spike-driven muscle responses during movement, that is suitable not only for insights into molecular mechanisms underlying muscle behaviors but also for large scale simulations.
Testing the paradigms of the glass transition in colloids
NASA Astrophysics Data System (ADS)
Zia, Roseanna; Wang, Jialun; Peng, Xiaoguang; Li, Qi; McKenna, Gregory
2017-11-01
Many molecular liquids freeze upon fast enough cooling. This so-called glass state is path dependent and out of equilibrium, as measured by the Kovacs signature experiments, i.e. intrinsic isotherms, asymmetry of approach and memory effect. The reasons for this path- and time-dependence are not fully understood, due to fast molecular relaxations. Colloids provide a natural way to model such behavior, owing to disparity in colloidal versus solvent time scales that can slow dynamics. To shed light on the ambiguity of glass transition, we study via large-scale dynamic simulation of hard-sphere colloidal glass after volume-fraction jumps, where particle size increases at fixed system volume followed by protocols of the McKenna-Kovacs signature experiments. During and following each jump, the positions, velocities, and particle-phase stress are tracked and utilized to characterize relaxation time scales. The impact of both quench depth and quench rate on arrested dynamics and ``state'' variables is explored. In addition, we expand our view to various structural signatures, and rearrangement mechanism is proposed. The results provide insight into not only the existence of an ``ideal'' glass transition, but also the role of structure in such a dense amorphous system.
Bjorgaard, J. A.; Nelson, T.; Kalinin, K.; ...
2015-04-28
In this study, an efficient method of treating solvent effects in excited state molecular dynamics (ESMD) is implemented and tested by exploring the solvatochromic effects in substituted p-phenylene vinylene oligomers. A continuum solvent model is used which has very little computational overhead. This allows simulations of ESMD with solvent effects on the scale of hundreds of picoseconds for systems of up to hundreds of atoms. At these time scales, solvatochromic shifts in fluoresence spectra can be described. Solvatochromic shifts in absorption and fluorescence spectra from ESMD are compared with time-dependent density functional theory calculations and experiments.
Random walkers with extreme value memory: modelling the peak-end rule
NASA Astrophysics Data System (ADS)
Harris, Rosemary J.
2015-05-01
Motivated by the psychological literature on the ‘peak-end rule’ for remembered experience, we perform an analysis within a random walk framework of a discrete choice model where agents’ future choices depend on the peak memory of their past experiences. In particular, we use this approach to investigate whether increased noise/disruption always leads to more switching between decisions. Here extreme value theory illuminates different classes of dynamics indicating that the long-time behaviour is dependent on the scale used for reflection; this could have implications, for example, in questionnaire design.
Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction
NASA Technical Reports Server (NTRS)
Li, Zhijin; Chao, Yi; Li, P. Peggy
2012-01-01
A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.
Pradhan, Ekadashi; Magyar, Rudolph J; Akimov, Alexey V
2016-11-30
Understanding the dynamics of electron-ion energy transfer in warm dense (WD) matter is important to the measurement of equation of state (EOS) properties and for understanding the energy balance in dynamic simulations. In this work, we present a comprehensive investigation of nonadiabatic electron relaxation and thermal excitation dynamics in aluminum under high pressure and temperature. Using quantum-classical trajectory surface hopping approaches, we examine the role of nonadiabatic couplings and electronic decoherence in electron-nuclear energy transfer in WD aluminum. The computed timescales range from 400 fs to 4.0 ps and are consistent with existing experimental studies. We have derived general scaling relationships between macroscopic parameters of WD systems such as temperature or mass density and the timescales of energy redistribution between quantum and classical degrees of freedom. The scaling laws are supported by computational results. We show that electronic decoherence plays essential role and can change the functional dependencies qualitatively. The established scaling relationships can be of use in modelling of WD matter.
Hysteresis, regime shifts, and non-stationarity in aquifer recharge-storage-discharge systems
NASA Astrophysics Data System (ADS)
Klammler, Harald; Jawitz, James; Annable, Michael; Hatfield, Kirk; Rao, Suresh
2016-04-01
Based on physical principles and geological information we develop a parsimonious aquifer model for Silver Springs, one of the largest karst springs in Florida. The model structure is linear and time-invariant with recharge, aquifer head (storage) and spring discharge as dynamic variables at the springshed (landscape) scale. Aquifer recharge is the hydrological driver with trends over a range of time scales from seasonal to multi-decadal. The freshwater-saltwater interaction is considered as a dynamic storage mechanism. Model results and observed time series show that aquifer storage causes significant rate-dependent hysteretic behavior between aquifer recharge and discharge. This leads to variable discharge per unit recharge over time scales up to decades, which may be interpreted as a gradual and cyclic regime shift in the aquifer drainage behavior. Based on field observations, we further amend the aquifer model by assuming vegetation growth in the spring run to be inversely proportional to stream velocity and to hinder stream flow. This simple modification introduces non-linearity into the dynamic system, for which we investigate the occurrence of rate-independent hysteresis and of different possible steady states with respective regime shifts between them. Results may contribute towards explaining observed non-stationary behavior potentially due to hydrological regime shifts (e.g., triggered by gradual, long-term changes in recharge or single extreme events) or long-term hysteresis (e.g., caused by aquifer storage). This improved understanding of the springshed hydrologic response dynamics is fundamental for managing the ecological, economic and social aspects at the landscape scale.
Menon, Binuraj R K; Menon, Navya; Fisher, Karl; Rigby, Stephen E J; Leys, David; Scrutton, Nigel S
2015-01-01
How cobalamin-dependent enzymes promote C–Co homolysis to initiate radical catalysis has been debated extensively. For the pyridoxal 5′-phosphate and cobalamin-dependent enzymes lysine 5,6-aminomutase and ornithine 4,5-aminomutase (OAM), large-scale re-orientation of the cobalamin-binding domain linked to C–Co bond breakage has been proposed. In these models, substrate binding triggers dynamic sampling of the B12-binding Rossmann domain to achieve a catalytically competent ‘closed’ conformational state. In ‘closed’ conformations of OAM, Glu338 is thought to facilitate C–Co bond breakage by close association with the cobalamin adenosyl group. We investigated this using stopped-flow continuous-wave photolysis, viscosity dependence kinetic measurements, and electron paramagnetic resonance spectroscopy of a series of Glu338 variants. We found that substrate-induced C–Co bond homolysis is compromised in Glu388 variant forms of OAM, although photolysis of the C–Co bond is not affected by the identity of residue 338. Electrostatic interactions of Glu338 with the 5′-deoxyadenosyl group of B12 potentiate C–Co bond homolysis in ‘closed’ conformations only; these conformations are unlocked by substrate binding. Our studies extend earlier models that identified a requirement for large-scale motion of the cobalamin domain. Our findings indicate that large-scale motion is required to pre-organize the active site by enabling transient formation of ‘closed’ conformations of OAM. In ‘closed’ conformations, Glu338 interacts with the 5′-deoxyadenosyl group of cobalamin. This interaction is required to potentiate C–Co homolysis, and is a crucial component of the approximately 1012 rate enhancement achieved by cobalamin-dependent enzymes for C–Co bond homolysis. PMID:25627283
Force-extension behavior of DNA in the presence of DNA-bending nucleoid associated proteins
NASA Astrophysics Data System (ADS)
Dahlke, K.; Sing, C. E.
2018-02-01
Interactions between nucleoid associated proteins (NAPs) and DNA affect DNA polymer conformation, leading to phenomena such as concentration dependent force-extension behavior. These effects, in turn, also impact the local binding behavior of the protein, such as high forces causing proteins to unbind, or proteins binding favorably to locally bent DNA. We develop a coarse-grained NAP-DNA simulation model that incorporates both force- and concentration-dependent behaviors, in order to study the interplay between NAP binding and DNA conformation. This model system includes multi-state protein binding and unbinding, motivated by prior work, but is now dependent on the local structure of the DNA, which is related to external forces acting on the DNA strand. We observe the expected qualitative binding behavior, where more proteins are bound at lower forces than at higher forces. Our model also includes NAP-induced DNA bending, which affects DNA elasticity. We see semi-quantitative matching of our simulated force-extension behavior to the reported experimental data. By using a coarse-grained simulation, we are also able to look at non-equilibrium behaviors, such as dynamic extension of a DNA strand. We stretch a DNA strand at different rates and at different NAP concentrations to observe how the time scales of the system (such as pulling time and unbinding time) work in concert. When these time scales are similar, we observe measurable rate-dependent changes in the system, which include the number of proteins bound and the force required to extend the DNA molecule. This suggests that the relative time scales of different dynamic processes play an important role in the behavior of NAP-DNA systems.
Scaling and efficiency determine the irreversible evolution of a market
Baldovin, F.; Stella, A. L.
2007-01-01
In setting up a stochastic description of the time evolution of a financial index, the challenge consists in devising a model compatible with all stylized facts emerging from the analysis of financial time series and providing a reliable basis for simulating such series. Based on constraints imposed by market efficiency and on an inhomogeneous-time generalization of standard simple scaling, we propose an analytical model which accounts simultaneously for empirical results like the linear decorrelation of successive returns, the power law dependence on time of the volatility autocorrelation function, and the multiscaling associated to this dependence. In addition, our approach gives a justification and a quantitative assessment of the irreversible character of the index dynamics. This irreversibility enters as a key ingredient in a novel simulation strategy of index evolution which demonstrates the predictive potential of the model.
Body-freedom flutter of a 1/2-scale forward-swept-wing model, an experimental and analytical study
NASA Technical Reports Server (NTRS)
Chipman, R.; Rauch, F.; Rimer, M.; Muniz, B.
1984-01-01
The aeroelastic phenomenon known as body-freedom flutter (BFF), a dynamic instability involving aircraft-pitch and wing-bending motions which, though rarely experienced on conventional vehicles, is characteristic of forward swept wing (FSW) aircraft was investigated. Testing was conducted in the Langley transonic dynamics tunnel on a flying, cable-mounted, 1/2-scale model of a FSW configuration with and without relaxed static stability (RSS). The BFF instability boundaries were found to occur at significantly lower airspeeds than those associated with aeroelastic wing divergence on the same model. For those cases with RSS, a canard-based stability augmentation system (SAS) was incorporated in the model. This SAS was designed using aerodynamic data measured during a preliminary tunnel test in which the model was attached to a force balance. Data from the subsequent flutter test indicated that BFF speed was not dependent on open-loop static margin but, rather, on the equivalent closed-loop dynamics provided by the SAS. Servo-aeroelastic stability analyses of the flying model were performed using a computer code known as SEAL and predicted the onset of BFF reasonably well.
PIV measurements of in-cylinder, large-scale structures in a water-analogue Diesel engine
NASA Astrophysics Data System (ADS)
Kalpakli Vester, A.; Nishio, Y.; Alfredsson, P. H.
2016-11-01
Swirl and tumble are large-scale structures that develop in an engine cylinder during the intake stroke. Their structure and strength depend on the design of the inlet ports and valves, but also on the valve lift history. Engine manufacturers make their design to obtain a specific flow structure that is assumed to give the best engine performance. Despite many efforts, there are still open questions, such as how swirl and tumble depend on the dynamics of the valves/piston as well as how cycle-to-cycle variations should be minimized. In collaboration with Swedish vehicle industry we perform PIV measurements of the flow dynamics during the intake stroke inside a cylinder of a water-analogue engine model having the same geometrical characteristics as a typical truck Diesel engine. Water can be used since during the intake stroke the flow is nearly incompressible. The flow from the valves moves radially outwards, hits the vertical walls of the cylinder, entrains surrounding fluid, moves along the cylinder walls and creates a central backflow, i.e. a tumble motion. Depending on the port and valve design and orientation none, low, or high swirl can be established. For the first time, the effect of the dynamic motion of the piston/valves on the large-scale structures is captured. Supported by the Swedish Energy Agency, Scania CV AB and Volvo GTT, through the FFI program.
NASA Astrophysics Data System (ADS)
Harman, C. J.
2014-12-01
Models that faithfully represent spatially-integrated hydrologic transport through the critical zone at sub-watershed scales are essential building blocks for large-scale models of land use and climate controls on non-point source contaminant delivery. A particular challenge facing these models is the need to represent the delay between inputs of soluble contaminants (such as nitrate) at the field scale, and the solute load that appears in streams. Recent advances in the theory of time-variable transit time distributions (e.g. Botter et al., GRL 38(L11403), 2011) have provided a rigorous framework for representing conservative solute transport and its coupling to hydrologic variability and partitioning. Here I will present a reformulation of this framework that offers several distinct advantages over existing formulations: 1) the derivation of the governing conservation equation is simple and intuitive, 2) the closure relations are expressed in a convenient and physically meaningful way as probability distributions Ω(ST)Omega(S_T) over the storage ranked by age STS_T, and 3) changes in transport behavior determined by storage-dependent dilution and flow-path dynamics (as distinct from those due only to changes in the rates and partitioning of water flux) are completely encapsulated by these probability distributions. The framework has been implemented to model to the rich dataset of long-term stream and precipitation chloride from the Plynlimon watershed in Wales, UK. With suitable choices for the functional form of the closure relationships, only a small number of free parameters are required to reproduce the observed chloride dynamics as well as previous models with many more parameters, including reproducing the observed fractal 1/f filtering of the streamflow chloride variability. The modeled transport dynamics are sensitive to the input precipitation variability and water balance partitioning to evapotranspiration. Apparent storage-dependent age-sampling suggests that the model can account for shifts in flow pathways across high and low flows. This approach suggests a path forward for catchment-scale coupled flow and transport modeling.
Localization and elasticity in entangled polymer liquids as a mesoscopic glass transition
NASA Astrophysics Data System (ADS)
Schweizer, Kenneth
2010-03-01
The reptation-tube model is widely viewed as the correct zeroth order model for entangled linear polymer dynamics under quiescent conditions. Its key ansatz is the existence of a mesoscopic dynamical length scale that prohibits transverse chain motion beyond a tube diameter of order 3-10 nm. However, the theory is phenomenological and lacks a microscopic foundation, and many fundamental questions remain unanswered. These include: (i) where does the confining tube field come from and can it be derived from statistical mechanics? (ii) what is the microscopic origin of the magnitude, and power law scaling with concentration and packing length, of the plateau shear modulus? (iii) is the tube diameter time-dependent? (iv) does the confinement field contribute to elasticity ? (v) do entanglement constraints have a finite strength? Building on our new force-level theories for the dynamical crossover and activated barrier hopping in glassy colloidal suspensions and polymer melts, a first principles self-consistent theory has been developed for entangled polymers. Its basic physical elements, and initial results that address the questions posed above, will be presented. The key idea is that beyond a critical degree of polymerization, the chain connectivity and excluded volume induced intermolecular correlation hole drives temporary localization on an intermediate length scale resulting in a mesoscopic ``ideal kinetic glass transition.'' Large scale isotropic motion is effectively quenched due to the emergence of chain length dependent entropic barriers. However, the barrier height is not infinite, resulting in softening of harmonic localization at large displacements, temporal increase of the confining length scale, and a finite strength of entanglement constraints which can be destroyed by applied stress.
NASA Astrophysics Data System (ADS)
Wang, S.; Sobel, A. H.; Nie, J.
2015-12-01
Two Madden Julian Oscillation (MJO) events were observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign. Precipitation rates and large-scale vertical motion profiles derived from the DYNAMO northern sounding array are simulated in a small-domain cloud-resolving model using parameterized large-scale dynamics. Three parameterizations of large-scale dynamics --- the conventional weak temperature gradient (WTG) approximation, vertical mode based spectral WTG (SWTG), and damped gravity wave coupling (DGW) --- are employed. The target temperature profiles and radiative heating rates are taken from a control simulation in which the large-scale vertical motion is imposed (rather than directly from observations), and the model itself is significantly modified from that used in previous work. These methodological changes lead to significant improvement in the results.Simulations using all three methods, with imposed time -dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large-scale vertical motion profile, however. WTG produces the most top-heavy and noisy profiles, while DGW's is smoother with a peak in midlevels. SWTG produces a smooth profile, somewhere between WTG and DGW, and in better agreement with observations than either of the others. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top-heaviness of large-scale vertical motion during the MJO active phases, while experiments in which the effect of cloud on radiation are disabled indicate that cloud-radiative interaction significantly amplifies the MJO. Experiments in which interactive radiation is used produce poorer agreement with observation than those with imposed time-varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and cloud-radiative feedback to the dynamics of the MJO, as well as to accurate simulation and prediction of it in models.
NASA Astrophysics Data System (ADS)
Botsford, L. W.; Moloney, C. L.; Hastings, A.; Largier, J. L.; Powell, T. M.; Higgins, K.; Quinn, J. F.
We synthesize the results of several modelling studies that address the influence of variability in larval transport and survival on the dynamics of marine metapopulations distributed along a coast. Two important benthic invertebrates in the California Current System (CCS), the Dungeness crab and the red sea urchin, are used as examples of the way in which physical oceanographic conditions can influence stability, synchrony and persistence of meroplanktonic metapopulations. We first explore population dynamics of subpopulations and metapopulations. Even without environmental forcing, isolated local subpopulations with density-dependence can vary on time scales roughly twice the generation time at high adult survival, shifting to annual time scales at low survivals. The high frequency behavior is not seen in models of the Dungeness crab, because of their high adult survival rates. Metapopulations with density-dependent recruitment and deterministic larval dispersal fluctuate in an asynchronous fashion. Along the coast, abundance varies on spatial scales which increase with dispersal distance. Coastwide, synchronous, random environmental variability tends to synchronize these metapopulations. Climate change could cause a long-term increase or decrease in mean larval survival, which in this model leads to greater synchrony or extinction respectively. Spatially managed metapopulations of red sea urchins go extinct when distances between harvest refugia become greater than the scale of larval dispersal. All assessments of population dynamics indicate that metapopulation behavior in general dependes critically on the temporal and spatial nature of larval dispersal, which is largely determined by physical oceanographic conditions. We therfore explore physical influences on larval dispersal patterns. Observed trends in temperature and salinity applied to laboratory-determined responses indicate that natural variability in temperature and salinity can lead to variability in larval development period on interannual (50%), intra-annual (20%) and latitudinal (200%) scales. Variability in development period significantly influences larval survival and, thus, net transport. Larval drifters that undertake diel vertical migration in a primitive equation model of coastal circulation (SPEM) demonstrate the importance of vertical migration in determining horizontal transport. Empirically derived estimates of the effects of wind forcing on larval transport of vertically migrating larvae (wind drift when near the surface and Ekman transport below the surface) match cross-shelf distributions in 4 years of existing larval data. We use a one-dimensional advection-diffusion model, which includes intra-annual timing of cross-shelf flows in the CCS, to explore the combined effects on settlement: (1) temperature- and salinity-dependent development and survival rates and (2) possible horizontal transport due to vertical migration of crab larvae. Natural variability in temperature, wind forcing, and the timing of the spring transition can cause the observed variability in recruitment. We conclude that understanding the dynamics of coastally distributed metapopulations in response to physically-induced variability in larval dispersal will be a critical step in assessing the effects of climate change on marine populations.
Nonlinear calculations of the time evolution of black hole accretion disks
NASA Technical Reports Server (NTRS)
Luo, C.
1994-01-01
Based on previous works on black hole accretion disks, I continue to explore the disk dynamics using the finite difference method to solve the highly nonlinear problem of time-dependent alpha disk equations. Here a radially zoned model is used to develop a computational scheme in order to accommodate functional dependence of the viscosity parameter alpha on the disk scale height and/or surface density. This work is based on the author's previous work on the steady disk structure and the linear analysis of disk dynamics to try to apply to x-ray emissions from black candidates (i.e., multiple-state spectra, instabilities, QPO's, etc.).
Species and Scale Dependence of Bacterial Motion Dynamics
NASA Astrophysics Data System (ADS)
Sund, N. L.; Yang, X.; Parashar, R.; Plymale, A.; Hu, D.; Kelly, R.; Scheibe, T. D.
2017-12-01
Many metal reducing bacteria are motile with their motion characteristics described by run-and-tumble behavior exhibiting series of flights (jumps) and waiting (residence) time spanning a wide range of values. Accurate models of motility allow for improved design and evaluation of in-situ bioremediation in the subsurface. While many bioremediation models neglect the motion of the bacteria, others treat motility using an advection dispersion equation, which assumes that the motion of the bacteria is Brownian.The assumption of Brownian motion to describe motility has enormous implications on predictive capabilities of bioremediation models, yet experimental evidence of this assumption is mixed [1][2][3]. We hypothesize that this is due to the species and scale dependence of the motion dynamics. We test our hypothesis by analyzing videos of motile bacteria of five different species in open domains. Trajectories of individual cells ranging from several seconds to few minutes in duration are extracted in neutral conditions (in the absence of any chemical gradient). The density of the bacteria is kept low so that the interaction between the bacteria is minimal. Preliminary results show a transition from Fickian (Brownian) to non-Fickian behavior for one species of bacteria (Pelosinus) and persistent Fickian behavior of another species (Geobacter).Figure: Video frames of motile bacteria with the last 10 seconds of their trajectories drawn in red. (left) Pelosinus and (right) Geobacter.[1] Ariel, Gil, et al. "Swarming bacteria migrate by Lévy Walk." Nature Communications 6 (2015).[2] Saragosti, Jonathan, Pascal Silberzan, and Axel Buguin. "Modeling E. coli tumbles by rotational diffusion. Implications for chemotaxis." PloS one 7.4 (2012): e35412.[3] Wu, Mingming, et al. "Collective bacterial dynamics revealed using a three-dimensional population-scale defocused particle tracking technique." Applied and Environmental Microbiology 72.7 (2006): 4987-4994.
Mathematical modeling of alignment dynamics in active motor-filament systems
NASA Astrophysics Data System (ADS)
Swaminathan, Sumanth
The formation of the cytoskeleton, via motor-mediated microtubule self-organization, is an important subject of study in the biological sciences as well as in nonequilibrium, soft matter physics. Accurate modeling of the dynamics is a formidable task as it involves intrinsic nonlinearities, structural anisotropies, nonequilibrium processes, and a broad window of time scales, length scales, and densities. In this thesis, we study the ordering dynamics and pattern formations arising from motor-mediated microtubule self-organization in dilute and semi-dilute filament solutions. In the dilute case, we use a probabilistic model in which microtubules interact through motor induced, inelastic binary collisions. This model shows that initially disordered filament solutions exhibit an ordering transition resulting in the emergence of well aligned rod bundles. We study the existence and dynamic interaction of microtubule bundles analytically and numerically. Our results show a long term attraction and coalescing of bundles indicating a clear coarsening in the system; microtubule bundles concentrate into fewer orientations on a slow logarithmic time scale. In the semi-dilute case, multiple motors can bind a filament to several others and, for a critical motor density, induce a transition to an ordered state with a nonzero mean orientation. We develop a spatially homogeneous, mean-field theory that explicitly accounts for motor forcing and thermal fluctuations which enter into the model as multiplicative and additive noises respectively. Our model further incorporates a force-dependent detachment rate of motors, which in turn affects the mean and the fluctuations of the net force acting on a filament. We demonstrate that the transition to the oriented state changes from second order to first order when the force-dependent detachment becomes important. In our final analysis, we add complex spatial inhomogeneities to our mean field theory. The revised model consists of a system of stochastic differential equations governing the time evolution of the orientation and center of mass of each filament; microtubules translate and rotate under the influence of motor forces and intrinsic thermal fluctuations. We show through a molecular dynamics type stochastic simulation that initially disordered systems of microtubules exhibit an ordering transition resulting in the formation of bundles and vortices. This finding is compared with previous binary interaction and hydrodynamic models and shown to be consistent with in vitro experiments on motor-mediated self-organization of microtubules and actin filaments.
Variable horizon in a peridynamic medium
Silling, Stewart A.; Littlewood, David J.; Seleson, Pablo
2015-12-10
Here, a notion of material homogeneity is proposed for peridynamic bodies with variable horizon but constant bulk properties. A relation is derived that scales the force state according to the position-dependent horizon while keeping the bulk properties unchanged. Using this scaling relation, if the horizon depends on position, artifacts called ghost forces may arise in a body under a homogeneous deformation. These artifacts depend on the second derivative of the horizon and can be reduced by employing a modified equilibrium equation using a new quantity called the partial stress. Bodies with piecewise constant horizon can be modeled without ghost forcesmore » by using a simpler technique called a splice. As a limiting case of zero horizon, both the partial stress and splice techniques can be used to achieve local-nonlocal coupling. Computational examples, including dynamic fracture in a one-dimensional model with local-nonlocal coupling, illustrate the methods.« less
A model-free characterization of recurrences in stationary time series
NASA Astrophysics Data System (ADS)
Chicheportiche, Rémy; Chakraborti, Anirban
2017-05-01
Study of recurrences in earthquakes, climate, financial time-series, etc. is crucial to better forecast disasters and limit their consequences. Most of the previous phenomenological studies of recurrences have involved only a long-ranged autocorrelation function, and ignored the multi-scaling properties induced by potential higher order dependencies. We argue that copulas is a natural model-free framework to study non-linear dependencies in time series and related concepts like recurrences. Consequently, we arrive at the facts that (i) non-linear dependences do impact both the statistics and dynamics of recurrence times, and (ii) the scaling arguments for the unconditional distribution may not be applicable. Hence, fitting and/or simulating the intertemporal distribution of recurrence intervals is very much system specific, and cannot actually benefit from universal features, in contrast to the previous claims. This has important implications in epilepsy prognosis and financial risk management applications.
The scaling of contact rates with population density for the infectious disease models.
Hu, Hao; Nigmatulina, Karima; Eckhoff, Philip
2013-08-01
Contact rates and patterns among individuals in a geographic area drive transmission of directly-transmitted pathogens, making it essential to understand and estimate contacts for simulation of disease dynamics. Under the uniform mixing assumption, one of two mechanisms is typically used to describe the relation between contact rate and population density: density-dependent or frequency-dependent. Based on existing evidence of population threshold and human mobility patterns, we formulated a spatial contact model to describe the appropriate form of transmission with initial growth at low density and saturation at higher density. We show that the two mechanisms are extreme cases that do not capture real population movement across all scales. Empirical data of human and wildlife diseases indicate that a nonlinear function may work better when looking at the full spectrum of densities. This estimation can be applied to large areas with population mixing in general activities. For crowds with unusually large densities (e.g., transportation terminals, stadiums, or mass gatherings), the lack of organized social contact structure deviates the physical contacts towards a special case of the spatial contact model - the dynamics of kinetic gas molecule collision. In this case, an ideal gas model with van der Waals correction fits well; existing movement observation data and the contact rate between individuals is estimated using kinetic theory. A complete picture of contact rate scaling with population density may help clarify the definition of transmission rates in heterogeneous, large-scale spatial systems. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
2014-07-01
of models for variable conditions: – Use implicit models to eliminate constraint of sequence of fast time scales: c, ve, – Price to pay: lack...collisions: – Elastic – Bragiinski terms – Inelastic – warning! Rates depend on both T and relative velocity – Multi-fluid CR model from...merge/split for particle management, efficient sampling, inelastic collisions … – Level grouping schemes of electronic states, for dynamical coarse
Rayleigh-Taylor mixing with time-dependent acceleration
NASA Astrophysics Data System (ADS)
Abarzhi, Snezhana
2016-10-01
We extend the momentum model to describe Rayleigh-Taylor (RT) mixing driven by a time-dependent acceleration. The acceleration is a power-law function of time, similarly to astrophysical and plasma fusion applications. In RT flow the dynamics of a fluid parcel is driven by a balance per unit mass of the rates of momentum gain and loss. We find analytical solutions in the cases of balanced and imbalanced gains and losses, and identify their dependence on the acceleration exponent. The existence is shown of two typical regimes of self-similar RT mixing-acceleration-driven Rayleigh-Taylor-type and dissipation-driven Richtymer-Meshkov-type with the latter being in general non-universal. Possible scenarios are proposed for transitions from the balanced dynamics to the imbalanced self-similar dynamics. Scaling and correlations properties of RT mixing are studied on the basis of dimensional analysis. Departures are outlined of RT dynamics with time-dependent acceleration from canonical cases of homogeneous turbulence as well as blast waves with first and second kind self-similarity. The work is supported by the US National Science Foundation.
Rayleigh-Taylor mixing with space-dependent acceleration
NASA Astrophysics Data System (ADS)
Abarzhi, Snezhana
2016-11-01
We extend the momentum model to describe Rayleigh-Taylor (RT) mixing driven by a space-dependent acceleration. The acceleration is a power-law function of space coordinate, similarly to astrophysical and plasma fusion applications. In RT flow the dynamics of a fluid parcel is driven by a balance per unit mass of the rates of momentum gain and loss. We find analytical solutions in the cases of balanced and imbalanced gains and losses, and identify their dependence on the acceleration exponent. The existence is shown of two typical sub-regimes of self-similar RT mixing - the acceleration-driven Rayleigh-Taylor-type mixing and dissipation-driven Richtymer-Meshkov-type mixing with the latter being in general non-universal. Possible scenarios are proposed for transitions from the balanced dynamics to the imbalanced self-similar dynamics. Scaling and correlations properties of RT mixing are studied on the basis of dimensional analysis. Departures are outlined of RT dynamics with space-dependent acceleration from canonical cases of homogeneous turbulence as well as blast waves with first and second kind self-similarity. The work is supported by the US National Science Foundation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richert, Ranko
2016-03-21
A model of non-linear dielectric polarization is studied in which the field induced entropy change is the source of polarization dependent retardation time constants. Numerical solutions for the susceptibilities of the system are obtained for parameters that represent the dynamic and thermodynamic behavior of glycerol. The calculations for high amplitude sinusoidal fields show a significant enhancement of the steady state loss for frequencies below that of the low field loss peak. Also at relatively low frequencies, the third harmonic susceptibility spectrum shows a “hump,” i.e., a maximum, with an amplitude that increases with decreasing temperature. Both of these non-linear effectsmore » are consistent with experimental evidence. While such features have been used to conclude on a temperature dependent number of dynamically correlated particles, N{sub corr}, the present result demonstrates that the third harmonic susceptibility display a peak with an amplitude that tracks the variation of the activation energy in a model that does not involve dynamical correlations or spatial scales.« less
NASA Astrophysics Data System (ADS)
Liang, Wenkel
This dissertation consists of two general parts: (I) developments of optimization algorithms (both nuclear and electronic degrees of freedom) for time-independent molecules and (II) novel methods, first-principle theories and applications in time dependent molecular structure modeling. In the first part, we discuss in specific two new algorithms for static geometry optimization, the eigenspace update (ESU) method in nonredundant internal coordinate that exhibits an enhanced performace with up to a factor of 3 savings in computational cost for large-sized molecular systems; the Car-Parrinello density matrix search (CP-DMS) method that enables direct minimization of the SCF energy as an effective alternative to conventional diagonalization approach. For the second part, we consider the time dependence and first presents two nonadiabatic dynamic studies that model laser controlled molecular photo-dissociation for qualitative understandings of intense laser-molecule interaction, using ab initio direct Ehrenfest dynamics scheme implemented with real-time time-dependent density functional theory (RT-TDDFT) approach developed in our group. Furthermore, we place our special interest on the nonadiabatic electronic dynamics in the ultrafast time scale, and presents (1) a novel technique that can not only obtain energies but also the electron densities of doubly excited states within a single determinant framework, by combining methods of CP-DMS with RT-TDDFT; (2) a solvated first-principles electronic dynamics method by incorporating the polarizable continuum solvation model (PCM) to RT-TDDFT, which is found to be very effective in describing the dynamical solvation effect in the charge transfer process and yields a consistent absorption spectrum in comparison to the conventional linear response results in solution. (3) applications of the PCM-RT-TDDFT method to study the intramolecular charge-transfer (CT) dynamics in a C60 derivative. Such work provides insights into the characteristics of ultrafast dynamics in photoexcited fullerene derivatives, and aids in the rational design for pre-dissociative exciton in the intramolecular CT process in organic solar cells.
NASA Astrophysics Data System (ADS)
Koochi, Ali; Hosseini-Toudeshky, Hossein; Abadyan, Mohamadreza
2018-03-01
Herein, a corrected theoretical model is proposed for modeling the static and dynamic behavior of electrostatically actuated narrow-width nanotweezers considering the correction due to finite dimensions, size dependency and surface energy. The Gurtin-Murdoch surface elasticity in conjunction with the modified couple stress theory is employed to consider the coupling effect of surface stresses and size phenomenon. In addition, the model accounts for the external force corrections by incorporating the impact of narrow width on the distribution of Casimir attraction, van der Waals (vdW) force and the fringing field effect. The proposed model is beneficial for the precise modeling of the narrow nanotweezers in nano-scale.
NASA Astrophysics Data System (ADS)
Mirzaev, Sirojiddin Z.; Kaatze, Udo
2016-09-01
Ultrasonic spectra of mixtures of nitrobenzene with n-alkanes, from n-hexane to n-nonane, are analyzed. They feature up to two Debye-type relaxation terms with discrete relaxation times and, near the critical point, an additional relaxation term due to the fluctuations in the local concentration. The latter can be well represented by the dynamic scaling theory. Its amplitude parameter reveals the adiabatic coupling constant of the mixtures of critical composition. The dependence of this thermodynamic parameter upon the length of the n-alkanes corresponds to that of the slope in the pressure dependence of the critical temperature and is thus taken another confirmation of the dynamic scaling model. The change in the variation of the coupling constant and of several other mixture parameters with alkane length probably reflects a structural change in the nitrobenzene- n-alkane mixtures when the number of carbon atoms per alkane exceeds eight.
NASA Technical Reports Server (NTRS)
Harrison, Phillip; Frady, Greg; Duvall, Lowery; Fulcher, Clay; LaVerde, Bruce
2010-01-01
The development of new launch vehicles in the Aerospace industry often relies on response measurements taken from previously developed vehicles during various stages of liftoff and ascent, and from wind tunnel models. These measurements include sound pressure levels, dynamic pressures in turbulent boundary layers and accelerations. Rigorous statistical scaling methods are applied to the data to derive new environments and estimate the performance of new skin panel structures. Scaling methods have proven to be reliable, particularly for designs similar to the vehicles used as the basis for scaling, and especially in regions of smooth acreage without exterior protuberances or heavy components mounted to the panel. To account for response attenuation of a panel-mounted component due to its apparent mass at higher frequencies, the vibroacoustics engineer often reduces the acreage vibration according to a weight ratio first suggested by Barrett. The accuracy of the reduction is reduced with increased weight of the panel-mounted component, and does not account for low-frequency amplification of the component/panel response as a system. A method is proposed that combines acreage vibration from scaling methods with finite element analysis to account for the frequency-dependent dynamics of heavy panel-mounted components. Since the acreage and mass-loaded skins respond to the same dynamic input pressure, such pressure may be eliminated in favor of a frequency-dependent scaling function applied to the acreage vibration to predict the mass-loaded panel response. The scaling function replaces the Barrett weight ratio, and contains all of the dynamic character of the loaded and unloaded skin panels. The solution simplifies for spatially uncorrelated and fully correlated input pressures. Since the prediction uses finite element models of the loaded and unloaded skins, a rich suite of response data are available to the design engineer, including interface forces, stress and strain, as well as acceleration and displacement. An extension of the method is also developed to incorporate the effect of a local protuberance near a heavy component. Acreage environments from traditional scaling methods with and without protuberance effects serve as the basis for the extension. Authors:
Nunez, Paul L.; Srinivasan, Ramesh
2013-01-01
The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628
Seriès, Peggy; Georges, Sébastien; Lorenceau, Jean; Frégnac, Yves
2002-11-01
Psychophysical and physiological studies suggest that long-range horizontal connections in primary visual cortex participate in spatial integration and contour processing. Until recently, little attention has been paid to their intrinsic temporal properties. Recent physiological studies indicate, however, that the propagation of activity through long-range horizontal connections is slow, with time scales comparable to the perceptual scales involved in motion processing. Using a simple model of V1 connectivity, we explore some of the implications of this slow dynamics. The model predicts that V1 responses to a stimulus in the receptive field can be modulated by a previous stimulation, a few milliseconds to a few tens of milliseconds before, in the surround. We analyze this phenomenon and its possible consequences on speed perception, as a function of the spatio-temporal configuration of the visual inputs (relative orientation, spatial separation, temporal interval between the elements, sequence speed). We show that the dynamical interactions between feed-forward and horizontal signals in V1 can explain why the perceived speed of fast apparent motion sequences strongly depends on the orientation of their elements relative to the motion axis and can account for the range of speed for which this perceptual effect occurs (Georges, Seriès, Frégnac and Lorenceau, this issue).
Dynamics of two-dimensional monolayer water confined in hydrophobic and charged environments.
Kumar, Pradeep; Han, Sungho
2012-09-21
We perform molecular dynamics simulations to study the effect of charged surfaces on the intermediate and long time dynamics of water in nanoconfinements. Here, we use the transferable interaction potential with five points (TIP5P) model of a water molecule confined in both hydrophobic and charged surfaces. For a single molecular layer of water between the surfaces, we find that the temperature dependence of the lateral diffusion constant of water up to very high temperatures remains Arrhenius with a high activation energy. In case of charged surfaces, however, the dynamics of water in the intermediate time regime is drastically modified presumably due to the transient coupling of dipoles of water molecules with electric field fluctuations induced by charges on the confining surfaces. Specifically, the lateral mean square displacements display a distinct super-diffusive behavior at intermediate time scale, defined as the time scale between ballistic and diffusive regimes. This change in the intermediate time-scale dynamics in the charged confinement leads to the enhancement of long-time dynamics as reflected in increasing diffusion constant. We introduce a simple model for a possible explanation of the super-diffusive behavior and find it to be in good agreement with our simulation results. Furthermore, we find that confinement and the surface polarity enhance the low frequency vibration in confinement compared to bulk water. By introducing a new effective length scale of coupling between translational and orientational motions, we find that the length scale increases with the increasing strength of the surface polarity. Further, we calculate the correlation between the diffusion constant and the excess entropy and find a disordering effect of polar surfaces on the structure of water. Finally, we find that the empirical relation between the diffusion constant and the excess entropy holds for a monolayer of water in nanoconfinement.
NASA Astrophysics Data System (ADS)
Stanojević, A.; Marković, V. M.; Čupić, Ž.; Vukojević, V.; Kolar-Anić, L.
2017-12-01
A model was developed that can be used to study the effect of gradual cholesterol intake by food on the HPA axis dynamics. Namely, well defined oscillatory dynamics of vital neuroendocrine hypothalamic-pituitary-adrenal (HPA) axis has proven to be necessary for maintaining regular basal physiology and formulating appropriate stress response to various types of perturbations. Cholesterol, as a precursor of all steroid HPA axis hormones, can alter the dynamics of HPA axis. To analyse its particular influence on the HPA axis dynamics we used stoichiometric model of HPA axis activity, and simulate cholesterol perturbations in the form of finite duration pulses, with asymmetrically distributed concentration profile. Our numerical simulations showed that there is a complex, nonlinear dependence between the HPA axis responsiveness and different forms of applied cholesterol concentration pulses, indicating the significance of kinetic modelling, and dynamical systems theory for the understanding of large-scale self-regulatory, and homeostatic processes within this neuroendocrine system.
Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions
NASA Astrophysics Data System (ADS)
Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph
2017-04-01
The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.
Adiabatic reduction of a model of stochastic gene expression with jump Markov process.
Yvinec, Romain; Zhuge, Changjing; Lei, Jinzhi; Mackey, Michael C
2014-04-01
This paper considers adiabatic reduction in a model of stochastic gene expression with bursting transcription considered as a jump Markov process. In this model, the process of gene expression with auto-regulation is described by fast/slow dynamics. The production of mRNA is assumed to follow a compound Poisson process occurring at a rate depending on protein levels (the phenomena called bursting in molecular biology) and the production of protein is a linear function of mRNA numbers. When the dynamics of mRNA is assumed to be a fast process (due to faster mRNA degradation than that of protein) we prove that, with appropriate scalings in the burst rate, jump size or translational rate, the bursting phenomena can be transmitted to the slow variable. We show that, depending on the scaling, the reduced equation is either a stochastic differential equation with a jump Poisson process or a deterministic ordinary differential equation. These results are significant because adiabatic reduction techniques seem to have not been rigorously justified for a stochastic differential system containing a jump Markov process. We expect that the results can be generalized to adiabatic methods in more general stochastic hybrid systems.
Subdiffusion in Membrane Permeation of Small Molecules.
Chipot, Christophe; Comer, Jeffrey
2016-11-02
Within the solubility-diffusion model of passive membrane permeation of small molecules, translocation of the permeant across the biological membrane is traditionally assumed to obey the Smoluchowski diffusion equation, which is germane for classical diffusion on an inhomogeneous free-energy and diffusivity landscape. This equation, however, cannot accommodate subdiffusive regimes, which have long been recognized in lipid bilayer dynamics, notably in the lateral diffusion of individual lipids. Through extensive biased and unbiased molecular dynamics simulations, we show that one-dimensional translocation of methanol across a pure lipid membrane remains subdiffusive on timescales approaching typical permeation times. Analysis of permeant motion within the lipid bilayer reveals that, in the absence of a net force, the mean squared displacement depends on time as t 0.7 , in stark contrast with the conventional model, which assumes a strictly linear dependence. We further show that an alternate model using a fractional-derivative generalization of the Smoluchowski equation provides a rigorous framework for describing the motion of the permeant molecule on the pico- to nanosecond timescale. The observed subdiffusive behavior appears to emerge from a crossover between small-scale rattling of the permeant around its present position in the membrane and larger-scale displacements precipitated by the formation of transient voids.
Study of Anti-Vortex Baffle Effect in Suppressing Swirling Flow in LOX Tank
NASA Technical Reports Server (NTRS)
Yang, H. Q.; Peugeot, John
2011-01-01
Experimental results describing the hydraulic dynamic pump transfer matrix (Yp) for a cavitating J-2X oxidizer turbopump inducer+impeller tested in subscale waterflow are presented. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Dynamic transfer functions across widely varying pump hydrodynamic inlet conditions are extracted from measured data in conjunction with 1D-model based corrections. Derived Dynamic transfer functions are initially interpreted relative to traditional Pogo pump equations. Water-to-liquid oxygen scaling of measured cavitation characteristics are discussed. Comparison of key dynamic transfer matrix terms derived from waterflow testing are made with those implemented in preliminary Ares Upper Stage Pogo stability modeling. Alternate cavitating pump hydraulic dynamic equations are suggested which better reflect frequency dependencies of measured transfer matrices.
Lee, Kyu Il; Jo, Sunhwan; Rui, Huan; Egwolf, Bernhard; Roux, Benoît; Pastor, Richard W; Im, Wonpil
2012-01-30
Brownian dynamics (BD) based on accurate potential of mean force is an efficient and accurate method for simulating ion transport through wide ion channels. Here, a web-based graphical user interface (GUI) is presented for carrying out grand canonical Monte Carlo (GCMC) BD simulations of channel proteins: http://www.charmm-gui.org/input/gcmcbd. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems. GCMC/BD simulation results for three proteins, the voltage dependent anion channel (VDAC), α-Hemolysin (α-HL), and the protective antigen pore of the anthrax toxin (PA), are presented to illustrate the system setup, input preparation, and typical output (conductance, ion density profile, ion selectivity, and ion asymmetry). Two models for the input diffusion constants for potassium and chloride ions in the pore are compared: scaling of the bulk diffusion constants by 0.5, as deduced from previous all-atom molecular dynamics simulations of VDAC, and a hydrodynamics based model (HD) of diffusion through a tube. The HD model yields excellent agreement with experimental conductances for VDAC and α-HL, while scaling bulk diffusion constants by 0.5 leads to underestimates of 10-20%. For PA, simulated ion conduction values overestimate experimental values by a factor of 1.5-7 (depending on His protonation state and the transmembrane potential), implying that the currently available computational model of this protein requires further structural refinement. Copyright © 2011 Wiley Periodicals, Inc.
Lee, Kyu Il; Jo, Sunhwan; Rui, Huan; Egwolf, Bernhard; Roux, Benoît; Pastor, Richard W.; Im, Wonpil
2011-01-01
Brownian dynamics (BD) in a suitably constructed potential of mean force is an efficient and accurate method for simulating ion transport through wide ion channels. Here, a web-based graphical user interface (GUI) is presented for grand canonical Monte Carlo (GCMC) BD simulations of channel proteins: http://www.charmm-gui.org/input/gcmcbd. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems. GCMC/BD simulation results for three proteins, the voltage dependent anion channel (VDAC), α-Hemolysin, and the protective antigen pore of the anthrax toxin (PA), are presented to illustrate system setup, input preparation, and typical output (conductance, ion density profile, ion selectivity, and ion asymmetry). Two models for the input diffusion constants for potassium and chloride ions in the pore are compared: scaling of the bulk diffusion constants by 0.5, as deduced from previous all-atom molecular dynamics simulations of VDAC; and a hydrodynamics based model (HD) of diffusion through a tube. The HD model yields excellent agreement with experimental conductances for VDAC and α-Hemolysin, while scaling bulk diffusion constants by 0.5 leads to underestimates of 10–20%. For PA, simulated ion conduction values overestimate experimental values by a factor of 1.5 to 7 (depending on His protonation state and the transmembrane potential), implying that the currently available computational model of this protein requires further structural refinement. PMID:22102176
NASA Astrophysics Data System (ADS)
Baya Toda, Hubert; Cabrit, Olivier; Truffin, Karine; Bruneaux, Gilles; Nicoud, Franck
2014-07-01
Large-Eddy Simulation (LES) in complex geometries and industrial applications like piston engines, gas turbines, or aircraft engines requires the use of advanced subgrid-scale (SGS) models able to take into account the main flow features and the turbulence anisotropy. Keeping this goal in mind, this paper reports a LES-dedicated experiment of a pulsatile hot-jet impinging a flat-plate in the presence of a cold turbulent cross-flow. Unlike commonly used academic test cases, this configuration involves different flow features encountered in complex configurations: shear/rotating regions, stagnation point, wall-turbulence, and the propagation of a vortex ring along the wall. This experiment was also designed with the aim to use quantitative and nonintrusive optical diagnostics such as Particle Image Velocimetry, and to easily perform a LES involving a relatively simple geometry and well-controlled boundary conditions. Hence, two eddy-viscosity-based SGS models are investigated: the dynamic Smagorinsky model [M. Germano, U. Piomelli, P. Moin, and W. Cabot, "A dynamic subgrid-scale eddy viscosity model," Phys. Fluids A 3(7), 1760-1765 (1991)] and the σ-model [F. Nicoud, H. B. Toda, O. Cabrit, S. Bose, and J. Lee, "Using singular values to build a subgrid-scale model for large eddy simulations," Phys. Fluids 23(8), 085106 (2011)]. Both models give similar results during the first phase of the experiment. However, it was found that the dynamic Smagorinsky model could not accurately predict the vortex-ring propagation, while the σ-model provides a better agreement with the experimental measurements. Setting aside the implementation of the dynamic procedure (implemented here in its simplest form, i.e., without averaging over homogeneous directions and with clipping of negative values to ensure numerical stability), it is suggested that the mitigated predictions of the dynamic Smagorinsky model are due to the dynamic constant, which strongly depends on the mesh resolution. Indeed, the shear-stress near the wall increases during the vortex-ring impingement leading to a less refined mesh in terms of wall units, y+. This loss of resolution induces a poor damping of the dynamic constant, which is no longer able to adjust itself to ensure the expected y3-behavior near the wall. It is shown that the dynamic constant is never small enough to properly balance the large values of the squared magnitude of the strain-rate tensor, 2SijSij. The experimental database is made available to the community upon request to the authors.
NASA Technical Reports Server (NTRS)
Zoladz, Tom; Patel, Sandeep; Lee, Erik; Karon, Dave
2011-01-01
Experimental results describing the hydraulic dynamic pump transfer matrix (Yp) for a cavitating J-2X oxidizer turbopump inducer+impeller tested in subscale waterflow are presented. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Dynamic transfer functions across widely varying pump hydrodynamic inlet conditions are extracted from measured data in conjunction with 1D-model based corrections. Derived Dynamic transfer functions are initially interpreted relative to traditional Pogo pump equations. Water-to-liquid oxygen scaling of measured cavitation characteristics are discussed. Comparison of key dynamic transfer matrix terms derived from waterflow testing are made with those implemented in preliminary Ares Upper Stage Pogo stability modeling. Alternate cavitating pump hydraulic dynamic equations are suggested which better reflect frequency dependencies of measured transfer matrices.
A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.
NASA Astrophysics Data System (ADS)
Brugger, D. R.; Maneta, M. P.
2015-12-01
Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.
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 non-invasive brain stimulation for stroke patients.
NASA Astrophysics Data System (ADS)
Dyakonova, Tatyana; Khoperskov, Alexander
2018-03-01
The correct description of the surface water dynamics in the model of shallow water requires accounting for friction. To simulate a channel flow in the Chezy model the constant Manning roughness coefficient is frequently used. The Manning coefficient nM is an integral parameter which accounts for a large number of physical factors determining the flow braking. We used computational simulations in a shallow water model to determine the relationship between the Manning coefficient and the parameters of small-scale perturbations of a bottom in a long channel. Comparing the transverse water velocity profiles in the channel obtained in the models with a perturbed bottom without bottom friction and with bottom friction on a smooth bottom, we constructed the dependence of nM on the amplitude and spatial scale of perturbation of the bottom relief.
NASA Astrophysics Data System (ADS)
Rajabi, F.; Battiato, I.
2016-12-01
Long term predictions of the impact of anthropogenic stressors on the environment is essential to reduce the risks associated with processes such as CO2 sequestration and nuclear waste storage in the subsurface. On the other hand, transient forcing factors (e.g. time-varying injection or pumping rate) with evolving heterogeneity of time scales spanning from days to years can influence transport phenomena at the pore scale. A comprehensive spatio-temporal prediction of reactive transport in porous media under time-dependent forcing factors for thousands of years requires the formulation of continuum scale models for time-averages. Yet, as every macroscopic model, time-averaged models can loose predictivity and accuracy when certain conditions are violated. This is true whenever lack of temporal and spatial scale separation occurs and it makes the continuum scale equation a poor assumption for the processes at the pore scale. In this work, we consider mass transport of a dissolved species undergoing a heterogeneous reaction and subject to time-varying boundary conditions in a periodic porous medium. By means of homogenization method and asymptotic expansion technique, we derive a macro-time continuum-scale equation as well as expressions for its effective properties. Our analysis demonstrates that the dynamics at the macro-scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. In addition, we provide the conditions under which the space-time averaged equations accurately describe pore-scale processes. To validate our theoretical predictions, we consider a thin fracture with reacting walls and transient boundary conditions at the inlet. Our analysis shows a good agreement between numerical simulations and theoretical predictions. Furthermore, our numerical experiments show that mixing patterns of the contaminant plumes at the pore level strongly depend on the signal frequency.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Domènech, Guillem; Hiramatsu, Takashi; Lin, Chunshan
We consider a cosmological model in which the tensor mode becomes massive during inflation, and study the Cosmic Microwave Background (CMB) temperature and polarization bispectra arising from the mixing between the scalar mode and the massive tensor mode during inflation. The model assumes the existence of a preferred spatial frame during inflation. The local Lorentz invariance is already broken in cosmology due to the existence of a preferred rest frame. The existence of a preferred spatial frame further breaks the remaining local SO(3) invariance and in particular gives rise to a mass in the tensor mode. At linear perturbation level,more » we minimize our model so that the vector mode remains non-dynamical, while the scalar mode is the same as the one in single-field slow-roll inflation. At non-linear perturbation level, this inflationary massive graviton phase leads to a sizeable scalar-scalar-tensor coupling, much greater than the scalar-scalar-scalar one, as opposed to the conventional case. This scalar-scalar-tensor interaction imprints a scale dependent feature in the CMB temperature and polarization bispectra. Very intriguingly, we find a surprizing similarity between the predicted scale dependence and the scale-dependent non-Gaussianities at low multipoles hinted in the WMAP and Planck results.« less
Integrated Modeling of Time Evolving 3D Kinetic MHD Equilibria and NTV Torque
NASA Astrophysics Data System (ADS)
Logan, N. C.; Park, J.-K.; Grierson, B. A.; Haskey, S. R.; Nazikian, R.; Cui, L.; Smith, S. P.; Meneghini, O.
2016-10-01
New analysis tools and integrated modeling of plasma dynamics developed in the OMFIT framework are used to study kinetic MHD equilibria evolution on the transport time scale. The experimentally observed profile dynamics following the application of 3D error fields are described using a new OMFITprofiles workflow that directly addresses the need for rapid and comprehensive analysis of dynamic equilibria for next-step theory validation. The workflow treats all diagnostic data as fundamentally time dependent, provides physics-based manipulations such as ELM phase data selection, and is consistent across multiple machines - including DIII-D and NSTX-U. The seamless integration of tokamak data and simulation is demonstrated by using the self-consistent kinetic EFIT equilibria and profiles as input into 2D particle, momentum and energy transport calculations using TRANSP as well as 3D kinetic MHD equilibrium stability and neoclassical transport modeling using General Perturbed Equilibrium Code (GPEC). The result is a smooth kinetic stability and NTV torque evolution over transport time scales. Work supported by DE-AC02-09CH11466.
Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces
Kim, Minsu; Or, Dani
2016-01-01
Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803
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.
Conceptual design and analysis of a dynamic scale model of the Space Station Freedom
NASA Technical Reports Server (NTRS)
Davis, D. A.; Gronet, M. J.; Tan, M. K.; Thorne, J.
1994-01-01
This report documents the conceptual design study performed to evaluate design options for a subscale dynamic test model which could be used to investigate the expected on-orbit structural dynamic characteristics of the Space Station Freedom early build configurations. The baseline option was a 'near-replica' model of the SSF SC-7 pre-integrated truss configuration. The approach used to develop conceptual design options involved three sets of studies: evaluation of the full-scale design and analysis databases, conducting scale factor trade studies, and performing design sensitivity studies. The scale factor trade study was conducted to develop a fundamental understanding of the key scaling parameters that drive design, performance and cost of a SSF dynamic scale model. Four scale model options were estimated: 1/4, 1/5, 1/7, and 1/10 scale. Prototype hardware was fabricated to assess producibility issues. Based on the results of the study, a 1/4-scale size is recommended based on the increased model fidelity associated with a larger scale factor. A design sensitivity study was performed to identify critical hardware component properties that drive dynamic performance. A total of 118 component properties were identified which require high-fidelity replication. Lower fidelity dynamic similarity scaling can be used for non-critical components.
NASA Astrophysics Data System (ADS)
Bloom, A. A.; Exbrayat, J. F.; van der Velde, I.; Peters, W.; Williams, M.
2014-12-01
Large uncertainties preside over terrestrial carbon flux estimates on a global scale. In particular, the strongly coupled dynamics between net ecosystem productivity and disturbance C losses are poorly constrained. To gain an improved understanding of ecosystem C dynamics from regional to global scale, we apply a Markov Chain Monte Carlo based model-data-fusion approach into the CArbon DAta-MOdel fraMework (CARDAMOM). We assimilate MODIS LAI and burned area, plant-trait data, and use the Harmonized World Soil Database (HWSD) and maps of above ground biomass as prior knowledge for initial conditions. We optimize model parameters based on (a) globally spanning observations and (b) ecological and dynamic constraints that force single parameter values and parameter inter-dependencies to be representative of real world processes. We determine the spatial and temporal dynamics of major terrestrial C fluxes and model parameter values on a global scale (GPP = 123 +/- 8 Pg C yr-1 & NEE = -1.8 +/- 2.7 Pg C yr-1). We further show that the incorporation of disturbance fluxes, and accounting for their instantaneous or delayed effect, is of critical importance in constraining global C cycle dynamics, particularly in the tropics. In a higher resolution case study centred on the Amazon Basin we show how fires not only trigger large instantaneous emissions of burned matter, but also how they are responsible for a sustained reduction of up to 50% in plant uptake following the depletion of biomass stocks. The combination of these two fire-induced effects leads to a 1 g C m-2 d-1reduction in the strength of the net terrestrial carbon sink. Through our simulations at regional and global scale, we advocate the need to assimilate disturbance metrics in global terrestrial carbon cycle models to bridge the gap between globally spanning terrestrial carbon cycle data and the full dynamics of the ecosystem C cycle. Disturbances are especially important because their quick occurrence may have long-term effects on ecosystems. Our synthetic simulations show that while tropical ecosystems uptake may reach pre-disturbance level after a decade, biomass stocks would most likely need more than a century to recover from a single extreme disturbance event.
NASA Astrophysics Data System (ADS)
Konovalenko S., Iv.; Psakhie, S. G.
2017-12-01
Using the molecular dynamics method, we simulated the atomic scale butt friction stir welding on two crystallites and varied the onset FSW tool plunge depth. The effects of the plunge depth value on the thermomechanical evolution of nanosized crystallites and mass transfer in the course of FSW have been studied. The increase of plunge depth values resulted in more intense heating and reducing the plasticized metal resistance to the tool movement. The mass transfer intensity was hardly dependent on the plunge depth value. The plunge depth was recommended to be used as a FSW process control parameter in addition to the commonly used ones.
Positive and Negative Feedbacks and Free-Scale Pattern Distribution in Rural-Population Dynamics
Alados, Concepción L.; Errea, Paz; Gartzia, Maite; Saiz, Hugo; Escós, Juan
2014-01-01
Depopulation of rural areas is a widespread phenomenon that has occurred in most industrialized countries, and has contributed significantly to a reduction in the productivity of agro-ecological resources. In this study, we identified the main trends in the dynamics of rural populations in the Central Pyrenees in the 20th C and early 21st C, and used density independent and density dependent models and identified the main factors that have influenced the dynamics. In addition, we investigated the change in the power law distribution of population size in those periods. Populations exhibited density-dependent positive feedback between 1960 and 2010, and a long-term positive correlation between agricultural activity and population size, which has resulted in a free-scale population distribution that has been disrupted by the collapse of the traditional agricultural society and by emigration to the industrialized cities. We concluded that complex socio-ecological systems that have strong feedback mechanisms can contribute to disruptive population collapses, which can be identified by changes in the pattern of population distribution. PMID:25474704
A stochastic fractional dynamics model of space-time variability of rain
NASA Astrophysics Data System (ADS)
Kundu, Prasun K.; Travis, James E.
2013-09-01
varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.
NASA Astrophysics Data System (ADS)
Ding, Feizhi
Understanding electronic behavior in molecular and nano-scale systems is fundamental to the development and design of novel technologies and materials for application in a variety of scientific contexts from fundamental research to energy conversion. This dissertation aims to provide insights into this goal by developing novel methods and applications of first-principle electronic structure theory. Specifically, we will present new methods and applications of excited state multi-electron dynamics based on the real-time (RT) time-dependent Hartree-Fock (TDHF) and time-dependent density functional theory (TDDFT) formalism, and new development of the multi-configuration self-consist field theory (MCSCF) for modeling ground-state electronic structure. The RT-TDHF/TDDFT based developments and applications can be categorized into three broad and coherently integrated research areas: (1) modeling of the interaction between moleculars and external electromagnetic perturbations. In this part we will first prove both analytically and numerically the gauge invariance of the TDHF/TDDFT formalisms, then we will present a novel, efficient method for calculating molecular nonlinear optical properties, and last we will study quantum coherent plasmon in metal namowires using RT-TDDFT; (2) modeling of excited-state charge transfer in molecules. In this part, we will investigate the mechanisms of bridge-mediated electron transfer, and then we will introduce a newly developed non-equilibrium quantum/continuum embedding method for studying charge transfer dynamics in solution; (3) developments of first-principles spin-dependent many-electron dynamics. In this part, we will present an ab initio non-relativistic spin dynamics method based on the two-component generalized Hartree-Fock approach, and then we will generalized it to the two-component TDDFT framework and combine it with the Ehrenfest molecular dynamics approach for modeling the interaction between electron spins and nuclear motion. All these developments and applications will open up new computational and theoretical tools to be applied to the development and understanding of chemical reactions, nonlinear optics, electromagnetism, and spintronics. Lastly, we present a new algorithm for large-scale MCSCF calculations that can utilize massively parallel machines while still maintaining optimal performance for each single processor. This will great improve the efficiency in the MCSCF calculations for studying chemical dissociation and high-accuracy quantum-mechanical simulations.
NASA Astrophysics Data System (ADS)
Tang, J.; Riley, W. J.
2017-12-01
Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.
NASA Astrophysics Data System (ADS)
Chen, X.; Song, X.; Shuai, P.; Hammond, G. E.; Ren, H.; Zachara, J. M.
2017-12-01
Hydrologic exchange flows (HEFs) in rivers play vital roles in watershed ecological and biogeochemical functions due to their strong capacity to attenuate contaminants and process significant quantities of carbon and nutrients. While most of existing HEF studies focus on headwater systems with the assumption of steady-state flow, there is lack of understanding of large-scale HEFs in high-order regulated rivers that experience high-frequency stage fluctuations. The large variability of HEFs is a result of interactions between spatial heterogeneity in hydrogeologic properties and temporal variation in river discharge induced by natural or anthropogenic perturbations. Our 9-year spatially distributed dataset (water elevation, specific conductance, and temperature) combined with mechanistic hydrobiogeochemical simulations have revealed complex spatial and temporal dynamics in km-scale HEFs and their significant impacts on contaminant plume mobility and hyporheic biogeochemical processes along the Hanford Reach. Extended multidirectional flow behaviors of unconfined, river corridor groundwater were observed hundreds of meters inland from the river shore resulting from discharge-dependent HEFs. An appropriately sized modeling domain to capture the impact of regional groundwater flow as well as knowledge of subsurface structures controlling intra-aquifer hydrologic connectivity were essential to realistically model transient storage in this large-scale river corridor. This work showed that both river water and mobile groundwater contaminants could serve as effective tracers of HEFs, thus providing valuable information for evaluating and validating the HEF models. Multimodal residence time distributions with long tails were resulted from the mixture of long and short exchange pathways, which consequently impact the carbon and nutrient cycling within the river corridor. Improved understanding of HEFs using integrated observational and modeling approaches sheds light on developing fundamental understanding of the influences of HEFs on water quality, nutrient dynamics, and ecosystem health in dynamic river corridor systems.
Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations.
Vorobev, Anatoliy
2010-11-01
We use the Cahn-Hilliard approach to model the slow dissolution dynamics of binary mixtures. An important peculiarity of the Cahn-Hilliard-Navier-Stokes equations is the necessity to use the full continuity equation even for a binary mixture of two incompressible liquids due to dependence of mixture density on concentration. The quasicompressibility of the governing equations brings a short time-scale (quasiacoustic) process that may not affect the slow dynamics but may significantly complicate the numerical treatment. Using the multiple-scale method we separate the physical processes occurring on different time scales and, ultimately, derive the equations with the filtered-out quasiacoustics. The derived equations represent the Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations. This approximation can be further employed as a universal theoretical model for an analysis of slow thermodynamic and hydrodynamic evolution of the multiphase systems with strongly evolving and diffusing interfacial boundaries, i.e., for the processes involving dissolution/nucleation, evaporation/condensation, solidification/melting, polymerization, etc.
NASA Astrophysics Data System (ADS)
Gale, Charles; Jeon, Sangyong; Schenke, Björn; Tribedy, Prithwish; Venugopalan, Raju
2013-01-01
Anisotropic flow coefficients v1-v5 in heavy ion collisions are computed by combining a classical Yang-Mills description of the early time Glasma flow with the subsequent relativistic viscous hydrodynamic evolution of matter through the quark-gluon plasma and hadron gas phases. The Glasma dynamics, as realized in the impact parameter dependent Glasma (IP-Glasma) model, takes into account event-by-event geometric fluctuations in nucleon positions and intrinsic subnucleon scale color charge fluctuations; the preequilibrium flow of matter is then matched to the music algorithm describing viscous hydrodynamic flow and particle production at freeze-out. The IP-Glasma+MUSIC model describes well both transverse momentum dependent and integrated vn data measured at the Large Hadron Collider and the Relativistic Heavy Ion Collider. The model also reproduces the event-by-event distributions of v2, v3 and v4 measured by the ATLAS Collaboration. The implications of our results for better understanding of the dynamics of the Glasma and for the extraction of transport properties of the quark-gluon plasma are outlined.
Nanoscopic length scale dependence of hydrogen bonded molecular associates’ dynamics in methanol
Bertrand, C. E.; Self, J. L.; Copley, J. R. D.; Faraone, A.
2017-01-01
In a recent paper [C. E. Bertrand et al., J. Chem. Phys. 145, 014502 (2016)], we have shown that the collective dynamics of methanol shows a fast relaxation process related to the standard density-fluctuation heat mode and a slow non-Fickian mode originating from the hydrogen bonded molecular associates. Here we report on the length scale dependence of this slow relaxation process. Using quasielastic neutron scattering and molecular dynamics simulations, we show that the dynamics of the slow process is affected by the structuring of the associates, which is accessible through polarized neutron diffraction experiments. Using a series of partially deuterated samples, the dynamics of the associates is investigated and is found to have a similar time scale to the lifetime of hydrogen bonding in the system. Both the structural relaxation and the dynamics of the associates are thermally activated by the breaking of hydrogen bonding. PMID:28527447
Temperature dependence of fast carbonyl backbone dynamics in chicken villin headpiece subdomain
Vugmeyster, Liliya; Ostrovsky, Dmitry
2012-01-01
Temperature-dependence of protein dynamics can provide information on details of the free energy landscape by probing the characteristics of the potential responsible for the fluctuations. We have investigated the temperature-dependence of picosecond to nanosecond backbone dynamics at carbonyl carbon sites in chicken villin headpiece subdomain protein using a combination of three NMR relaxation rates: 13C′ longitudinal rate, and two cross-correlated rates involving dipolar and chemical shift anisotropy (CSA) relaxation mechanisms, 13C′/13C′−13Cα CSA/dipolar and 13C′/13C′−15N CSA/dipolar. Order parameters have been extracted using the Lipari-Szabo model-free approach assuming a separation of the time scales of internal and molecular motions in the 2–16°C temperature range. There is a gradual deviation from this assumption from lower to higher temperatures, such that above 16°C the separation of the time scales is inconsistent with the experimental data and, thus, the Lipari-Szabo formalism can not be applied. While there are variations among the residues, on the average the order parameters indicate a markedly steeper temperature dependence at backbone carbonyl carbons compared to that probed at amide nitrogens in an earlier study. This strongly advocates for probing sites other than amide nitrogen for accurate characterization of the potential and other thermodynamics characteristics of protein backbone. PMID:21416162
NASA Astrophysics Data System (ADS)
Condon, Laura E.; Maxwell, Reed M.
2014-03-01
Regional scale water management analysis increasingly relies on integrated modeling tools. Much recent work has focused on groundwater-surface water interactions and feedbacks. However, to our knowledge, no study has explicitly considered impacts of management operations on the temporal dynamics of the natural system. Here, we simulate twenty years of hourly moisture dependent, groundwater-fed irrigation using a three-dimensional, fully integrated, hydrologic model (ParFlow-CLM). Results highlight interconnections between irrigation demand, groundwater oscillation frequency and latent heat flux variability not previously demonstrated. Additionally, the three-dimensional model used allows for novel consideration of spatial patterns in temporal dynamics. Latent heat flux and water table depth both display spatial organization in temporal scaling, an important finding given the spatial homogeneity and weak scaling observed in atmospheric forcings. Pumping and irrigation amplify high frequency (sub-annual) variability while attenuating low frequency (inter-annual) variability. Irrigation also intensifies scaling within irrigated areas, essentially increasing temporal memory in both the surface and the subsurface. These findings demonstrate management impacts that extend beyond traditional water balance considerations to the fundamental behavior of the system itself. This is an important step to better understanding groundwater’s role as a buffer for natural variability and the impact that water management has on this capacity.
A study on the dependence of nuclear viscosity on temperature
NASA Astrophysics Data System (ADS)
Vardaci, E.; Di Nitto, A.; Nadtochy, P. N.; La Rana, G.; Cinausero, M.; Prete, G.; Gelli, N.; Ashaduzzaman, M.; Davide, F.; Pulcini, A.; Quero, D.; Kozulin, E. M.; Knyazheva, G. N.; Itkis, I. M.
2018-05-01
Nuclear viscosity is an irreplaceable ingredient of nuclear fission collective dynamical models. It drives the exchange of energy between the collective variables and the thermal bath of single particle degrees of freedom. Its dependence on the shape and temperature is a matter of controversy. By using systems of intermediate fissility we have demonstrated in a recent study that the viscosity parameters is larger for compact shapes, and decreases for larger deformations of the fissioning system, at variance with the conclusions of the statistical model modified to include empirically viscosity and time scales. In this contribution we propose an experimental scenario to highlight the possible dependence of the viscosity from the temperature.
Density-dependence as a size-independent regulatory mechanism.
de Vladar, Harold P
2006-01-21
The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.
Kibble-Zurek Scaling and String-Net Coarsening in Topologically Ordered Systems
NASA Astrophysics Data System (ADS)
Khemani, Vedika; Chandran, Anushya; Burnell, F. J.; Sondhi, S. L.
2013-03-01
We consider the non-equilibrium dynamics of topologically ordered systems, such as spin liquids, driven across a continuous phase transition into proximate phases with no, or reduced, topological order. This dynamics exhibits scaling in the spirit of Kibble and Zurek but now without the presence of symmetry breaking and a local order parameter. The non-equilibrium dynamics near the critical point is universal in a particular scaling limit. The late stages of the process are seen to exhibit slow, quantum coarsening dynamics for the extended string-nets characterizing the topological phase, a potentially interesting signature of topological order. Certain gapped degrees of freedom that could potentially destroy coarsening are, at worst, dangerously irrelevant in the scaling limit. We also note a time dependent amplification of the energy splitting between topologically degenerate states on closed manifolds. We illustrate these phenomena in the context of particular phase transitions out of the abelian Z2 topologically ordered phase of the toric code, and the non-abelian SU(2)k ordered phases of the relevant Levin-Wen models. This research was supported in part by the National Science Foundation under Grant No. NSF PHY11-25915 and DMR 10-06608.
Nonadiabatic Dynamics for Electrons at Second-Order: Real-Time TDDFT and OSCF2.
Nguyen, Triet S; Parkhill, John
2015-07-14
We develop a new model to simulate nonradiative relaxation and dephasing by combining real-time Hartree-Fock and density functional theory (DFT) with our recent open-systems theory of electronic dynamics. The approach has some key advantages: it has been systematically derived and properly relaxes noninteracting electrons to a Fermi-Dirac distribution. This paper combines the new dissipation theory with an atomistic, all-electron quantum chemistry code and an atom-centered model of the thermal environment. The environment is represented nonempirically and is dependent on molecular structure in a nonlocal way. A production quality, O(N(3)) closed-shell implementation of our theory applicable to realistic molecular systems is presented, including timing information. This scaling implies that the added cost of our nonadiabatic relaxation model, time-dependent open self-consistent field at second order (OSCF2), is computationally inexpensive, relative to adiabatic propagation of real-time time-dependent Hartree-Fock (TDHF) or time-dependent density functional theory (TDDFT). Details of the implementation and numerical algorithm, including factorization and efficiency, are discussed. We demonstrate that OSCF2 approaches the stationary self-consistent field (SCF) ground state when the gap is large relative to k(b)T. The code is used to calculate linear-response spectra including the effects of bath dynamics. Finally, we show how our theory of finite-temperature relaxation can be used to correct ground-state DFT calculations.
Sweet Spot Supersymmetry and Composite Messengers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ibe, Masahiro; Kitano, Ryuichiro
2007-10-30
Sweet spot supersymmetry is a phenomenologically and cosmologically perfect framework to realize a supersymmetric world at short distance. We discuss a class of dynamical models of supersymmetry breaking and its mediation whose low-energy effective description falls into this framework. Hadron fields in the dynamical models play a role of the messengers of the supersymmetry breaking. As is always true in the models of the sweet spot supersymmetry, the messenger scale is predicted to be 10{sup 5} GeV {approx}< M{sub mess} {approx}< 10{sup 10} GeV. Various values of the effective number of messenger fields N{sub mess} are possible depending on themore » choice of the gauge group.« less
Dimension reduction and multiscaling law through source extraction
NASA Astrophysics Data System (ADS)
Capobianco, Enrico
2003-04-01
Through the empirical analysis of financial return generating processes one may find features that are common to other research fields, such as internet data from network traffic, physiological studies about human heart beat, speech and sleep recorded time series, geophysics signals, just to mention well-known cases of study. In particular, long range dependence, intermittency, heteroscedasticity are clearly appearing, and consequently power laws and multi-scaling behavior result typical signatures of either the spectral or the time correlation diagnostics. We study these features and the dynamics underlying financial volatility, which can respectively be detected and inferred from high frequency realizations of stock index returns, and show that they vary according to the resolution levels used for both the analysis and the synthesis of the available information. Discovering whether the volatility dynamics are subject to changes in scaling regimes requires the consideration of a model embedding scale-dependent information packets, thus accounting for possible heterogeneous activity occurring in financial markets. Independent component analysis result to be an important tool for reducing the dimension of the problem and calibrating greedy approximation techniques aimed to learn the structure of the underlying volatility.
NASA Astrophysics Data System (ADS)
Paul, Subhajit; Das, Subir K.
2018-03-01
Via event-driven molecular dynamics simulations we study kinetics of clustering in assemblies of inelastic particles in various space dimensions. We consider two models, viz., the ballistic aggregation model (BAM) and the freely cooling granular gas model (GGM), for each of which we quantify the time dependence of kinetic energy and average mass of clusters (that form due to inelastic collisions). These quantities, for both the models, exhibit power-law behavior, at least in the long time limit. For the BAM, corresponding exponents exhibit strong dimension dependence and follow a hyperscaling relation. In addition, in the high packing fraction limit the behavior of these quantities become consistent with a scaling theory that predicts an inverse relation between energy and mass. On the other hand, in the case of the GGM we do not find any evidence for such a picture. In this case, even though the energy decay, irrespective of packing fraction, matches quantitatively with that for the high packing fraction picture of the BAM, it is inversely proportional to the growth of mass only in one dimension, and the growth appears to be rather insensitive to the choice of the dimension, unlike the BAM.
Cheng, Ryan R; Hawk, Alexander T; Makarov, Dmitrii E
2013-02-21
Recent experiments showed that the reconfiguration dynamics of unfolded proteins are often adequately described by simple polymer models. In particular, the Rouse model with internal friction (RIF) captures internal friction effects as observed in single-molecule fluorescence correlation spectroscopy (FCS) studies of a number of proteins. Here we use RIF, and its non-free draining analog, Zimm model with internal friction, to explore the effect of internal friction on the rate with which intramolecular contacts can be formed within the unfolded chain. Unlike the reconfiguration times inferred from FCS experiments, which depend linearly on the solvent viscosity, the first passage times to form intramolecular contacts are shown to display a more complex viscosity dependence. We further describe scaling relationships obeyed by contact formation times in the limits of high and low internal friction. Our findings provide experimentally testable predictions that can serve as a framework for the analysis of future studies of contact formation in proteins.
Collective hydration dynamics in some amino acid solutions: A combined GHz-THz spectroscopic study
NASA Astrophysics Data System (ADS)
Samanta, Nirnay; Das Mahanta, Debasish; Choudhury, Samiran; Barman, Anjan; Kumar Mitra, Rajib
2017-03-01
A detailed understanding of hydration of amino acids, the building units of protein, is a key step to realize the overall solvation processes in proteins. In the present contribution, we have made a combined GHz (0.2-50) to THz (0.3-2.0) experimental spectroscopic study to investigate the dynamics of water at room temperature in the presence of different amino acids (glycine, L-serine, L-lysine, L-tryptophan, L-arginine, and L-aspartic acid). The THz absorption coefficient, α(ν), of amino acids follows a trend defined by their solvent accessible surface area. The imaginary and real dielectric constants obtained in GHz and THz regions are fitted into multiple Debye model to obtain various relaxation times. The ˜100 ps time scale obtained in the GHz frequency region is attributed to the rotational motion of the amino acids. In the THz region, we obtain ˜8 ps and ˜200 fs time scales which are related to the cooperative dynamics of H-bond network and partial rotation or sudden jump of the under-coordinated water molecules. These time scales are found to be dependent on the amino acid type and the cooperative motion is found to be dependent on both the hydrophobic as well as the hydrophilic residue of amino acids.
Hite, Jessica L; Cressler, Clayton E
2018-05-05
What drives the evolution of parasite life-history traits? Recent studies suggest that linking within- and between-host processes can provide key insight into both disease dynamics and parasite evolution. Still, it remains difficult to understand how to pinpoint the critical factors connecting these cross-scale feedbacks, particularly under non-equilibrium conditions; many natural host populations inherently fluctuate and parasites themselves can strongly alter the stability of host populations. Here, we develop a general model framework that mechanistically links resources to parasite evolution across a gradient of stable and unstable conditions. First, we dynamically link resources and between-host processes (host density, stability, transmission) to virulence evolution, using a 'non-nested' model. Then, we consider a 'nested' model where population-level processes (transmission and virulence) depend on resource-driven changes to individual-level (within-host) processes (energetics, immune function, parasite production). Contrary to 'non-nested' model predictions, the 'nested' model reveals complex effects of host population dynamics on parasite evolution, including regions of evolutionary bistability; evolution can push parasites towards strongly or weakly stabilizing strategies. This bistability results from dynamic feedbacks between resource-driven changes to host density, host immune function and parasite production. Together, these results highlight how cross-scale feedbacks can provide key insights into the structuring role of parasites and parasite evolution.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Author(s).
NASA Astrophysics Data System (ADS)
Brigatti, E.; Vieira, M. V.; Kajin, M.; Almeida, P. J. A. L.; de Menezes, M. A.; Cerqueira, R.
2016-02-01
We study the population size time series of a Neotropical small mammal with the intent of detecting and modelling population regulation processes generated by density-dependent factors and their possible delayed effects. The application of analysis tools based on principles of statistical generality are nowadays a common practice for describing these phenomena, but, in general, they are more capable of generating clear diagnosis rather than granting valuable modelling. For this reason, in our approach, we detect the principal temporal structures on the bases of different correlation measures, and from these results we build an ad-hoc minimalist autoregressive model that incorporates the main drivers of the dynamics. Surprisingly our model is capable of reproducing very well the time patterns of the empirical series and, for the first time, clearly outlines the importance of the time of attaining sexual maturity as a central temporal scale for the dynamics of this species. In fact, an important advantage of this analysis scheme is that all the model parameters are directly biologically interpretable and potentially measurable, allowing a consistency check between model outputs and independent measurements.
Multiscale Modeling of Human-Water Interactions: The Role of Time-Scales
NASA Astrophysics Data System (ADS)
Bloeschl, G.; Sivapalan, M.
2015-12-01
Much of the interest in hydrological modeling in the past decades revolved around resolving spatial variability. With the rapid changes brought about by human impacts on the hydrologic cycle, there is now an increasing need to refocus on time dependency. We present a co-evolutionary view of hydrologic systems, in which every part of the system including human systems, co-evolve, albeit at different rates. The resulting coupled human-nature system is framed as a dynamical system, characterized by interactions of fast and slow time scales and feedbacks between environmental and social processes. This gives rise to emergent phenomena such as the levee effect, adaptation to change and system collapse due to resource depletion. Changing human values play a key role in the emergence of these phenomena and should therefore be considered as internal to the system in a dynamic way. The co-evolutionary approach differs from the traditional view of water resource systems analysis as it allows for path dependence, multiple equilibria, lock-in situations and emergent phenomena. The approach may assist strategic water management for long time scales through facilitating stakeholder participation, exploring the possibility space of alternative futures, and helping to synthesise the observed dynamics of different case studies. Future research opportunities include the study of how changes in human values are connected to human-water interactions, historical analyses of trajectories of system co-evolution in individual places and comparative analyses of contrasting human-water systems in different climate and socio-economic settings. Reference Sivapalan, M. and G. Blöschl (2015) Time Scale Interactions and the Co-evolution of Humans and Water. Water Resour. Res., 51, in press.
Fernando L. Dri; Xiawa Wu; Robert J. Moon; Ashlie Martini; Pablo D. Zavattieri
2015-01-01
Molecular dynamics simulation is commonly used to study the properties of nanocellulose-based materials at the atomic scale. It is well known that the accuracy of these simulations strongly depends on the force field that describes energetic interactions. However, since there is no force field developed specifically for cellulose, researchers utilize models...
Adiabatic invariants in stellar dynamics. 1: Basic concepts
NASA Technical Reports Server (NTRS)
Weinberg, Martin D.
1994-01-01
The adiabatic criterion, widely used in astronomical dynamics, is based on the harmonic oscillator. It asserts that the change in action under a slowly varying perturbation is exponentially small. Recent mathematical results that precisely define the conditions for invariance show that this model does not apply in general. In particular, a slowly varying perturbation may cause significant evolution stellar dynamical systems even if its time scale is longer than any internal orbital time scale. This additional 'heating' may have serious implications for the evolution of star clusters and dwarf galaxies which are subject to long-term environmental forces. The mathematical developments leading to these results are reviewed, and the conditions for applicability to and further implications for stellar systems are discussed. Companion papers present a computational method for a general time-dependent disturbance and detailed example.
Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities
NASA Technical Reports Server (NTRS)
Bonan, Gordon; Santanello, Joseph A., Jr.
2013-01-01
Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.
Riparian vegetation controls on the hydraulic geometry of streams
NASA Astrophysics Data System (ADS)
McBride, M.
2010-12-01
A synthesis of field measurements, remote observations, and numerical modeling techniques highlights the significance of riparian vegetation in determining the geometry of streams and impacting sediment transport dynamics in temperate, Piedmont regions. Specifically, forested and grassy riparian vegetation establish streams with significantly different widths and with different timescales for attaining a state of dynamic equilibrium. The interactions between riparian vegetation, channel form, and channel dynamics are scale dependent. Scale dependency arises because of variations in ratios of vegetation length scales and geomorphic scales (e.g., channel width and depth). Stream reaches with grassy vegetation experience more frequent overbank discharges, migrate more quickly, and exhibit a more classic dynamic equilibrium than forested reaches. These phenomena are relevant to current watershed management efforts that aim to reduce sediment and nutrient loads to receiving water bodies, such as the Chesapeake Bay. The reforestation of riparian buffers is a common restoration technique that intends to improve water quality, temperature regimes, and in-stream physical habitat. Passive reforestation of riparian areas along a tributary to Sleepers River in Danville, VT, USA caused an increase in channel width and cross-sectional area over a 40-year period. From a comparison of historical records and current cross-sectional dimensions, the channel widening resulted in the mobilization of approximately 85 kg/ha/yr of floodplain sediments. Long-term monitoring of suspended sediments in an adjacent watershed indicates that this sediment source may account for roughly 40 percent of the total suspended sediment load. In some instances, increased sediment loads associated with channel widening may be an unforeseen consequence that compromises riparian restoration efforts.
Brinzer, Thomas; Garrett-Roe, Sean
2017-11-21
Ultrafast two-dimensional infrared spectroscopy of a thiocyanate vibrational probe (SCN - ) was used to investigate local dynamics in alkylimidazolium bis-[trifluoromethylsulfonyl]imide ionic liquids ([Im n,1 ][Tf 2 N], n = 2, 4, 6) at temperatures from 5 to 80 °C. The rate of frequency fluctuations reported by SCN - increases with increasing temperature and decreasing alkyl chain length. Temperature-dependent correlation times scale proportionally to temperature-dependent bulk viscosities of each ionic liquid studied. A multimode Brownian oscillator model demonstrates that very low frequency (<10 cm -1 ) modes primarily drive the observed spectral diffusion and that these modes broaden and blue shift on average with increasing temperature. An Arrhenius analysis shows activation barriers for local motions around the probe between 5.5 and 6.5 kcal/mol that are very similar to those for translational diffusion of ions. [Im 6,1 ][Tf 2 N] shows an unexpected decrease in activation energy compared to [Im 4,1 ][Tf 2 N] that may be related to mesoscopically ordered polar and nonpolar domains. A model of dynamics on a rugged potential energy landscape provides a unifying description of the observed Arrhenius behavior and the Brownian oscillator model of the low frequency modes.
NASA Astrophysics Data System (ADS)
Ward, A. S.; Schmadel, N.; Wondzell, S. M.
2017-12-01
River networks are broadly recognized to expand and contract in response to hydrologic forcing. Additionally, the individual controls on river corridor dynamics of hydrologic forcing and geologic setting are well recognized. However, we currently lack tools to integrate our understanding of process dynamics in the river corridor and make predictions at the scale of river networks. In this study, we develop a perceptual model of the river corridor in mountain river networks, translate this into a reduced-complexity mechanistic model, and implement the model in a well-studied headwater catchment. We found that the river network was most sensitive to hydrologic dynamics under the lowest discharges (Qgauge < 1 L s-1). We also demonstrate a discharge-dependence on the dominant controls on network expansion, contraction, and river corridor exchange. Finally, we suggest this parsimonious model will be useful to managers of water resources who need to estimate connectivity and flow initiation location along the river corridor over broad, unstudied catchments.
Shear banding leads to accelerated aging dynamics in a metallic glass
DOE Office of Scientific and Technical Information (OSTI.GOV)
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less
Shear banding leads to accelerated aging dynamics in a metallic glass
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; ...
2018-01-11
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less
NASA Astrophysics Data System (ADS)
Parmentier, Geneviève; Baumgardt, Holger
2012-12-01
We highlight the impact of cluster-mass-dependent evolutionary rates upon the evolution of the cluster mass function during violent relaxation, that is, while clusters dynamically respond to the expulsion of their residual star-forming gas. Mass-dependent evolutionary rates arise when the mean volume density of cluster-forming regions is mass-dependent. In that case, even if the initial conditions are such that the cluster mass function at the end of violent relaxation has the same shape as the embedded-cluster mass function (i.e. infant weight-loss is mass-independent), the shape of the cluster mass function does change transiently during violent relaxation. In contrast, for cluster-forming regions of constant mean volume density, the cluster mass function shape is preserved all through violent relaxation since all clusters then evolve at the same mass-independent rate. On the scale of individual clusters, we model the evolution of the ratio of the dynamical mass to luminous mass of a cluster after gas expulsion. Specifically, we map the radial dependence of the time-scale for a star cluster to return to equilibrium. We stress that fields of view a few pc in size only, typical of compact clusters with rapid evolutionary rates, are likely to reveal cluster regions which have returned to equilibrium even if the cluster experienced a major gas expulsion episode a few Myr earlier. We provide models with the aperture and time expressed in units of the initial half-mass radius and initial crossing-time, respectively, so that our results can be applied to clusters with initial densities, sizes, and apertures different from ours.
NASA Astrophysics Data System (ADS)
Neelin, J.; Langenbrunner, B.; Meyerson, J. E.
2012-12-01
Precipitation changes under global warming are often discussed in terms of wet areas receiving more precipitation and dry areas receiving less, sometimes termed the "rich-get-richer" effect. Since the first use of this term, it has been known that contributions can be broken diagnostically into a relatively straightforward tendency associated with moisture increases acted on by the climatological circulation and dynamical feedbacks associated with changes in circulation. A number of studies indicate the latter to be prone to yield scatter in model projections of precipitation change. At the spatial scales of the major monsoon regions, substantial contributions from dynamical feedbacks tend to occur. Factors affecting this dependence will be reviewed with an eye to asking how the community can make succinct statements without oversimplifying the challenges at the regional scale.
Evolutionary dynamics of social dilemmas in structured heterogeneous populations.
Santos, F C; Pacheco, J M; Lenaerts, Tom
2006-02-28
Real populations have been shown to be heterogeneous, in which some individuals have many more contacts than others. This fact contrasts with the traditional homogeneous setting used in studies of evolutionary game dynamics. We incorporate heterogeneity in the population by studying games on graphs, in which the variability in connectivity ranges from single-scale graphs, for which heterogeneity is small and associated degree distributions exhibit a Gaussian tale, to scale-free graphs, for which heterogeneity is large with degree distributions exhibiting a power-law behavior. We study the evolution of cooperation, modeled in terms of the most popular dilemmas of cooperation. We show that, for all dilemmas, increasing heterogeneity favors the emergence of cooperation, such that long-term cooperative behavior easily resists short-term noncooperative behavior. Moreover, we show how cooperation depends on the intricate ties between individuals in scale-free populations.
Dimensional study of the dynamical arrest in a random Lorentz gas.
Jin, Yuliang; Charbonneau, Patrick
2015-04-01
The random Lorentz gas (RLG) is a minimal model for transport in heterogeneous media. Upon increasing the obstacle density, it exhibits a growing subdiffusive transport regime and then a dynamical arrest. Here, we study the dimensional dependence of the dynamical arrest, which can be mapped onto the void percolation transition for Poisson-distributed point obstacles. We numerically determine the arrest in dimensions d=2-6. Comparison of the results with standard mode-coupling theory reveals that the dynamical theory prediction grows increasingly worse with d. In an effort to clarify the origin of this discrepancy, we relate the dynamical arrest in the RLG to the dynamic glass transition of the infinite-range Mari-Kurchan-model glass former. Through a mixed static and dynamical analysis, we then extract an improved dimensional scaling form as well as a geometrical upper bound for the arrest. The results suggest that understanding the asymptotic behavior of the random Lorentz gas may be key to surmounting fundamental difficulties with the mode-coupling theory of glasses.
Penn, Colin A.; Bearup, Lindsay A.; Maxwell, Reed M.; Clow, David W.
2016-01-01
The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.
Universality of clone dynamics during tissue development
NASA Astrophysics Data System (ADS)
Rulands, Steffen; Lescroart, Fabienne; Chabab, Samira; Hindley, Christopher J.; Prior, Nicole; Sznurkowska, Magdalena K.; Huch, Meritxell; Philpott, Anna; Blanpain, Cedric; Simons, Benjamin D.
2018-05-01
The emergence of complex organs is driven by the coordinated proliferation, migration and differentiation of precursor cells. The fate behaviour of these cells is reflected in the time evolution of their progeny, termed clones, which serve as a key experimental observable. In adult tissues, where cell dynamics is constrained by the condition of homeostasis, clonal tracing studies based on transgenic animal models have advanced our understanding of cell fate behaviour and its dysregulation in disease1,2. But what can be learnt from clonal dynamics in development, where the spatial cohesiveness of clones is impaired by tissue deformations during tissue growth? Drawing on the results of clonal tracing studies, we show that, despite the complexity of organ development, clonal dynamics may converge to a critical state characterized by universal scaling behaviour of clone sizes. By mapping clonal dynamics onto a generalization of the classical theory of aerosols, we elucidate the origin and range of scaling behaviours and show how the identification of universal scaling dependences may allow lineage-specific information to be distilled from experiments. Our study shows the emergence of core concepts of statistical physics in an unexpected context, identifying cellular systems as a laboratory to study non-equilibrium statistical physics.
The dynamics of oceanic fronts. I - The Gulf Stream
NASA Technical Reports Server (NTRS)
Kao, T. W.
1980-01-01
The establishment and maintenance of the mean hydrographic properties of large-scale density fronts in the upper ocean is considered. The dynamics is studied by posing an initial value problem starting with a near-surface discharge of buoyant water with a prescribed density deficit into an ambient stationary fluid of uniform density; full time dependent diffusion and Navier-Stokes equations are then used with constant eddy diffusion and viscosity coefficients, together with a constant Coriolis parameter. Scaling analysis reveals three independent scales of the problem including the radius of deformation of the inertial length, buoyancy length, and diffusive length scales. The governing equations are then suitably scaled and the resulting normalized equations are shown to depend on the Ekman number alone for problems of oceanic interest. It is concluded that the mean Gulf Stream dynamics can be interpreted in terms of a solution of the Navier-Stokes and diffusion equations, with the cross-stream circulation responsible for the maintenance of the front; this mechanism is suggested for the maintenance of the Gulf Stream dynamics.
Detonation failure characterization of non-ideal explosives
NASA Astrophysics Data System (ADS)
Janesheski, Robert S.; Groven, Lori J.; Son, Steven
2012-03-01
Non-ideal explosives are currently poorly characterized, hence limiting the modeling of them. Current characterization requires large-scale testing to obtain steady detonation wave characterization for analysis due to the relatively thick reaction zones. Use of a microwave interferometer applied to small-scale confined transient experiments is being implemented to allow for time resolved characterization of a failing detonation. The microwave interferometer measures the position of a failing detonation wave in a tube that is initiated with a booster charge. Experiments have been performed with ammonium nitrate and various fuel compositions (diesel fuel and mineral oil). It was observed that the failure dynamics are influenced by factors such as chemical composition and confiner thickness. Future work is planned to calibrate models to these small-scale experiments and eventually validate the models with available large scale experiments. This experiment is shown to be repeatable, shows dependence on reactive properties, and can be performed with little required material.
NASA Astrophysics Data System (ADS)
Barthel, Roland; Haaf, Ezra
2016-04-01
Regional hydrogeology is becoming increasingly important, but at the same time, scientifically sound, universal solutions for typical groundwater problems encountered on the regional scale are hard to find. While managers, decision-makers and state agencies operating on regional and national levels have always shown a strong interest in regional scale hydrogeology, researchers from academia tend to avoid the subject, focusing instead on local scales. Additionally, hydrogeology has always had a tendency to regard every problem as unique to its own site- and problem-specific context. Regional scale hydrogeology is therefore pragmatic rather than aiming at developing generic methodology (Barthel, 2014; Barthel and Banzhaf, 2016). One of the main challenges encountered on the regional scale in hydrogeology is the extreme heterogeneity that generally increases with the size of the studied area - paired with relative data scarcity. Even in well-monitored regions of the world, groundwater observations are usually clustered, leaving large areas without any direct data. However, there are many good reasons for assessing the status and predicting the behavior of groundwater systems under conditions of global change even for those areas and aquifers without observations. This is typically done by using rather coarsely discretized and / or poorly parameterized numerical models, or by using very simplistic conceptual hydrological models that do not take into account the complex three-dimensional geological setup. Numerical models heavily rely on local data and are resource-demanding. Conceptual hydrological models only deliver reliable information on groundwater if the geology is extremely simple. In this contribution, we present an approach to derive statistically relevant information for un-monitored areas, making use of existing information from similar localities that are or have been monitored. The approach combines site-specific knowledge with conceptual assumptions on the behavior of groundwater systems. It is based on the hypothesis that similar groundwater systems respond similarly to similar impacts. At its core is the classification of (i) static hydrogeological characteristics (such as aquifer geometry and hydraulic properties), (ii) dynamic changes of the boundary conditions (such as recharge, water levels in surface waters), and (iii) dynamic groundwater system responses (groundwater head and chemical parameters). The dependencies of system responses on explanatory variables are used to map knowledge from observed locations to areas without measurements. Classification of static and dynamic system features combined with information about known system properties and their dependencies provide insight into system behavior that cannot be directly derived through the analysis of raw data. Classification and dependency analysis could finally lead to a new framework for groundwater system assessment on the regional scale as a replacement or supplement to numerical groundwater models and catchment scale hydrological models. This contribution focusses on the main hydrogeological concepts underlying the approach while another EGU contribution (Haaf and Barthel, 2016) explains the methodologies used to classify groundwater systems. References: Barthel, R., 2014. A call for more fundamental science in regional hydrogeology. Hydrogeol J, 22(3): 507-510. Barthel, R., Banzhaf, S., 2016. Groundwater and Surface Water Interaction at the Regional-scale - A Review with Focus on Regional Integrated Models. Water Resour Manag, 30(1): 1-32. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs. Abstract submitted to EGU General Assembly 2016, Vienna, Austria.
Scale dependence in species turnover reflects variance in species occupancy.
McGlinn, Daniel J; Hurlbert, Allen H
2012-02-01
Patterns of species turnover may reflect the processes driving community dynamics across scales. While the majority of studies on species turnover have examined pairwise comparison metrics (e.g., the average Jaccard dissimilarity), it has been proposed that the species-area relationship (SAR) also offers insight into patterns of species turnover because these two patterns may be analytically linked. However, these previous links only apply in a special case where turnover is scale invariant, and we demonstrate across three different plant communities that over 90% of the pairwise turnover values are larger than expected based on scale-invariant predictions from the SAR. Furthermore, the degree of scale dependence in turnover was negatively related to the degree of variance in the occupancy frequency distribution (OFD). These findings suggest that species turnover diverges from scale invariance, and as such pairwise turnover and the slope of the SAR are not redundant. Furthermore, models developed to explain the OFD should be linked with those developed to explain species turnover to achieve a more unified understanding of community structure.
Dynamics of proteins aggregation. II. Dynamic scaling in confined media
NASA Astrophysics Data System (ADS)
Zheng, Size; Shing, Katherine S.; Sahimi, Muhammad
2018-03-01
In this paper, the second in a series devoted to molecular modeling of protein aggregation, a mesoscale model of proteins together with extensive discontinuous molecular dynamics simulation is used to study the phenomenon in a confined medium. The medium, as a model of a crowded cellular environment, is represented by a spherical cavity, as well as cylindrical tubes with two aspect ratios. The aggregation process leads to the formation of β sheets and eventually fibrils, whose deposition on biological tissues is believed to be a major factor contributing to many neuro-degenerative diseases, such as Alzheimer's, Parkinson's, and amyotrophic lateral sclerosis diseases. Several important properties of the aggregation process, including dynamic evolution of the total number of the aggregates, the mean aggregate size, and the number of peptides that contribute to the formation of the β sheets, have been computed. We show, similar to the unconfined media studied in Paper I [S. Zheng et al., J. Chem. Phys. 145, 134306 (2016)], that the computed properties follow dynamic scaling, characterized by power laws. The existence of such dynamic scaling in unconfined media was recently confirmed by experiments. The exponents that characterize the power-law dependence on time of the properties of the aggregation process in spherical cavities are shown to agree with those in unbounded fluids at the same protein density, while the exponents for aggregation in the cylindrical tubes exhibit sensitivity to the geometry of the system. The effects of the number of amino acids in the protein, as well as the size of the confined media, have also been studied. Similarities and differences between aggregation in confined and unconfined media are described, including the possibility of no fibril formation, if confinement is severe.
NASA Astrophysics Data System (ADS)
Hararuk, Oleksandra; Zwart, Jacob A.; Jones, Stuart E.; Prairie, Yves; Solomon, Christopher T.
2018-03-01
Formal integration of models and data to test hypotheses about the processes controlling carbon dynamics in lakes is rare, despite the importance of lakes in the carbon cycle. We built a suite of models (n = 102) representing different hypotheses about lake carbon processing, fit these models to data from a north-temperate lake using data assimilation, and identified which processes were essential for adequately describing the observations. The hypotheses that we tested concerned organic matter lability and its variability through time, temperature dependence of biological decay, photooxidation, microbial dynamics, and vertical transport of water via hypolimnetic entrainment and inflowing density currents. The data included epilimnetic and hypolimnetic CO2 and dissolved organic carbon, hydrologic fluxes, carbon loads, gross primary production, temperature, and light conditions at high frequency for one calibration and one validation year. The best models explained 76-81% and 64-67% of the variability in observed epilimnetic CO2 and dissolved organic carbon content in the validation data. Accurately describing C dynamics required accounting for hypolimnetic entrainment and inflowing density currents, in addition to accounting for biological transformations. In contrast, neither photooxidation nor variable organic matter lability improved model performance. The temperature dependence of biological decay (Q10) was estimated at 1.45, significantly lower than the commonly assumed Q10 of 2. By confronting multiple models of lake C dynamics with observations, we identified processes essential for describing C dynamics in a temperate lake at daily to annual scales, while also providing a methodological roadmap for using data assimilation to further improve understanding of lake C cycling.
Collet, Olivier; Chipot, Christophe
2003-05-28
The unfolding of the last, C-terminal residue of AcNH(2)-(l-Leu)(11)-NHMe in its alpha-helical form has been investigated by measuring the variation of free energy involved in the alpha(R) to beta conformational transition. These calculations were performed using large-scale molecular dynamics simulations in conjunction with the umbrella sampling method. For different temperatures ranging from 280 to 370 K, the free energy of activation was estimated. Concurrently, unfolding simulations of a homopolypeptide formed by twelve hydrophobic residues were carried out, employing a three-dimensional lattice model description of the peptide, with a temperature-dependent interaction potential. Using a Monte Carlo approach, the lowest free energy conformation, an analogue of a right-handed alpha-helix, was determined in the region where the peptide chain is well ordered. The free energy barrier separating this state from a distinct, compact conformation, analogue to a beta-strand, was determined over a large enough range of temperatures. The results of these molecular dynamics and lattice model simulations are consistent and indicate that the kinetics of the unfolding of a hydrophobic peptide exhibits a non-Arrhenius behavior closely related to the temperature dependence of the hydrophobic effect. These results further illuminate the necessity to include a temperature dependence in potential energy functions designed for coarse-grained models of proteins.
Protocols for efficient simulations of long-time protein dynamics using coarse-grained CABS model.
Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian
2014-01-01
Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long-time scale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific-requiring user-defined assumptions about the folding scenario-to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or a selected (e.g., native) structure. The described protocol has been validated using experimental data for protein folding model systems-the prediction results agreed well with the experimental results.
Imaging high-speed friction at the nanometer scale
Thorén, Per-Anders; de Wijn, Astrid S.; Borgani, Riccardo; Forchheimer, Daniel; Haviland, David B.
2016-01-01
Friction is a complicated phenomenon involving nonlinear dynamics at different length and time scales. Understanding its microscopic origin requires methods for measuring force on nanometer-scale asperities sliding at velocities reaching centimetres per second. Despite enormous advances in experimental technique, this combination of small length scale and high velocity remain elusive. We present a technique for rapidly measuring the frictional forces on a single asperity over a velocity range from zero to several centimetres per second. At each image pixel we obtain the velocity dependence of both conservative and dissipative forces, revealing the transition from stick-slip to smooth sliding friction. We explain measurements on graphite using a modified Prandtl–Tomlinson model, including the damped elastic deformation of the asperity. With its improved force sensitivity and small sliding amplitude, our method enables rapid and detailed surface mapping of the velocity dependence of frictional forces with less than 10 nm spatial resolution. PMID:27958267
Robustness and Vulnerability of Networks with Dynamical Dependency Groups.
Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi
2016-11-28
The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.
NASA Astrophysics Data System (ADS)
Tsige, Mesfin
While an extensive literature dealing with the structure and dynamics of polymers at surfaces and interfaces exist, there has been a paucity of information regarding the length scale of the influence of the surface on polymer mobility and its dependence on polymer-surface interaction. To address this issue, we have investigated using molecular dynamics simulations the dynamics of PMMA and PS films of similar system sizes on two different surfaces as a function of film thickness, polymer molecular weight, and temperature. The dynamics of the polymer chains in the film on two different surfaces will be discussed in the context of a three-layer model. This work was supported by NSF Grant DMR1410290.
NASA Astrophysics Data System (ADS)
Ruaud, M.; Wakelam, V.; Gratier, P.; Bonnell, I. A.
2018-04-01
Aim. We study the effect of large scale dynamics on the molecular composition of the dense interstellar medium during the transition between diffuse to dense clouds. Methods: We followed the formation of dense clouds (on sub-parsec scales) through the dynamics of the interstellar medium at galactic scales. We used results from smoothed particle hydrodynamics (SPH) simulations from which we extracted physical parameters that are used as inputs for our full gas-grain chemical model. In these simulations, the evolution of the interstellar matter is followed for 50 Myr. The warm low-density interstellar medium gas flows into spiral arms where orbit crowding produces the shock formation of dense clouds, which are held together temporarily by the external pressure. Results: We show that depending on the physical history of each SPH particle, the molecular composition of the modeled dense clouds presents a high dispersion in the computed abundances even if the local physical properties are similar. We find that carbon chains are the most affected species and show that these differences are directly connected to differences in (1) the electronic fraction, (2) the C/O ratio, and (3) the local physical conditions. We argue that differences in the dynamical evolution of the gas that formed dense clouds could account for the molecular diversity observed between and within these clouds. Conclusions: This study shows the importance of past physical conditions in establishing the chemical composition of the dense medium.
Wind reversals in turbulent Rayleigh-Bénard convection.
Araujo, Francisco Fontenele; Grossmann, Siegfried; Lohse, Detlef
2005-08-19
The phenomenon of irregular cessation and subsequent reversal of the large-scale circulation in turbulent Rayleigh-Bénard convection is theoretically analyzed. The force and thermal balance on a single plume detached from the thermal boundary layer yields a set of coupled nonlinear equations, whose dynamics is related to the Lorenz equations. For Prandtl and Rayleigh numbers in the range 10(-2) < or = Pr < or = 10(3) and 10(7) < or = Ra < or = 10(12), the model has the following features: (i) chaotic reversals may be exhibited at Ra > or = 10(7); (ii) the Reynolds number based on the root mean square velocity scales as Re(rms) approximately Ra([0.41...0.47]) (depending on Pr), and as Re(rms) approximately Pr(-[0.66...0.76]) (depending on Ra); and (iii) the mean reversal frequency follows an effective scaling law omega/(nu L(-2)) approximately Pr(-(0.64 +/- 0.01))Ra(0.44 +/- 0.01). The phase diagram of the model is sketched, and the observed transitions are discussed.
Cavitation erosion - scale effect and model investigations
NASA Astrophysics Data System (ADS)
Geiger, F.; Rutschmann, P.
2015-12-01
The experimental works presented in here contribute to the clarification of erosive effects of hydrodynamic cavitation. Comprehensive cavitation erosion test series were conducted for transient cloud cavitation in the shear layer of prismatic bodies. The erosion pattern and erosion rates were determined with a mineral based volume loss technique and with a metal based pit count system competitively. The results clarified the underlying scale effects and revealed a strong non-linear material dependency, which indicated significantly different damage processes for both material types. Furthermore, the size and dynamics of the cavitation clouds have been assessed by optical detection. The fluctuations of the cloud sizes showed a maximum value for those cavitation numbers related to maximum erosive aggressiveness. The finding suggests the suitability of a model approach which relates the erosion process to cavitation cloud dynamics. An enhanced experimental setup is projected to further clarify these issues.
NASA Astrophysics Data System (ADS)
Pelissetto, Andrea; Rossini, Davide; Vicari, Ettore
2018-03-01
We investigate the quantum dynamics of many-body systems subject to local (i.e., restricted to a limited space region) time-dependent perturbations. If the system crosses a quantum phase transition, an off-equilibrium behavior is observed, even for a very slow driving. We show that, close to the transition, time-dependent quantities obey scaling laws. In first-order transitions, the scaling behavior is universal, and some scaling functions can be computed exactly. For continuous transitions, the scaling laws are controlled by the standard critical exponents and by the renormalization-group dimension of the perturbation at the transition. Our protocol can be implemented in existing relatively small quantum simulators, paving the way for a quantitative probe of the universal off-equilibrium scaling behavior, without the need to manipulate systems close to the thermodynamic limit.
Feng, Sha; Vogelmann, Andrew M.; Li, Zhijin; ...
2015-01-20
Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scalesmore » larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.« less
"Going solid": a model of system dynamics and consequences for patient safety
Cook, R; Rasmussen, J
2005-01-01
Rather than being a static property of hospitals and other healthcare facilities, safety is dynamic and often on short time scales. In the past most healthcare delivery systems were loosely coupled—that is, activities and conditions in one part of the system had only limited effect on those elsewhere. Loose coupling allowed the system to buffer many conditions such as short term surges in demand. Modern management techniques and information systems have allowed facilities to reduce inefficiencies in operation. One side effect is the loss of buffers that previously accommodated demand surges. As a result, situations occur in which activities in one area of the hospital become critically dependent on seemingly insignificant events in seemingly distant areas. This tight coupling condition is called "going solid". Rasmussen's dynamic model of risk and safety can be used to formulate a model of patient safety dynamics that includes "going solid" and its consequences. Because the model addresses the dynamic aspects of safety, it is particularly suited to understanding current conditions in modern healthcare delivery and the way these conditions may lead to accidents. PMID:15805459
Unravelling the physics of size-dependent dislocation-mediated plasticity
NASA Astrophysics Data System (ADS)
El-Awady, Jaafar A.
2015-01-01
Size-affected dislocation-mediated plasticity is important in a wide range of materials and technologies. Here we develop a generalized size-dependent dislocation-based model that predicts strength as a function of crystal/grain size and the dislocation density. Three-dimensional (3D) discrete dislocation dynamics (DDD) simulations reveal the existence of a well-defined relationship between strength and dislocation microstructure at all length scales for both single crystals and polycrystalline materials. The results predict a transition from dislocation-source strengthening to forest-dominated strengthening at a size-dependent critical dislocation density. It is also shown that the Hall-Petch relationship can be physically interpreted by coupling with an appropriate kinetic equation of the evolution of the dislocation density in polycrystals. The model is shown to be in remarkable agreement with experiments. This work presents a micro-mechanistic framework to predict and interpret strength size-scale effects, and provides an avenue towards performing multiscale simulations without ad hoc assumptions.
Agent-based modeling of malaria vectors: the importance of spatial simulation.
Bomblies, Arne
2014-07-03
The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as "agents" in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important.
Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes
Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...
2015-08-07
While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less
Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.
While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less
Constantinescu, Adi; Golubović, Leonardo; Levandovsky, Artem
2013-09-01
Long range dewetting forces acting across thin films, such as the fundamental van der Waals interactions, may drive the formation of large clusters (tall multilayer islands) and pits, observed in thin films of diverse materials such as polymers, liquid crystals, and metals. In this study we further develop the methodology of the nonequilibrium statistical mechanics of thin films coarsening within continuum interface dynamics model incorporating long range dewetting interactions. The theoretical test bench model considered here is a generalization of the classical Mullins model for the dynamics of solid film surfaces. By analytic arguments and simulations of the model, we study the coarsening growth laws of clusters formed in thin films due to the dewetting interactions. The ultimate cluster growth scaling laws at long times are strongly universal: Short and long range dewetting interactions yield the same coarsening exponents. However, long range dewetting interactions, such as the van der Waals forces, introduce a distinct long lasting early time scaling behavior characterized by a slow growth of the cluster height/lateral size aspect ratio (i.e., a time-dependent Young angle) and by effective coarsening exponents that depend on cluster size. In this study, we develop a theory capable of analytically calculating these effective size-dependent coarsening exponents characterizing the cluster growth in the early time regime. Such a pronounced early time scaling behavior has been indeed seen in experiments; however, its physical origin has remained elusive to this date. Our theory attributes these observed phenomena to ubiquitous long range dewetting interactions acting across thin solid and liquid films. Our results are also applicable to cluster growth in initially very thin fluid films, formed by depositing a few monolayers or by a submonolayer deposition. Under this condition, the dominant coarsening mechanism is diffusive intercluster mass transport while the cluster coalescence plays a minor role, both in solid and in fluid films.
Dynamical Adaptation in Photoreceptors
Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava
2013-01-01
Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119
Dissipative gravitational bouncer on a vibrating surface
NASA Astrophysics Data System (ADS)
Espinoza Ortiz, J. S.; Lagos, R. E.
2017-12-01
We study the dynamical behavior of a particle flying under the influence of a gravitational field, with dissipation constant λ (Stokes-like), colliding successive times against a rigid surface vibrating harmonically with restitution coefficient α. We define re-scaled dimensionless dynamical variables, such as the relative particle velocity Ω with respect to the surface’s velocity; and the real parameter τ accounting for the temporal evolution of the system. At the particle-surface contact point and for the k‧th collision, we construct the mapping described by (τk ; Ω k ) in order to analyze the system’s nonlinear dynamical behavior. From the dynamical mapping, the fixed point trajectory is computed and its stability is analyzed. We find the dynamical behavior of the fixed point trajectory to be stable or unstable, depending on the values of the re-scaled vibrating surface amplitude Γ, the restitution coefficient α and the damping constant λ. Other important dynamical aspects such as the phase space volume and the one cycle vibrating surface (decomposed into absorbing and transmitting regions) are also discussed. Furthermore, the model rescues well known results in the limit λ = 0.
Local orientational mobility in regular hyperbranched polymers.
Dolgushev, Maxim; Markelov, Denis A; Fürstenberg, Florian; Guérin, Thomas
2016-07-01
We study the dynamics of local bond orientation in regular hyperbranched polymers modeled by Vicsek fractals. The local dynamics is investigated through the temporal autocorrelation functions of single bonds and the corresponding relaxation forms of the complex dielectric susceptibility. We show that the dynamic behavior of single segments depends on their remoteness from the periphery rather than on the size of the whole macromolecule. Remarkably, the dynamics of the core segments (which are most remote from the periphery) shows a scaling behavior that differs from the dynamics obtained after structural average. We analyze the most relevant processes of single segment motion and provide an analytic approximation for the corresponding relaxation times. Furthermore, we describe an iterative method to calculate the orientational dynamics in the case of very large macromolecular sizes.
A Stochastic Fractional Dynamics Model of Space-time Variability of Rain
NASA Technical Reports Server (NTRS)
Kundu, Prasun K.; Travis, James E.
2013-01-01
Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.
Dynamic molecular confinement in the plasma membrane by microdomains and the cytoskeleton meshwork.
Lenne, Pierre-François; Wawrezinieck, Laure; Conchonaud, Fabien; Wurtz, Olivier; Boned, Annie; Guo, Xiao-Jun; Rigneault, Hervé; He, Hai-Tao; Marguet, Didier
2006-07-26
It is by now widely recognized that cell membranes show complex patterns of lateral organization. Two mechanisms involving either a lipid-dependent (microdomain model) or cytoskeleton-based (meshwork model) process are thought to be responsible for these plasma membrane organizations. In the present study, fluorescence correlation spectroscopy measurements on various spatial scales were performed in order to directly identify and characterize these two processes in live cells with a high temporal resolution, without any loss of spatial information. Putative raft markers were found to be dynamically compartmented within tens of milliseconds into small microdomains (Ø <120 nm) that are sensitive to the cholesterol and sphingomyelin levels, whereas actin-based cytoskeleton barriers are responsible for the confinement of the transferrin receptor protein. A free-like diffusion was observed when both the lipid-dependent and cytoskeleton-based organizations were disrupted, which suggests that these are two main compartmentalizing forces at work in the plasma membrane.
Omnivory in birds is a macroevolutionary sink
Burin, Gustavo; Kissling, W. Daniel; Guimarães, Paulo R.; Şekercioğlu, Çağan H.; Quental, Tiago B.
2016-01-01
Diet is commonly assumed to affect the evolution of species, but few studies have directly tested its effect at macroevolutionary scales. Here we use Bayesian models of trait-dependent diversification and a comprehensive dietary database of all birds worldwide to assess speciation and extinction dynamics of avian dietary guilds (carnivores, frugivores, granivores, herbivores, insectivores, nectarivores, omnivores and piscivores). Our results suggest that omnivory is associated with higher extinction rates and lower speciation rates than other guilds, and that overall net diversification is negative. Trait-dependent models, dietary similarity and network analyses show that transitions into omnivory occur at higher rates than into any other guild. We suggest that omnivory acts as macroevolutionary sink, where its ephemeral nature is retrieved through transitions from other guilds rather than from omnivore speciation. We propose that these dynamics result from competition within and among dietary guilds, influenced by the deep-time availability and predictability of food resources. PMID:27052750
Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical Neurons
Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves
2009-01-01
Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of Vm activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the Vm reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the “effective” connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI. PMID:19779556
Network-state modulation of power-law frequency-scaling in visual cortical neurons.
El Boustani, Sami; Marre, Olivier; Béhuret, Sébastien; Baudot, Pierre; Yger, Pierre; Bal, Thierry; Destexhe, Alain; Frégnac, Yves
2009-09-01
Various types of neural-based signals, such as EEG, local field potentials and intracellular synaptic potentials, integrate multiple sources of activity distributed across large assemblies. They have in common a power-law frequency-scaling structure at high frequencies, but it is still unclear whether this scaling property is dominated by intrinsic neuronal properties or by network activity. The latter case is particularly interesting because if frequency-scaling reflects the network state it could be used to characterize the functional impact of the connectivity. In intracellularly recorded neurons of cat primary visual cortex in vivo, the power spectral density of V(m) activity displays a power-law structure at high frequencies with a fractional scaling exponent. We show that this exponent is not constant, but depends on the visual statistics used to drive the network. To investigate the determinants of this frequency-scaling, we considered a generic recurrent model of cortex receiving a retinotopically organized external input. Similarly to the in vivo case, our in computo simulations show that the scaling exponent reflects the correlation level imposed in the input. This systematic dependence was also replicated at the single cell level, by controlling independently, in a parametric way, the strength and the temporal decay of the pairwise correlation between presynaptic inputs. This last model was implemented in vitro by imposing the correlation control in artificial presynaptic spike trains through dynamic-clamp techniques. These in vitro manipulations induced a modulation of the scaling exponent, similar to that observed in vivo and predicted in computo. We conclude that the frequency-scaling exponent of the V(m) reflects stimulus-driven correlations in the cortical network activity. Therefore, we propose that the scaling exponent could be used to read-out the "effective" connectivity responsible for the dynamical signature of the population signals measured at different integration levels, from Vm to LFP, EEG and fMRI.
Lakghomi, B; Lawryshyn, Y; Hofmann, R
2015-01-01
Computational fluid dynamics (CFD) models of dissolved air flotation (DAF) have shown formation of stratified flow (back and forth horizontal flow layers at the top of the separation zone) and its impact on improved DAF efficiency. However, there has been a lack of experimental validation of CFD predictions, especially in the presence of solid particles. In this work, for the first time, both two-phase (air-water) and three-phase (air-water-solid particles) CFD models were evaluated at pilot scale using measurements of residence time distribution, bubble layer position and bubble-particle contact efficiency. The pilot-scale results confirmed the accuracy of the CFD model for both two-phase and three-phase flows, but showed that the accuracy of the three-phase CFD model would partly depend on the estimation of bubble-particle attachment efficiency.
Impact of Adsorption on Gas Transport in Nanopores.
Wu, Tianhao; Zhang, Dongxiao
2016-03-29
Given the complex nature of the interaction between gas and solid atoms, the development of nanoscale science and technology has engendered a need for further understanding of gas transport behavior through nanopores and more tractable models for large-scale simulations. In the present paper, we utilize molecular dynamic simulations to demonstrate the behavior of gas flow under the influence of adsorption in nano-channels consisting of illite and graphene, respectively. The results indicate that velocity oscillation exists along the cross-section of the nano-channel, and the total mass flow could be either enhanced or reduced depending on variations in adsorption under different conditions. The mechanisms can be explained by the extra average perturbation stress arising from density oscillation via the novel perturbation model for micro-scale simulation, and approximated via the novel dual-region model for macro-scale simulation, which leads to a more accurate permeability correction model for industrial applications than is currently available.
NASA Astrophysics Data System (ADS)
Asimow, P. D.; Thomas, C.; Wolf, A. S.
2012-12-01
Silicate melts are the essential agents of planetary differentiation and evolution. Their phase relations, element partitioning preferences, density, and transport properties determine the fates of heat and mass flow in the high-temperature interior of active planets. In the early Earth and in extrasolar super-Earth-mass terrestrial planets it is these properties at very high pressure (> 100 GPa) that control the evolution from possible magma oceans to solid-state convecting mantles. Yet these melts are complex, dynamic materials that present many challenges to experimental, theoretical, and computational understanding or prediction of their properties. There has been encouraging convergence among various approaches to understanding the structure and dynamics of silicate melts at multiple scales: nearest- and next-nearest neighbor structural information is derived from spectroscopic techniques such as high-resolution multinuclear NMR; first-principles molecular dynamics probe structure and dynamics at scales up to hundreds of atoms; Archimedean, ultrasonic, sink/float, and shock wave methods probe macroscopic properties (and occasionally dynamics); and deformation and diffusion experiments probe dynamics at macroscopic scale and various time scales. One challenge that remains to integrating all this information is a predictive model of silicate liquid structure that agrees with experiments and simulation both at microscopic and macroscopic scale. In addition to our efforts to collect macroscopic equation of state data using shock wave methods across ever-wider ranges of temperature, pressure, and composition space, we have introduced a simple model of coordination statistics around cations that can form the basis of a conceptual and predictive link across scales and methods. This idea is explored in this presentation specifically with regard to the temperature dependence of sound speed in ultramafic liquids. This is a highly uncertain quantity and yet it is key, in many models, to extrapolating the equation of state up or down temperature to geophysically relevant conditions. Ultrasonic data on felsic to basaltic melts, across a fairly narrow temperature range from their liquidi to ≤1650 °C, suggest either no temperature dependence or sound speeds that increase with temperature. Simulations, conducted at much higher temperature to obtain relaxation, suggest a strong decrease in sound speed with temperature. Our shock wave data on Mg2SiO4 liquid at 2000 °C yield a sound speed significantly lower than that predicted from data on less mafic liquids collected at lower temperatures where Mg2SiO4 liquid is not stable. The same shock method applied to melt compositions that are stable at 1300-1550 °C, however, yields sound speeds comparable to the ultrasonic results. Although each of these methods has its shortcomings, we show that considerable insight can be obtained in the context of a predictive model of Mg2+ and Si4+ coordination statistics as functions of temperature and pressure. We suggest that this can explain the difference between results obtained at ordinary upper mantle magmatic temperatures and those expected for magma oceans.
NASA Astrophysics Data System (ADS)
Sadeghzadeh, Sadegh; Farshad Mir Saeed Ghazi, Seyyed
2018-03-01
Piezoelectric Nanogenerator (PENG) is one of the novel energy harvester systems that recently, has been a subject of interest for researchers. By the use of nanogenerators, it’s possible to harvest different forms of energy in the environment like mechanical vibrations and generate electricity. The structure of a PENG consists of vertical arrays of nanowires between two electrodes. In this paper, dynamic analysis of a PENG is studied numerically. The modified couple stress theory which includes one length scale material parameter is used to study the size-dependent behavior of PENGs. Then, by application of a complete form of linear hybrid piezoelectric—pyroelectric equations, and using the Euler-Bernoulli beam model, the equations of motion has been derived. Generalized Differential Quadrature (GDQ) method was employed to solve the equations of motion. The effect of damping ratio, temperature rise, excitation frequency and length scale parameter was studied. It was found that the PENG voltage maximizes at the resonant frequency of nanowire. The temperature rise has a significant effect on PENG’s efficiency. When temperature increases about 10 {{K}}, the maximum voltage increases about 26%. Increasing the damping ratio, the maximum voltage decreases gradually.
Scale-dependent diffusion anisotropy in nanoporous silicon
Kondrashova, Daria; Lauerer, Alexander; Mehlhorn, Dirk; Jobic, Hervé; Feldhoff, Armin; Thommes, Matthias; Chakraborty, Dipanjan; Gommes, Cedric; Zecevic, Jovana; de Jongh, Petra; Bunde, Armin; Kärger, Jörg; Valiullin, Rustem
2017-01-01
Nanoporous silicon produced by electrochemical etching of highly B-doped p-type silicon wafers can be prepared with tubular pores imbedded in a silicon matrix. Such materials have found many technological applications and provide a useful model system for studying phase transitions under confinement. This paper reports a joint experimental and simulation study of diffusion in such materials, covering displacements from molecular dimensions up to tens of micrometers with carefully selected probe molecules. In addition to mass transfer through the channels, diffusion (at much smaller rates) is also found to occur in directions perpendicular to the channels, thus providing clear evidence of connectivity. With increasing displacements, propagation in both axial and transversal directions is progressively retarded, suggesting a scale-dependent, hierarchical distribution of transport resistances (“constrictions” in the channels) and of shortcuts (connecting “bridges”) between adjacent channels. The experimental evidence from these studies is confirmed by molecular dynamics (MD) simulation in the range of atomistic displacements and rationalized with a simple model of statistically distributed “constrictions” and “bridges” for displacements in the micrometer range via dynamic Monte Carlo (DMC) simulation. Both ranges are demonstrated to be mutually transferrable by DMC simulations based on the pore space topology determined by electron tomography. PMID:28106047
NASA Astrophysics Data System (ADS)
Verma, Aman; Mahesh, Krishnan
2012-08-01
The dynamic Lagrangian averaging approach for the dynamic Smagorinsky model for large eddy simulation is extended to an unstructured grid framework and applied to complex flows. The Lagrangian time scale is dynamically computed from the solution and does not need any adjustable parameter. The time scale used in the standard Lagrangian model contains an adjustable parameter θ. The dynamic time scale is computed based on a "surrogate-correlation" of the Germano-identity error (GIE). Also, a simple material derivative relation is used to approximate GIE at different events along a pathline instead of Lagrangian tracking or multi-linear interpolation. Previously, the time scale for homogeneous flows was computed by averaging along directions of homogeneity. The present work proposes modifications for inhomogeneous flows. This development allows the Lagrangian averaged dynamic model to be applied to inhomogeneous flows without any adjustable parameter. The proposed model is applied to LES of turbulent channel flow on unstructured zonal grids at various Reynolds numbers. Improvement is observed when compared to other averaging procedures for the dynamic Smagorinsky model, especially at coarse resolutions. The model is also applied to flow over a cylinder at two Reynolds numbers and good agreement with previous computations and experiments is obtained. Noticeable improvement is obtained using the proposed model over the standard Lagrangian model. The improvement is attributed to a physically consistent Lagrangian time scale. The model also shows good performance when applied to flow past a marine propeller in an off-design condition; it regularizes the eddy viscosity and adjusts locally to the dominant flow features.
NASA Astrophysics Data System (ADS)
Marras, S.; Suckale, J.; Eguzkitza, B.; Houzeaux, G.; Vázquez, M.; Lesage, A. C.
2016-12-01
The propagation of tsunamis in the open ocean has been studied in detail with many excellent numerical approaches available to researchers. Our understanding of the processes that govern the onshore propagation of tsunamis is less advanced. Yet, the reach of tsunamis on land is an important predictor of the damage associated with a given event, highlighting the need to investigate the factors that govern tsunami propagation onshore. In this study, we specifically focus on understanding the effect of bottom roughness at a variety of scales. The term roughness is to be understood broadly, as it represents scales ranging from small features like rocks, to vegetation, up to the size of larger structures and topography. In this poster, we link applied mathematics, computational fluid dynamics, and tsunami physics to analyze the small scales features of coastal hydrodynamics and the effect of roughness on the motion of tsunamis as they run up a sloping beach and propagate inland. We solve the three-dimensional Navier-Stokes equations of incompressible flows with free surface, which is tracked by a level set function in combination with an accurate re-distancing scheme. We discretize the equations via linear finite elements for space approximation and fully implicit time integration. Stabilization is achieved via the variational multiscale method whereas the subgrid scales for our large eddy simulations are modeled using a dynamically adaptive Smagorinsky eddy viscosity. As the geometrical characteristics of roughness in this study vary greatly across different scales, we implement a scale-dependent representation of the roughness elements. We model the smallest sub-grid scale roughness features by the use of a properly defined law of the wall. Furthermore, we utilize a Manning formula to compute the shear stress at the boundary. As the geometrical scales become larger, we resolve the geometry explicitly and compute the effective volume drag introduced by large scale immersed bodies. This study is a necessary step to verify and validate our model before proceeding further into the simulation of sediment transport in turbulent free surface flows. The simulation of such problems requires a space and time-dependent viscosity to model the effect of solid bodies transported by the incoming flow on onshore tsunami propagation.
Thermalization and light cones in a model with weak integrability breaking
Bertini, Bruno; Essler, Fabian H. L.; Groha, Stefan; ...
2016-12-09
Here, we employ equation-of-motion techniques to study the nonequilibrium dynamics in a lattice model of weakly interacting spinless fermions. Our model provides a simple setting for analyzing the effects of weak integrability-breaking perturbations on the time evolution after a quantum quench. We establish the accuracy of the method by comparing results at short and intermediate times to time-dependent density matrix renormalization group computations. For sufficiently weak integrability-breaking interactions we always observe prethermalization plateaus, where local observables relax to nonthermal values at intermediate time scales. At later times a crossover towards thermal behavior sets in. We determine the associated time scale,more » which depends on the initial state, the band structure of the noninteracting theory, and the strength of the integrability-breaking perturbation. Our method allows us to analyze in some detail the spreading of correlations and in particular the structure of the associated light cones in our model. We find that the interior and exterior of the light cone are separated by an intermediate region, the temporal width of which appears to scale with a universal power law t 1/3.« less
Null expectations for disease dynamics in shrinking habitat: dilution or amplification?
McCallum, Hamish I.; Gillespie, Thomas R.
2017-01-01
As biodiversity declines with anthropogenic land-use change, it is increasingly important to understand how changing biodiversity affects infectious disease risk. The dilution effect hypothesis, which points to decreases in biodiversity as critical to an increase in infection risk, has received considerable attention due to the allure of a win–win scenario for conservation and human well-being. Yet some empirical data suggest that the dilution effect is not a generalizable phenomenon. We explore the response of pathogen transmission dynamics to changes in biodiversity that are driven by habitat loss using an allometrically scaled multi-host model. With this model, we show that declining habitat, and thus declining biodiversity, can lead to either increasing or decreasing infectious-disease risk, measured as endemic prevalence. Whether larger habitats, and thus greater biodiversity, lead to a decrease (dilution effect) or increase (amplification effect) in infection prevalence depends upon the pathogen transmission mode and how host competence scales with body size. Dilution effects were detected for most frequency-transmitted pathogens and amplification effects were detected for density-dependent pathogens. Amplification effects were also observed over a particular range of habitat loss in frequency-dependent pathogens when we assumed that host competence was greatest in large-bodied species. By contrast, only amplification effects were observed for density-dependent pathogens; host competency only affected the magnitude of the effect. These models can be used to guide future empirical studies of biodiversity–disease relationships across gradients of habitat loss. The type of transmission, the relationship between host competence and community assembly, the identity of hosts contributing to transmission, and how transmission scales with area are essential factors to consider when elucidating the mechanisms driving disease risk in shrinking habitat. This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications'. PMID:28438921
Null expectations for disease dynamics in shrinking habitat: dilution or amplification?
Faust, Christina L; Dobson, Andrew P; Gottdenker, Nicole; Bloomfield, Laura S P; McCallum, Hamish I; Gillespie, Thomas R; Diuk-Wasser, Maria; Plowright, Raina K
2017-06-05
As biodiversity declines with anthropogenic land-use change, it is increasingly important to understand how changing biodiversity affects infectious disease risk. The dilution effect hypothesis, which points to decreases in biodiversity as critical to an increase in infection risk, has received considerable attention due to the allure of a win-win scenario for conservation and human well-being. Yet some empirical data suggest that the dilution effect is not a generalizable phenomenon. We explore the response of pathogen transmission dynamics to changes in biodiversity that are driven by habitat loss using an allometrically scaled multi-host model. With this model, we show that declining habitat, and thus declining biodiversity, can lead to either increasing or decreasing infectious-disease risk, measured as endemic prevalence. Whether larger habitats, and thus greater biodiversity, lead to a decrease (dilution effect) or increase (amplification effect) in infection prevalence depends upon the pathogen transmission mode and how host competence scales with body size. Dilution effects were detected for most frequency-transmitted pathogens and amplification effects were detected for density-dependent pathogens. Amplification effects were also observed over a particular range of habitat loss in frequency-dependent pathogens when we assumed that host competence was greatest in large-bodied species. By contrast, only amplification effects were observed for density-dependent pathogens; host competency only affected the magnitude of the effect. These models can be used to guide future empirical studies of biodiversity-disease relationships across gradients of habitat loss. The type of transmission, the relationship between host competence and community assembly, the identity of hosts contributing to transmission, and how transmission scales with area are essential factors to consider when elucidating the mechanisms driving disease risk in shrinking habitat.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'. © 2017 The Author(s).
Scale Dependence of Dark Energy Antigravity
NASA Astrophysics Data System (ADS)
Perivolaropoulos, L.
2002-09-01
We investigate the effects of negative pressure induced by dark energy (cosmological constant or quintessence) on the dynamics at various astrophysical scales. Negative pressure induces a repulsive term (antigravity) in Newton's law which dominates on large scales. Assuming a value of the cosmological constant consistent with the recent SnIa data we determine the critical scale $r_c$ beyond which antigravity dominates the dynamics ($r_c \\sim 1Mpc $) and discuss some of the dynamical effects implied. We show that dynamically induced mass estimates on the scale of the Local Group and beyond are significantly modified due to negative pressure. We also briefly discuss possible dynamical tests (eg effects on local Hubble flow) that can be applied on relatively small scales (a few $Mpc$) to determine the density and equation of state of dark energy.
NASA Astrophysics Data System (ADS)
Lee, Kyu Sang; Gill, Wonpyong
2017-11-01
The dynamic properties, such as the crossing time and time-dependence of the relative density of the four-state haploid coupled discrete-time mutation-selection model, were calculated with the assumption that μ ij = μ ji , where μ ij denotes the mutation rate between the sequence elements, i and j. The crossing time for s = 0 and r 23 = r 42 = 1 in the four-state model became saturated at a large fitness parameter when r 12 > 1, was scaled as a power law in the fitness parameter when r 12 = 1, and diverged when the fitness parameter approached the critical fitness parameter when r 12 < 1, where r ij = μ ij / μ 14.
Quasi-steady solar wind dynamics
NASA Technical Reports Server (NTRS)
Pizzo, V. J.
1983-01-01
Progress in understanding the large scale dynamics of quasisteady, corotating solar wind structure was reviewed. The nature of the solar wind at large heliocentric distances preliminary calculations from a 2-D MHD model are used to demonstrate theoretical expectations of corotating structure out to 30 AU. It is found that the forward and reverse shocks from adjacent CIR's begin to interact at about 10 AU, producing new shock pairs flanking secondary CIR's. These sawtooth secondary CIR's interact again at about 20 AU and survive as visible entities to 30 AU. The model predicts the velocity jumps at the leading edge of the secondary CIR's at 30 AU should be very small but there should still be sizable variations in the thermodynamic and magnetic parameters. The driving dynamic mechanism in the distant solar wind is the relaxation of pressure gradients. The second topic is the influence of weak, nonimpulsive time dependence in quasisteady dynamics. It is suggested that modest large scale variations in the coronal flow speed on periods of several hours to a day may be responsible for many of the remaining discrepancies between theory and observation. Effects offer a ready explanation for the apparent rounding of stream fronts between 0.3 and 1.0 AU discovered by Helios.
Large-amplitude jumps and non-Gaussian dynamics in highly concentrated hard sphere fluids.
Saltzman, Erica J; Schweizer, Kenneth S
2008-05-01
Our microscopic stochastic nonlinear Langevin equation theory of activated dynamics has been employed to study the real-space van Hove function of dense hard sphere fluids and suspensions. At very short times, the van Hove function is a narrow Gaussian. At sufficiently high volume fractions, such that the entropic barrier to relaxation is greater than the thermal energy, its functional form evolves with time to include a rapidly decaying component at small displacements and a long-range exponential tail. The "jump" or decay length scale associated with the tail increases with time (or particle root-mean-square displacement) at fixed volume fraction, and with volume fraction at the mean alpha relaxation time. The jump length at the alpha relaxation time is predicted to be proportional to a measure of the decoupling of self-diffusion and structural relaxation. At long times corresponding to mean displacements of order a particle diameter, the volume fraction dependence of the decay length disappears. A good superposition of the exponential tail feature based on the jump length as a scaling variable is predicted at high volume fractions. Overall, the theoretical results are in good accord with recent simulations and experiments. The basic aspects of the theory are also compared with a classic jump model and a dynamically facilitated continuous time random-walk model. Decoupling of the time scales of different parts of the relaxation process predicted by the theory is qualitatively similar to facilitated dynamics models based on the concept of persistence and exchange times if the elementary event is assumed to be associated with transport on a length scale significantly smaller than the particle size.
Le Mouël, Jean-Louis; Allègre, Claude J.; Narteau, Clément
1997-01-01
A scaling law approach is used to simulate the dynamo process of the Earth’s core. The model is made of embedded turbulent domains of increasing dimensions, until the largest whose size is comparable with the site of the core, pervaded by large-scale magnetic fields. Left-handed or right-handed cyclones appear at the lowest scale, the scale of the elementary domains of the hierarchical model, and disappear. These elementary domains then behave like electromotor generators with opposite polarities depending on whether they contain a left-handed or a right-handed cyclone. To transfer the behavior of the elementary domains to larger ones, a dynamic renormalization approach is used. A simple rule is adopted to determine whether a domain of scale l is a generator—and what its polarity is—in function of the state of the (l − 1) domains it is made of. This mechanism is used as the main ingredient of a kinematic dynamo model, which displays polarity intervals, excursions, and reversals of the geomagnetic field. PMID:11038547
NASA Astrophysics Data System (ADS)
Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.
2015-12-01
Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.
Criticality and Phase Transition in Stock-Price Fluctuations
NASA Astrophysics Data System (ADS)
Kiyono, Ken; Struzik, Zbigniew R.; Yamamoto, Yoshiharu
2006-02-01
We analyze the behavior of the U.S. S&P 500 index from 1984 to 1995, and characterize the non-Gaussian probability density functions (PDF) of the log returns. The temporal dependence of fat tails in the PDF of a ten-minute log return shows a gradual, systematic increase in the probability of the appearance of large increments on approaching black Monday in October 1987, reminiscent of parameter tuning towards criticality. On the occurrence of the black Monday crash, this culminates in an abrupt transition of the scale dependence of the non-Gaussian PDF towards scale-invariance characteristic of critical behavior. These facts suggest the need for revisiting the turbulent cascade paradigm recently proposed for modeling the underlying dynamics of the financial index, to account for time varying—phase transitionlike and scale invariant-critical-like behavior.
An new MHD/kinetic model for exploring energetic particle production in macro-scale systems
NASA Astrophysics Data System (ADS)
Drake, J. F.; Swisdak, M.; Dahlin, J. T.
2017-12-01
A novel MHD/kinetic model is being developed to explore magneticreconnection and particle energization in macro-scale systems such asthe solar corona and the outer heliosphere. The model blends the MHDdescription with a macro-particle description. The rationale for thismodel is based on the recent discovery that energetic particleproduction during magnetic reconnection is controlled by Fermireflection and Betatron acceleration and not parallel electricfields. Since the former mechanisms are not dependent on kineticscales such as the Debye length and the electron and ion inertialscales, a model that sheds these scales is sufficient for describingparticle acceleration in macro-systems. Our MHD/kinetic model includesmacroparticles laid out on an MHD grid that are evolved with the MHDfields. Crucially, the feedback of the energetic component on the MHDfluid is included in the dynamics. Thus, energy of the total system,the MHD fluid plus the energetic component, is conserved. The systemhas no kinetic scales and therefore can be implemented to modelenergetic particle production in macro-systems with none of theconstraints associated with a PIC model. Tests of the new model insimple geometries will be presented and potential applications will bediscussed.
Evolution of regulatory networks towards adaptability and stability in a changing environment
NASA Astrophysics Data System (ADS)
Lee, Deok-Sun
2014-11-01
Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.
Multi-scale Modeling of Plasticity in Tantalum.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay
In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describingmore » temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct and quantitative comparisons between experimental measurements and simulation show that the proposed model accurately captures plasticity in deformation of polycrystalline tantalum.« less
Generalized Pseudo-Reaction Zone Model for Non-Ideal Explosives
NASA Astrophysics Data System (ADS)
Wescott, Bradley
2007-06-01
The pseudo-reaction zone model was proposed to improve engineering scale simulations when using Detonation Shock Dynamics with high explosives that have a slow reaction component. In this work an extension of the pseudo-reaction zone model is developed for non-ideal explosives that propagate well below their steady-planar Chapman-Jouguet velocity. A programmed burn method utilizing Detonation Shock Dynamics and a detonation velocity dependent pseudo-reaction rate has been developed for non-ideal explosives and applied to the explosive mixture of ammonium nitrate and fuel oil (ANFO). The pseudo-reaction rate is calibrated to the experimentally obtained normal detonation velocity---shock curvature relation. The generalized pseudo-reaction zone model proposed here predicts the cylinder expansion to within 1% by accounting for the slow reaction in ANFO.
The structure and dynamics of tornado-like vortices
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nolan, D.S.; Farrell, B.F.
The structure and dynamics of axisymmetric tornado-like vortices are explored with a numerical model of axisymmetric incompressible flow based on recently developed numerical methods. The model is first shown to compare favorably with previous results and is then used to study the effects of varying the major parameters controlling the vortex: the strength of the convective forcing, the strength of the rotational forcing, and the magnitude of the model eddy viscosity. Dimensional analysis of the model problem indicates that the results must depend on only two dimensionless parameters. The natural choices for these two parameters are a convective Reynolds numbermore » (based on the velocity scale associated with the convective forcing) and a parameter analogous to the swirl ratio in laboratory models. However, by examining sets of simulations with different model parameters it is found that a dimensionless parameter known as the vortex Reynolds number, which is the ratio of the far-field circulation to the eddy viscosity, is more effective than the convention swirl ratio for predicting the structure of the vortex. The parameter space defined by the choices for model parameters is further explored with large sets of numerical simulations. For much of this parameter space it is confirmed that the vortex structure and time-dependent behavior depend strongly on the vortex Reynolds number and only weakly on the convective Reynolds number. The authors also find that for higher convective Reynolds numbers, the maximum possible wind speed increases, and the rotational forcing necessary to achieve that wind speed decreases. Physical reasoning is used to explain this behavior, and implications for tornado dynamics are discussed.« less
NASA Astrophysics Data System (ADS)
Elbanna, A. E.
2013-12-01
Numerous field and experimental observations suggest that faults surfaces are rough at multiple scales and tend to produce a wide range of branch sizes ranging from micro-branching to large scale secondary faults. The development and evolution of fault roughness and branching is believed to play an important role in rupture dynamics and energy partitioning. Previous work by several groups has succeeded in determining conditions under which a main rupture may branch into a secondary fault. Recently, there great progress has been made in investigating rupture propagation on rough faults with and without off-fault plasticity. Nonetheless, in most of these models the heterogeneity, whether the roughness profile or the secondary faults orientation, was built into the system from the beginning and consequently the final outcome depends strongly on the initial conditions. Here we introduce an adaptive mesh technique for modeling mode-II crack propagation on slip weakening frictional interfaces. We use a Finite Element Framework with random mesh topology that adapts to crack dynamics through element splitting and sequential insertion of frictional interfaces dictated by the failure criterion. This allows the crack path to explore non-planar paths and develop the roughness profile that is most compatible with the dynamical constraints. It also enables crack branching at different scales. We quantify energy dissipation due to the roughening process and small scale branching. We compare the results of our model to a reference case for propagation on a planar fault. We show that the small scale processes of roughening and branching influence many characteristics of the rupture propagation including the energy partitioning, rupture speed and peak slip rates. We also estimate the fracture energy required for propagating a crack on a planar fault that will be required to produce comparable results. We anticipate that this modeling approach provides an attractive methodology that complements the current efforts in modeling off-fault plasticity and damage.
Chen, Pan; Terenzi, Camilla; Furó, István; Berglund, Lars A; Wohlert, Jakob
2018-05-15
Macromolecular dynamics in biological systems, which play a crucial role for biomolecular function and activity at ambient temperature, depend strongly on moisture content. Yet, a generally accepted quantitative model of hydration-dependent phenomena based on local relaxation and diffusive dynamics of both polymer and its adsorbed water is still missing. In this work, atomistic-scale spatial distributions of motional modes are calculated using molecular dynamics simulations of hydrated xyloglucan (XG). These are shown to reproduce experimental hydration-dependent 13 C NMR longitudinal relaxation times ( T 1 ) at room temperature, and relevant features of their broad distributions, which are indicative of locally heterogeneous polymer reorientational dynamics. At low hydration, the self-diffusion behavior of water shows that water molecules are confined to particular locations in the randomly aggregated XG network while the average polymer segmental mobility remains low. Upon increasing water content, the hydration network becomes mobile and fully accessible for individual water molecules, and the motion of hydrated XG segments becomes faster. Yet, the polymer network retains a heterogeneous gel-like structure even at the highest level of hydration. We show that the observed distribution of relaxations times arises from the spatial heterogeneity of chain mobility that in turn is a result of heterogeneous distribution of water-chain and chain-chain interactions. Our findings contribute to the picture of hydration-dependent dynamics in other macromolecules such as proteins, DNA, and synthetic polymers, and hold important implications for the mechanical properties of polysaccharide matrixes in plants and plant-based materials.
Engineering a Sustainable Blue Planet: Exploring the dynamics
NASA Astrophysics Data System (ADS)
Lall, U.
2004-12-01
Man's hand as a geomorphic agent is now endemic. The dynamics of water and other material cycles is now significantly impacted at all scales: from hillsides to watersheds to the earth, and from urban flash flood events to mean long term flow. Locally and regionally, climatic exigencies serve to spur either ruin (in the poorest societies) or a flurry of human infrastructure development. Thus, at the local scale, geomorphology depends on man's struggle for survival, and the associated interaction with nature's vagaries. Of course, we now recognize that man induced changes in land surface attributes (related to agriculture or deforestation) and in atmospheric composition translate into relatively unforeseeable climate changes, i.e., nature at a planetary scale has a different face. Despite the recognition of these interacting factors, a conceptual model that treats the dynamics of man and nature as separable and separate, dominates the earth sciences. We study global climate change and its impacts as sequential outcomes of a carbon emission scenario, and not as endogenous processes of the earth-man system with mutual feedbacks. The definition of a man-nature dynamical system is feasible as an abstraction. I explore such a definition through examples, one at the global scale, and one at a local scale. These examples are formulated in the context of meeting the challenge of poverty reduction through the provision of water for health and food, while considering vulnerability to a dynamic climate and to changes in the environment.
Impact of the glass transition on exciton dynamics in polymer thin films
NASA Astrophysics Data System (ADS)
Ehrenreich, Philipp; Proepper, Daniel; Graf, Alexander; Jores, Stefan; Boris, Alexander V.; Schmidt-Mende, Lukas
2017-11-01
In the development of organic electronics, unlimited design possibilities of conjugated polymers offer a wide variety of mechanical and electronic properties. Thereby, it is crucially important to reveal universal physical characteristics that allow efficient and forward developments of new chemical compounds. In particular for organic solar cells, a deeper understanding of exciton dynamics in polymer films can help to improve the charge generation process further. For this purpose, poly(3-hexylthiophene) (P3HT) is commonly used as a model system, although exciton decay kinetics have found different interpretations. Using temperature-dependent time-resolved photoluminescence spectroscopy in combination with low-temperature spectroscopic ellipsometry, we can show that P3HT is indeed a model system in which excitons follow a simple diffusion/hopping model. Based on our results we can exclude the relevance of hot-exciton emission as well as a dynamic torsional relaxation upon photoexcitation on a ps time scale. Instead, we depict the glass transition temperature of polymers to strongly affect exciton dynamics.
A study of a diffusive model of asset returns and an empirical analysis of financial markets
NASA Astrophysics Data System (ADS)
Alejandro Quinones, Angel Luis
A diffusive model for market dynamics is studied and the predictions of the model are compared to real financial markets. The model has a non-constant diffusion coefficient which depends both on the asset value and the time. A general solution for the distribution of returns is obtained and shown to match the results of computer simulations for two simple cases, piecewise linear and quadratic diffusion. The effects of discreteness in the market dynamics on the model are also studied. For the quadratic diffusion case, a type of phase transition leading to fat tails is observed as the discrete distribution approaches the continuum limit. It is also found that the model captures some of the empirical stylized facts observed in real markets, including fat-tails and scaling behavior in the distribution of returns. An analysis of empirical data for the EUR/USD currency exchange rate and the S&P 500 index is performed. Both markets show time scaling behavior consistent with a value of 1/2 for the Hurst exponent. Finally, the results show that the distribution of returns for the two markets is well fitted by the model, and the corresponding empirical diffusion coefficients are determined.
On neutral metacommunity patterns of river basins at different scales of aggregation
NASA Astrophysics Data System (ADS)
Convertino, Matteo; Muneepeerakul, Rachata; Azaele, Sandro; Bertuzzo, Enrico; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio
2009-08-01
Neutral metacommunity models for spatial biodiversity patterns are implemented on river networks acting as ecological corridors at different resolution. Coarse-graining elevation fields (under the constraint of preserving the basin mean elevation) produce a set of reconfigured drainage networks. The hydrologic assumption made implies uniform runoff production such that each link has the same habitat capacity. Despite the universal scaling properties shown by river basins regardless of size, climate, vegetation, or exposed lithology, we find that species richness at local and regional scales exhibits resolution-dependent behavior. In addition, we investigate species-area relationships and rank-abundance patterns. The slopes of the species-area relationships, which are consistent over coarse-graining resolutions, match those found in real landscapes in the case of long-distance dispersal. The rank-abundance patterns are independent of the resolution over a broad range of dispersal length. Our results confirm that strong interactions occur between network structure and the dispersal of species and that under the assumption of neutral dynamics, these interactions produce resolution-dependent biodiversity patterns that diverge from expectations following from universal geomorphic scaling laws. Both in theoretical and in applied ecology studying how patterns change in resolution is relevant for understanding how ecological dynamics work in fragmented landscape and for sampling and biodiversity management campaigns, especially in consideration of climate change.
Shock Wave Propagation in Cementitious Materials at Micro/Meso Scales
NASA Astrophysics Data System (ADS)
Rajendran, Arunachalam
2015-06-01
The mechanical and constitutive response of materials like cement, and bio materials like fish scale and abalone shell is very complex due to heterogeneities that are inherently present in the nano and microstructures. The intrinsic constitutive behaviors are driven by the chemical composition and the molecular, micro, and meso structures. Therefore, it becomes important to identify the material genome as the building block for the material. For instance, in cementitious materials, the genome of C-S-H phase (the glue or the paste) that holds the various clinkers, such as the dicalcium silicate, tricalcium silicate, calcium ferroaluminates, and others is extremely complex. Often mechanical behaviors of C-S-H type materials are influenced by the chemistry and the structures at all nano to micro length scales. By explicitly modeling the molecular structures using appropriate potentials, it is then possible to compute the elastic tensor from molecular dynamics simulations using all atom method. The elastic tensors for the C-S-H gel and other clinkers are determined using the software suite ``Accelrys Materials Studio.'' A strain rate dependent, fracture mechanics based tensile damage model has been incorporated into ABAQUS finite element code to model spall evolution in the heterogeneous cementitious material with all constituents explicitly modeled through one micron element resolution. This paper presents results from nano/micro/meso scale analyses of shock wave propagation in a heterogeneous cementitious material using both molecular dynamic and finite element codes.
Universal Ferroelectric Switching Dynamics of Vinylidene Fluoride-trifluoroethylene Copolymer Films
Hu, Wei Jin; Juo, Deng-Ming; You, Lu; Wang, Junling; Chen, Yi-Chun; Chu, Ying-Hao; Wu, Tom
2014-01-01
In this work, switching dynamics of poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] copolymer films are investigated over unprecedentedly wide ranges of temperature and electric field. Remarkably, domain switching of copolymer films obeys well the classical domain nucleation and growth model although the origin of ferroelectricity in organic ferroelectric materials inherently differs from the inorganic counterparts. A lower coercivity limit of 50 MV/m and 180° domain wall energy of 60 mJ/m2 are determined for P(VDF-TrFE) films. Furthermore, we discover in copolymer films an anomalous temperature-dependent crossover behavior between two power-law scaling regimes of frequency-dependent coercivity, which is attributed to the transition between flow and creep motions of domain walls. Our observations shed new light on the switching dynamics of semi-crystalline ferroelectric polymers, and such understandings are critical for realizing their reliable applications. PMID:24759786
NASA Astrophysics Data System (ADS)
Rezaei Kivi, Araz; Azizi, Saber; Norouzi, Peyman
2017-12-01
In this paper, the nonlinear size-dependent static and dynamic behavior of an electrostatically actuated nano-beam is investigated. A fully clamped nano-beam is considered for the modeling of the deformable electrode of the NEMS. The governing differential equation of the motion is derived using Hamiltonian principle based on couple stress theory; a non-classical theory for considering length scale effects. The nonlinear partial differential equation of the motion is discretized to a nonlinear Duffing type ODE's using Galerkin method. Static and dynamic pull-in instabilities obtained by both classical theory and MCST are compared. At the second stage of analysis, shooting technique is utilized to obtain the frequency response curve, and to capture the periodic solutions of the motion; the stability of the periodic solutions are gained by Floquet theory. The nonlinear dynamic behavior of the deformable electrode due to the AC harmonic accompanied with size dependency is investigated.
NASA Astrophysics Data System (ADS)
Kluber, Alexander; Hayre, Robert; Cox, Daniel
2012-02-01
Motivated by the need to find beta-structure aggregation nuclei for the polyQ diseases such as Huntington's, we have undertaken a search for length dependent structure in model polyglutamine proteins. We use the Onufriev-Bashford-Case (OBC) generalized Born implicit solvent GPU based AMBER11 molecular dynamics with the parm96 force field coupled with a replica exchange method to characterize monomeric strands of polyglutamine as a function of chain length and temperature. This force field and solvation method has been shown among other methods to accurately reproduce folded metastability in certain small peptides, and to yield accurately de novo folded structures in a millisecond time-scale protein. Using GPU molecular dynamics we can sample out into the microsecond range. Additionally, explicit solvent runs will be used to verify results from the implicit solvent runs. We will assess order using measures of secondary structure and hydrogen bond content.
NASA Astrophysics Data System (ADS)
Lou, Yu-Qing; Hu, Xu-Yao
2016-06-01
We present a theoretical model framework for general polytropic (GP) hydrodynamic cylinder under self-gravity of infinite length with axial uniformity and axisymmetry. For self-similar dynamic solutions, we derive valuable integrals, analytic asymptotic solutions, sonic critical curves, shock conditions, and global numerical solutions with or without expansion shocks. Among others, we investigate various dynamic solutions featured with central free-fall asymptotic behaviours, corresponding to a collapsed mass string with a sustained dynamic accretion from a surrounding mass reservoir. Depending on the allowed ranges of a scaling index a < -1, such cylindrical dynamic mass accretion rate could be steady, increasing with time and decreasing with time. Physically, such a collapsed mass string or filament would break up into a sequence of sub-clumps and segments as induced by gravitational Jeans instabilities. Depending on the scales involved, such sub-clumps would evolve into collapsed objects or gravitationally bound systems. In diverse astrophysical and cosmological contexts, such a scenario can be adapted on various temporal, spatial and mass scales to form a chain of collapsed clumps and/or compact objects. Examples include the formation of chains of proto-stars, brown dwarfs and gaseous planets along molecular filaments; the formation of luminous massive stars along magnetized spiral arms and circum-nuclear starburst rings in barred spiral galaxies; the formation of chains of compact stellar objects such as white dwarfs, neutron stars, and black holes along a highly condensed mass string. On cosmological scales, one can perceive the formation of chains of galaxies, chains of galaxy clusters or even chains of supermassive and hypermassive black holes in the Universe including the early Universe. All these chains referred to above include possible binaries.
Anomalous diffusion and scaling in coupled stochastic processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bel, Golan; Nemenman, Ilya
2009-01-01
Inspired by problems in biochemical kinetics, we study statistical properties of an overdamped Langevin processes with the friction coefficient depending on the state of a similar, unobserved, process. Integrating out the latter, we derive the Pocker-Planck the friction coefficient of the first depends on the state of the second. Integrating out the latter, we derive the Focker-Planck equation for the probability distribution of the former. This has the fonn of diffusion equation with time-dependent diffusion coefficient, resulting in an anomalous diffusion. The diffusion exponent can not be predicted using a simple scaling argument, and anomalous scaling appears as well. Themore » diffusion exponent of the Weiss-Havlin comb model is derived as a special case, and the same exponent holds even for weakly coupled processes. We compare our theoretical predictions with numerical simulations and find an excellent agreement. The findings caution against treating biochemical systems with unobserved dynamical degrees of freedom by means of standandard, diffusive Langevin descritpion.« less
Modeling the effects of weather and climate change on malaria transmission.
Parham, Paul Edward; Michael, Edwin
2010-05-01
In recent years, the impact of climate change on human health has attracted considerable attention; the effects on malaria have been of particular interest because of its disease burden and its transmission sensitivity to environmental conditions. We investigated and illustrated the role that dynamic process-based mathematical models can play in providing strategic insights into the effects of climate change on malaria transmission. We evaluated a relatively simple model that permitted valuable and novel insights into the simultaneous effects of rainfall and temperature on mosquito population dynamics, malaria invasion, persistence and local seasonal extinction, and the impact of seasonality on transmission. We illustrated how large-scale climate simulations and infectious disease systems may be modeled and analyzed and how these methods may be applied to predicting changes in the basic reproduction number of malaria across Tanzania. We found extinction to be more strongly dependent on rainfall than on temperature and identified a temperature window of around 32-33 degrees C where endemic transmission and the rate of spread in disease-free regions is optimized. This window was the same for Plasmodium falciparum and P. vivax, but mosquito density played a stronger role in driving the rate of malaria spread than did the Plasmodium species. The results improved our understanding of how temperature shifts affect the global distribution of at-risk regions, as well as how rapidly malaria outbreaks take off within vulnerable populations. Disease emergence, extinction, and transmission all depend strongly on climate. Mathematical models offer powerful tools for understanding geographic shifts in incidence as climate changes. Nonlinear dependences of transmission on climate necessitates consideration of both changing climate trends and variability across time scales of interest.
Park, Sang-Won; Kim, Soree; Jung, YounJoon
2015-11-21
We study how dynamic heterogeneity in ionic liquids is affected by the length scale of structural relaxation and the ionic charge distribution by the molecular dynamics simulations performed on two differently charged models of ionic liquid and their uncharged counterpart. In one model of ionic liquid, the charge distribution in the cation is asymmetric, and in the other it is symmetric, while their neutral counterpart has no charge with the ions. It is found that all the models display heterogeneous dynamics, exhibiting subdiffusive dynamics and a nonexponential decay of structural relaxation. We investigate the lifetime of dynamic heterogeneity, τ(dh), in these systems by calculating the three-time correlation functions to find that τ(dh) has in general a power-law behavior with respect to the structural relaxation time, τ(α), i.e., τ(dh) ∝ τ(α)(ζ(dh)). Although the dynamics of the asymmetric-charge model is seemingly more heterogeneous than that of the symmetric-charge model, the exponent is found to be similar, ζ(dh) ≈ 1.2, for all the models studied in this work. The same scaling relation is found regardless of interactions, i.e., with or without Coulomb interaction, and it holds even when the length scale of structural relaxation is long enough to become the Fickian diffusion. This fact indicates that τ(dh) is a distinctive time scale from τ(α), and the dynamic heterogeneity is mainly affected by the short-range interaction and the molecular structure.
Scale dependant compensational stacking of channelized sedimentary deposits
NASA Astrophysics Data System (ADS)
Wang, Y.; Straub, K. M.; Hajek, E. A.
2010-12-01
Compensational stacking, the tendency for sediment transport system to preferentially fill topographic lows, thus smoothing out topographic relief is a concept used in the interpretation of the stratigraphic record. Recently, a metric was developed to quantify the strength of compensation in sedimentary basins by comparing observed stacking patterns to what would be expected from simple, uncorrelated stacking. This method uses the rate of decay of spatial variability in sedimentation between picked depositional horizons with increasing vertical stratigraphic averaging distance. We explore how this metric varies as a function of stratigraphic scale using data from physical experiments, stratigraphy exposed in outcrops and numerical models. In an experiment conducted at Tulane University’s Sediment Dynamics Laboratory, the topography of a channelized delta formed by weakly cohesive sediment was monitored along flow-perpendicular transects at a high temporal resolution relative to channel kinematics. Over the course of this experiment a uniform relative subsidence pattern, designed to isolate autogenic processes, resulted in the construction of a stratigraphic package that is 25 times as thick as the depth of the experimental channels. We observe a scale-dependence on the compensational stacking of deposits set by the system’s avulsion time-scale. Above the avulsion time-scale deposits stack purely compensationally, but below this time-scale deposits stack somewhere between randomly and deterministically. The well-exposed Ferris Formation (Cretaceous/Paleogene, Hanna Basin, Wyoming, USA) also shows scale-dependant stratigraphic organization which appears to be set by an avulsion time-scale. Finally, we utilize simple object-based models to illustrate how channel avulsions influence compensation in alluvial basins.
Modeling of scale-dependent bacterial growth by chemical kinetics approach.
Martínez, Haydee; Sánchez, Joaquín; Cruz, José-Manuel; Ayala, Guadalupe; Rivera, Marco; Buhse, Thomas
2014-01-01
We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.
A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS
This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...
Edgeworth streaming model for redshift space distortions
NASA Astrophysics Data System (ADS)
Uhlemann, Cora; Kopp, Michael; Haugg, Thomas
2015-09-01
We derive the Edgeworth streaming model (ESM) for the redshift space correlation function starting from an arbitrary distribution function for biased tracers of dark matter by considering its two-point statistics and show that it reduces to the Gaussian streaming model (GSM) when neglecting non-Gaussianities. We test the accuracy of the GSM and ESM independent of perturbation theory using the Horizon Run 2 N -body halo catalog. While the monopole of the redshift space halo correlation function is well described by the GSM, higher multipoles improve upon including the leading order non-Gaussian correction in the ESM: the GSM quadrupole breaks down on scales below 30 Mpc /h whereas the ESM stays accurate to 2% within statistical errors down to 10 Mpc /h . To predict the scale-dependent functions entering the streaming model we employ convolution Lagrangian perturbation theory (CLPT) based on the dust model and local Lagrangian bias. Since dark matter halos carry an intrinsic length scale given by their Lagrangian radius, we extend CLPT to the coarse-grained dust model and consider two different smoothing approaches operating in Eulerian and Lagrangian space, respectively. The coarse graining in Eulerian space features modified fluid dynamics different from dust while the coarse graining in Lagrangian space is performed in the initial conditions with subsequent single-streaming dust dynamics, implemented by smoothing the initial power spectrum in the spirit of the truncated Zel'dovich approximation. Finally, we compare the predictions of the different coarse-grained models for the streaming model ingredients to N -body measurements and comment on the proper choice of both the tracer distribution function and the smoothing scale. Since the perturbative methods we considered are not yet accurate enough on small scales, the GSM is sufficient when applied to perturbation theory.
Pore-scale modeling of moving contact line problems in immiscible two-phase flow
NASA Astrophysics Data System (ADS)
Kucala, Alec; Noble, David; Martinez, Mario
2016-11-01
Accurate modeling of moving contact line (MCL) problems is imperative in predicting capillary pressure vs. saturation curves, permeability, and preferential flow paths for a variety of applications, including geological carbon storage (GCS) and enhanced oil recovery (EOR). Here, we present a model for the moving contact line using pore-scale computational fluid dynamics (CFD) which solves the full, time-dependent Navier-Stokes equations using the Galerkin finite-element method. The MCL is modeled as a surface traction force proportional to the surface tension, dependent on the static properties of the immiscible fluid/solid system. We present a variety of verification test cases for simple two- and three-dimensional geometries to validate the current model, including threshold pressure predictions in flows through pore-throats for a variety of wetting angles. Simulations involving more complex geometries are also presented to be used in future simulations for GCS and EOR problems. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Angle-adjustable density field formulation for the modeling of crystalline microstructure
NASA Astrophysics Data System (ADS)
Wang, Zi-Le; Liu, Zhirong; Huang, Zhi-Feng
2018-05-01
A continuum density field formulation with particle-scale resolution is constructed to simultaneously incorporate the orientation dependence of interparticle interactions and the rotational invariance of the system, a fundamental but challenging issue in modeling the structure and dynamics of a broad range of material systems across variable scales. This generalized phase field crystal-type approach is based upon the complete expansion of particle direct correlation functions and the concept of isotropic tensors. Through applications to the modeling of various two- and three-dimensional crystalline structures, our study demonstrates the capability of bond-angle control in this continuum field theory and its effects on the emergence of ordered phases, and provides a systematic way of performing tunable angle analyses for crystalline microstructures.
Simplifications in modelling of dynamical response of coupled electro-mechanical system
NASA Astrophysics Data System (ADS)
Darula, Radoslav; Sorokin, Sergey
2016-12-01
The choice of a most suitable model of an electro-mechanical system depends on many variables, such as a scale of the system, type and frequency range of its operation, or power requirements. The article focuses on the model of the electromagnetic element used in passive regime (no feedback loops are assumed) and a general lumped parameter model (a conventional mass-spring-damper system coupled to an electric circuit consisting of a resistance, an inductance and a capacitance) is compared with its simplified version, where the full RLC circuit is replaced with its RL simplification, i.e. the capacitance of the electric system is neglected and just its inductance and the resistance are considered. From the comparison of dynamical responses of these systems, the range of applicability of a simplified model is assessed for free as well as forced vibration.
Multiscale Modeling of Cell Interaction in Angiogenesis: From the Micro- to Macro-scale
NASA Astrophysics Data System (ADS)
Pillay, Samara; Maini, Philip; Byrne, Helen
Solid tumors require a supply of nutrients to grow in size. To this end, tumors induce the growth of new blood vessels from existing vasculature through the process of angiogenesis. In this work, we use a discrete agent-based approach to model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death processes. We use the transition probabilities associated with the discrete models to determine collective cell behavior, in terms of partial differential equations, using a Markov chain and master equation framework. We find that the cell-level dynamics gives rise to a migrating cell front in the form of a traveling wave on the macro-scale. The behavior of this front depends on the cell interactions that are included and the extent to which volume exclusion is taken into account in the discrete micro-scale model. We also find that well-established continuum models of angiogenesis cannot distinguish between certain types of cell behavior on the micro-scale. This may impact drug development strategies based on these models.
Interplay of interfacial noise and curvature-driven dynamics in two dimensions
NASA Astrophysics Data System (ADS)
Roy, Parna; Sen, Parongama
2017-02-01
We explore the effect of interplay of interfacial noise and curvature-driven dynamics in a binary spin system. An appropriate model is the generalized two-dimensional voter model proposed earlier [M. J. de Oliveira, J. F. F. Mendes, and M. A. Santos, J. Phys. A: Math. Gen. 26, 2317 (1993), 10.1088/0305-4470/26/10/006], where the flipping probability of a spin depends on the state of its neighbors and is given in terms of two parameters, x and y . x =0.5 andy =1 correspond to the conventional voter model which is purely interfacial noise driven, while x =1 and y =1 correspond to the Ising model, where coarsening is fully curvature driven. The coarsening phenomena for 0.5
Geometry-dependent viscosity reduction in sheared active fluids
NASA Astrophysics Data System (ADS)
Słomka, Jonasz; Dunkel, Jörn
2017-04-01
We investigate flow pattern formation and viscosity reduction mechanisms in active fluids by studying a generalized Navier-Stokes model that captures the experimentally observed bulk vortex dynamics in microbial suspensions. We present exact analytical solutions including stress-free vortex lattices and introduce a computational framework that allows the efficient treatment of higher-order shear boundary conditions. Large-scale parameter scans identify the conditions for spontaneous flow symmetry breaking, geometry-dependent viscosity reduction, and negative-viscosity states amenable to energy harvesting in confined suspensions. The theory uses only generic assumptions about the symmetries and long-wavelength structure of active stress tensors, suggesting that inviscid phases may be achievable in a broad class of nonequilibrium fluids by tuning confinement geometry and pattern scale selection.
Meso-scopic Densification in Brittle Granular Materials
NASA Astrophysics Data System (ADS)
Neal, William; Appleby-Thomas, Gareth; Collins, Gareth
2013-06-01
Particulate materials are ideally suited to shock absorbing applications due to the large amounts of energy required to deform their inherently complex meso-structure. Significant effort is being made to improve macro-scale material models to represent these atypical materials. On the long road towards achieving this capability, an important milestone would be to understand how particle densification mechanisms are affected by loading rate. In brittle particulate materials, the majority of densification is caused by particle fracture. Macro-scale quasi-static and dynamic compaction curves have been measured that show good qualitative agreement. There are, however, some differences that appear to be dependent on the loading rate that require further investigation. This study aims to investigate the difference in grain-fracture behavior between the quasi-static and shock loading response of brittle glass microsphere beds using a combination of quasi-static and dynamic loading techniques. Results from pressure-density measurements, sample recovery, and meso-scale hydrocode models (iSALE, an in-house simulation package) are discussed to explain the differences in particle densification mechanisms between the two loading rate regimes. Gratefully funded by AWE.plc.
NASA Technical Reports Server (NTRS)
Stepinski, Tomasz F.; Reyes-Ruiz, Mauricio; Vanhala, Harri A. T.
1993-01-01
A hydromagnetic dynamo provides the best mechanism for contemporaneously producing magnetic fields in a turbulent solar nebula. We investigate the solar nebula in the framework of a steady-state accretion disk model and establish the criteria for a viable nebular dynamo. We have found that typically a magnetic gap exists in the nebula, the region where the degree of ionization is too small for the magnetic field to couple to the gas. The location and width of this gap depend on the particular model; the supposition is that gaps cover different parts of the nebula at different evolutionary stages. We have found, from several dynamical constraints, that the generated magnetic field is likely to saturate at a strength equal to equipartition with the kinetic energy of turbulence. Maxwell stress arising from a large-scale magnetic field may significantly influence nebular structure, and Maxwell stress due to small-scale fields can actually dominate other stresses in the inner parts of the nebula. We also argue that the bulk of nebular gas, within the scale height from the midplane, is stable against Balbus-Hawley instability.
Linking crop yield anomalies to large-scale atmospheric circulation in Europe.
Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J
2017-06-15
Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.
Micron-scale coherence in interphase chromatin dynamics
Zidovska, Alexandra; Weitz, David A.; Mitchison, Timothy J.
2013-01-01
Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood, especially at large length scales. We developed an approach, displacement correlation spectroscopy based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. This method revealed that chromatin movement was coherent across large regions (4–5 µm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP dependent and unidirectional for several seconds, perhaps accounting for ATP-dependent directed movement of single genes. Perturbation of major nuclear ATPases such as DNA polymerase, RNA polymerase II, and topoisomerase II eliminated micron-scale coherence, while causing rapid, local movement to increase; i.e., local motions accelerated but became uncoupled from their neighbors. We observe similar trends in chromatin dynamics upon inducing a direct DNA damage; thus we hypothesize that this may be due to DNA damage responses that physically relax chromatin and block long-distance communication of forces. PMID:24019504
NASA Astrophysics Data System (ADS)
Portner, Hanspeter; Wolf, Annett; Rühr, Nadine; Bugmann, Harald
2010-05-01
Many biogeochemical models have been applied to study the response of the carbon cycle to changes in climate, whereby the process of carbon uptake (photosynthesis) has usually gained more attention than the equally important process of carbon release by respiration. The decomposition of soil organic matter is driven by a combination of factors like soil temperature, soil moisture and litter quality. We have introduced dependence on litter substrate quality to heterotrophic soil respiration in the ecosystem model LPJ-GUESS [Smith et al.(2001)]. We were interested in differences in model projections before and after the inclusion of the dependency both in respect to short- and long-term soil carbon dynamics. The standard implementation of heterotrophic soil respiration in LPJ-GUESS is a simple carbon three-pool model whose decay rates are dependent on soil temperature and soil moisture. We have added dependence on litter quality by coupling LPJ-GUESS to the soil carbon model Yasso07 [Tuomi et al.(2008)]. The Yasso07 model is based on an extensive number of measurements of litter decomposition of forest soils. Apart from the dependence on soil temperature and soil moisture, the Yasso07 model uses carbon soil pools representing different substrate qualities: acid hydrolyzable, water soluble, ethanol soluble, lignin compounds and humus. Additionally Yasso07 differentiates between woody and non-woody litter. In contrary to the reference implementation of LPJ-GUESS, in the new model implementation, the litter now is divided according to its specific quality and added to the corresponding soil carbon pool. The litter quality thereby differs between litter source (leaves, roots, stems) and plant functional type (broadleaved, needleleaved, grass). The two contrasting model implementations were compared and validated at one specific CarboEuropeIP site (Lägern, Switzerland) and on a broader scale all over Switzerland. Our focus lay on the soil respiration for the years 2006 and 2007 [Rühr(2009)] and present soil carbon stocks [Heim et al.(2009)]. Our Results show, that for short-term soil carbon dynamics, e.g. estimates of heterotrophic soil respiration on an annual basis, the inclusion of the dependency on litter quality is not necessary, as the differences are minor only. However, when considering long-term soil carbon dynamics, e.g. simulated estimates of present soil carbon content, the dependency on litter quality shows effect, as there are correlations with specific site factors such as site location and forest type. The inclusion of the dependence on litter quality therefore may be of importance for the projection of future soil carbon dynamics, as forest types may well be altered due to climatic change. References [Heim et al.(2009)] A. Heim, L. Wehrli, W. Eugster, and M.W.I. Schmidt. Effects of sampling design on the probability to detect soil carbon stock changes at the swiss CarboEurope site Lägeren. Geoderma, 149(3-4):347-354, 2009. [Rühr(2009)] Nadine Katrin Rühr. Soil respiration in a mixed mountain forest : environmental drivers and partitioning of component fluxes. PhD thesis, ETH, 2009. [Smith et al.(2001)] Benjamin Smith, I. Colin Prentice, and Martin T. Sykes. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within european climate space. Global Ecology and Biogeography, 10(6):621-637, 2001. [Tuomi et al.(2008)] Mikko Tuomi, Pekka Vanhala, Kristiina Karhu, Hannu Fritze, and Jari Liski. Heterotrophic soil respiration-Comparison of different models describing its temperature dependence. Ecological Modelling, 211(1-2): 182-190, 2008.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.
Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less
Simulating the Thermal Response of High Explosives on Time Scales of Days to Microseconds
NASA Astrophysics Data System (ADS)
Yoh, Jack J.; McClelland, Matthew A.
2004-07-01
We present an overview of computational techniques for simulating the thermal cookoff of high explosives using a multi-physics hydrodynamics code, ALE3D. Recent improvements to the code have aided our computational capability in modeling the response of energetic materials systems exposed to extreme thermal environments, such as fires. We consider an idealized model process for a confined explosive involving the transition from slow heating to rapid deflagration in which the time scale changes from days to hundreds of microseconds. The heating stage involves thermal expansion and decomposition according to an Arrhenius kinetics model while a pressure-dependent burn model is employed during the explosive phase. We describe and demonstrate the numerical strategies employed to make the transition from slow to fast dynamics.
Evolutionary dynamics of taxonomic structure
Foote, Michael
2012-01-01
The distribution of species among genera and higher taxa has largely untapped potential to reveal among-clade variation in rates of origination and extinction. The probability distribution of the number of species within a genus is modelled with a stochastic, time-homogeneous birth–death model having two parameters: the rate of species extinction, μ, and the rate of genus origination, γ, each scaled as a multiple of the rate of within-genus speciation, λ. The distribution is more sensitive to γ than to μ, although μ affects the size of the largest genera. The species : genus ratio depends strongly on both γ and μ, and so is not a good diagnostic of evolutionary dynamics. The proportion of monotypic genera, however, depends mainly on γ, and so may provide an index of the genus origination rate. Application to living marine molluscs of New Zealand shows that bivalves have a higher relative rate of genus origination than gastropods. This is supported by the analysis of palaeontological data. This concordance suggests that analysis of living taxonomic distributions may allow inference of macroevolutionary dynamics even without a fossil record. PMID:21865239
A Cellular Automata Model for the Study of Landslides
NASA Astrophysics Data System (ADS)
Liucci, Luisa; Suteanu, Cristian; Melelli, Laura
2016-04-01
Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model parameters, and its temporal behavior. Results show that the model reproduces the scaling behavior of real landslide areas; while the value of the scaling exponent is stable over time, it linearly decreases with increasing rate of weakening. This suggests that it is the intensity of the triggering mechanism rather than its duration that affects the probability of landslide magnitudes. A quantitative relationship between the scaling exponent of the area frequency distribution of the generated landslides, on one hand, and the changes regarding the topographic surface affected by landslides, on the other hand, is established. The fact that a similar behavior could be observed in real systems may have useful implications in the context of landslide hazard assessment. These results support the hypotheses that landslides are driven by SOC dynamics, and that topography plays a key role in the scaling properties of their size distribution.
cellGPU: Massively parallel simulations of dynamic vertex models
NASA Astrophysics Data System (ADS)
Sussman, Daniel M.
2017-10-01
Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation
Correlated phonons and the Tc-dependent dynamical phonon anomalies
NASA Astrophysics Data System (ADS)
Hakioğlu, T.; Türeci, H.
1997-11-01
Anomalously large low-temperature phonon anharmonicities can lead to static as well as dynamical changes in the low-temperature properties of the electron-phonon system. In this work, we focus our attention on the dynamically generated low-temperature correlations in an interacting electron-phonon system using a self-consistent dynamical approach in the intermediate coupling range. In the context of the model, the polaron correlations are produced by the charge-density fluctuations which are generated dynamically by the electron-phonon coupling. Conversely, the latter is influenced in the presence of the former. The purpose of this work is to examine the dynamics of this dual mechanism between the two using the illustrative Fröhlich model. In particular, the influence of the low-temperature phonon dynamics on the superconducting properties in the intermediate coupling range is investigated. The influence on the Holstein reduction factor as well as the enhancement in the zero-point fluctuations and in the electron-phonon coupling are calculated numerically. We also examine these effects in the presence of superconductivity. Within this model, the contribution of the electron-phonon interaction as one of the important elements in the mechanisms of superconductivity can reach values as high as 15-20% of the characteristic scale of the lattice vibrational energy. The second motivation of this work is to understand the nature of the Tc-dependent temperature anomalies observed in the Debye-Waller factor, dynamical pair correlations, and average atomic vibrational energies for a number of high-temperature superconductors. In our approach we do not claim nor believe that the electron-phonon interaction is the primary mechanism leading to high-temperature superconductivity. Nevertheless, our calculations suggest that the dynamically induced low-temperature phonon correlation model can account for these anomalies and illustrates their possible common origin. Finally, the relevance of incorporating these low-temperature effects into more realistic models of high-temperature superconductivity including both the charge and spin degrees and other similar ideas existing in the literature are discussed.
NASA Astrophysics Data System (ADS)
Moosavi, S. Amin; Montakhab, Afshin
2014-05-01
Motivated by recent experiments in neuroscience which indicate that neuronal avalanches exhibit scale invariant behavior similar to self-organized critical systems, we study the role of noisy (nonconservative) local dynamics on the critical behavior of a sandpile model which can be taken to mimic the dynamics of neuronal avalanches. We find that despite the fact that noise breaks the strict local conservation required to attain criticality, our system exhibits true criticality for a wide range of noise in various dimensions, given that conservation is respected on the average. Although the system remains critical, exhibiting finite-size scaling, the value of critical exponents change depending on the intensity of local noise. Interestingly, for a sufficiently strong noise level, the critical exponents approach and saturate at their mean-field values, consistent with empirical measurements of neuronal avalanches. This is confirmed for both two and three dimensional models. However, the addition of noise does not affect the exponents at the upper critical dimension (D =4). In addition to an extensive finite-size scaling analysis of our systems, we also employ a useful time-series analysis method to establish true criticality of noisy systems. Finally, we discuss the implications of our work in neuroscience as well as some implications for the general phenomena of criticality in nonequilibrium systems.
Finite size scaling analysis on Nagel-Schreckenberg model for traffic flow
NASA Astrophysics Data System (ADS)
Balouchi, Ashkan; Browne, Dana
2015-03-01
The traffic flow problem as a many-particle non-equilibrium system has caught the interest of physicists for decades. Understanding the traffic flow properties and though obtaining the ability to control the transition from the free-flow phase to the jammed phase plays a critical role in the future world of urging self-driven cars technology. We have studied phase transitions in one-lane traffic flow through the mean velocity, distributions of car spacing, dynamic susceptibility and jam persistence -as candidates for an order parameter- using the Nagel-Schreckenberg model to simulate traffic flow. The length dependent transition has been observed for a range of maximum velocities greater than a certain value. Finite size scaling analysis indicates power-law scaling of these quantities at the onset of the jammed phase.
Scaling ansatz for the ac magnetic response in two-dimensional spin ice
NASA Astrophysics Data System (ADS)
Otsuka, Hiromi; Takatsu, Hiroshi; Goto, Kazuki; Kadowaki, Hiroaki
2014-10-01
A theory for frequency-dependent magnetic susceptibility χ (ω ) is developed for thermally activated magnetic monopoles in a two-dimensional (2D) spin ice. By modeling the system in the vicinity of the ground-state manifold as a 2D Coulomb gas with an entropic interaction, and then as a 2D sine-Gordon model, we have shown that the susceptibility has a scaling form χ (ω ) /χ (0 ) =F (ω /ω1) , where the characteristic frequency ω1 is related to a charge correlation length between diffusively moving monopoles, and to the principal-breather excitation. The dynamical scaling is universal and applicable not only for kagome ice, but also for superfluid and superconducting films and generic 2D ices possibly including the artificial spin ice.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.
Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less
Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.; ...
2017-06-21
Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less
Linear and non-linear perturbations in dark energy models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Escamilla-Rivera, Celia; Casarini, Luciano; Fabris, Júlio C.
2016-11-01
In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state w ( z ). In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected w ( z ) parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard ΛCDM model.
Research on the F/A-18E/F Using a 22%-Dynamically-Scaled Drop Model
NASA Technical Reports Server (NTRS)
Croom, M.; Kenney, H.; Murri, D.; Lawson, K.
2000-01-01
Research on the F/A-18E/F configuration was conducted using a 22%-dynamically-scaled drop model to study flight dynamics in the subsonic regime. Several topics were investigated including longitudinal response, departure/spin resistance, developed spins and recoveries, and the failing leaf mode. Comparisons to full-scale flight test results were made and show the drop model strongly correlates to the airplane even under very dynamic conditions. The capability to use the drop model to expand on the information gained from full-scale flight testing is also discussed. Finally, a preliminary analysis of an unusual inclined spinning motion, dubbed the "cartwheel", is presented here for the first time.
NASA Astrophysics Data System (ADS)
Wu, Zikai; Hou, Baoyu; Zhang, Hongjuan; Jin, Feng
2014-04-01
Deterministic network models have been attractive media for discussing dynamical processes' dependence on network structural features. On the other hand, the heterogeneity of weights affect dynamical processes taking place on networks. In this paper, we present a family of weighted expanded Koch networks based on Koch networks. They originate from a r-polygon, and each node of current generation produces m r-polygons including the node and whose weighted edges are scaled by factor w in subsequent evolutionary step. We derive closed-form expressions for average weighted shortest path length (AWSP). In large network, AWSP stays bounded with network order growing (0 < w < 1). Then, we focus on a special random walks and trapping issue on the networks. In more detail, we calculate exactly the average receiving time (ART). ART exhibits a sub-linear dependence on network order (0 < w < 1), which implies that nontrivial weighted expanded Koch networks are more efficient than un-weighted expanded Koch networks in receiving information. Besides, efficiency of receiving information at hub nodes is also dependent on parameters m and r. These findings may pave the way for controlling information transportation on general weighted networks.
Universality of local dissipation scales in buoyancy-driven turbulence.
Zhou, Quan; Xia, Ke-Qing
2010-03-26
We report an experimental investigation of the local dissipation scale field eta in turbulent thermal convection. Our results reveal two types of universality of eta. The first one is that, for the same flow, the probability density functions (PDFs) of eta are insensitive to turbulent intensity and large-scale inhomogeneity and anisotropy of the system. The second is that the small-scale dissipation dynamics in buoyancy-driven turbulence can be described by the same models developed for homogeneous and isotropic turbulence. However, the exact functional form of the PDF of the local dissipation scale is not universal with respect to different types of flows, but depends on the integral-scale velocity boundary condition, which is found to have an exponential, rather than Gaussian, distribution in turbulent Rayleigh-Bénard convection.
Li, Chen; Nagasaki, Masao; Saito, Ayumu; Miyano, Satoru
2010-04-01
With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.
NASA Astrophysics Data System (ADS)
Khan, Valentina; Tscepelev, Valery; Vilfand, Roman; Kulikova, Irina; Kruglova, Ekaterina; Tischenko, Vladimir
2016-04-01
Long-range forecasts at monthly-seasonal time scale are in great demand of socio-economic sectors for exploiting climate-related risks and opportunities. At the same time, the quality of long-range forecasts is not fully responding to user application necessities. Different approaches, including combination of different prognostic models, are used in forecast centers to increase the prediction skill for specific regions and globally. In the present study, two forecasting methods are considered which are exploited in operational practice of Hydrometeorological Center of Russia. One of them is synoptical-analogous method of forecasting of surface air temperature at monthly scale. Another one is dynamical system based on the global semi-Lagrangian model SL-AV, developed in collaboration of Institute of Numerical Mathematics and Hydrometeorological Centre of Russia. The seasonal version of this model has been used to issue global and regional forecasts at monthly-seasonal time scales. This study presents results of the evaluation of surface air temperature forecasts generated with using above mentioned synoptical-statistical and dynamical models, and their combination to potentially increase skill score over Northern Eurasia. The test sample of operational forecasts is encompassing period from 2010 through 2015. The seasonal and interannual variability of skill scores of these methods has been discussed. It was noticed that the quality of all forecasts is highly dependent on the inertia of macro-circulation processes. The skill scores of forecasts are decreasing during significant alterations of synoptical fields for both dynamical and empirical schemes. Procedure of combination of forecasts from different methods, in some cases, has demonstrated its effectiveness. For this study the support has been provided by Grant of Russian Science Foundation (№14-37-00053).
Nonlinear Hysteretic Torsional Waves
NASA Astrophysics Data System (ADS)
Cabaret, J.; Béquin, P.; Theocharis, G.; Andreev, V.; Gusev, V. E.; Tournat, V.
2015-07-01
We theoretically study and experimentally report the propagation of nonlinear hysteretic torsional pulses in a vertical granular chain made of cm-scale, self-hanged magnetic beads. As predicted by contact mechanics, the torsional coupling between two beads is found to be nonlinear hysteretic. This results in a nonlinear pulse distortion essentially different from the distortion predicted by classical nonlinearities and in a complex dynamic response depending on the history of the wave particle angular velocity. Both are consistent with the predictions of purely hysteretic nonlinear elasticity and the Preisach-Mayergoyz hysteresis model, providing the opportunity to study the phenomenon of nonlinear dynamic hysteresis in the absence of other types of material nonlinearities. The proposed configuration reveals a plethora of interesting phenomena including giant amplitude-dependent attenuation, short-term memory, as well as dispersive properties. Thus, it could find interesting applications in nonlinear wave control devices such as strong amplitude-dependent filters.
NASA Astrophysics Data System (ADS)
Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.
2014-12-01
Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.
NASA Astrophysics Data System (ADS)
Nazarieh, F.; Ansari, H.; Ziaei, A. N.; Izady, A.; Davari, K.; Brunner, P.
2018-05-01
The time required for deep percolating water to reach the water table can be considerable in areas with a thick vadose zone. Sustainable groundwater management, therefore, has to consider the spatial and temporal dynamics of groundwater recharge. The key parameters that control the lag time have been widely examined in soil physics using small-scale lysimeters and modeling studies. However, only a small number of studies have analyzed how deep-percolation rates affect groundwater recharge dynamics over large spatial scales. This study examined how the parameters influencing lag time affect groundwater recharge in a semi-arid catchment under irrigation (in northeastern Iran) using a numerical modeling approach. Flow simulations were performed by the MODFLOW-NWT code with the Vadose-Zone Flow (UZF) Package. Calibration of the groundwater model was based on data from 48 observation wells. Flow simulations showed that lag times vary from 1 to more than 100 months. A sensitivity analysis demonstrated that during drought conditions, the lag time was highly sensitive to the rate of deep percolation. The study illustrated two critical points: (1) the importance of providing estimates of the lag time as a basis for sustainable groundwater management, and (2) lag time not only depends on factors such as soil hydraulic conductivity or vadose zone depth but also depends on the deep-percolation rates and the antecedent soil-moisture condition. Therefore, estimates of the lag time have to be associated with specific percolation rates, in addition to depth to groundwater and soil properties.
NASA Astrophysics Data System (ADS)
Dutta, Rituraj; Kumar, A.
2017-10-01
Dielectric relaxation dynamics and AC conductivity scaling of a metal-organic framework (MOF-5) based poly (vinylidene fluoride-co-hexafluoropropylene) (PVdf-HFP) incorporated with 1-Butyl-3-methylimidazolium hexafluorophosphate have been studied over a frequency range of 40 Hz-5 MHz and in the temperature range of 300 K-380 K. High values of dielectric permittivity (~{{\\varepsilon }\\prime} ) having strong dispersion are obtained at low frequency because of interfacial polarization. The real part of the dielectric modulus spectra (M‧) shows no prominent peak, whereas the imaginary part (M″) shows certain peaks, with a reduction in relaxation time (τ) that can be attributed to a non-Debye relaxation mechanism. The spectra also depict both concentration- and temperature-independent scaling behavior. The power law dependent variation of AC conductivity follows the jump relaxation model and reveals activated ion hopping over diffusion barriers. The value of the frequency exponent is observed to decrease with increasing concentration of ionic liquid, indicating the forward hopping of ions in the relaxation process. The AC conductivity scaling curves at different temperatures also depict the temperature-independent relaxation dynamics.
Modeling Fluvial Incision and Transient Landscape Evolution: Influence of Dynamic Channel Adjustment
NASA Astrophysics Data System (ADS)
Attal, M.; Tucker, G. E.; Cowie, P. A.; Whittaker, A. C.; Roberts, G. P.
2007-12-01
Channel geometry exerts a fundamental control on fluvial processes. Recent work has shown that bedrock channel width (W) depends on a number of parameters, including channel slope, and is not only a function of drainage area (A) as is commonly assumed. The present work represents the first attempt to investigate the consequences, for landscape evolution, of using a static expression of channel width (W ~ A0.5) versus a relationship that allows channels to dynamically adjust to changes in slope. We consider different models for the evolution of the channel geometry, including constant width-to-depth ratio (after Finnegan et al., Geology, v. 33, no. 3, 2005), and width-to-depth ratio varying as a function of slope (after Whittaker et al., Geology, v. 35, no. 2, 2007). We use the Channel-Hillslope Integrated Landscape Development (CHILD) model to analyze the response of a catchment to a given tectonic disturbance. The topography of a catchment in the footwall of an active normal fault in the Apennines (Italy) is used as a template for the study. We show that, for this catchment, the transient response can be fairly well reproduced using a simple detachment-limited fluvial incision law. We also show that, depending on the relationship used to express channel width, initial steady-state topographies differ, as do transient channel width, slope, and the response time of the fluvial system. These differences lead to contrasting landscape morphologies when integrated at the scale of a whole catchment. Our results emphasize the importance of channel width in controlling fluvial processes and landscape evolution. They stress the need for using a dynamic hydraulic scaling law when modeling landscape evolution, particularly when the uplift field is non-uniform.
Dynamics of proteins aggregation. I. Universal scaling in unbounded media
NASA Astrophysics Data System (ADS)
Zheng, Size; Javidpour, Leili; Shing, Katherine S.; Sahimi, Muhammad
2016-10-01
It is well understood that in some cases proteins do not fold correctly and, depending on their environment, even properly-folded proteins change their conformation spontaneously, taking on a misfolded state that leads to protein aggregation and formation of large aggregates. An important factor that contributes to the aggregation is the interactions between the misfolded proteins. Depending on the aggregation environment, the aggregates may take on various shapes forming larger structures, such as protein plaques that are often toxic. Their deposition in tissues is a major contributing factor to many neuro-degenerative diseases, such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and prion. This paper represents the first part in a series devoted to molecular simulation of protein aggregation. We use the PRIME, a meso-scale model of proteins, together with extensive discontinuous molecular dynamics simulation to study the aggregation process in an unbounded fluid system, as the first step toward MD simulation of the same phenomenon in crowded cellular environments. Various properties of the aggregates have been computed, including dynamic evolution of aggregate-size distribution, mean aggregate size, number of peptides that contribute to the formation of β sheets, number of various types of hydrogen bonds formed in the system, radius of gyration of the aggregates, and the aggregates' diffusivity. We show that many of such quantities follow dynamic scaling, similar to those for aggregation of colloidal clusters. In particular, at long times the mean aggregate size S(t) grows with time as, S(t) ˜ tz, where z is the dynamic exponent. To our knowledge, this is the first time that the qualitative similarity between aggregation of proteins and colloidal aggregates has been pointed out.
NASA Astrophysics Data System (ADS)
Chand, Avtar; Mishra, R. K.; Pradhan, Anirudh
2016-02-01
Exact solution of modified Einstein's field equations are considered within the scope of spatially homogeneous and isotropic Fraidmann-Robertson-Walker (FRW) space-time filled with perfect fluid in the frame work of Brans-Dicke scalar-tensor theory of gravity. In this paper we have investigated the flat, open and closed FRW models and the effect of dynamic cosmological term on the evolution of the universe. Two types of FRW cosmological models are obtained by setting the power law between the scalar field φ and the scale factor a and deceleration parameter (DP) q as a time dependent. The concept of time dependent DP with some proper assumptions yield two type of the average scale factors (i) a(t)=[sinh(α t)]^{1/n} and (ii) a(t)=[t^{α}et]^{1/n}, α and n≠ 0 are arbitrary constants. In case (i), for 0 < n ≤ 1, it generates a class of accelerating models while for n > 1, the models of the universe exhibit phase transition from early decelerating to present accelerating phase and the transition redshift zt has been calculated and found to be in good agreement with the results from recent astrophysical observations. In case (ii), for n ≥ 2 and α = 1, we obtain a class of transit models of the universe from early decelerating to present accelerating phase. Taking into consideration the observational data, we conclude that the cosmological constant behaves as a positive decreasing function of time. The physical and geometric properties of the models are also discussed with the help of graphical presentations.
Thermally induced magnetic relaxation in square artificial spin ice.
Andersson, M S; Pappas, S D; Stopfel, H; Östman, E; Stein, A; Nordblad, P; Mathieu, R; Hjörvarsson, B; Kapaklis, V
2016-11-24
The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.
Thermally induced magnetic relaxation in square artificial spin ice
NASA Astrophysics Data System (ADS)
Andersson, M. S.; Pappas, S. D.; Stopfel, H.; Östman, E.; Stein, A.; Nordblad, P.; Mathieu, R.; Hjörvarsson, B.; Kapaklis, V.
2016-11-01
The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.
Estimating dynamic permeability in fractal pore network saturated by Maxwellian fluid
NASA Astrophysics Data System (ADS)
Sun, W.
2017-12-01
The frequency dependent flow of fluid in porous media is an important issue in geophysical prospecting. Oscillating flow in pipe leads to frequency dependent dynamic permeability and has been studied in pore network containing Newtonian fluid. But there is little work on oscillating complex fluid in pipe network, especially in irregular network. Here we formulated frequency dependent permeability for Maxwellian fluid and estimated the permeability in three-dimensional fractal network model. We consider an infinitely long cylindrical pipe with rigid solid wall. The pipe is filled with Maxwellian fluids. Based on the mass conservation equation, the equilibrium equation of force and Maxwell constitutive relationship, we formulated the flux by integration of axial velocity component over the pipe's cross section. Then we extend single pipe formulation to a 3D irregular network. Flux balance condition yields a set of linear equations whose unknowns are the fluid pressure at each node. By evaluating the total flow flux through the network, the dynamic permeability can be calculated.We investigated the dynamic permeability of brine and CPyCl/NaSal in a 3D porous sample with a cubic side length 1 cm. The pore network is created by a Voronoi cell filling method. The porosity, i.e., volume ratio between pore/pipe network and the overall cubic, is set as 0.1. The irregular pore network has a fractal structure. The dimension d of the pore network is defined by the relation between node number M within a sphere and the radius r of the sphere,M=rd.The results show that both brine and Maxwellian fluid's permeability maintain a stable value at low frequency, then decreases with fluctuating peaks. The dynamic permeability in pore networks saturated by Maxwellian fluid (CPyCl/NaSal (60 mM)) show larger peaks during the decline process at high frequency, which represents the typical resonance behavior. Dynamic permeability shows clear dependence on the dimension of the fractal network. Small-scale network has higher dimension than large-scale networks. The reason is that in larger networks pore and inter-pore connections are so dense that the probability P(r) to have a neighboring pore at distance r decays faster. The proposed model may be used to explain velocity dispersion in unconventional reservoir rocks observed in laboratory.
Symbolic dynamics techniques for complex systems: Application to share price dynamics
NASA Astrophysics Data System (ADS)
Xu, Dan; Beck, Christian
2017-05-01
The symbolic dynamics technique is well known for low-dimensional dynamical systems and chaotic maps, and lies at the roots of the thermodynamic formalism of dynamical systems. Here we show that this technique can also be successfully applied to time series generated by complex systems of much higher dimensionality. Our main example is the investigation of share price returns in a coarse-grained way. A nontrivial spectrum of Rényi entropies is found. We study how the spectrum depends on the time scale of returns, the sector of stocks considered, as well as the number of symbols used for the symbolic description. Overall our analysis confirms that in the symbol space transition probabilities of observed share price returns depend on the entire history of previous symbols, thus emphasizing the need for a modelling based on non-Markovian stochastic processes. Our method allows for quantitative comparisons of entirely different complex systems, for example the statistics of symbol sequences generated by share price returns using 4 symbols can be compared with that of genomic sequences.
Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora
2016-02-05
Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion ismore » used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.« less
Shear banding leads to accelerated aging dynamics in a metallic glass
NASA Astrophysics Data System (ADS)
Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; Shin, Jeremy; Maaß, Robert
2018-01-01
Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. Using site-specific x-ray photon correlation spectroscopy, we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretched exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. These insights highlight how a ubiquitous nanoscale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.
Relationship between femtosecond-picosecond dynamics to enzyme catalyzed H-transfer
Cheatum, Christopher M.; Kohen, Amnon
2015-01-01
At physiological temperatures, enzymes exhibit a broad spectrum of conformations, which interchange via thermally activated dynamics. These conformations are sampled differently in different complexes of the protein and its ligands, and the dynamics of exchange between these conformers depends on the mass of the group that is moving and the length scale of the motion, as well as restrictions imposed by the globular fold of the enzymatic complex. Many of these motions have been examined and their role in the enzyme function illuminated, yet most experimental tools applied so far have identified dynamics at time scales of seconds to nanoseconds, which are much slower than the time scale for H-transfer between two heavy atoms. This chemical conversion and other processes involving cleavage of covalent bonds occur on picosecond to femtosecond time scales, where slower processes mask both the kinetics and dynamics. Here we present a combination of kinetic and spectroscopic methods that may enable closer examination of the relationship between enzymatic C-H→C transfer and the dynamics of the active site environment at the chemically relevant time scale. These methods include kinetic isotope effects and their temperature dependence, which are used to study the kinetic nature of the H-transfer, and 2D IR spectroscopy, which is used to study the dynamics of transition-state- and ground-state-analog complexes. The combination of these tools is likely to provide a new approach to examine the protein dynamics that directly influence the chemical conversion catalyzed by enzymes. PMID:23539379
Ultrafast Three-Dimensional X-ray Imaging of Deformation Modes in ZnO Nanocrystals.
Cherukara, Mathew J; Sasikumar, Kiran; Cha, Wonsuk; Narayanan, Badri; Leake, Steven J; Dufresne, Eric M; Peterka, Tom; McNulty, Ian; Wen, Haidan; Sankaranarayanan, Subramanian K R S; Harder, Ross J
2017-02-08
Imaging the dynamical response of materials following ultrafast excitation can reveal energy transduction mechanisms and their dissipation pathways, as well as material stability under conditions far from equilibrium. Such dynamical behavior is challenging to characterize, especially operando at nanoscopic spatiotemporal scales. In this letter, we use X-ray coherent diffractive imaging to show that ultrafast laser excitation of a ZnO nanocrystal induces a rich set of deformation dynamics including characteristic "hard" or inhomogeneous and "soft" or homogeneous modes at different time scales, corresponding respectively to the propagation of acoustic phonons and resonant oscillation of the crystal. By integrating the 3D nanocrystal structure obtained from the ultrafast X-ray measurements with a continuum thermo-electro-mechanical finite element model, we elucidate the deformation mechanisms following laser excitation, in particular, a torsional mode that generates a 50% greater electric potential gradient than that resulting from the flexural mode. Understanding of the time-dependence of these mechanisms on ultrafast scales has significant implications for development of new materials for nanoscale power generation.
Ultrafast Three-Dimensional X-ray Imaging of Deformation Modes in ZnO Nanocrystals
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cherukara, Mathew J.; Sasikumar, Kiran; Cha, Wonsuk
Imaging the dynamical response of materials following ultrafast excitation can reveal energy transduction mechanisms and their dissipation pathways, as well as material stability under conditions far from equilibrium. Such dynamical behaviour is challenging to characterize, especially operando at nanoscopic spatiotemporal scales. In this letter, we use x-ray coherent diffractive imaging to show that ultrafast laser excitation of a ZnO nanocrystal induces a rich set of deformation dynamics including characteristic ‘hard’ or inhomogeneous and ‘soft’ or homogeneous modes at different time scales, corresponding respectively to the propagation of acoustic phonons and resonant oscillation of the crystal. By integrating the 3D nanocrystalmore » structure obtained from the ultrafast x-ray measurements with a continuum thermo-electro-mechanical finite element model, we elucidate the deformation mechanisms following laser excitation, in particular, a torsional mode that generates a 50% greater electric potential gradient than that resulting from the flexural mode. Furthermore, understanding of the time-dependence of these mechanisms on ultrafast scales has significant implications for development of new materials for nanoscale power generation.« less
Ultrafast Three-Dimensional X-ray Imaging of Deformation Modes in ZnO Nanocrystals
Cherukara, Mathew J.; Sasikumar, Kiran; Cha, Wonsuk; ...
2016-12-27
Imaging the dynamical response of materials following ultrafast excitation can reveal energy transduction mechanisms and their dissipation pathways, as well as material stability under conditions far from equilibrium. Such dynamical behaviour is challenging to characterize, especially operando at nanoscopic spatiotemporal scales. In this letter, we use x-ray coherent diffractive imaging to show that ultrafast laser excitation of a ZnO nanocrystal induces a rich set of deformation dynamics including characteristic ‘hard’ or inhomogeneous and ‘soft’ or homogeneous modes at different time scales, corresponding respectively to the propagation of acoustic phonons and resonant oscillation of the crystal. By integrating the 3D nanocrystalmore » structure obtained from the ultrafast x-ray measurements with a continuum thermo-electro-mechanical finite element model, we elucidate the deformation mechanisms following laser excitation, in particular, a torsional mode that generates a 50% greater electric potential gradient than that resulting from the flexural mode. Furthermore, understanding of the time-dependence of these mechanisms on ultrafast scales has significant implications for development of new materials for nanoscale power generation.« less
NASA Astrophysics Data System (ADS)
Peruani, Fernando
2016-11-01
Bacteria, chemically-driven rods, and motility assays are examples of active (i.e. self-propelled) Brownian rods (ABR). The physics of ABR, despite their ubiquity in experimental systems, remains still poorly understood. Here, we review the large-scale properties of collections of ABR moving in a dissipative medium. We address the problem by presenting three different models, of decreasing complexity, which we refer to as model I, II, and III, respectively. Comparing model I, II, and III, we disentangle the role of activity and interactions. In particular, we learn that in two dimensions by ignoring steric or volume exclusion effects, large-scale nematic order seems to be possible, while steric interactions prevent the formation of orientational order at large scales. The macroscopic behavior of ABR results from the interplay between active stresses and local alignment. ABR exhibit, depending on where we locate ourselves in parameter space, a zoology of macroscopic patterns that ranges from polar and nematic bands to dynamic aggregates.
Chaotic dynamics in the (47171) Lempo triple system
NASA Astrophysics Data System (ADS)
Correia, Alexandre C. M.
2018-05-01
We investigate the dynamics of the (47171) Lempo triple system, also known by 1999 TC36. We derive a full 3D N-body model that takes into account the orbital and spin evolution of all bodies, which are assumed triaxial ellipsoids. We show that, for reasonable values of the shapes and rotational periods, the present best fitted orbital solution for the Lempo system is chaotic and unstable in short time-scales. The formation mechanism of this system is unknown, but the orbits can be stabilised when tidal dissipation is taken into account. The dynamics of the Lempo system is very rich, but depends on many parameters that are presently unknown. A better understanding of this systems thus requires more observations, which also need to be fitted with a complete model like the one presented here.
Dynamic Pore-Scale Imaging of Reactive Transport in Heterogeneous Carbonates at Reservior Conditions
NASA Astrophysics Data System (ADS)
Menke, Hannah; Bijeljic, Branko; Andrew, Matthew; Blunt, Martin
2014-05-01
Sequestering carbon in deep geologic formations is one way of reducing anthropogenic CO2 emissions. Carbon capture, Utilization, and Storage (CCUS) in carbonate reservoirs has the added benefit of mobilizing more oil for extraction, increasing oil reservoir yield, and generating revenue while also mitigating climate change. The magnitude, speed, and type of dissolution are dependent the intrinsic properties of the rock. Understanding how small changes in the pore structure affect dissolution is paramount for successful predictive modelling both on the pore-scale and for up-scaled reservoir simulations. We propose an experimental method whereby both 'Pink Beam' synchrotron radiation and a Micro-CT lab source are used in dynamic X-ray microtomography to investigate the pore structure changes in carbonate rocks of varying heterogeneity at high temperatures and pressures. Four carbonate rock types were studied, two relatively homogeneous carbonates, Ketton and Mt. Gambier, and two very heterogeneous carbonates, Estalliades and Portland Basebed. Each rock type was imaged under the same reservoir and flow conditions to gain insight into the impact of heterogeneity. A 4-mm carbonate core was injected with CO2-saturated brine at 10 MPa and 50oC for 2 hours. Depending on sample heterogeneity and X-ray source, tomographic images were taken at between 30-second and 20-minute time-resolutions and a 4-micron spatial resolution during injection. Changes in porosity, permeability, and structure were obtained by first binning and filtering the images, then binarizing them with watershed segmentation, and finally extracting a pore/throat network. Furthermore, pore-scale flow modelling was performed directly on the binarized image and used to track velocity distributions as the pore network evolved. Significant differences in dissolution type and magnitude were found for each rock type. The most homogeneous carbonate, Ketton, was seen to have predominately uniform dissolution with minor dissolution rate differences between the pores and pore throats. This was not true for the heterogeneous carbonates, Estalliades and Portland Basebed, which formed wormholes. Pore-scale modelling of flow directly on the voxels showed the differences in the evolution of complex flow fields with changes in dissolution regime. The PDFs of normalized velocity for uniform dissolution showed that the maximum pore velocity within the system decreased as dissolution occurred. This is due to dissolution enlarging pores and pore throats. However, in the wormholing regime, there was a large increase in maximum velocity once the wormhole broke through the length of the core and a preferential flow path was created. Additionally, this study serves as a unique benchmark for pore-scale reactive transport modelling directly on the binarized Micro-CT images. This dynamic pore-scale imaging method offers advantages in helping fully explain the dominant physical and chemical processes at the pore scale so that they may be up-scaled to the reservoir scale for increased accuracy in model prediction.
Dynamic decoupling and local atomic order of a model multicomponent metallic glass-former.
Kim, Jeongmin; Sung, Bong June
2015-06-17
The dynamics of multicomponent metallic alloys is spatially heterogeneous near glass transition. The diffusion coefficient of one component of the metallic alloys may also decouple from those of other components, i.e., the diffusion coefficient of each component depends differently on the viscosity of metallic alloys. In this work we investigate the dynamic heterogeneity and decoupling of a model system for multicomponent Pd43Cu27Ni10P20 melts by using a hard sphere model that considers the size disparity of alloys but does not take chemical effects into account. We also study how such dynamic behaviors would relate to the local atomic structure of metallic alloys. We find, from molecular dynamics simulations, that the smallest component P of multicomponent Pd43Cu27Ni10P20 melts becomes dynamically heterogeneous at a translational relaxation time scale and that the largest major component Pd forms a slow subsystem, which has been considered mainly responsible for the stabilization of amorphous state of alloys. The heterogeneous dynamics of P atoms accounts for the breakdown of Stokes-Einstein relation and also leads to the dynamic decoupling of P and Pd atoms. The dynamically heterogeneous P atoms decrease the lifetime of the local short-range atomic orders of both icosahedral and close-packed structures by orders of magnitude.
Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L
2018-05-01
A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.
CONSISTENT SCALING LAWS IN ANELASTIC SPHERICAL SHELL DYNAMOS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yadav, Rakesh K.; Gastine, Thomas; Christensen, Ulrich R.
2013-09-01
Numerical dynamo models always employ parameter values that differ by orders of magnitude from the values expected in natural objects. However, such models have been successful in qualitatively reproducing properties of planetary and stellar dynamos. This qualitative agreement fuels the idea that both numerical models and astrophysical objects may operate in the same asymptotic regime of dynamics. This can be tested by exploring the scaling behavior of the models. For convection-driven incompressible spherical shell dynamos with constant material properties, scaling laws had been established previously that relate flow velocity and magnetic field strength to the available power. Here we analyzemore » 273 direct numerical simulations using the anelastic approximation, involving also cases with radius-dependent magnetic, thermal, and viscous diffusivities. These better represent conditions in gas giant planets and low-mass stars compared to Boussinesq models. Our study provides strong support for the hypothesis that both mean velocity and mean magnetic field strength scale as a function of the power generated by buoyancy forces in the same way for a wide range of conditions.« less
Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling
2015-03-01
Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
NASA Technical Reports Server (NTRS)
Starr, D. OC.; Cox, S. K.
1985-01-01
A simplified cirrus cloud model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus cloud. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on cloud-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus cloud are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of cloud-scale processes in determining the cloud properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the cloud. It is shown that cirrus clouds operate in an entirely different manner than liquid phase stratiform clouds.
Scaling properties of a rice-pile model: inertia and friction effects.
Khfifi, M; Loulidi, M
2008-11-01
We present a rice-pile cellular automaton model that includes inertial and friction effects. This model is studied in one dimension, where the updating of metastable sites is done according to a stochastic dynamics governed by a probabilistic toppling parameter p that depends on the accumulated energy of moving grains. We investigate the scaling properties of the model using finite-size scaling analysis. The avalanche size, the lifetime, and the residence time distributions exhibit a power-law behavior. Their corresponding critical exponents, respectively, tau, y, and yr, are not universal. They present continuous variation versus the parameters of the system. The maximal value of the critical exponent tau that our model gives is very close to the experimental one, tau=2.02 [Frette, Nature (London) 379, 49 (1996)], and the probability distribution of the residence time is in good agreement with the experimental results. We note that the critical behavior is observed only in a certain range of parameter values of the system which correspond to low inertia and high friction.
NASA Astrophysics Data System (ADS)
Scholz, Robert; Floß, Gereon; Saalfrank, Peter; Füchsel, Gernot; Lončarić, Ivor; Juaristi, J. I.
2016-10-01
A Langevin model accounting for all six molecular degrees of freedom is applied to femtosecond-laser induced, hot-electron driven dynamics of Ru(0001)(2 ×2 ):CO. In our molecular dynamics with electronic friction approach, a recently developed potential energy surface based on gradient-corrected density functional theory accounting for van der Waals interactions is adopted. Electronic friction due to the coupling of molecular degrees of freedom to electron-hole pairs in the metal are included via a local density friction approximation, and surface phonons by a generalized Langevin oscillator model. The action of ultrashort laser pulses enters through a substrate-mediated, hot-electron mechanism via a time-dependent electronic temperature (derived from a two-temperature model), causing random forces acting on the molecule. The model is applied to laser induced lateral diffusion of CO on the surface, "hot adsorbate" formation, and laser induced desorption. Reaction probabilities are strongly enhanced compared to purely thermal processes, both for diffusion and desorption. Reaction yields depend in a characteristic (nonlinear) fashion on the applied laser fluence, as well as branching ratios for various reaction channels. Computed two-pulse correlation traces for desorption and other indicators suggest that aside from electron-hole pairs, phonons play a non-negligible role for laser induced dynamics in this system, acting on a surprisingly short time scale. Our simulations on precomputed potentials allow for good statistics and the treatment of long-time dynamics (300 ps), giving insight into this system which hitherto has not been reached. We find generally good agreement with experimental data where available and make predictions in addition. A recently proposed laser induced population of physisorbed precursor states could not be observed with the present low-coverage model.
Velocity dependence of biphasic flow structuration: steady-state and oscillating flow effects
NASA Astrophysics Data System (ADS)
Tore Tallakstad, Ken; Jankov, Mihailo; Løvoll, Grunde; Toussaint, Renaud; Jørgen Mâløy, Knut; Grude Flekkøy, Eirik; Schmittbuhl, Jean; Schäfer, Gerhard; Méheust, Yves; Arendt Knudsen, Henning
2010-05-01
We study various types of biphasic flows in quasi-two-dimensional transparent porous models. These flows imply a viscous wetting fluid, and a lowly viscous one. The models are transparent, allowing the displacement process and structure to be monitored in space and time. Three different aspects will be presented: 1. In stationary biphasic flows, we study the relationship between the macroscopic pressure drop (related to relative permeability) and the average flow rate, and how this arises from the cluster size distribution of the lowly viscous fluid [1]. 2. In drainage situations, we study how the geometry of the invader can be explained, and how it gives rise to apparent dynamic capillary effects. We show how these can be explained by viscous effects on evolving geometries of invading fluid [2]. 3. We study the impact of oscillating pressure fields superimposed to a background flow over the flow regimes patterns [3]. Steady-State Two-Phase Flow in Porous Media: Statistics and Transport Properties. First, in stationary flow with a control of the flux of both fluids, we show how the pressure drop depends on the flow rate. We will show that the dynamics is dominated by the interplay between a viscous pressure field from the wetting fluid and bubble transport of a less viscous, nonwetting phase. In contrast with more studied displacement front systems, steady-state flow is in equilibrium, statistically speaking. The corresponding theoretical simplicity allows us to explain a data collapse in the cluster size distribution of lowly viscous fluid in the system, as well as the relation |?P|∞√Ca--. This allows to explain so called relative permeability effects by the morphological changes of the cluster size distribution. Influence of viscous fingering on dynamic saturation-pressure curves in porous media. Next, we study drainage in such models, and investigate the relationship between the pressure field and the morphology of the invading fluid. This allows to model the impact of the saturation changes in the system over the pressure difference between the wetting and non wetting phase. We show that the so-called dynamic effects referred in the hydrology literature of experimentally measured capillary pressure curves might be explained by the combined effect of capillary pressure along the invasion front of the gaseous phase and pressure changes caused by viscous effects. A detailed study of the structure optically followed shows that the geometry of the invader is self-similar with two different behaviors at small and large scales: the structure corresponds to the ones of invasion percolation models at small scales (capillary fingering structures with fractal dimension D=1.83), whereas at large scales, viscous pressure drops dominate over the capillary threshold variations, and the structures are self-similar fingering structures with a fractal dimension corresponding to Dielectric Breakdown Models (variants of the DLA model), with D ≠ 1.5. The cross-over scale is set by the scale at which capillary fluctuations are of the order of the viscous pressure drops. This leads physically to the fact that cross-over scale between the two fingering dimensions, goes like the inverse of the capillary number. This study utilizes these geometrical characteristics of the viscous fingers forming in dynamic drainage, to obtain a meaningfull scaling law for the saturation-pressure curve at finite speed, i.e. the so-called dynamic capillary pressure relations. We thus show how the micromechanical interplay between viscous and capillary forces leads to some pattern formation, which results in a general form of dynamic capillary pressure relations. By combining these detailed informations on the displacement structure with global measures of pressure, saturation and controlling the capillary number Ca, a scaling relation relating pressure, saturation, system size and capillary number is developed. By applying this scaling relation, pressure-saturation curves for a wide range of capillary numbers can be collapsed. Effects of pressure oscillations on drainage in an elastic porous medium: The effects of seismic stimulation on the flow of two immiscible fluids in an elastic synthetic porous medium is experimentally investigated. A wetting fluid is slowly evacuated from the medium, while a pressure oscillation is applied on the injected non-wetting fluid. The amplitude and frequency of the pressure oscillations as well as the evacuation speed are kept constant throughout an experiment. The resulting morphology of the invading structure is found to be strongly dependent on the interplay between the amplitude and the frequency of the applied pressure oscillations and the elasticity of the porous medium. Different combinations of these properties yield morphologically similar structures, allowing a classification of structures that is found to depend on a proposed dimensionless number. [1] Tallakstad, K.T., H.A. Knudsen, T. Ramstad, G. Løvoll, K.J. Maløy, R. Toussaint and E.G. Flekkøy , Steady-state two-phase flow in porous media: statistics and transport properties, Phys. Rev. Lett. 102, 074502 (2009). doi:10.1103/PhysRevLett.102.074502 [2] Løvoll, G., M. Jankov, K.J. Maløy, R. Toussaint, J. Schmittbuhl, G. Schaefer and Y. Ḿ eheust, Influence of viscous fingering on dynamic saturation-pressure curves in porous media, submitted to Transport In Porous Media, (2010) [3] Jankov, M., G. Løvoll, H.A. Knudsen, K.J. Maløy, R. Planet, R. Toussaint and E.G. Flekkøy; Effects of pressure oscillations on drainage in an elastic porous medium, Transport In Porous Media, in press (2010).
DEPENDENCE OF STELLAR MAGNETIC ACTIVITY CYCLES ON ROTATIONAL PERIOD IN A NONLINEAR SOLAR-TYPE DYNAMO
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pipin, V. V.; Kosovichev, A. G.
2016-06-01
We study the turbulent generation of large-scale magnetic fields using nonlinear dynamo models for solar-type stars in the range of rotational periods from 14 to 30 days. Our models take into account nonlinear effects of dynamical quenching of magnetic helicity, and escape of magnetic field from the dynamo region due to magnetic buoyancy. The results show that the observed correlation between the period of rotation and the duration of activity cycles can be explained in the framework of a distributed dynamo model with a dynamical magnetic feedback acting on the turbulent generation from either magnetic buoyancy or magnetic helicity. Wemore » discuss implications of our findings for the understanding of dynamo processes operating in solar-like stars.« less
NASA Astrophysics Data System (ADS)
Alapaty, Kiran; Bullock, O. Russell; Herwehe, Jerold; Spero, Tanya; Nolte, Christopher; Mallard, Megan
2014-05-01
The Regional Climate Modeling Team at the U.S. Environmental Protection Agency has been improving the quality of regional climate fields generated by the Weather Research and Forecasting (WRF) model. Active areas of research include improving core physics within the WRF model and adapting the physics for regional climate applications, improving the representation of inland lakes that are unresolved by the driving fields, evaluating nudging strategies, and devising techniques to demonstrate value added by dynamical downscaling. These research efforts have been conducted using reanalysis data as driving fields, and then their results have been applied to downscale data from global climate models. The goals of this work are to equip environmental managers and policy/decision makers in the U.S. with science, tools, and data to inform decisions related to adapting to and mitigating the potential impacts of climate change on air quality, ecosystems, and human health. Our presentation will focus mainly on one area of the Team's research: Development and testing of a seamless convection parameterization scheme. For the continental U.S., one of the impediments to high-resolution (~3 to 15 km) climate modeling is related to the lack of a seamless convection parameterization that works across many scales. Since many convection schemes are not developed to work at those "gray scales", they often lead to excessive precipitation during warm periods (e.g., summer). The Kain-Fritsch (KF) convection parameterization in the WRF model has been updated such that it can be used seamlessly across spatial scales down to ~1 km grid spacing. First, we introduced subgrid-scale cloud and radiation interactions that had not been previously considered in the KF scheme. Then, a scaling parameter was developed to introduce scale-dependency in the KF scheme for use with various processes. In addition, we developed new formulations for: (1) convective adjustment timescale; (2) entrainment of environmental air; (3) impacts of convective updraft on grid-scale vertical velocity; (4) convective cloud microphysics; (5) stabilizing capacity; (6) elimination of double counting of precipitation; and (7) estimation of updraft mass flux at the lifting condensation level. Some of these scale-dependent formulations make the KF scheme operable at all scales up to about sub-kilometer grid resolution. In this presentation, regional climate simulations using the WRF model will be presented to demonstrate the effects of these changes to the KF scheme. Additionally, we briefly present results obtained from the improved representation of inland lakes, various nudging strategies, and added value of dynamical downscaling of regional climate. Requesting for a plenary talk for the session: "Regional climate modeling, including CORDEX" (session number CL6.4) at the EGU 2014 General Assembly, to be held 27 April - 2 May 2014 in Vienna, Austria.
A coarse-grained model to study calcium activation of the cardiac thin filament
NASA Astrophysics Data System (ADS)
Zhang, Jing; Schwartz, Steven
2015-03-01
Familial hypertrophic cardiomyopathy (FHC) is one of the most common heart disease caused by genetic mutations. Cardiac muscle contraction and relaxation involve regulation of crossbridge binding to the cardiac thin filament, which regulates actomyosin interactions through calcium-dependent alterations in the dynamics of cardiac troponin (cTn) and tropomyosin (Tm). An atomistic model of cTn complex interacting with Tm has been studied by our group. A more realistic model requires the inclusion of the dynamics of actin filament, which is almost 6 times larger than cTn and Tm in terms of atom numbers, and extensive sampling of the model becomes very resource-demanding. By using physics-based protein united-residue force field, we introduce a coarse-grained model to study the calcium activation of the thin filament resulting from cTn's allosteric regulation of Tm dynamics on actin. The time scale is much longer than that of all-atom molecular dynamics simulation because of the reduction of the degrees of freedom. The coarse-grained model is a good template for studying cardiac thin filament mutations that cause FHC, and reduces the cost of computational resources.
Stegen, James C; Ferriere, Regis; Enquist, Brian J
2012-03-22
In ectothermic organisms, it is hypothesized that metabolic rates mediate influences of temperature on the ecological and evolutionary processes governing biodiversity. However, it is unclear how and to what extent the influence of temperature on metabolism scales up to shape large-scale diversity patterns. In order to clarify the roles of temperature and metabolism, new theory is needed. Here, we establish such theory and model eco-evolutionary dynamics of trophic networks along a broad temperature gradient. In the model temperature can influence, via metabolism, resource supply, consumers' vital rates and mutation rate. Mutation causes heritable variation in consumer body size, which diversifies and governs consumer function in the ecological network. The model predicts diversity to increase with temperature if resource supply is temperature-dependent, whereas temperature-dependent consumer vital rates cause diversity to decrease with increasing temperature. When combining both thermal dependencies, a unimodal temperature-diversity pattern evolves, which is reinforced by temperature-dependent mutation rate. Studying coexistence criteria for two consumers showed that these outcomes are owing to temperature effects on mutual invasibility and facilitation. Our theory shows how and why metabolism can influence diversity, generates predictions useful for understanding biodiversity gradients and represents an extendable framework that could include factors such as colonization history and niche conservatism.
NASA Astrophysics Data System (ADS)
Paiewonsky, Pablo; Elison Timm, Oliver
2018-03-01
In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.
Temporal node centrality in complex networks
NASA Astrophysics Data System (ADS)
Kim, Hyoungshick; Anderson, Ross
2012-02-01
Many networks are dynamic in that their topology changes rapidly—on the same time scale as the communications of interest between network nodes. Examples are the human contact networks involved in the transmission of disease, ad hoc radio networks between moving vehicles, and the transactions between principals in a market. While we have good models of static networks, so far these have been lacking for the dynamic case. In this paper we present a simple but powerful model, the time-ordered graph, which reduces a dynamic network to a static network with directed flows. This enables us to extend network properties such as vertex degree, closeness, and betweenness centrality metrics in a very natural way to the dynamic case. We then demonstrate how our model applies to a number of interesting edge cases, such as where the network connectivity depends on a small number of highly mobile vertices or edges, and show that our centrality definition allows us to track the evolution of connectivity. Finally we apply our model and techniques to two real-world dynamic graphs of human contact networks and then discuss the implication of temporal centrality metrics in the real world.
Analytic model to estimate thermonuclear neutron yield in z-pinches using the magnetic Noh problem
NASA Astrophysics Data System (ADS)
Allen, Robert C.
The objective was to build a model which could be used to estimate neutron yield in pulsed z-pinch experiments, benchmark future z-pinch simulation tools and to assist scaling for breakeven systems. To accomplish this, a recent solution to the magnetic Noh problem was utilized which incorporates a self-similar solution with cylindrical symmetry and azimuthal magnetic field (Velikovich, 2012). The self-similar solution provides the conditions needed to calculate the time dependent implosion dynamics from which batch burn is assumed and used to calculate neutron yield. The solution to the model is presented. The ion densities and time scales fix the initial mass and implosion velocity, providing estimates of the experimental results given specific initial conditions. Agreement is shown with experimental data (Coverdale, 2007). A parameter sweep was done to find the neutron yield, implosion velocity and gain for a range of densities and time scales for DD reactions and a curve fit was done to predict the scaling as a function of preshock conditions.
Reconstructing the regulatory circuit of cell fate determination in yeast mating response.
Shao, Bin; Yuan, Haiyu; Zhang, Rongfei; Wang, Xuan; Zhang, Shuwen; Ouyang, Qi; Hao, Nan; Luo, Chunxiong
2017-07-01
Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.
NASA Technical Reports Server (NTRS)
Gullbrand, Jessica
2003-01-01
In this paper, turbulence-closure models are evaluated using the 'true' LES approach in turbulent channel flow. The study is an extension of the work presented by Gullbrand (2001), where fourth-order commutative filter functions are applied in three dimensions in a fourth-order finite-difference code. The true LES solution is the grid-independent solution to the filtered governing equations. The solution is obtained by keeping the filter width constant while the computational grid is refined. As the grid is refined, the solution converges towards the true LES solution. The true LES solution will depend on the filter width used, but will be independent of the grid resolution. In traditional LES, because the filter is implicit and directly connected to the grid spacing, the solution converges towards a direct numerical simulation (DNS) as the grid is refined, and not towards the solution of the filtered Navier-Stokes equations. The effect of turbulence-closure models is therefore difficult to determine in traditional LES because, as the grid is refined, more turbulence length scales are resolved and less influence from the models is expected. In contrast, in the true LES formulation, the explicit filter eliminates all scales that are smaller than the filter cutoff, regardless of the grid resolution. This ensures that the resolved length-scales do not vary as the grid resolution is changed. In true LES, the cell size must be smaller than or equal to the cutoff length scale of the filter function. The turbulence-closure models investigated are the dynamic Smagorinsky model (DSM), the dynamic mixed model (DMM), and the dynamic reconstruction model (DRM). These turbulence models were previously studied using two-dimensional explicit filtering in turbulent channel flow by Gullbrand & Chow (2002). The DSM by Germano et al. (1991) is used as the USFS model in all the simulations. This enables evaluation of different reconstruction models for the RSFS stresses. The DMM consists of the scale-similarity model (SSM) by Bardina et al. (1983), which is an RSFS model, in linear combination with the DSM. In the DRM, the RSFS stresses are modeled by using an estimate of the unfiltered velocity in the unclosed term, while the USFS stresses are modeled by the DSM. The DSM and the DMM are two commonly used turbulence-closure models, while the DRM is a more recent model.
Nonlinear spherical perturbations in quintessence models of dark energy
NASA Astrophysics Data System (ADS)
Pratap Rajvanshi, Manvendra; Bagla, J. S.
2018-06-01
Observations have confirmed the accelerated expansion of the universe. The accelerated expansion can be modelled by invoking a cosmological constant or a dynamical model of dark energy. A key difference between these models is that the equation of state parameter w for dark energy differs from ‑1 in dynamical dark energy (DDE) models. Further, the equation of state parameter is not constant for a general DDE model. Such differences can be probed using the variation of scale factor with time by measuring distances. Another significant difference between the cosmological constant and DDE models is that the latter must cluster. Linear perturbation analysis indicates that perturbations in quintessence models of dark energy do not grow to have a significant amplitude at small length scales. In this paper we study the response of quintessence dark energy to non-linear perturbations in dark matter. We use a fully relativistic model for spherically symmetric perturbations. In this study we focus on thawing models. We find that in response to non-linear perturbations in dark matter, dark energy perturbations grow at a faster rate than expected in linear perturbation theory. We find that dark energy perturbation remains localised and does not diffuse out to larger scales. The dominant drivers of the evolution of dark energy perturbations are the local Hubble flow and a supression of gradients of the scalar field. We also find that the equation of state parameter w changes in response to perturbations in dark matter such that it also becomes a function of position. The variation of w in space is correlated with density contrast for matter. Variation of w and perturbations in dark energy are more pronounced in response to large scale perturbations in matter while the dependence on the amplitude of matter perturbations is much weaker.
Efficient Parallel Algorithms for Landscape Evolution Modelling
NASA Astrophysics Data System (ADS)
Moresi, L. N.; Mather, B.; Beucher, R.
2017-12-01
Landscape erosion and the deposition of sediments by river systems are strongly controlled bytopography, rainfall patterns, and the susceptibility of the basement to the action ofrunning water. It is well understood that each of these processes depends on the other, for example:topography results from active tectonic processes; deformation, metamorphosis andexhumation alter the competence of the basement; rainfall patterns depend on topography;uplift and subsidence in response to tectonic stress can be amplified by erosionand sediment deposition. We typically gain understanding of such coupled systems through forward models which capture theessential interactions of the various components and attempt parameterise those parts of the individual systemthat are unresolvable at the scale of the interaction. Here we address the problem of predicting erosion and deposition rates at a continental scalewith a resolution of tens to hundreds of metres in a dynamic, Lagrangian framework. This isa typical requirement for a code to interface with a mantle / lithosphere dynamics model anddemands an efficient, unstructured, parallel implementation. We address this through a very general algorithm that treats all parts of the landscape evolution equationsin sparse-matrix form including those for stream-flow accumulation, dam-filling and catchment determination. This givesus considerable flexibility in developing unstructured, parallel code, and in creating a modular packagethat can be configured by users to work at different temporal and spatial scales, but is also has potential advantagesin treating the non-linear parts of the problem in a general manner.
Pump-Probe Noise Spectroscopy of Molecular Junctions.
Ochoa, Maicol A; Selzer, Yoram; Peskin, Uri; Galperin, Michael
2015-02-05
The slow response of electronic components in junctions limits the direct applicability of pump-probe type spectroscopy in assessing the intramolecular dynamics. Recently the possibility of getting information on a sub-picosecond time scale from dc current measurements was proposed. We revisit the idea of picosecond resolution by pump-probe spectroscopy from dc measurements and show that any intramolecular dynamics not directly related to charge transfer in the current direction is missed by current measurements. We propose a pump-probe dc shot noise spectroscopy as a suitable alternative. Numerical examples of time-dependent and average responses of junctions are presented for generic models.
Substructure of fuzzy dark matter haloes
NASA Astrophysics Data System (ADS)
Du, Xiaolong; Behrens, Christoph; Niemeyer, Jens C.
2017-02-01
We derive the halo mass function (HMF) for fuzzy dark matter (FDM) by solving the excursion set problem explicitly with a mass-dependent barrier function, which has not been done before. We find that compared to the naive approach of the Sheth-Tormen HMF for FDM, our approach has a higher cutoff mass and the cutoff mass changes less strongly with redshifts. Using merger trees constructed with a modified version of the Lacey & Cole formalism that accounts for suppressed small-scale power and the scale-dependent growth of FDM haloes and the semi-analytic GALACTICUS code, we study the statistics of halo substructure including the effects from dynamical friction and tidal stripping. We find that if the dark matter is a mixture of cold dark matter (CDM) and FDM, there will be a suppression on the halo substructure on small scales which may be able to solve the missing satellites problem faced by the pure CDM model. The suppression becomes stronger with increasing FDM fraction or decreasing FDM mass. Thus, it may be used to constrain the FDM model.
Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System
NASA Astrophysics Data System (ADS)
He, Qing; Li, Hong
Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.
Construction of Penrose Diagrams for Dynamic Black Holes
NASA Technical Reports Server (NTRS)
Brown, Beth A.; Lindesay, James
2008-01-01
A set of Penrose diagrams is constructed in order to examine the large-scale causal structure of black holes with dynamic horizons. Coordinate dependencies of significant features, such as the event horizon and radial mass scale, are demonstrated on the diagrams. Unlike in static Schwarzschild geometries, the radial mass scale is clearly seen to differ from the horizon. Trajectories for photons near the horizon are briefly discussed.
Status of DSMT research program
NASA Technical Reports Server (NTRS)
Mcgowan, Paul E.; Javeed, Mehzad; Edighoffer, Harold H.
1991-01-01
The status of the Dynamic Scale Model Technology (DSMT) research program is presented. DSMT is developing scale model technology for large space structures as part of the Control Structure Interaction (CSI) program at NASA Langley Research Center (LaRC). Under DSMT a hybrid-scale structural dynamics model of Space Station Freedom was developed. Space Station Freedom was selected as the focus structure for DSMT since the station represents the first opportunity to obtain flight data on a complex, three-dimensional space structure. Included is an overview of DSMT including the development of the space station scale model and the resulting hardware. Scaling technology was developed for this model to achieve a ground test article which existing test facilities can accommodate while employing realistically scaled hardware. The model was designed and fabricated by the Lockheed Missile and Space Co., and is assembled at LaRc for dynamic testing. Also, results from ground tests and analyses of the various model components are presented along with plans for future subassembly and matted model tests. Finally, utilization of the scale model for enhancing analysis verification of the full-scale space station is also considered.
Dynamic correlations at different time-scales with empirical mode decomposition
NASA Astrophysics Data System (ADS)
Nava, Noemi; Di Matteo, T.; Aste, Tomaso
2018-07-01
We introduce a simple approach which combines Empirical Mode Decomposition (EMD) and Pearson's cross-correlations over rolling windows to quantify dynamic dependency at different time scales. The EMD is a tool to separate time series into implicit components which oscillate at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S&P 500 (USA), the IPC (Mexico) and the VIX (volatility index USA), obtaining time-varying multidimensional cross-correlations at different time-scales. The correlations computed over a rolling window are compared across the three indices, across the components at different time-scales and across different time lags. We uncover a rich heterogeneity of interactions, which depends on the time-scale and has important lead-lag relations that could have practical use for portfolio management, risk estimation and investment decisions.
NASA Astrophysics Data System (ADS)
O'Donncha, Fearghal; Hartnett, Michael; Nash, Stephen; Ren, Lei; Ragnoli, Emanuele
2015-02-01
In this study, High Frequency Radar (HFR), observations in conjunction with numerical model simulations investigate surface flow dynamics in a tidally-active, wind-driven bay; Galway Bay situated on the West coast of Ireland. Comparisons against ADCP sensor data permit an independent assessment of HFR and model performance, respectively. Results show root-mean-square (rms) differences in the range 10 - 12cm/s while model rms equalled 12 - 14cm/s. Subsequent analysis focus on a detailed comparison of HFR and model output. Harmonic analysis decompose both sets of surface currents based on distinct flow process, enabling a correlation analysis between the resultant output and dominant forcing parameters. Comparisons of barotropic model simulations and HFR tidal signal demonstrate consistently high agreement, particularly of the dominant M2 tidal signal. Analysis of residual flows demonstrate considerably poorer agreement, with the model failing to replicate complex flows. A number of hypotheses explaining this discrepancy are discussed, namely: discrepancies between regional-scale, coastal-ocean models and globally-influenced bay-scale dynamics; model uncertainties arising from highly-variable wind-driven flows across alarge body of water forced by point measurements of wind vectors; and the high dependence of model simulations on empirical wind-stress coefficients. The research demonstrates that an advanced, widely-used hydro-environmental model does not accurately reproduce aspects of surface flow processes, particularly with regards wind forcing. Considering the significance of surface boundary conditions in both coastal and open ocean dynamics, the viability of using a systematic analysis of results to improve model predictions is discussed.
NASA Astrophysics Data System (ADS)
Separovic, Leo; Husain, Syed Zahid; Yu, Wei
2015-09-01
Internal variability (IV) in dynamical downscaling with limited-area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables toward high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity, and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations, and probabilistic approach to downscaling is therefore recommended.
Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.
2015-01-01
Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367
Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J
2015-02-01
Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.
NASA Astrophysics Data System (ADS)
Zamani Kouhpanji, Mohammad Reza; Behzadirad, Mahmoud; Busani, Tito
2017-12-01
We used the stable strain gradient theory including acceleration gradients to investigate the classical and nonclassical mechanical properties of gallium nitride (GaN) nanowires (NWs). We predicted the static length scales, Young's modulus, and shear modulus of the GaN NWs from the experimental data. Combining these results with atomic simulations, we also found the dynamic length scale of the GaN NWs. Young's modulus, shear modulus, static, and dynamic length scales were found to be 318 GPa, 131 GPa, 8 nm, and 8.9 nm, respectively, usable for demonstrating the static and dynamic behaviors of GaN NWs having diameters from a few nm to bulk dimensions. Furthermore, the experimental data were analyzed with classical continuum theory (CCT) and compared with the available literature to illustrate the size-dependency of the mechanical properties of GaN NWs. This practice resolves the previous published discrepancies that happened due to the limitations of CCT used for determining the mechanical properties of GaN NWs and their size-dependency.
Bonded-cell model for particle fracture.
Nguyen, Duc-Hanh; Azéma, Emilien; Sornay, Philippe; Radjai, Farhang
2015-02-01
Particle degradation and fracture play an important role in natural granular flows and in many applications of granular materials. We analyze the fracture properties of two-dimensional disklike particles modeled as aggregates of rigid cells bonded along their sides by a cohesive Mohr-Coulomb law and simulated by the contact dynamics method. We show that the compressive strength scales with tensile strength between cells but depends also on the friction coefficient and a parameter describing cell shape distribution. The statistical scatter of compressive strength is well described by the Weibull distribution function with a shape parameter varying from 6 to 10 depending on cell shape distribution. We show that this distribution may be understood in terms of percolating critical intercellular contacts. We propose a random-walk model of critical contacts that leads to particle size dependence of the compressive strength in good agreement with our simulation data.
Frequency-dependent hydrodynamic interaction between two solid spheres
NASA Astrophysics Data System (ADS)
Jung, Gerhard; Schmid, Friederike
2017-12-01
Hydrodynamic interactions play an important role in many areas of soft matter science. In simulations with implicit solvent, various techniques such as Brownian or Stokesian dynamics explicitly include hydrodynamic interactions a posteriori by using hydrodynamic diffusion tensors derived from the Stokes equation. However, this equation assumes the interaction to be instantaneous which is an idealized approximation and only valid on long time scales. In the present paper, we go one step further and analyze the time-dependence of hydrodynamic interactions between finite-sized particles in a compressible fluid on the basis of the linearized Navier-Stokes equation. The theoretical results show that at high frequencies, the compressibility of the fluid has a significant impact on the frequency-dependent pair interactions. The predictions of hydrodynamic theory are compared to molecular dynamics simulations of two nanocolloids in a Lennard-Jones fluid. For this system, we reconstruct memory functions by extending the inverse Volterra technique. The simulation data agree very well with the theory, therefore, the theory can be used to implement dynamically consistent hydrodynamic interactions in the increasingly popular field of non-Markovian modeling.
Energy Current Cumulants in One-Dimensional Systems in Equilibrium
NASA Astrophysics Data System (ADS)
Dhar, Abhishek; Saito, Keiji; Roy, Anjan
2018-06-01
A recent theory based on fluctuating hydrodynamics predicts that one-dimensional interacting systems with particle, momentum, and energy conservation exhibit anomalous transport that falls into two main universality classes. The classification is based on behavior of equilibrium dynamical correlations of the conserved quantities. One class is characterized by sound modes with Kardar-Parisi-Zhang scaling, while the second class has diffusive sound modes. The heat mode follows Lévy statistics, with different exponents for the two classes. Here we consider heat current fluctuations in two specific systems, which are expected to be in the above two universality classes, namely, a hard particle gas with Hamiltonian dynamics and a harmonic chain with momentum conserving stochastic dynamics. Numerical simulations show completely different system-size dependence of current cumulants in these two systems. We explain this numerical observation using a phenomenological model of Lévy walkers with inputs from fluctuating hydrodynamics. This consistently explains the system-size dependence of heat current fluctuations. For the latter system, we derive the cumulant-generating function from a more microscopic theory, which also gives the same system-size dependence of cumulants.
Multi-scale coarse-graining of non-conservative interactions in molecular liquids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Izvekov, Sergei, E-mail: sergiy.izvyekov.civ@mail.mil; Rice, Betsy M.
2014-03-14
A new bottom-up procedure for constructing non-conservative (dissipative and stochastic) interactions for dissipative particle dynamics (DPD) models is described and applied to perform hierarchical coarse-graining of a polar molecular liquid (nitromethane). The distant-dependent radial and shear frictions in functional-free form are derived consistently with a chosen form for conservative interactions by matching two-body force-velocity and three-body velocity-velocity correlations along the microscopic trajectories of the centroids of Voronoi cells (clusters), which represent the dissipative particles within the DPD description. The Voronoi tessellation is achieved by application of the K-means clustering algorithm at regular time intervals. Consistently with a notion of many-bodymore » DPD, the conservative interactions are determined through the multi-scale coarse-graining (MS-CG) method, which naturally implements a pairwise decomposition of the microscopic free energy. A hierarchy of MS-CG/DPD models starting with one molecule per Voronoi cell and up to 64 molecules per cell is derived. The radial contribution to the friction appears to be dominant for all models. As the Voronoi cell sizes increase, the dissipative forces rapidly become confined to the first coordination shell. For Voronoi cells of two and more molecules the time dependence of the velocity autocorrelation function becomes monotonic and well reproduced by the respective MS-CG/DPD models. A comparative analysis of force and velocity correlations in the atomistic and CG ensembles indicates Markovian behavior with as low as two molecules per dissipative particle. The models with one and two molecules per Voronoi cell yield transport properties (diffusion and shear viscosity) that are in good agreement with the atomistic data. The coarser models produce slower dynamics that can be appreciably attributed to unaccounted dissipation introduced by regular Voronoi re-partitioning as well as by larger numerical errors in mapping out the dissipative forces. The framework presented herein can be used to develop computational models of real liquids which are capable of bridging the atomistic and mesoscopic scales.« less
A model of partial differential equations for HIV propagation in lymph nodes
NASA Astrophysics Data System (ADS)
Marinho, E. B. S.; Bacelar, F. S.; Andrade, R. F. S.
2012-01-01
A system of partial differential equations is used to model the dissemination of the Human Immunodeficiency Virus (HIV) in CD4+T cells within lymph nodes. Besides diffusion terms, the model also includes a time-delay dependence to describe the time lag required by the immunologic system to provide defenses to new virus strains. The resulting dynamics strongly depends on the properties of the invariant sets of the model, consisting of three fixed points related to the time independent and spatial homogeneous tissue configurations in healthy and infected states. A region in the parameter space is considered, for which the time dependence of the space averaged model variables follows the clinical pattern reported for infected patients: a short scale primary infection, followed by a long latency period of almost complete recovery and third phase characterized by damped oscillations around a value with large HIV counting. Depending on the value of the diffusion coefficient, the latency time increases with respect to that one obtained for the space homogeneous version of the model. It is found that same initial conditions lead to quite different spatial patterns, which depend strongly on the latency interval.
Matsuura, Tomoaki; Tanimura, Naoki; Hosoda, Kazufumi; Yomo, Tetsuya; Shimizu, Yoshihiro
2017-01-01
To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions. PMID:28167777
Green roofs'retention performances in different climates
NASA Astrophysics Data System (ADS)
Viola, Francesco; Hellies, Matteo; Deidda, Roberto
2017-04-01
The ongoing process of global urbanization contributes to increasing stormwater runoff from impervious surfaces, threatening also water quality. Green roofs have been proved to be an innovative stormwater management tool to partially restore natural state, enhancing interception, infiltration and evapotranspiration fluxes. The amount of water that is retained within green roofs depends mainly on both soil properties and climate. The evaluation of the retained water is not trivial since it depends on the stochastic soil moisture dynamics. The aim of this work is to explore performances of green roofs, in terms of water retention, as a function of their depth considering different climate regimes. The role of climate in driving water retention has been mainly represented by rainfall and potential evapotranspiration dynamics, which are simulated by a simple conceptual weather generator at daily time scale. The model is able to describe seasonal (in-phase and counter-phase) and stationary behaviors of climatic forcings. Model parameters have been estimated on more than 20,000 historical time series retrieved worldwide. Exemplifying cases are discussed for five different climate scenarios, changing the amplitude and/or the phase of daily mean rainfall and evapotranspiration forcings. The first scenario represents stationary climates, in two other cases the daily mean rainfall or the potential evapotranspiration evolve sinusoidally. In the latter two cases, we simulated the in-phase or in counter-phase conditions. Stochastic forcings have been then used as an input to a simple conceptual hydrological model which simulate soil moisture dynamics, evapotranspiration fluxes, runoff and leakage from soil pack at daily time scale. For several combinations of annual rainfall and potential evapotranspiration, the analysis allowed assessing green roofs' retaining capabilities, at annual time scale. Provided abacus allows a first approximation of possible hydrological benefits deriving from the implementation of intensive or extensive green roofs in different world areas, i.e. less input to sewer systems.
Ensemble Kalman filters for dynamical systems with unresolved turbulence
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grooms, Ian, E-mail: grooms@cims.nyu.edu; Lee, Yoonsang; Majda, Andrew J.
Ensemble Kalman filters are developed for turbulent dynamical systems where the forecast model does not resolve all the active scales of motion. Coarse-resolution models are intended to predict the large-scale part of the true dynamics, but observations invariably include contributions from both the resolved large scales and the unresolved small scales. The error due to the contribution of unresolved scales to the observations, called ‘representation’ or ‘representativeness’ error, is often included as part of the observation error, in addition to the raw measurement error, when estimating the large-scale part of the system. It is here shown how stochastic superparameterization (amore » multiscale method for subgridscale parameterization) can be used to provide estimates of the statistics of the unresolved scales. In addition, a new framework is developed wherein small-scale statistics can be used to estimate both the resolved and unresolved components of the solution. The one-dimensional test problem from dispersive wave turbulence used here is computationally tractable yet is particularly difficult for filtering because of the non-Gaussian extreme event statistics and substantial small scale turbulence: a shallow energy spectrum proportional to k{sup −5/6} (where k is the wavenumber) results in two-thirds of the climatological variance being carried by the unresolved small scales. Because the unresolved scales contain so much energy, filters that ignore the representation error fail utterly to provide meaningful estimates of the system state. Inclusion of a time-independent climatological estimate of the representation error in a standard framework leads to inaccurate estimates of the large-scale part of the signal; accurate estimates of the large scales are only achieved by using stochastic superparameterization to provide evolving, large-scale dependent predictions of the small-scale statistics. Again, because the unresolved scales contain so much energy, even an accurate estimate of the large-scale part of the system does not provide an accurate estimate of the true state. By providing simultaneous estimates of both the large- and small-scale parts of the solution, the new framework is able to provide accurate estimates of the true system state.« less
A Nonlocal Peridynamic Plasticity Model for the Dynamic Flow and Fracture of Concrete.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vogler, Tracy; Lammi, Christopher James
A nonlocal, ordinary peridynamic constitutive model is formulated to numerically simulate the pressure-dependent flow and fracture of heterogeneous, quasi-brittle ma- terials, such as concrete. Classical mechanics and traditional computational modeling methods do not accurately model the distributed fracture observed within this family of materials. The peridynamic horizon, or range of influence, provides a characteristic length to the continuum and limits localization of fracture. Scaling laws are derived to relate the parameters of peridynamic constitutive model to the parameters of the classical Drucker-Prager plasticity model. Thermodynamic analysis of associated and non-associated plastic flow is performed. An implicit integration algorithm is formu-more » lated to calculate the accumulated plastic bond extension and force state. The gov- erning equations are linearized and the simulation of the quasi-static compression of a cylinder is compared to the classical theory. A dissipation-based peridynamic bond failure criteria is implemented to model fracture and the splitting of a concrete cylinder is numerically simulated. Finally, calculation of the impact and spallation of a con- crete structure is performed to assess the suitability of the material and failure models for simulating concrete during dynamic loadings. The peridynamic model is found to accurately simulate the inelastic deformation and fracture behavior of concrete during compression, splitting, and dynamically induced spall. The work expands the types of materials that can be modeled using peridynamics. A multi-scale methodology for simulating concrete to be used in conjunction with the plasticity model is presented. The work was funded by LDRD 158806.« less
Dynamics of thermal plumes in three-dimensional isoviscous thermal convection
NASA Astrophysics Data System (ADS)
Zhong, Shijie
2005-07-01
The dynamics of mantle plumes are important for understanding intraplate volcanism and heat transfer in the mantle. Using 3-D numerical models and scaling analyses, we investigated the controls of convective vigour or Ra (Rayleigh number) on the dynamics of thermal plumes in isoviscous and basal heating thermal convection. We examined the Ra dependence of plume number, plume spacing, plume vertical velocity and plume radius. We found that plume number does not increase monotonically with Ra. At relatively small Ra(<=106), plume number is insensitive to Ra. For 3 × 106<=Ra<= 3 × 107, plume number scales as Ra0.31 and plume spacing λ~Ra-0.16~δ1/2, where δ is the thickness of the thermal boundary layer. However, for larger Ra(~108) plume number and plume spacing again become insensitive to Ra. This indicates that the box depth poses a limit on plume spacing and plume number. We demonstrate from both scaling analyses and numerical experiments that the scaling exponents for plume number, n, heat flux, β, and average velocity on the bottom boundary, v, satisfy n= 4β- 2v. Our scaling analyses also suggest that vertical velocity in upwelling plumes Vup~Ra2(1-n+β/2)/3 and that plume radius Rup~Ra(β-1-n/2)/3, which differ from the scalings for the bottom boundary velocity and boundary layer thickness.
Statistics of initial density perturbations in heavy ion collisions and their fluid dynamic response
NASA Astrophysics Data System (ADS)
Floerchinger, Stefan; Wiedemann, Urs Achim
2014-08-01
An interesting opportunity to determine thermodynamic and transport properties in more detail is to identify generic statistical properties of initial density perturbations. Here we study event-by-event fluctuations in terms of correlation functions for two models that can be solved analytically. The first assumes Gaussian fluctuations around a distribution that is fixed by the collision geometry but leads to non-Gaussian features after averaging over the reaction plane orientation at non-zero impact parameter. In this context, we derive a three-parameter extension of the commonly used Bessel-Gaussian event-by-event distribution of harmonic flow coefficients. Secondly, we study a model of N independent point sources for which connected n-point correlation functions of initial perturbations scale like 1 /N n-1. This scaling is violated for non-central collisions in a way that can be characterized by its impact parameter dependence. We discuss to what extent these are generic properties that can be expected to hold for any model of initial conditions, and how this can improve the fluid dynamical analysis of heavy ion collisions.
Baryon spectrum of SU(4) composite Higgs theory with two distinct fermion representations
NASA Astrophysics Data System (ADS)
Ayyar, Venkitesh; DeGrand, Thomas; Hackett, Daniel C.; Jay, William I.; Neil, Ethan T.; Shamir, Yigal; Svetitsky, Benjamin
2018-06-01
We use lattice simulations to compute the baryon spectrum of SU(4) lattice gauge theory coupled to dynamical fermions in the fundamental and two-index antisymmetric (sextet) representations simultaneously. This model is closely related to a composite Higgs model in which the chimera baryon made up of fermions from both representations plays the role of a composite top-quark partner. The dependence of the baryon masses on each underlying fermion mass is found to be generally consistent with a quark-model description and large-Nc scaling. We combine our numerical results with experimental bounds on the scale of the new strong sector to estimate a lower bound on the mass of the top-quark partner. We discuss some theoretical uncertainties associated with this estimate.
Resolution dependence of cross-tropopause ozone transport over east Asia
NASA Astrophysics Data System (ADS)
Büker, M. L.; Hitchman, Matthew H.; Tripoli, Gregory J.; Pierce, R. B.; Browell, E. V.; Avery, M. A.
2005-02-01
Detailed analysis of mesoscale transport of ozone across the tropopause over east Asia during the spring of 2001 is conducted using regional simulations with the University of Wisconsin Nonhydrostatic Modeling System (UWNMS), in situ flight data, and a new two-scale approach to diagnosing this ozone flux. From late February to early April, synoptic activity regularly deformed the tropopause, leading to observations of ozone-rich (concentration exceeding 80 ppbv) stratospheric intrusions and filaments at tropospheric altitudes. Since model resolution is generally not sufficient to capture detailed small-scale mixing processes, an upper bound on the flux is proposed by assuming that there exists a dynamical division by spatial scale, above which the wind conservatively advects large-scale structures, while below it the wind leads to irreversible transport through nonconservative random strain. A formulation for this diagnosis is given and applied to ozone flux across the dynamical tropopause. Simulations were chosen to correspond with DC-8 flight 15 on 26-27 March over east Asia during the Transport and Chemical Evolution Over the Pacific (TRACE-P) campaign. Local and domain-averaged flux values using this method agree with other numerical and observational studies in similar synoptic environments. Sensitivity to numerical resolution, prescribed divisional spatial scale, and potential vorticity (PV) level is investigated. Divergent residual flow in regions of high ozone, and PV gradients tended to maximize flux magnitudes. We estimated the domain-integrated flow of ozone out of the lowermost stratosphere to be about 0.127 Tg/day. Spectral analysis of the wind field lends support for utilization of this dynamical division in this methodology.
Multi-scale Modeling of Chromosomal DNA in Living Cells
NASA Astrophysics Data System (ADS)
Spakowitz, Andrew
The organization and dynamics of chromosomal DNA play a pivotal role in a range of biological processes, including gene regulation, homologous recombination, replication, and segregation. Establishing a quantitative theoretical model of DNA organization and dynamics would be valuable in bridging the gap between the molecular-level packaging of DNA and genome-scale chromosomal processes. Our research group utilizes analytical theory and computational modeling to establish a predictive theoretical model of chromosomal organization and dynamics. In this talk, I will discuss our efforts to develop multi-scale polymer models of chromosomal DNA that are both sufficiently detailed to address specific protein-DNA interactions while capturing experimentally relevant time and length scales. I will demonstrate how these modeling efforts are capable of quantitatively capturing aspects of behavior of chromosomal DNA in both prokaryotic and eukaryotic cells. This talk will illustrate that capturing dynamical behavior of chromosomal DNA at various length scales necessitates a range of theoretical treatments that accommodate the critical physical contributions that are relevant to in vivo behavior at these disparate length and time scales. National Science Foundation, Physics of Living Systems Program (PHY-1305516).
Xiao, Min; Zheng, Wei Xing; Cao, Jinde
2013-01-01
Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.
Critical carbon input to maintain current soil organic carbon stocks in global wheat systems
Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing
2016-01-01
Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha−1 yr−1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content. PMID:26759192
Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems
NASA Astrophysics Data System (ADS)
Wang, G.
2017-12-01
Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.
Preliminary design, analysis, and costing of a dynamic scale model of the NASA space station
NASA Technical Reports Server (NTRS)
Gronet, M. J.; Pinson, E. D.; Voqui, H. L.; Crawley, E. F.; Everman, M. R.
1987-01-01
The difficulty of testing the next generation of large flexible space structures on the ground places an emphasis on other means for validating predicted on-orbit dynamic behavior. Scale model technology represents one way of verifying analytical predictions with ground test data. This study investigates the preliminary design, scaling and cost trades for a Space Station dynamic scale model. The scaling of nonlinear joint behavior is studied from theoretical and practical points of view. Suspension system interaction trades are conducted for the ISS Dual Keel Configuration and Build-Up Stages suspended in the proposed NASA/LaRC Large Spacecraft Laboratory. Key issues addressed are scaling laws, replication vs. simulation of components, manufacturing, suspension interactions, joint behavior, damping, articulation capability, and cost. These issues are the subject of parametric trades versus the scale model factor. The results of these detailed analyses are used to recommend scale factors for four different scale model options, each with varying degrees of replication. Potential problems in constructing and testing the scale model are identified, and recommendations for further study are outlined.
Modulation of Temporal Precision in Thalamic Population Responses to Natural Visual Stimuli
Desbordes, Gaëlle; Jin, Jianzhong; Alonso, Jose-Manuel; Stanley, Garrett B.
2010-01-01
Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise – on a time scale of 10–25 ms – both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment. PMID:21151356
Phase Transitions in Geomorphology
NASA Astrophysics Data System (ADS)
Ortiz, C. P.; Jerolmack, D. J.
2015-12-01
Landscapes are patterns in a dynamic steady-state, due to competing processes that smooth or sharpen features over large distances and times. Geomorphic transport laws have been developed to model the mass-flux due to different processes, but are unreasonably effective at recovering the scaling relations of landscape features. Using a continuum approximation to compare experimental landscapes and the observed landscapes of the earth, one finds they share similar morphodynamics despite a breakdown of classical dynamical similarity between the two. We propose the origin of this effectiveness is a different kind of dynamic similarity in the statistics of initiation and cessation of motion of groups of grains, which is common to disordered systems of grains under external driving. We will show how the existing data of sediment transport points to common signatures with dynamical phase transitions between "mobile" and "immobile" phases in other disordered systems, particularly granular materials, colloids, and foams. Viewing landscape evolution from the lens of non-equilibrium statistical physics of disordered systems leads to predictions that the transition of bulk measurements such as particle flux is continuous from one phase to another, that the collective nature of the particle dynamics leads to very slow aging of bulk properties, and that the dynamics are history-dependent. Recent results from sediment transport experiments support these predictions, suggesting that existing geomorphic transport laws may need to be replaced by a new generation of stochastic models with ingredients based on the physics of disordered phase transitions. We discuss possible strategies for extracting the necessary information to develop these models from measurements of geomorphic transport noise by connecting particle-scale collective dynamics and space-time fluctuations over landscape features.
The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain.
Olbrich, Eckehard; Claussen, Jens Christian; Achermann, Peter
2011-10-13
A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.
Nonconservative dynamics in long atomic wires
NASA Astrophysics Data System (ADS)
Cunningham, Brian; Todorov, Tchavdar N.; Dundas, Daniel
2014-09-01
The effect of nonconservative current-induced forces on the ions in a defect-free metallic nanowire is investigated using both steady-state calculations and dynamical simulations. Nonconservative forces were found to have a major influence on the ion dynamics in these systems, but their role in increasing the kinetic energy of the ions decreases with increasing system length. The results illustrate the importance of nonconservative effects in short nanowires and the scaling of these effects with system size. The dependence on bias and ion mass can be understood with the help of a simple pen and paper model. This material highlights the benefit of simple preliminary steady-state calculations in anticipating aspects of brute-force dynamical simulations, and provides rule of thumb criteria for the design of stable quantum wires.
A dynamic multi-scale Markov model based methodology for remaining life prediction
NASA Astrophysics Data System (ADS)
Yan, Jihong; Guo, Chaozhong; Wang, Xing
2011-05-01
The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.
NASA Astrophysics Data System (ADS)
Köhler, T.; Schumann, O.; Biebl, F.; Kramer, S.; Kehrein, S.; Manmana, S.; Rajpurohit, S.; Sotoudeh, M.; Blöchl, P.
We investigate 1D correlated systems following a photoexcitation by combining ab-initio methods, time-dependent matrix product state (MPS) approaches, analytical insights from linearized quantum Boltzmann equations (LBE), and molecular dynamics (MD) simulations to describe the dynamics on different time scales ranging from femto- up to nanoseconds. This is done for manganite systems in the material class Pr1-xCaxMnO3. We derive 1D ab-initio model Hamiltonians for which we compute the ground states at different values of the doping using MD simulations. At half doping, we obtain a magnetic microstructure of alternating dimers from which we derive a 1D Hubbard-type model. The dynamics is analyzed concerning the formation and lifetime of such quasiparticles via a LBE. We find that the magnetic microstructure strongly enhances the lifetime of the excitations. In this way, our work constitutes a first step to building a unifying theoretical framework for the description of photoexcitations in strongly correlated materials over a wide range of time scales, capable of making predictions for ongoing experiments investigating pump-probe situations and unconventional photovoltaics. Financial support from the Deutsche Forschungsgemeinschaft (DFG) through SFB/CRC1073 (Projects B03 and C03) is gratefully acknowledged.
Molecular dynamics of conformational substates for a simplified protein model
NASA Astrophysics Data System (ADS)
Grubmüller, Helmut; Tavan, Paul
1994-09-01
Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.
Why many polymers are so fragile: A new perspective
Dalle-Ferrier, C.; Kisliuk, A.; Hong, L.; ...
2016-10-21
Many polymers exhibit much steeper temperature dependence of their structural relaxation time (higher fragility) than liquids of small molecules, and the mechanism of this unusually high fragility in polymers remains a puzzle. To reveal additional hints for understanding the underlying mechanism, we analyzed correlation of many properties of polymers to their fragility on example of model polymer polystyrene with various molecular weights (MWs). Here, we demonstrate that these correlations work for short chains (oligomers), but fail progressively with increase in MW. Our surprising discovery is that the steepness of the temperature dependence (fragility) of the viscosity that is determined bymore » chain relaxation follows the correlations at all molecular weights. These results suggest that the molecular level relaxation still follows the behavior usual for small molecules even in polymers, and its fragility (chain fragility) falls in the range usual for molecular liquids. It is the segmental relaxation that has this unusually high fragility. We also speculate that many polymers cannot reach an ergodic state on the time scale of segmental dynamics due to chain connectivity and rigidity. This leads to sharper decrease in accessible configurational entropy upon cooling and results in steeper temperature dependence of segmental relaxation. Our proposed scenario provides a new important insight into the specifics of polymer dynamics: the role of ergodicity time and length scale. At the end, we suggest that a similar scenario can be applicable also to other molecular systems with slow intra-molecular degrees of freedom and to chemically complex systems where the time scale of chemical fluctuations can be longer than the time scale of structural relaxation.« less
Why many polymers are so fragile: A new perspective
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dalle-Ferrier, C.; Kisliuk, A.; Hong, L.
Many polymers exhibit much steeper temperature dependence of their structural relaxation time (higher fragility) than liquids of small molecules, and the mechanism of this unusually high fragility in polymers remains a puzzle. To reveal additional hints for understanding the underlying mechanism, we analyzed correlation of many properties of polymers to their fragility on example of model polymer polystyrene with various molecular weights (MWs). Here, we demonstrate that these correlations work for short chains (oligomers), but fail progressively with increase in MW. Our surprising discovery is that the steepness of the temperature dependence (fragility) of the viscosity that is determined bymore » chain relaxation follows the correlations at all molecular weights. These results suggest that the molecular level relaxation still follows the behavior usual for small molecules even in polymers, and its fragility (chain fragility) falls in the range usual for molecular liquids. It is the segmental relaxation that has this unusually high fragility. We also speculate that many polymers cannot reach an ergodic state on the time scale of segmental dynamics due to chain connectivity and rigidity. This leads to sharper decrease in accessible configurational entropy upon cooling and results in steeper temperature dependence of segmental relaxation. Our proposed scenario provides a new important insight into the specifics of polymer dynamics: the role of ergodicity time and length scale. At the end, we suggest that a similar scenario can be applicable also to other molecular systems with slow intra-molecular degrees of freedom and to chemically complex systems where the time scale of chemical fluctuations can be longer than the time scale of structural relaxation.« less
A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS
Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...
Thermomechanical Properties and Glass Dynamics of Polymer-Tethered Colloidal Particles and Films
2017-01-01
Polymer-tethered colloidal particles (aka “particle brush materials”) have attracted interest as a platform for innovative material technologies and as a model system to elucidate glass formation in complex structured media. In this contribution, Brillouin light scattering is used to sequentially evaluate the role of brush architecture on the dynamical properties of brush particles in both the individual and assembled (film) state. In the former state, the analysis reveals that brush–brush interactions as well as global chain relaxation sensitively depend on grafting density; i.e., more polymer-like behavior is observed in sparse brush systems. This is interpreted to be a consequence of more extensive chain entanglement. In contrast, the local relaxation of films does not depend on grafting density. The results highlight that relaxation processes in particle brush-based materials span a wider range of time and length scales as compared to linear chain polymers. Differentiation between relaxation on local and global scale is necessary to reveal the influence of molecular structure and connectivity on the aging behavior of these complex systems. PMID:29755139
Thermomechanical Properties and Glass Dynamics of Polymer-Tethered Colloidal Particles and Films.
Cang, Yu; Reuss, Anna N; Lee, Jaejun; Yan, Jiajun; Zhang, Jianan; Alonso-Redondo, Elena; Sainidou, Rebecca; Rembert, Pascal; Matyjaszewski, Krzysztof; Bockstaller, Michael R; Fytas, George
2017-11-14
Polymer-tethered colloidal particles (aka "particle brush materials") have attracted interest as a platform for innovative material technologies and as a model system to elucidate glass formation in complex structured media. In this contribution, Brillouin light scattering is used to sequentially evaluate the role of brush architecture on the dynamical properties of brush particles in both the individual and assembled (film) state. In the former state, the analysis reveals that brush-brush interactions as well as global chain relaxation sensitively depend on grafting density; i.e., more polymer-like behavior is observed in sparse brush systems. This is interpreted to be a consequence of more extensive chain entanglement. In contrast, the local relaxation of films does not depend on grafting density. The results highlight that relaxation processes in particle brush-based materials span a wider range of time and length scales as compared to linear chain polymers. Differentiation between relaxation on local and global scale is necessary to reveal the influence of molecular structure and connectivity on the aging behavior of these complex systems.
Power suppression at large scales in string inflation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cicoli, Michele; Downes, Sean; Dutta, Bhaskar, E-mail: mcicoli@ictp.it, E-mail: sddownes@physics.tamu.edu, E-mail: dutta@physics.tamu.edu
2013-12-01
We study a possible origin of the anomalous suppression of the power spectrum at large angular scales in the cosmic microwave background within the framework of explicit string inflationary models where inflation is driven by a closed string modulus parameterizing the size of the extra dimensions. In this class of models the apparent power loss at large scales is caused by the background dynamics which involves a sharp transition from a fast-roll power law phase to a period of Starobinsky-like slow-roll inflation. An interesting feature of this class of string inflationary models is that the number of e-foldings of inflationmore » is inversely proportional to the string coupling to a positive power. Therefore once the string coupling is tuned to small values in order to trust string perturbation theory, enough e-foldings of inflation are automatically obtained without the need of extra tuning. Moreover, in the less tuned cases the sharp transition responsible for the power loss takes place just before the last 50-60 e-foldings of inflation. We illustrate these general claims in the case of Fibre Inflation where we study the strength of this transition in terms of the attractor dynamics, finding that it induces a pivot from a blue to a redshifted power spectrum which can explain the apparent large scale power loss. We compute the effects of this pivot for example cases and demonstrate how magnitude and duration of this effect depend on model parameters.« less
Power suppression at large scales in string inflation
NASA Astrophysics Data System (ADS)
Cicoli, Michele; Downes, Sean; Dutta, Bhaskar
2013-12-01
We study a possible origin of the anomalous suppression of the power spectrum at large angular scales in the cosmic microwave background within the framework of explicit string inflationary models where inflation is driven by a closed string modulus parameterizing the size of the extra dimensions. In this class of models the apparent power loss at large scales is caused by the background dynamics which involves a sharp transition from a fast-roll power law phase to a period of Starobinsky-like slow-roll inflation. An interesting feature of this class of string inflationary models is that the number of e-foldings of inflation is inversely proportional to the string coupling to a positive power. Therefore once the string coupling is tuned to small values in order to trust string perturbation theory, enough e-foldings of inflation are automatically obtained without the need of extra tuning. Moreover, in the less tuned cases the sharp transition responsible for the power loss takes place just before the last 50-60 e-foldings of inflation. We illustrate these general claims in the case of Fibre Inflation where we study the strength of this transition in terms of the attractor dynamics, finding that it induces a pivot from a blue to a redshifted power spectrum which can explain the apparent large scale power loss. We compute the effects of this pivot for example cases and demonstrate how magnitude and duration of this effect depend on model parameters.
Dynamic Scaling of Colloidal Gel Formation at Intermediate Concentrations
Zhang, Qingteng; Bahadur, Divya; Dufresne, Eric M.; ...
2017-10-25
Here, we have examined the formation and dissolution of gels composed of intermediate volume-fraction nanoparticles with temperature-dependent short-range attractions using small-angle x-ray scatter- ing (SAXS), x-ray photon correlation spectroscopy (XPCS), and rheology to obtain nanoscale and macroscale sensitivity to structure and dynamics. Gel formation after temperature quenches to the vicinity of the rheologically-determined gel temperature, T gel, was characterized via the slow-down of dynamics and changes in microstructure observed in the intensity autocorrelation functions and structure factor, respectively, as a function of quench depth (ΔT = T quench - T gel), wave vector, and formation time (t f). We findmore » similar patterns in the slow-down of dynamics that maps the wave-vector-dependent dynamics at a particular ΔT and t f to that at other ΔTs and t fs via an effective scaling temperature, Ts. A single Ts applies to a broad range of ΔT and tf but does depend on the particle size. The rate of formation implied by the scaling is a far stronger function of ΔT than that of the attraction strength between colloids. Finally, we interpret this strong temperature de- pendence in terms of changes in cooperative bonding required to form stable, energetically favored, local structures.« less
Dynamic Scaling of Colloidal Gel Formation at Intermediate Concentrations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Qingteng; Bahadur, Divya; Dufresne, Eric M.
Here, we have examined the formation and dissolution of gels composed of intermediate volume-fraction nanoparticles with temperature-dependent short-range attractions using small-angle x-ray scatter- ing (SAXS), x-ray photon correlation spectroscopy (XPCS), and rheology to obtain nanoscale and macroscale sensitivity to structure and dynamics. Gel formation after temperature quenches to the vicinity of the rheologically-determined gel temperature, T gel, was characterized via the slow-down of dynamics and changes in microstructure observed in the intensity autocorrelation functions and structure factor, respectively, as a function of quench depth (ΔT = T quench - T gel), wave vector, and formation time (t f). We findmore » similar patterns in the slow-down of dynamics that maps the wave-vector-dependent dynamics at a particular ΔT and t f to that at other ΔTs and t fs via an effective scaling temperature, Ts. A single Ts applies to a broad range of ΔT and tf but does depend on the particle size. The rate of formation implied by the scaling is a far stronger function of ΔT than that of the attraction strength between colloids. Finally, we interpret this strong temperature de- pendence in terms of changes in cooperative bonding required to form stable, energetically favored, local structures.« less
The fluid dynamics of atmospheric clouds
NASA Astrophysics Data System (ADS)
Randall, David A.
2017-11-01
Clouds of many types are of leading-order importance for Earth's weather and climate. This importance is most often discussed in terms of the effects of clouds on radiative transfer, but the fluid dynamics of clouds are at least equally significant. Some very small-scale cloud fluid-dynamical processes have significant consequences on the global scale. These include viscous dissipation near falling rain drops, and ``buoyancy reversal'' associated with the evaporation of liquid water. Major medium-scale cloud fluid-dynamical processes include cumulus convection and convective aggregation. Planetary-scale processes that depend in an essential way on cloud fluid dynamics include the Madden-Julian Oscillation, which is one of the largest and most consequential weather systems on Earth. I will attempt to give a coherent introductory overview of this broad range of phenomena.
Modeling and numerical simulations of the influenced Sznajd model
NASA Astrophysics Data System (ADS)
Karan, Farshad Salimi Naneh; Srinivasan, Aravinda Ramakrishnan; Chakraborty, Subhadeep
2017-08-01
This paper investigates the effects of independent nonconformists or influencers on the behavioral dynamic of a population of agents interacting with each other based on the Sznajd model. The system is modeled on a complete graph using the master equation. The acquired equation has been numerically solved. Accuracy of the mathematical model and its corresponding assumptions have been validated by numerical simulations. Regions of initial magnetization have been found from where the system converges to one of two unique steady-state PDFs, depending on the distribution of influencers. The scaling property and entropy of the stationary system in presence of varying level of influence have been presented and discussed.
Modeling and numerical simulations of the influenced Sznajd model.
Karan, Farshad Salimi Naneh; Srinivasan, Aravinda Ramakrishnan; Chakraborty, Subhadeep
2017-08-01
This paper investigates the effects of independent nonconformists or influencers on the behavioral dynamic of a population of agents interacting with each other based on the Sznajd model. The system is modeled on a complete graph using the master equation. The acquired equation has been numerically solved. Accuracy of the mathematical model and its corresponding assumptions have been validated by numerical simulations. Regions of initial magnetization have been found from where the system converges to one of two unique steady-state PDFs, depending on the distribution of influencers. The scaling property and entropy of the stationary system in presence of varying level of influence have been presented and discussed.
Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.
Jepsen, Jane U; Hagen, Snorre B; Karlsen, Stein-Rune; Ims, Rolf A
2009-12-07
Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.
Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology
Jepsen, Jane U.; Hagen, Snorre B.; Karlsen, Stein-Rune; Ims, Rolf A.
2009-01-01
Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000–2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks. PMID:19740876
Driving terrestrial ecosystem models from space
NASA Technical Reports Server (NTRS)
Waring, R. H.
1993-01-01
Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.
Computational fluid dynamics modelling in cardiovascular medicine
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019
Kang, Chang-kwon; Shyy, Wei
2014-01-01
In the analysis of flexible flapping wings of insects, the aerodynamic outcome depends on the combined structural dynamics and unsteady fluid physics. Because the wing shape and hence the resulting effective angle of attack are a priori unknown, predicting aerodynamic performance is challenging. Here, we show that a coupled aerodynamics/structural dynamics model can be established for hovering, based on a linear beam equation with the Morison equation to account for both added mass and aerodynamic damping effects. Lift strongly depends on the instantaneous angle of attack, resulting from passive pitch associated with wing deformation. We show that both instantaneous wing deformation and lift can be predicted in a much simplified framework. Moreover, our analysis suggests that resulting wing kinematics can be explained by the interplay between acceleration-related and aerodynamic damping forces. Interestingly, while both forces combine to create a high angle of attack resulting in high lift around the midstroke, they offset each other for phase control at the end of the stroke. PMID:25297319
NASA Astrophysics Data System (ADS)
Levashov, Valentin A.; Morris, James R.; Egami, Takeshi
2012-02-01
Temporal and spatial correlations among the local atomic level shear stresses were studied for a model liquid iron by molecular dynamics simulation [PRL 106,115703]. Integration over time and space of the shear stress correlation function F(r,t) yields viscosity via Green-Kubo relation. The stress correlation function in time and space F(r,t) was Fourier transformed to study the dependence on frequency, E, and wave vector, Q. The results, F(Q,E), showed damped shear stress waves propagating in the liquid for small Q at high and low temperatures. We also observed additional diffuse feature that appears as temperature is reduced below crossover temperature of potential energy landscape at relatively low frequencies at small Q. We suggest that this additional feature might be related to dynamic heterogeneity and boson peaks. We also discuss a relation between the time-scale of the stress-stress correlation function and the alpha-relaxation time of the intermediate self-scattering function S(Q,E).
Dynamic molecular confinement in the plasma membrane by microdomains and the cytoskeleton meshwork
Lenne, Pierre-François; Wawrezinieck, Laure; Conchonaud, Fabien; Wurtz, Olivier; Boned, Annie; Guo, Xiao-Jun; Rigneault, Hervé; He, Hai-Tao; Marguet, Didier
2006-01-01
It is by now widely recognized that cell membranes show complex patterns of lateral organization. Two mechanisms involving either a lipid-dependent (microdomain model) or cytoskeleton-based (meshwork model) process are thought to be responsible for these plasma membrane organizations. In the present study, fluorescence correlation spectroscopy measurements on various spatial scales were performed in order to directly identify and characterize these two processes in live cells with a high temporal resolution, without any loss of spatial information. Putative raft markers were found to be dynamically compartmented within tens of milliseconds into small microdomains (∅<120 nm) that are sensitive to the cholesterol and sphingomyelin levels, whereas actin-based cytoskeleton barriers are responsible for the confinement of the transferrin receptor protein. A free-like diffusion was observed when both the lipid-dependent and cytoskeleton-based organizations were disrupted, which suggests that these are two main compartmentalizing forces at work in the plasma membrane. PMID:16858413
Lubricant Rheology in Concentrated Contacts
NASA Technical Reports Server (NTRS)
Jacobson, B. O.
1984-01-01
Lubricant behavior in highly stressed situtations shows that a Newtonian model for lubricant rheology is insufficient for explanation of traction behavior. The oil film build up is predicted by using a Newtonian lubricant model except at high slide to roll ratios and at very high loads, where the nonNewtonian behavior starts to be important already outside the Hertzian contact area. Static and dynamic experiments are reported. In static experiments the pressure is applied to the lubricant more than a million times longer than in an EHD contact. Depending on the pressure-temperature history of the experiment the lubricant will become a crystallized or amorphous solid at high pressures. In dynamic experiments, the oil is in an amorphous solid state. Depending on the viscosity, time scale, elasticity of the oil and the bearing surfaces, the oil film pressure, shear strain rate and the type of lubricant, different properties of the oil are important for prediction of shear stresses in the oil. The different proposed models for the lubricant, which describe it to a Newtonian liquid, an elastic liquid, a plastic liquid and an elastic-plastic solid.
Scale-dependent erosional patterns in steady-state and transient-state landscapes.
Tejedor, Alejandro; Singh, Arvind; Zaliapin, Ilya; Densmore, Alexander L; Foufoula-Georgiou, Efi
2017-09-01
Landscape topography is the expression of the dynamic equilibrium between external forcings (for example, climate and tectonics) and the underlying lithology. The magnitude and spatial arrangement of erosional and depositional fluxes dictate the evolution of landforms during both statistical steady state (SS) and transient state (TS) of major landscape reorganization. For SS landscapes, the common expectation is that any point of the landscape has an equal chance to erode below or above the landscape median erosion rate. We show that this is not the case. Afforded by a unique experimental landscape that provided a detailed space-time recording of erosional fluxes and by defining the so-called E50-area curve, we reveal for the first time that there exists a hierarchical pattern of erosion. Specifically, hillslopes and fluvial channels erode more rapidly than the landscape median erosion rate, whereas intervening parts of the landscape in terms of upstream contributing areas (colluvial regime) erode more slowly. We explain this apparent paradox by documenting the dynamic nature of SS landscapes-landscape locations may transition from being a hillslope to being a valley and then to being a fluvial channel due to ridge migration, channel piracy, and small-scale landscape dynamics through time. Under TS conditions caused by increased precipitation, we show that the E50-area curve drastically changes shape during landscape reorganization. Scale-dependent erosional patterns, as observed in this study, suggest benchmarks in evaluating numerical models and interpreting the variability of sampled erosional rates in field landscapes.
Scale-dependent erosional patterns in steady-state and transient-state landscapes
Tejedor, Alejandro; Singh, Arvind; Zaliapin, Ilya; Densmore, Alexander L.; Foufoula-Georgiou, Efi
2017-01-01
Landscape topography is the expression of the dynamic equilibrium between external forcings (for example, climate and tectonics) and the underlying lithology. The magnitude and spatial arrangement of erosional and depositional fluxes dictate the evolution of landforms during both statistical steady state (SS) and transient state (TS) of major landscape reorganization. For SS landscapes, the common expectation is that any point of the landscape has an equal chance to erode below or above the landscape median erosion rate. We show that this is not the case. Afforded by a unique experimental landscape that provided a detailed space-time recording of erosional fluxes and by defining the so-called E50-area curve, we reveal for the first time that there exists a hierarchical pattern of erosion. Specifically, hillslopes and fluvial channels erode more rapidly than the landscape median erosion rate, whereas intervening parts of the landscape in terms of upstream contributing areas (colluvial regime) erode more slowly. We explain this apparent paradox by documenting the dynamic nature of SS landscapes—landscape locations may transition from being a hillslope to being a valley and then to being a fluvial channel due to ridge migration, channel piracy, and small-scale landscape dynamics through time. Under TS conditions caused by increased precipitation, we show that the E50-area curve drastically changes shape during landscape reorganization. Scale-dependent erosional patterns, as observed in this study, suggest benchmarks in evaluating numerical models and interpreting the variability of sampled erosional rates in field landscapes. PMID:28959728
Dynamics of flow control in an emulated boundary layer-ingesting offset diffuser
NASA Astrophysics Data System (ADS)
Gissen, A. N.; Vukasinovic, B.; Glezer, A.
2014-08-01
Dynamics of flow control comprised of arrays of active (synthetic jets) and passive (vanes) control elements , and its effectiveness for suppression of total-pressure distortion is investigated experimentally in an offset diffuser, in the absence of internal flow separation. The experiments are conducted in a wind tunnel inlet model at speeds up to M = 0.55 using approach flow conditioning that mimics boundary layer ingestion on a Blended-Wing-Body platform. Time-dependent distortion of the dynamic total-pressure field at the `engine face' is measured using an array of forty total-pressure probes, and the control-induced distortion changes are analyzed using triple decomposition and proper orthogonal decomposition (POD). These data indicate that an array of the flow control small-scale synthetic jet vortices merge into two large-scale, counter-rotating streamwise vortices that exert significant changes in the flow distortion. The two most energetic POD modes appear to govern the distortion dynamics in either active or hybrid flow control approaches. Finally, it is shown that the present control approach is sufficiently robust to reduce distortion with different inlet conditions of the baseline flow.
Dark energy in the three-body problem: Wide triple galaxies
NASA Astrophysics Data System (ADS)
Emel'yanov, N. V.; Kovalev, M. Yu.; Chernin, A. D.
2016-04-01
The structure and evolution of triple galaxy systems in the presence of the cosmic dark-energy background is studied in the framework of the three-body problem. The dynamics of wide triple systems are determinedmainly by the competition between the mutual gravitational forces between the three bodies and the anti-gravity created by the dark-energy background. This problem can be solved via numerical integration of the equations of motion with initial conditions that admit various types of evolutionary behavior of the system. Such dynamical models show that the anti-gravity created by dark energy makes a triple system less tightly bound, thereby facilitating its decay, with a subsequent transition to motion of the bodies away from each other in an accelerating regime with a linear Hubble-law dependence of the velocity on distance. The coefficient of proportionality between the velocity and distance in this asymptotic relation corresponds to the universal value H Λ = 61 km s-1 Mpc-1, which depends only on the dark-energy density. The similarity of this relation to the large-scale recession of galaxies indicates that double and triple galaxies represent elementary dynamical cells realizing the overall behavior of a system dominated by dark energy on their own scale, independent of their masses and dimensions.
Landing impact studies of a 0.3-scale model air cushion landing system for a Navy fighter airplane
NASA Technical Reports Server (NTRS)
Leland, T. J. W.; Thompson, W. C.
1975-01-01
An experimental study was conducted in order to determine the landing-impact behavior of a 0.3-scale, dynamically (but not physically) similar model of a high-density Navy fighter equipped with an air cushion landing system. The model was tested over a range of landing contact attitudes at high forward speeds and sink rates on a specialized test fixture at the Langley aircraft landing loads and traction facility. The investigation indicated that vertical acceleration at landing impact was highly dependent on the pitch angle at ground contact, the higher acceleration of approximately 5g occurring near zero body-pitch attitude. A limited number of low-speed taxi tests were made in order to determine model stability characteristics. The model was found to have good pitch-damping characteristics but stability in roll was marginal.
Where do we stand after twenty years of dynamic triggering studies? (Invited)
NASA Astrophysics Data System (ADS)
Prejean, S. G.; Hill, D. P.
2013-12-01
In the past two decades, remote dynamic triggering of earthquakes by other earthquakes has been explored in a variety of physical environments with a wide array of observation and modeling techniques. These studies have significantly refined our understanding of the state of the crust and the physical conditions controlling earthquake nucleation. Despite an ever growing database of dynamic triggering observations, significant uncertainties remain and vigorous debate in almost all aspects of the science continues. For example, although dynamic earthquake triggering can occur with peak dynamic stresses as small as 1 kPa, triggering thresholds and their dependence on local stress state, hydrological environment, and frictional properties of faults are not well understood. Some studies find a simple threshold based on the peak amplitude of shaking while others find dependencies on frequency, recharge time, and other parameters. Considerable debate remains over the range of physical processes responsible for dynamic triggering, and the wide variation in dynamic triggering responses and time scales suggests triggering by multiple physical processes. Although Coulomb shear failure with various friction laws can often explain dynamic triggering, particularly instantaneous triggering, delayed dynamic triggering may be dependent on fluid transport and other slowly evolving aseismic processes. Although our understanding of the global distribution of dynamic triggering has improved, it is far from complete due to spatially uneven monitoring. A major challenge involves establishing statistical significance of potentially triggered earthquakes, particularly if they are isolated events or time-delayed with respect to triggering stresses. Here we highlight these challenges and opportunities with existing data. We focus on environmental dependence of dynamic triggering by large remote earthquakes particularly in volcanic and geothermal systems, as these systems often have high rates of background seismicity. In many volcanic and geothermal systems, such as the Geysers in Northern California, dynamic triggering of micro-earthquakes is frequent and predictable. In contrast, most active and even erupting volcanoes in Alaska (with the exception of the Katmai Volcanic Cluster) do not experience dynamic triggering. We explore why.
The many faces of graph dynamics
NASA Astrophysics Data System (ADS)
Pignolet, Yvonne Anne; Roy, Matthieu; Schmid, Stefan; Tredan, Gilles
2017-06-01
The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is known today about the network dynamics: indeed, complex networks in reality are not static, but rather dynamically evolve over time. Our paper is motivated by the empirical observation that network evolution patterns seem far from random, but exhibit structure. Moreover, the specific patterns appear to depend on the network type, contradicting the existence of a ‘one fits it all’ model. However, we still lack observables to quantify these intuitions, as well as metrics to compare graph evolutions. Such observables and metrics are needed for extrapolating or predicting evolutions, as well as for interpolating graph evolutions. To explore the many faces of graph dynamics and to quantify temporal changes, this paper suggests to build upon the concept of centrality, a measure of node importance in a network. In particular, we introduce the notion of centrality distance, a natural similarity measure for two graphs which depends on a given centrality, characterizing the graph type. Intuitively, centrality distances reflect the extent to which (non-anonymous) node roles are different or, in case of dynamic graphs, have changed over time, between two graphs. We evaluate the centrality distance approach for five evolutionary models and seven real-world social and physical networks. Our results empirically show the usefulness of centrality distances for characterizing graph dynamics compared to a null-model of random evolution, and highlight the differences between the considered scenarios. Interestingly, our approach allows us to compare the dynamics of very different networks, in terms of scale and evolution speed.
NASA Astrophysics Data System (ADS)
Park, DaeKil
2018-06-01
The dynamics of entanglement and uncertainty relation is explored by solving the time-dependent Schrödinger equation for coupled harmonic oscillator system analytically when the angular frequencies and coupling constant are arbitrarily time dependent. We derive the spectral and Schmidt decompositions for vacuum solution. Using the decompositions, we derive the analytical expressions for von Neumann and Rényi entropies. Making use of Wigner distribution function defined in phase space, we derive the time dependence of position-momentum uncertainty relations. To show the dynamics of entanglement and uncertainty relation graphically, we introduce two toy models and one realistic quenched model. While the dynamics can be conjectured by simple consideration in the toy models, the dynamics in the realistic quenched model is somewhat different from that in the toy models. In particular, the dynamics of entanglement exhibits similar pattern to dynamics of uncertainty parameter in the realistic quenched model.
Nonlinear temperature effects on multifractal complexity of metabolic rate of mice
Bogdanovich, Jose M.; Bozinovic, Francisco
2016-01-01
Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO2), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO2) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 102 s), either monofractal or weak multifractal dynamics are observed depending on whether Ta < 15 °C or Ta > 15 °C respectively. For larger time scales, r(VO2) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO2) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system. PMID:27781179
Nonlinear temperature effects on multifractal complexity of metabolic rate of mice.
Labra, Fabio A; Bogdanovich, Jose M; Bozinovic, Francisco
2016-01-01
Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r ( VO 2 ), in the laboratory mouse Mus musculus , assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO 2 ) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 10 2 s), either monofractal or weak multifractal dynamics are observed depending on whether T a < 15 °C or T a > 15 °C respectively. For larger time scales, r(VO 2 ) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ ( q ), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b . We also show that the long-range correlation structure of r(VO 2 ) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zimnyakov, D. A., E-mail: zimnykov@sgu.ru; Sadovoi, A. V.; Vilenskii, M. A.
2009-02-15
Image sequences of the surface of disordered layers of porous medium (paper) obtained under noncoherent and coherent illumination during capillary rise of a liquid are analyzed. As a result, principles that govern the critical behavior of the interface between liquid and gaseous phases during its pinning are established. By a cumulant analysis of speckle-modulated images of the surface and by the statistical analysis of binarized difference images of the surface under noncoherent illumination, it is shown that the macroscopic dynamics of the interface at the stage of pinning is mainly controlled by the power law dependence of the appearance ratemore » of local instabilities (avalanches) of the interface on the critical parameter, whereas the growth dynamics of the local instabilities is controlled by the diffusion of a liquid in a layer and weakly depends on the critical parameter. A phenomenological model is proposed for the macroscopic dynamics of the phase interface for interpreting experimental data. The values of critical indices are determined that characterize the samples under test within this model. These values are compared with the results of numerical simulation for discrete models of directed percolation corresponding to the Kardar-Parisi-Zhang equation.« less
Rubinov, Mikail; Sporns, Olaf; Thivierge, Jean-Philippe; Breakspear, Michael
2011-06-01
Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches) and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect their importance for neuronal information processing.
NASA Astrophysics Data System (ADS)
Ellis, Matthew O. A.; Stamenova, Maria; Sanvito, Stefano
2017-12-01
There exists a significant challenge in developing efficient magnetic tunnel junctions with low write currents for nonvolatile memory devices. With the aim of analyzing potential materials for efficient current-operated magnetic junctions, we have developed a multi-scale methodology combining ab initio calculations of spin-transfer torque with large-scale time-dependent simulations using atomistic spin dynamics. In this work we introduce our multiscale approach, including a discussion on a number of possible schemes for mapping the ab initio spin torques into the spin dynamics. We demonstrate this methodology on a prototype Co/MgO/Co/Cu tunnel junction showing that the spin torques are primarily acting at the interface between the Co free layer and MgO. Using spin dynamics we then calculate the reversal switching times for the free layer and the critical voltages and currents required for such switching. Our work provides an efficient, accurate, and versatile framework for designing novel current-operated magnetic devices, where all the materials details are taken into account.
Application of process tomography in gas-solid fluidised beds in different scales and structures
NASA Astrophysics Data System (ADS)
Wang, H. G.; Che, H. Q.; Ye, J. M.; Tu, Q. Y.; Wu, Z. P.; Yang, W. Q.; Ocone, R.
2018-04-01
Gas-solid fluidised beds are commonly used in particle-related processes, e.g. for coal combustion and gasification in the power industry, and the coating and granulation process in the pharmaceutical industry. Because the operation efficiency depends on the gas-solid flow characteristics, it is necessary to investigate the flow behaviour. This paper is about the application of process tomography, including electrical capacitance tomography (ECT) and microwave tomography (MWT), in multi-scale gas-solid fluidisation processes in the pharmaceutical and power industries. This is the first time that both ECT and MWT have been applied for this purpose in multi-scale and complex structure. To evaluate the sensor design and image reconstruction and to investigate the effects of sensor structure and dimension on the image quality, a normalised sensitivity coefficient is introduced. In the meantime, computational fluid dynamic (CFD) analysis based on a computational particle fluid dynamic (CPFD) model and a two-phase fluid model (TFM) is used. Part of the CPFD-TFM simulation results are compared and validated by experimental results from ECT and/or MWT. By both simulation and experiment, the complex flow hydrodynamic behaviour in different scales is analysed. Time-series capacitance data are analysed both in time and frequency domains to reveal the flow characteristics.
2010-01-01
Background With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. Results We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Conclusions Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics. PMID:20356411
NASA Astrophysics Data System (ADS)
Alawasa, Khaled Mohammad
Voltage-source converters (VSCs) have gained widespread acceptance in modern power systems. The stability and dynamics of power systems involving these devices have recently become salient issues. In the small-signal sense, the dynamics of VSC-based systems is dictated by its incremental output impedance, which is formed by a combination of 'passive' circuit components and 'active' control elements. Control elements such as control parameters, control loops, and control topologies play a significant role in shaping the impedance profile. Depending on the control schemes and strategies used, VSC-based systems can exhibit different incremental impedance dynamics. As the control elements and dynamics are involved in the impedance structure, the frequency-dependent output impedance might have a negative real-part (i.e., a negative resistance). In the grid-connected mode, the negative resistance degrades the system damping and negatively impacts the stability. In high-voltage networks where high-power VSC-based systems are usually employed and where sub-synchronous dynamics usually exist, integrating large VSC-based systems might reduce the overall damping and results in unstable dynamics. The objectives of this thesis are to (1) investigate and analyze the output impedance properties under different control strategies and control functions, (2) identify and characterize the key contributors to the impedance and sub-synchronous damping profiles, and (3) propose mitigation techniques to minimize and eliminate the negative impact associated with integrating VSC-based systems into power systems. Different VSC configurations are considered in this thesis; in particular, the full-scale and partial-scale topologies (doubly fed-induction generators) are addressed. Additionally, the impedance and system damping profiles are studied under two different control strategies: the standard vector control strategy and the recently-developed power synchronization control strategy. Furthermore, this thesis proposes a simple and robust technique for damping the sub-synchronous resonance in a power system.
NASA Astrophysics Data System (ADS)
Lubashevsky, I.; Kanemoto, S.
2010-07-01
A continuous time model for multiagent systems governed by reinforcement learning with scale-free memory is developed. The agents are assumed to act independently of one another in optimizing their choice of possible actions via trial-and-error search. To gain awareness about the action value the agents accumulate in their memory the rewards obtained from taking a specific action at each moment of time. The contribution of the rewards in the past to the agent current perception of action value is described by an integral operator with a power-law kernel. Finally a fractional differential equation governing the system dynamics is obtained. The agents are considered to interact with one another implicitly via the reward of one agent depending on the choice of the other agents. The pairwise interaction model is adopted to describe this effect. As a specific example of systems with non-transitive interactions, a two agent and three agent systems of the rock-paper-scissors type are analyzed in detail, including the stability analysis and numerical simulation. Scale-free memory is demonstrated to cause complex dynamics of the systems at hand. In particular, it is shown that there can be simultaneously two modes of the system instability undergoing subcritical and supercritical bifurcation, with the latter one exhibiting anomalous oscillations with the amplitude and period growing with time. Besides, the instability onset via this supercritical mode may be regarded as “altruism self-organization”. For the three agent system the instability dynamics is found to be rather irregular and can be composed of alternate fragments of oscillations different in their properties.
A New Model for Self-organized Dynamics and Its Flocking Behavior
NASA Astrophysics Data System (ADS)
Motsch, Sebastien; Tadmor, Eitan
2011-09-01
We introduce a model for self-organized dynamics which, we argue, addresses several drawbacks of the celebrated Cucker-Smale (C-S) model. The proposed model does not only take into account the distance between agents, but instead, the influence between agents is scaled in term of their relative distance. Consequently, our model does not involve any explicit dependence on the number of agents; only their geometry in phase space is taken into account. The use of relative distances destroys the symmetry property of the original C-S model, which was the key for the various recent studies of C-S flocking behavior. To this end, we introduce here a new framework to analyze the phenomenon of flocking for a rather general class of dynamical systems, which covers systems with non-symmetric influence matrices. In particular, we analyze the flocking behavior of the proposed model as well as other strongly asymmetric models with "leaders". The methodology presented in this paper, based on the notion of active sets, carries over from the particle to kinetic and hydrodynamic descriptions. In particular, we discuss the hydrodynamic formulation of our proposed model, and prove its unconditional flocking for slowly decaying influence functions.
Multi-scale, multi-model assessment of projected land allocation
NASA Astrophysics Data System (ADS)
Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.
2017-12-01
Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the default LUMIP scenarios to illustrate the uncertainties in projected LULC as a result of difference in downscaling algorithms. Our results show that such uncertainties could propagate to other components in ACME and CESM and lead to significant differences in simulated water and biogeochemical cycles.
Coherence penalty functional: A simple method for adding decoherence in Ehrenfest dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Akimov, Alexey V., E-mail: alexvakimov@gmail.com, E-mail: oleg.prezhdo@rochester.edu; Chemistry Department, Brookhaven National Laboratory, Upton, New York 11973; Long, Run
2014-05-21
We present a new semiclassical approach for description of decoherence in electronically non-adiabatic molecular dynamics. The method is formulated on the grounds of the Ehrenfest dynamics and the Meyer-Miller-Thoss-Stock mapping of the time-dependent Schrödinger equation onto a fully classical Hamiltonian representation. We introduce a coherence penalty functional (CPF) that accounts for decoherence effects by randomizing the wavefunction phase and penalizing development of coherences in regions of strong non-adiabatic coupling. The performance of the method is demonstrated with several model and realistic systems. Compared to other semiclassical methods tested, the CPF method eliminates artificial interference and improves agreement with the fullymore » quantum calculations on the models. When applied to study electron transfer dynamics in the nanoscale systems, the method shows an improved accuracy of the predicted time scales. The simplicity and high computational efficiency of the CPF approach make it a perfect practical candidate for applications in realistic systems.« less
NASTRAN analysis of the 1/8-scale space shuttle dynamic model
NASA Technical Reports Server (NTRS)
Bernstein, M.; Mason, P. W.; Zalesak, J.; Gregory, D. J.; Levy, A.
1973-01-01
The space shuttle configuration has more complex structural dynamic characteristics than previous launch vehicles primarily because of the high model density at low frequencies and the high degree of coupling between the lateral and longitudinal motions. An accurate analytical representation of these characteristics is a primary means for treating structural dynamics problems during the design phase of the shuttle program. The 1/8-scale model program was developed to explore the adequacy of available analytical modeling technology and to provide the means for investigating problems which are more readily treated experimentally. The basic objectives of the 1/8-scale model program are: (1) to provide early verification of analytical modeling procedures on a shuttle-like structure, (2) to demonstrate important vehicle dynamic characteristics of a typical shuttle design, (3) to disclose any previously unanticipated structural dynamic characteristics, and (4) to provide for development and demonstration of cost effective prototype testing procedures.
NASA Astrophysics Data System (ADS)
Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.
This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.
Empirical Investigation of Critical Transitions in Paleoclimate
NASA Astrophysics Data System (ADS)
Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.
2016-12-01
In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1
Dynamic compensation in the central Pacific Ocean
NASA Technical Reports Server (NTRS)
Hinojosa, Juan Homero; Marsh, Bruce D.
1988-01-01
The intermediate-wavelength geoid (lambda similar to 2000 km) and sea-floor topography fields in the central Pacific Ocean were studied in terms of static and dynamic compensation models. Topographic features on the sea-floor with lambda less than 1000 km were found to be compensated both regionally, by the elastic strength of the lithosphere, and locally, by displacing mantle material to reach isostatic adjustment. The larger-scale sea-floor topography and the corresponding geoid anomalies with lambda similar to 2000 km cannot be explained by either local or regional compensation. The topography and the resulting geoid anomaly at this wavelength were modeled by considering the dynamic effects arising from viscous stresses in a layer of fluid with a highly temperature-dependent viscosity for the cases of: (1) surface cooling, and (2) basal heating. In this model, the mechanical properties of the elastic part of the lithosphere were taken into account by considering an activation energy of about 520 kJ/mol in the Arrhenius law for the viscosity. Numerical predictions of the topography, total geoid anomaly, and admittance were obtained, and the results show that the thermal perturbation in the layer, which accounts for the mass deficit, must be located close to the surface to compensate the gravitational effect of the surface deformation. For the case of basal heating, the temperature dependence of viscosity results in a separation of the upper, quasi-rigid lid from the lower mobile fluid, hence inhibiting the development of a compensating thermal perturbation at shallow depths. The results clearly rule out small-scale, upper-mantle convection as the source of these anomalies. Instead, the geophysical observables can be well explained by a shallow, transient thermal perturbation.
NASA Astrophysics Data System (ADS)
Singh, Rakesh; Paul, Ajay; Kumar, Arjun; Kumar, Parveen; Sundriyal, Y. P.
2018-06-01
Source parameters of the small to moderate earthquakes are significant for understanding the dynamic rupture process, the scaling relations of the earthquakes and for assessment of seismic hazard potential of a region. In this study, the source parameters were determined for 58 small to moderate size earthquakes (3.0 ≤ Mw ≤ 5.0) occurred during 2007-2015 in the Garhwal-Kumaun region. The estimated shear wave quality factor (Qβ(f)) values for each station at different frequencies have been applied to eliminate any bias in the determination of source parameters. The Qβ(f) values have been estimated by using coda wave normalization method in the frequency range 1.5-16 Hz. A frequency-dependent S wave quality factor relation is obtained as Qβ(f) = (152.9 ± 7) f(0.82±0.005) by fitting a power-law frequency dependence model for the estimated values over the whole study region. The spectral (low-frequency spectral level and corner frequency) and source (static stress drop, seismic moment, apparent stress and radiated energy) parameters are obtained assuming ω-2 source model. The displacement spectra are corrected for estimated frequency-dependent attenuation, site effect using spectral decay parameter "Kappa". The frequency resolution limit was resolved by quantifying the bias in corner frequencies, stress drop and radiated energy estimates due to finite-bandwidth effect. The data of the region shows shallow focused earthquakes with low stress drop. The estimation of Zúñiga parameter (ε) suggests the partial stress drop mechanism in the region. The observed low stress drop and apparent stress can be explained by partial stress drop and low effective stress model. Presence of subsurface fluid at seismogenic depth certainly manipulates the dynamics of the region. However, the limited event selection may strongly bias the scaling relation even after taking as much as possible precaution in considering effects of finite bandwidth, attenuation and site corrections. Although, the scaling can be improved further with the integration of large dataset of microearthquakes and use of a stable and robust approach.
Environment overwhelms both nature and nurture in a model spin glass
NASA Astrophysics Data System (ADS)
Middleton, A. Alan; Yang, Jie
We are interested in exploring what information determines the particular history of the glassy long term dynamics in a disordered material. We study the effect of initial configurations and the realization of stochastic dynamics on the long time evolution of configurations in a two-dimensional Ising spin glass model. The evolution of nearest neighbor correlations is computed using patchwork dynamics, a coarse-grained numerical heuristic for temporal evolution. The dependence of the nearest neighbor spin correlations at long time on both initial spin configurations and noise histories are studied through cross-correlations of long-time configurations and the spin correlations are found to be independent of both. We investigate how effectively rigid bond clusters coarsen. Scaling laws are used to study the convergence of configurations and the distribution of sizes of nearly rigid clusters. The implications of the computational results on simulations and phenomenological models of spin glasses are discussed. We acknowledge NSF support under DMR-1410937 (CMMT program).
Duchstein, Patrick; Milek, Theodor; Zahn, Dirk
2015-01-01
Molecular models of 5 nm sized ZnO/Zn(OH)2 core-shell nanoparticles in ethanolic solution were derived as scale-up models (based on an earlier model created from ion-by-ion aggregation and self-organization) and subjected to mechanistic analyses of surface stabilization by block-copolymers. The latter comprise a poly-methacrylate chain accounting for strong surfactant association to the nanoparticle by hydrogen bonding and salt-bridges. While dangling poly-ethylene oxide chains provide only a limited degree of sterical hindering to nanoparticle agglomeration, the key mechanism of surface stabilization is electrostatic shielding arising from the acrylates and a halo of Na+ counter ions associated to the nanoparticle. Molecular dynamics simulations reveal different solvent shells and distance-dependent mobility of ions and solvent molecules. From this, we provide a molecular rationale of effective particle size, net charge and polarizability of the nanoparticles in solution.
Duchstein, Patrick; Milek, Theodor; Zahn, Dirk
2015-01-01
Molecular models of 5 nm sized ZnO/Zn(OH)2 core-shell nanoparticles in ethanolic solution were derived as scale-up models (based on an earlier model created from ion-by-ion aggregation and self-organization) and subjected to mechanistic analyses of surface stabilization by block-copolymers. The latter comprise a poly-methacrylate chain accounting for strong surfactant association to the nanoparticle by hydrogen bonding and salt-bridges. While dangling poly-ethylene oxide chains provide only a limited degree of sterical hindering to nanoparticle agglomeration, the key mechanism of surface stabilization is electrostatic shielding arising from the acrylates and a halo of Na+ counter ions associated to the nanoparticle. Molecular dynamics simulations reveal different solvent shells and distance-dependent mobility of ions and solvent molecules. From this, we provide a molecular rationale of effective particle size, net charge and polarizability of the nanoparticles in solution. PMID:25962096
NASA Technical Reports Server (NTRS)
French, K. W., Jr.
1985-01-01
The flexibility of the PHOENICS computational fluid dynamics package was assessed along two general avenues; parallel modeling and analog modeling. In parallel modeling the dependent and independent variables retain their identity within some scaling factors, even though the boundary conditions and especially the constitutive relations do not correspond to any realistic fluid dynamic situation. PHOENICS was used to generate a CFD model that should exhibit the physical anomalies of a granular medium and permit reasonable similarity with boundary conditions typical to membrane or porous piston loading. A considerable portion of the study was spent prying into the existing code with a prejudice toward rate type and disarming any inherent fluid behavior. The final stages of the study were directed at the more specific problem of multiaxis loading of cylindrical geometry with a concern for the appearance of bulging, cross slab shear failure modes.
A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains
Poleszczuk, Jan; Enderling, Heiko
2014-01-01
Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862
Strategic behavior and governance challenges in self-organized coupled natural-human systems
NASA Astrophysics Data System (ADS)
Muneepeerakul, R.; Anderies, J. M.
2017-12-01
Successful and sustainable coupling of human societies and natural systems requires effective governance, which depends on the existence of proper infrastructure (both hard and soft). In recent decades, much attention has been paid to what has allowed many small-scale self-organized coupled natural-human systems around the world to persist for centuries, thanks to a large part to the work by Elinor Ostrom and colleagues. In this work, we mathematically operationalize a conceptual framework that is developed based on this body of work by way of a stylized model. The model captures the interplay between replicator dynamics within the population, dynamics of natural resources, and threshold characteristics of public infrastructure. The model analysis reveals conditions for long-term sustainability and collapse of the coupled systems as well as other tradeoffs and potential pitfalls in governing these systems.
An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.
Fink, Christian G
2017-01-01
While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.
Kim, Seyoung; Park, Sukyung; Choi, Sangkyu
2014-09-22
In this study, we developed a curve-fit model of countermovement dynamics and examined whether the characteristics of a countermovement jump can be quantified using the model parameter and its scaling; we expected that the model-based analysis would facilitate an understanding of the basic mechanisms of force reduction and propulsion with a simplified framework of the center of mass (CoM) mechanics. Ten healthy young subjects jumped straight up to five different levels ranging from approximately 10% to 35% of their body heights. The kinematic and kinetic data on the CoM were measured using a force plate system synchronized with motion capture cameras. All subjects generated larger vertical forces compared with their body weights from the countermovement and sufficiently lowered their CoM position to support the work performed by push-off as the vertical elevations became more challenging. The model simulation reasonably reproduced the trajectories of vertical force during the countermovement, and the model parameters were replaced by linear and polynomial regression functions in terms of the vertical jump height. Gradual scaling trends of the individual model parameters were observed as a function of the vertical jump height with different degrees of scaling, depending on the subject. The results imply that the subjects may be aware of the jumping dynamics when subjected to various vertical jump heights and may select their countermovement strategies to effectively accommodate biomechanical constraints, i.e., limited force generation for the standing vertical jump. Copyright © 2014 Elsevier Ltd. All rights reserved.
Ultrafast dynamics of defect-assisted electron-hole recombination in monolayer MoS2.
Wang, Haining; Zhang, Changjian; Rana, Farhan
2015-01-14
In this Letter, we present nondegenerate ultrafast optical pump-probe studies of the carrier recombination dynamics in MoS2 monolayers. By tuning the probe to wavelengths much longer than the exciton line, we make the probe transmission sensitive to the total population of photoexcited electrons and holes. Our measurement reveals two distinct time scales over which the photoexcited electrons and holes recombine; a fast time scale that lasts ∼ 2 ps and a slow time scale that lasts longer than ∼ 100 ps. The temperature and the pump fluence dependence of the observed carrier dynamics are consistent with defect-assisted recombination as being the dominant mechanism for electron-hole recombination in which the electrons and holes are captured by defects via Auger processes. Strong Coulomb interactions in two-dimensional atomic materials, together with strong electron and hole correlations in two-dimensional metal dichalcogenides, make Auger processes particularly effective for carrier capture by defects. We present a model for carrier recombination dynamics that quantitatively explains all features of our data for different temperatures and pump fluences. The theoretical estimates for the rate constants for Auger carrier capture are in good agreement with the experimentally determined values. Our results underscore the important role played by Auger processes in two-dimensional atomic materials.
Rodríguez-Arias, Miquel Angel; Rodó, Xavier
2004-03-01
Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.
Micromechanics of sea ice gouge in shear zones
NASA Astrophysics Data System (ADS)
Sammonds, Peter; Scourfield, Sally; Lishman, Ben
2015-04-01
The deformation of sea ice is a key control on the Arctic Ocean dynamics. Shear displacement on all scales is an important deformation process in the sea cover. Shear deformation is a dominant mechanism from the scale of basin-scale shear lineaments, through floe-floe interaction and block sliding in ice ridges through to the micro-scale mechanics. Shear deformation will not only depend on the speed of movement of ice surfaces but also the degree that the surfaces have bonded during thermal consolidation and compaction. Recent observations made during fieldwork in the Barents Sea show that shear produces a gouge similar to a fault gouge in a shear zone in the crust. A range of sizes of gouge are exhibited. The consolidation of these fragments has a profound influence on the shear strength and the rate of the processes involved. We review experimental results in sea ice mechanics from mid-scale experiments, conducted in the Hamburg model ship ice tank, simulating sea ice floe motion and interaction and compare these with laboratory experiments on ice friction done in direct shear, and upscale to field measurement of sea ice friction and gouge deformation made during experiments off Svalbard. We find that consolidation, fragmentation and bridging play important roles in the overall dynamics and fit the model of Sammis and Ben-Zion, developed for understanding the micro-mechanics of rock fault gouge, to the sea ice problem.
Nanoscale movements of cellulose microfibrils in primary cell walls.
Zhang, Tian; Vavylonis, Dimitrios; Durachko, Daniel M; Cosgrove, Daniel J
2017-04-28
The growing plant cell wall is commonly considered to be a fibre-reinforced structure whose strength, extensibility and anisotropy depend on the orientation of crystalline cellulose microfibrils, their bonding to the polysaccharide matrix and matrix viscoelasticity 1-4 . Structural reinforcement of the wall by stiff cellulose microfibrils is central to contemporary models of plant growth, mechanics and meristem dynamics 4-12 . Although passive microfibril reorientation during wall extension has been inferred from theory and from bulk measurements 13-15 , nanometre-scale movements of individual microfibrils have not been directly observed. Here we combined nanometre-scale imaging of wet cell walls by atomic force microscopy (AFM) with a stretching device and endoglucanase treatment that induces wall stress relaxation and creep, mimicking wall behaviours during cell growth. Microfibril movements during forced mechanical extensions differ from those during creep of the enzymatically loosened wall. In addition to passive angular reorientation, we observed a diverse repertoire of microfibril movements that reveal the spatial scale of molecular connections between microfibrils. Our results show that wall loosening alters microfibril connectivity, enabling microfibril dynamics not seen during mechanical stretch. These insights into microfibril movements and connectivities need to be incorporated into refined models of plant cell wall structure, growth and morphogenesis.
Water circulation and global mantle dynamics: Insight from numerical modeling
NASA Astrophysics Data System (ADS)
Nakagawa, Takashi; Nakakuki, Tomoeki; Iwamori, Hikaru
2015-05-01
We investigate water circulation and its dynamical effects on global-scale mantle dynamics in numerical thermochemical mantle convection simulations. Both dehydration-hydration processes and dehydration melting are included. We also assume the rheological properties of hydrous minerals and density reduction caused by hydrous minerals. Heat transfer due to mantle convection seems to be enhanced more effectively than water cycling in the mantle convection system when reasonable water dependence of viscosity is assumed, due to effective slab dehydration at shallow depths. Water still affects significantly the global dynamics by weakening the near-surface oceanic crust and lithosphere, enhancing the activity of surface plate motion compared to dry mantle case. As a result, including hydrous minerals, the more viscous mantle is expected with several orders of magnitude compared to the dry mantle. The average water content in the whole mantle is regulated by the dehydration-hydration process. The large-scale thermochemical anomalies, as is observed in the deep mantle, is found when a large density contrast between basaltic material and ambient mantle is assumed (4-5%), comparable to mineral physics measurements. Through this study, the effects of hydrous minerals in mantle dynamics are very important for interpreting the observational constraints on mantle convection.
Intergenerational Wealth Transmission and the Dynamics of Inequality in Small-Scale Societies*
Mulder, Monique Borgerhoff; Bowles, Samuel; Hertz, Tom; Bell, Adrian; Beise, Jan; Clark, Greg; Fazzio, Ila; Gurven, Michael; Hill, Kim; Hooper, Paul L.; Irons, William; Kaplan, Hillard; Leonetti, Donna; Low, Bobbi; Marlowe, Frank; McElreath, Richard; Naidu, Suresh; Nolin, David; Piraino, Patrizio; Quinlan, Rob; Schniter, Eric; Sear, Rebecca; Shenk, Mary; Smith, Eric Alden; von Rueden, Christopher; Wiessner, Polly
2009-01-01
Small-scale human societies range from foraging bands with a strong egalitarian ethos to more economically stratified agrarian and pastoral societies. We explain this variation in inequality using a dynamic model in which a population’s long-run steady-state level of inequality depends on the extent to which its most important forms of wealth are transmitted within families across generations. We estimate the degree of intergenerational transmission of three different types of wealth (material, embodied, and relational) as well as the extent of wealth inequality in 21 historical and contemporary populations. We show that intergenerational transmission of wealth and wealth inequality are substantial among pastoral and small-scale agricultural societies (on a par with or even exceeding the most unequal modern industrial economies) and quite limited among horticultural and foraging peoples (equivalent to the most egalitarian of modern industrial populations). Differences in the technology by which a people derive their livelihood and in the institutions and norms making up the economic system jointly contribute to this pattern. PMID:19900925
High pressure study of molecular dynamics of protic ionic liquid lidocaine hydrochloride.
Swiety-Pospiech, A; Wojnarowska, Z; Pionteck, J; Pawlus, S; Grzybowski, A; Hensel-Bielowka, S; Grzybowska, K; Szulc, A; Paluch, M
2012-06-14
In this paper, we investigate the effect of pressure on the molecular dynamics of protic ionic liquid lidocaine hydrochloride, a commonly used pharmaceutical, by means of dielectric spectroscopy and pressure-temperature-volume methods. We observed that near T(g) the pressure dependence of conductivity relaxation times reveals a peculiar behavior, which can be treated as a manifestation of decoupling between ion migration and structural relaxation times. Moreover, we discuss the validity of thermodynamic scaling in lidocaine HCl. We also employed the temperature-volume Avramov model to determine the value of pressure coefficient of glass transition temperature, dT(g)/dP|(P = 0.1). Finally, we investigate the role of thermal and density fluctuations in controlling of molecular dynamics of the examined compound.
Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme
2013-01-01
Background Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. Methods And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. Conclusions In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales. PMID:24367636
Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme
2013-01-01
Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Donner, Leo J.; O'Brien, Travis A.; Rieger, Daniel
Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud-aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climatemore » and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations which do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of scale-dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.« less
Temporal scaling in information propagation.
Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi
2014-06-18
For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.
Temporal scaling in information propagation
NASA Astrophysics Data System (ADS)
Huang, Junming; Li, Chao; Wang, Wen-Qiang; Shen, Hua-Wei; Li, Guojie; Cheng, Xue-Qi
2014-06-01
For the study of information propagation, one fundamental problem is uncovering universal laws governing the dynamics of information propagation. This problem, from the microscopic perspective, is formulated as estimating the propagation probability that a piece of information propagates from one individual to another. Such a propagation probability generally depends on two major classes of factors: the intrinsic attractiveness of information and the interactions between individuals. Despite the fact that the temporal effect of attractiveness is widely studied, temporal laws underlying individual interactions remain unclear, causing inaccurate prediction of information propagation on evolving social networks. In this report, we empirically study the dynamics of information propagation, using the dataset from a population-scale social media website. We discover a temporal scaling in information propagation: the probability a message propagates between two individuals decays with the length of time latency since their latest interaction, obeying a power-law rule. Leveraging the scaling law, we further propose a temporal model to estimate future propagation probabilities between individuals, reducing the error rate of information propagation prediction from 6.7% to 2.6% and improving viral marketing with 9.7% incremental customers.
The predictability of a lake phytoplankton community, over time-scales of hours to years.
Thomas, Mridul K; Fontana, Simone; Reyes, Marta; Kehoe, Michael; Pomati, Francesco
2018-05-01
Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R 2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics. © 2018 John Wiley & Sons Ltd/CNRS.
Beyond Word Frequency: Bursts, Lulls, and Scaling in the Temporal Distributions of Words
Altmann, Eduardo G.; Pierrehumbert, Janet B.; Motter, Adilson E.
2009-01-01
Background Zipf's discovery that word frequency distributions obey a power law established parallels between biological and physical processes, and language, laying the groundwork for a complex systems perspective on human communication. More recent research has also identified scaling regularities in the dynamics underlying the successive occurrences of events, suggesting the possibility of similar findings for language as well. Methodology/Principal Findings By considering frequent words in USENET discussion groups and in disparate databases where the language has different levels of formality, here we show that the distributions of distances between successive occurrences of the same word display bursty deviations from a Poisson process and are well characterized by a stretched exponential (Weibull) scaling. The extent of this deviation depends strongly on semantic type – a measure of the logicality of each word – and less strongly on frequency. We develop a generative model of this behavior that fully determines the dynamics of word usage. Conclusions/Significance Recurrence patterns of words are well described by a stretched exponential distribution of recurrence times, an empirical scaling that cannot be anticipated from Zipf's law. Because the use of words provides a uniquely precise and powerful lens on human thought and activity, our findings also have implications for other overt manifestations of collective human dynamics. PMID:19907645
PCTDSE: A parallel Cartesian-grid-based TDSE solver for modeling laser-atom interactions
NASA Astrophysics Data System (ADS)
Fu, Yongsheng; Zeng, Jiaolong; Yuan, Jianmin
2017-01-01
We present a parallel Cartesian-grid-based time-dependent Schrödinger equation (TDSE) solver for modeling laser-atom interactions. It can simulate the single-electron dynamics of atoms in arbitrary time-dependent vector potentials. We use a split-operator method combined with fast Fourier transforms (FFT), on a three-dimensional (3D) Cartesian grid. Parallelization is realized using a 2D decomposition strategy based on the Message Passing Interface (MPI) library, which results in a good parallel scaling on modern supercomputers. We give simple applications for the hydrogen atom using the benchmark problems coming from the references and obtain repeatable results. The extensions to other laser-atom systems are straightforward with minimal modifications of the source code.
Wind Tunnel to Atmospheric Mapping for Static Aeroelastic Scaling
NASA Technical Reports Server (NTRS)
Heeg, Jennifer; Spain, Charles V.; Rivera, J. A.
2004-01-01
Wind tunnel to Atmospheric Mapping (WAM) is a methodology for scaling and testing a static aeroelastic wind tunnel model. The WAM procedure employs scaling laws to define a wind tunnel model and wind tunnel test points such that the static aeroelastic flight test data and wind tunnel data will be correlated throughout the test envelopes. This methodology extends the notion that a single test condition - combination of Mach number and dynamic pressure - can be matched by wind tunnel data. The primary requirements for affecting this extension are matching flight Mach numbers, maintaining a constant dynamic pressure scale factor and setting the dynamic pressure scale factor in accordance with the stiffness scale factor. The scaling is enabled by capabilities of the NASA Langley Transonic Dynamics Tunnel (TDT) and by relaxation of scaling requirements present in the dynamic problem that are not critical to the static aeroelastic problem. The methodology is exercised in two example scaling problems: an arbitrarily scaled wing and a practical application to the scaling of the Active Aeroelastic Wing flight vehicle for testing in the TDT.
Yan, Zhi; Jiang, Liying
2017-01-01
Piezoelectric nanomaterials (PNs) are attractive for applications including sensing, actuating, energy harvesting, among others in nano-electro-mechanical-systems (NEMS) because of their excellent electromechanical coupling, mechanical and physical properties. However, the properties of PNs do not coincide with their bulk counterparts and depend on the particular size. A large amount of efforts have been devoted to studying the size-dependent properties of PNs by using experimental characterization, atomistic simulation and continuum mechanics modeling with the consideration of the scale features of the nanomaterials. This paper reviews the recent progresses and achievements in the research on the continuum mechanics modeling of the size-dependent mechanical and physical properties of PNs. We start from the fundamentals of the modified continuum mechanics models for PNs, including the theories of surface piezoelectricity, flexoelectricity and non-local piezoelectricity, with the introduction of the modified piezoelectric beam and plate models particularly for nanostructured piezoelectric materials with certain configurations. Then, we give a review on the investigation of the size-dependent properties of PNs by using the modified continuum mechanics models, such as the electromechanical coupling, bending, vibration, buckling, wave propagation and dynamic characteristics. Finally, analytical modeling and analysis of nanoscale actuators and energy harvesters based on piezoelectric nanostructures are presented. PMID:28336861
Yan, Zhi; Jiang, Liying
2017-01-26
Piezoelectric nanomaterials (PNs) are attractive for applications including sensing, actuating, energy harvesting, among others in nano-electro-mechanical-systems (NEMS) because of their excellent electromechanical coupling, mechanical and physical properties. However, the properties of PNs do not coincide with their bulk counterparts and depend on the particular size. A large amount of efforts have been devoted to studying the size-dependent properties of PNs by using experimental characterization, atomistic simulation and continuum mechanics modeling with the consideration of the scale features of the nanomaterials. This paper reviews the recent progresses and achievements in the research on the continuum mechanics modeling of the size-dependent mechanical and physical properties of PNs. We start from the fundamentals of the modified continuum mechanics models for PNs, including the theories of surface piezoelectricity, flexoelectricity and non-local piezoelectricity, with the introduction of the modified piezoelectric beam and plate models particularly for nanostructured piezoelectric materials with certain configurations. Then, we give a review on the investigation of the size-dependent properties of PNs by using the modified continuum mechanics models, such as the electromechanical coupling, bending, vibration, buckling, wave propagation and dynamic characteristics. Finally, analytical modeling and analysis of nanoscale actuators and energy harvesters based on piezoelectric nanostructures are presented.
Peridynamic Multiscale Finite Element Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Costa, Timothy; Bond, Stephen D.; Littlewood, David John
The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less
NASA Astrophysics Data System (ADS)
Ulrich, Thomas; Gabriel, Alice-Agnes
2017-04-01
Natural fault geometries are subject to a large degree of uncertainty. Their geometrical structure is not directly observable and may only be inferred from surface traces, or geophysical measurements. Most studies aiming at assessing the potential seismic hazard of natural faults rely on idealised shaped models, based on observable large-scale features. Yet, real faults are wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. Dynamic rupture simulations aim to capture the observed complexity of earthquake sources and ground-motions. From a numerical point of view, incorporating rough faults in such simulations is challenging - it requires optimised codes able to run efficiently on high-performance computers and simultaneously handle complex geometries. Physics-based rupture dynamics hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Moreover, the simulated ground-motions present many similarities with observed ground-motions records. Thus, such simulations may foster our understanding of earthquake source processes, and help deriving more accurate seismic hazard estimates. In this presentation, the software package SeisSol (www.seissol.org), based on an ADER-Discontinuous Galerkin scheme, is used to solve the spontaneous dynamic earthquake rupture problem. The usage of tetrahedral unstructured meshes naturally allows for complicated fault geometries. However, SeisSol's high-order discretisation in time and space is not particularly suited for small-scale fault roughness. We will demonstrate modelling conditions under which SeisSol resolves rupture dynamics on rough faults accurately. The strong impact of the geometric gradient of the fault surface on the rupture process is then shown in 3D simulations. Following, the benefits of explicitly modelling fault curvature and roughness, in distinction to prescribing heterogeneous initial stress conditions on a planar fault, is demonstrated. Furthermore, we show that rupture extend, rupture front coherency and rupture speed are highly dependent on the initial amplitude of stress acting on the fault, defined by the normalized prestress factor R, the ratio of the potential stress drop over the breakdown stress drop. The effects of fault complexity are particularly pronounced for lower R. By low-pass filtering a rough fault at several cut-off wavelengths, we then try to capture rupture complexity using a simplified fault geometry. We find that equivalent source dynamics can only be obtained using a scarcely filtered fault associated with a reduced stress level. To investigate the wavelength-dependent roughness effect, the fault geometry is bandpass-filtered over several spectral ranges. We show that geometric fluctuations cause rupture velocity fluctuations of similar length scale. The impact of fault geometry is especially pronounced when the rupture front velocity is near supershear. Roughness fluctuations significantly smaller than the rupture front characteristic dimension (cohesive zone size) affect only macroscopic rupture properties, thus, posing a minimum length scale limiting the required resolution of 3D fault complexity. Lastly, the effect of fault curvature and roughness on the simulated ground-motions is assessed. Despite employing a simple linear slip weakening friction law, the simulated ground-motions compare well with estimates from ground motions prediction equations, even at relatively high frequencies.
Vaccination intervention on epidemic dynamics in networks
NASA Astrophysics Data System (ADS)
Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Zhou, Tao
2013-02-01
Vaccination is an important measure available for preventing or reducing the spread of infectious diseases. In this paper, an epidemic model including susceptible, infected, and imperfectly vaccinated compartments is studied on Watts-Strogatz small-world, Barabási-Albert scale-free, and random scale-free networks. The epidemic threshold and prevalence are analyzed. For small-world networks, the effective vaccination intervention is suggested and its influence on the threshold and prevalence is analyzed. For scale-free networks, the threshold is found to be strongly dependent both on the effective vaccination rate and on the connectivity distribution. Moreover, so long as vaccination is effective, it can linearly decrease the epidemic prevalence in small-world networks, whereas for scale-free networks it acts exponentially. These results can help in adopting pragmatic treatment upon diseases in structured populations.
Dynamical origins of the community structure of an online multi-layer society
NASA Astrophysics Data System (ADS)
Klimek, Peter; Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi; Thurner, Stefan
2016-08-01
Social structures emerge as a result of individuals managing a variety of different social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various layers in the multiplex network. Community sizes distributions are either fat-tailed or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex network. Depending on link and node fluctuation probabilities, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.
Qvist, Johan; Schober, Helmut; Halle, Bertil
2011-04-14
One of the outstanding challenges presented by liquid water is to understand how molecules can move on a picosecond time scale despite being incorporated in a three-dimensional network of relatively strong H-bonds. This challenge is exacerbated in the supercooled state, where the dramatic slowing down of structural dynamics is reminiscent of the, equally poorly understood, generic behavior of liquids near the glass transition temperature. By probing single-molecule dynamics on a wide range of time and length scales, quasielastic neutron scattering (QENS) can potentially reveal the mechanistic details of water's structural dynamics, but because of interpretational ambiguities this potential has not been fully realized. To resolve these issues, we present here an extensive set of high-quality QENS data from water in the range 253-293 K and a corresponding set of molecular dynamics (MD) simulations to facilitate and validate the interpretation. Using a model-free approach, we analyze the QENS data in terms of two motional components. Based on the dynamical clustering observed in MD trajectories, we identify these components with two distinct types of structural dynamics: picosecond local (L) structural fluctuations within dynamical basins and slower interbasin jumps (J). The Q-dependence of the dominant QENS component, associated with J dynamics, can be quantitatively rationalized with a continuous-time random walk (CTRW) model with an apparent jump length that depends on low-order moments of the jump length and waiting time distributions. Using a simple coarse-graining algorithm to quantitatively identify dynamical basins, we map the newtonian MD trajectory on a CTRW trajectory, from which the jump length and waiting time distributions are computed. The jump length distribution is gaussian and the rms jump length increases from 1.5 to 1.9 Å as the temperature increases from 253 to 293 K. The rms basin radius increases from 0.71 to 0.75 Å over the same range. The waiting time distribution is exponential at all investigated temperatures, ruling out significant dynamical heterogeneity. However, a simulation at 238 K reveals a small but significant dynamical heterogeneity. The macroscopic diffusion coefficient deduced from the QENS data agrees quantitatively with NMR and tracer results. We compare our QENS analysis with existing approaches, arguing that the apparent dynamical heterogeneity implied by stretched exponential fitting functions results from the failure to distinguish intrabasin (L) from interbasin (J) structural dynamics. We propose that the apparent dynamical singularity at ∼220 K corresponds to freezing out of J dynamics, while the calorimetric glass transition corresponds to freezing out of L dynamics.
NASA Astrophysics Data System (ADS)
Qvist, Johan; Schober, Helmut; Halle, Bertil
2011-04-01
One of the outstanding challenges presented by liquid water is to understand how molecules can move on a picosecond time scale despite being incorporated in a three-dimensional network of relatively strong H-bonds. This challenge is exacerbated in the supercooled state, where the dramatic slowing down of structural dynamics is reminiscent of the, equally poorly understood, generic behavior of liquids near the glass transition temperature. By probing single-molecule dynamics on a wide range of time and length scales, quasielastic neutron scattering (QENS) can potentially reveal the mechanistic details of water's structural dynamics, but because of interpretational ambiguities this potential has not been fully realized. To resolve these issues, we present here an extensive set of high-quality QENS data from water in the range 253-293 K and a corresponding set of molecular dynamics (MD) simulations to facilitate and validate the interpretation. Using a model-free approach, we analyze the QENS data in terms of two motional components. Based on the dynamical clustering observed in MD trajectories, we identify these components with two distinct types of structural dynamics: picosecond local (L) structural fluctuations within dynamical basins and slower interbasin jumps (J). The Q-dependence of the dominant QENS component, associated with J dynamics, can be quantitatively rationalized with a continuous-time random walk (CTRW) model with an apparent jump length that depends on low-order moments of the jump length and waiting time distributions. Using a simple coarse-graining algorithm to quantitatively identify dynamical basins, we map the Newtonian MD trajectory on a CTRW trajectory, from which the jump length and waiting time distributions are computed. The jump length distribution is Gaussian and the rms jump length increases from 1.5 to 1.9 Å as the temperature increases from 253 to 293 K. The rms basin radius increases from 0.71 to 0.75 Å over the same range. The waiting time distribution is exponential at all investigated temperatures, ruling out significant dynamical heterogeneity. However, a simulation at 238 K reveals a small but significant dynamical heterogeneity. The macroscopic diffusion coefficient deduced from the QENS data agrees quantitatively with NMR and tracer results. We compare our QENS analysis with existing approaches, arguing that the apparent dynamical heterogeneity implied by stretched exponential fitting functions results from the failure to distinguish intrabasin (L) from interbasin (J) structural dynamics. We propose that the apparent dynamical singularity at ˜220 K corresponds to freezing out of J dynamics, while the calorimetric glass transition corresponds to freezing out of L dynamics.
Foraminifera Record the Good Years More than the Bad
NASA Astrophysics Data System (ADS)
Hull, P. M.
2014-12-01
Past ocean conditions are primarily discerned from geochemical and community-based analyses of fossilized taxa, each of which have unique environmental niches and dynamics. A key requirement of such paleoceanographic studies is that some unbiased or well-constrained record of the living ecosystem and climate is deposited on the sea floor and preserved through the post-depositional processes that act to distort them. It is widely known that foraminiferal species exhibit varying seasonal preferences and that seasonality is a key variable to account for in paleoceanographic reconstructions. However, on longer time scales (> year), it is generally assumed that species record the 'average' environmental conditions or typical variance (e.g., El Nino intensity) that existed in a given, time-averaged sediment sample. Here I examine planktonic foraminiferal population dynamics on yearly and longer time scales, in order to quantify their effect on paleoceanographic reconstructions. Using a previously published record of >250 years of population dynamics in the Santa Barbara Basin sediments, I find that the majority of individuals in a given species lived during a small subset of the total years (~15- 37% of years depending on the species). Populations of shallow, mixed layer species primarily represent the warmest, youngest years, while thermocline species primarily represent the cooler, older years. Importantly, the seasonality of species does not always predict their interannual dynamics. The general importance of long time-scale population dynamics on paleoceanographic reconstructions will also be considered in a theoretical model parameterized with temporally explicit species co-variances and temperature variability. Such modeling is needed to constrain the relative impact that a very good year can have on our interpretation of the 'average' of hundreds to thousands of years.
Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.
2015-01-01
An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.
Schmidt, Elliot; Shi, Sha; Ruden, P Paul; Frisbie, C Daniel
2016-06-15
Although ionic liquids (ILs) have been used extensively in recent years as a high-capacitance "dielectric" in electric double layer transistors, the dynamics of the double layer formation have remained relatively unexplored. Better understanding of the dynamics and relaxation processes involved in electric double layer formation will guide device optimization, particularly with regard to switching speed. In this paper, we explore the dynamical characteristics of an IL in a metal/ionic liquid/metal (M/IL/M) capacitor. In particular, we examine a Au/IL/Au structure where the IL is 1-butyl-1-methylpyrrolidinium tris(pentafluoroethyl)trifluorophosphate. The experiments consist of frequency-dependent impedance measurements and time-dependent current vs voltage measurements for applied linear voltage ramps and abrupt voltage steps. The parameters of an equivalent circuit model are determined by fits to the impedance vs frequency data and subsequently verified by calculating the current vs voltage characteristics for the applied potential profiles. The data analysis indicates that the dynamics of the structure are characterized by a wide distribution of relaxation times spanning the range of less than microseconds to longer than seconds. Possible causes for these time scales are discussed.