Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

On-line implementation of nonlinear parameter estimation for the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Buckland, Julia H.; Musgrave, Jeffrey L.; Walker, Bruce K.

1992-01-01

We investigate the performance of a nonlinear estimation scheme applied to the estimation of several parameters in a performance model of the Space Shuttle Main Engine. The nonlinear estimator is based upon the extended Kalman filter which has been augmented to provide estimates of several key performance variables. The estimated parameters are directly related to the efficiency of both the low pressure and high pressure fuel turbopumps. Decreases in the parameter estimates may be interpreted as degradations in turbine and/or pump efficiencies which can be useful measures for an online health monitoring algorithm. This paper extends previous work which has focused on off-line parameter estimation by investigating the filter's on-line potential from a computational standpoint. ln addition, we examine the robustness of the algorithm to unmodeled dynamics. The filter uses a reduced-order model of the engine that includes only fuel-side dynamics. The on-line results produced during this study are comparable to off-line results generated previously. The results show that the parameter estimates are sensitive to dynamics not included in the filter model. Off-line results using an extended Kalman filter with a full order engine model to address the robustness problems of the reduced-order model are also presented.

Dynamical recovery of SU(2) symmetry in the mass-quenched Hubbard model

NASA Astrophysics Data System (ADS)

Du, Liang; Fiete, Gregory A.

2018-02-01

We use nonequilibrium dynamical mean-field theory with iterative perturbation theory as an impurity solver to study the recovery of SU(2) symmetry in real time following a hopping integral parameter quench from a mass-imbalanced to a mass-balanced single-band Hubbard model at half filling. A dynamical order parameter γ (t ) is defined to characterize the evolution of the system towards SU(2) symmetry. By comparing the momentum-dependent occupation from an equilibrium calculation [with the SU(2) symmetric Hamiltonian after the quench at an effective temperature] with the data from our nonequilibrium calculation, we conclude that the SU(2) symmetry recovered state is a thermalized state. Further evidence from the evolution of the density of states supports this conclusion. We find the order parameter in the weak Coulomb interaction regime undergoes an approximate exponential decay. We numerically investigate the interplay of the relevant parameters (initial temperature, Coulomb interaction strength, initial mass-imbalance ratio) and their combined effect on the thermalization behavior. Finally, we study evolution of the order parameter as the hopping parameter is changed with either a linear ramp or a pulse. Our results can be useful in strategies to engineer the relaxation behavior of interacting quantum many-particle systems.

Role of dimensionality in Axelrod's model for the dissemination of culture

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San

2003-09-01

We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.

Drawing dynamical and parameters planes of iterative families and methods.

PubMed

Chicharro, Francisco I; Cordero, Alicia; Torregrosa, Juan R

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones).

Thermodynamic scaling of dynamic properties of liquid crystals: Verifying the scaling parameters using a molecular model

NASA Astrophysics Data System (ADS)

Satoh, Katsuhiko

2013-08-01

The thermodynamic scaling of molecular dynamic properties of rotation and thermodynamic parameters in a nematic phase was investigated by a molecular dynamic simulation using the Gay-Berne potential. A master curve for the relaxation time of flip-flop motion was obtained using thermodynamic scaling, and the dynamic property could be solely expressed as a function of TV^{γ _τ }, where T and V are the temperature and volume, respectively. The scaling parameter γτ was in excellent agreement with the thermodynamic parameter Γ, which is the logarithm of the slope of a line plotted for the temperature and volume at constant P2. This line was fairly linear, and as good as the line for p-azoxyanisole or using the highly ordered small cluster model. The equivalence relation between Γ and γτ was compared with results obtained from the highly ordered small cluster model. The possibility of adapting the molecular model for the thermodynamic scaling of other dynamic rotational properties was also explored. The rotational diffusion constant and rotational viscosity coefficients, which were calculated using established theoretical and experimental expressions, were rescaled onto master curves with the same scaling parameters. The simulation illustrates the universal nature of the equivalence relation for liquid crystals.

Dynamic Computation of Change Operations in Version Management of Business Process Models

NASA Astrophysics Data System (ADS)

Küster, Jochen Malte; Gerth, Christian; Engels, Gregor

Version management of business process models requires that changes can be resolved by applying change operations. In order to give a user maximal freedom concerning the application order of change operations, position parameters of change operations must be computed dynamically during change resolution. In such an approach, change operations with computed position parameters must be applicable on the model and dependencies and conflicts of change operations must be taken into account because otherwise invalid models can be constructed. In this paper, we study the concept of partially specified change operations where parameters are computed dynamically. We provide a formalization for partially specified change operations using graph transformation and provide a concept for their applicability. Based on this, we study potential dependencies and conflicts of change operations and show how these can be taken into account within change resolution. Using our approach, a user can resolve changes of business process models without being unnecessarily restricted to a certain order.

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higher-order dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

'Scaling' analysis of the ice accretion process on aircraft surfaces

NASA Technical Reports Server (NTRS)

Keshock, E. G.; Tabrizi, A. H.; Missimer, J. R.

1982-01-01

A comprehensive set of scaling parameters is developed for the ice accretion process by analyzing the energy equations of the dynamic freezing zone and the already frozen ice layer, the continuity equation associated with supercooled liquid droplets entering into and impacting within the dynamic freezing zone, and energy equation of the ice layer. No initial arbitrary judgments are made regarding the relative magnitudes of each of the terms. The method of intrinsic reference variables in employed in order to develop the appropriate scaling parameters and their relative significance in rime icing conditions in an orderly process, rather than utilizing empiricism. The significance of these parameters is examined and the parameters are combined with scaling criteria related to droplet trajectory similitude.

Drawing Dynamical and Parameters Planes of Iterative Families and Methods

PubMed Central

Chicharro, Francisco I.

2013-01-01

The complex dynamical analysis of the parametric fourth-order Kim's iterative family is made on quadratic polynomials, showing the MATLAB codes generated to draw the fractal images necessary to complete the study. The parameter spaces associated with the free critical points have been analyzed, showing the stable (and unstable) regions where the selection of the parameter will provide us the excellent schemes (or dreadful ones). PMID:24376386

Heterogeneity-induced large deviations in activity and (in some cases) entropy production

NASA Astrophysics Data System (ADS)

Gingrich, Todd R.; Vaikuntanathan, Suriyanarayanan; Geissler, Phillip L.

2014-10-01

We solve a simple model that supports a dynamic phase transition and show conditions for the existence of the transition. Using methods of large deviation theory we analytically compute the probability distribution for activity and entropy production rates of the trajectories on a large ring with a single heterogeneous link. The corresponding joint rate function demonstrates two dynamical phases—one localized and the other delocalized, but the marginal rate functions do not always exhibit the underlying transition. Symmetries in dynamic order parameters influence the observation of a transition, such that distributions for certain dynamic order parameters need not reveal an underlying dynamical bistability. Solution of our model system furthermore yields the form of the effective Markov transition matrices that generate dynamics in which the two dynamical phases are at coexistence. We discuss the implications of the transition for the response of bacterial cells to antibiotic treatment, arguing that even simple models of a cell cycle lacking an explicit bistability in configuration space will exhibit a bistability of dynamical phases.

Simulating the multicellular homeostasis with a cell-based discrete receptor dynamics model: The non-mutational origin of cancer and aging.

PubMed

Lou, Yuting; Chen, Yu

2016-09-07

The purpose of the study is to investigate the multicellular homeostasis in epithelial tissues over very large timescales. Inspired by the receptor dynamics of IBCell model proposed by Rejniak et al. an on-grid agent-based model for multicellular system is constructed. Instead of observing the multicellular architectural morphologies, the diversity of homeostatic states is quantitatively analyzed through a substantial number of simulations by measuring three new order parameters, the phenotypic population structure, the average proliferation age and the relaxation time to stable homeostasis. Nearby the interfaces of distinct homeostatic phases in 3D phase diagrams of the three order parameters, intermediate quasi-stable phases of slow dynamics that features quasi-stability with a large spectrum of relaxation timescales are found. A further exploration on the static and dynamic correlations among the three order parameters reveals that the quasi-stable phases evolve towards two terminations, tumorigenesis and degeneration, which are respectively accompanied by rejuvenation and aging. With the exclusion of the environmental impact and the mutational strategies, the results imply that cancer and aging may share the non-mutational origin in the intrinsic slow dynamics of the multicellular systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Scale-invariant entropy-based theory for dynamic ordering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahulikar, Shripad P., E-mail: spm@iitmandi.ac.in, E-mail: spm@aero.iitb.ac.in; Department of Aerospace Engineering, Indian Institute of Technology Bombay, Mumbai 400076; Kumari, Priti

2014-09-01

Dynamically Ordered self-organized dissipative structure exists in various forms and at different scales. This investigation first introduces the concept of an isolated embedding system, which embeds an open system, e.g., dissipative structure and its mass and/or energy exchange with its surroundings. Thereafter, scale-invariant theoretical analysis is presented using thermodynamic principles for Order creation, existence, and destruction. The sustainability criterion for Order existence based on its structured mass and/or energy interactions with the surroundings is mathematically defined. This criterion forms the basis for the interrelationship of physical parameters during sustained existence of dynamic Order. It is shown that the sufficient conditionmore » for dynamic Order existence is approached if its sustainability criterion is met, i.e., its destruction path is blocked. This scale-invariant approach has the potential to unify the physical understanding of universal dynamic ordering based on entropy considerations.« less

Backbone dynamics in an intramolecular prolylpeptide-SH3 complex from the diphtheria toxin repressor, DtxR

PubMed Central

Bhattacharya, Nilakshee; Yi, Myunggi; Zhou, Huan-Xiang; Logan, Timothy M.

2008-01-01

Summary The diphtheria toxin repressor contains an SH3-like domain that forms an intramolecular complex with a proline-rich (Pr) peptide segment and stabilizes the inactive state of the repressor. Upon activation of DtxR by transition metals, this intramolecular complex must dissociate as the SH3 domain and Pr segment form different interactions in the active repressor. In this study we investigate the dynamics of this intramolecular complex using backbone amide nuclear spin relaxation rates determined using NMR spectroscopy and molecular dynamics trajectories. The SH3 domain in the unbound and bound states showed typical dynamics in that the secondary structures were fairly ordered with high generalized order parameters and low effective correlation times while residues in the loops connecting β-strands exhibited reduced generalized order parameters and required additional motional terms to adequately model the relaxation rates. Residues forming the Pr segment exhibited low order parameters with internal rotational correlation times on the order of 0.6 – 1 ns. Further analysis showed that the SH3 domain was rich in millisecond timescale motions while the Pr segment was rich in motions on the 100s μs timescale. Molecular dynamics simultations indicated structural rearrangements that may contribute to the observed relaxation rates and, together with the observed relaxation rate data, suggested that the Pr segment exhibits a binding ↔ unbinding equilibrium. The results of this study provide new insights into the nature of the intramolecular complex and provide a better understanding of the biological role of the SH3 domain in regulating DtxR activity. PMID:17976643

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ortoleva, Peter J.

Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

Two-degree-of-freedom fractional order-PID controllers design for fractional order processes with dead-time.

PubMed

Li, Mingjie; Zhou, Ping; Zhao, Zhicheng; Zhang, Jinggang

2016-03-01

Recently, fractional order (FO) processes with dead-time have attracted more and more attention of many researchers in control field, but FO-PID controllers design techniques available for the FO processes with dead-time suffer from lack of direct systematic approaches. In this paper, a simple design and parameters tuning approach of two-degree-of-freedom (2-DOF) FO-PID controller based on internal model control (IMC) is proposed for FO processes with dead-time, conventional one-degree-of-freedom control exhibited the shortcoming of coupling of robustness and dynamic response performance. 2-DOF control can overcome the above weakness which means it realizes decoupling of robustness and dynamic performance from each other. The adjustable parameter η2 of FO-PID controller is directly related to the robustness of closed-loop system, and the analytical expression is given between the maximum sensitivity specification Ms and parameters η2. In addition, according to the dynamic performance requirement of the practical system, the parameters η1 can also be selected easily. By approximating the dead-time term of the process model with the first-order Padé or Taylor series, the expressions for 2-DOF FO-PID controller parameters are derived for three classes of FO processes with dead-time. Moreover, compared with other methods, the proposed method is simple and easy to implement. Finally, the simulation results are given to illustrate the effectiveness of this method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamical phase transitions in generalized Kuramoto model with distributed Sakaguchi phase

NASA Astrophysics Data System (ADS)

Banerjee, Amitava

2017-11-01

In this numerical work, we have systematically studied the dynamical phase transitions in the Kuramoto-Sakaguchi model of synchronizing phase oscillators controlled by disorder in the Sakaguchi phases. We derive the numerical steady state phase diagrams for quenched and annealed kinds of disorder in the Sakaguchi parameters, using the conventional order parameter and other such statistical quantities as strength of incoherence and discontinuity measures. We have also considered the correlation profile of the local order parameter fluctuations in the various phases identified. The phase diagrams for quenched disorder are qualitatively much different from those in the global coupling regime. The order of various transitions is confirmed by a study of the distribution of the order parameter and its fourth order Binder’s cumulant across the transition for an ensemble of initial distribution of phases. For the annealed type of disorder, in contrast to the case with quenched disorder, the system is almost insensitive to the amount of disorder. We also elucidate the role of chimeralike states in the synchronizing transition of the system, and study the effect of disorder on these states. Finally, we seek justification of our results from simulations guided by the Ott-Antonsen ansatz.

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365

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.

High-order sliding-mode control for blood glucose regulation in the presence of uncertain dynamics.

PubMed

Hernández, Ana Gabriela Gallardo; Fridman, Leonid; Leder, Ron; Andrade, Sergio Islas; Monsalve, Cristina Revilla; Shtessel, Yuri; Levant, Arie

2011-01-01

The success of blood glucose automatic regulation depends on the robustness of the control algorithm used. It is a difficult task to perform due to the complexity of the glucose-insulin regulation system. The variety of model existing reflects the great amount of phenomena involved in the process, and the inter-patient variability of the parameters represent another challenge. In this research a High-Order Sliding-Mode Control is proposed. It is applied to two well known models, Bergman Minimal Model, and Sorensen Model, to test its robustness with respect to uncertain dynamics, and patients' parameter variability. The controller designed based on the simulations is tested with the specific Bergman Minimal Model of a diabetic patient whose parameters were identified from an in vivo assay. To minimize the insulin infusion rate, and avoid the hypoglycemia risk, the glucose target is a dynamical profile.

Populational Growth Models Proportional to Beta Densities with Allee Effect

NASA Astrophysics Data System (ADS)

Aleixo, Sandra M.; Rocha, J. Leonel; Pestana, Dinis D.

2009-05-01

We consider populations growth models with Allee effect, proportional to beta densities with shape parameters p and 2, where the dynamical complexity is related with the Malthusian parameter r. For p>2, these models exhibit a population dynamics with natural Allee effect. However, in the case of 1

Quantum critical fluctuations in disordered d-wave superconductors.

PubMed

Meyer, Julia S; Gornyi, Igor V; Altland, Alexander

2003-03-14

To explain the strong quasiparticle damping in the cuprates, Sachdev and collaborators proposed to couple the system to a critically fluctuating id(xy)- or is-order parameter mode. Here we generalize the approach to the presence of static disorder. In the id case, the order parameter dynamics becomes diffusive, but otherwise much of the phenomenology of the clean case remains intact. In contrast, the interplay of disorder and is-order parameter fluctuations leads to a secondary superconductor transition, with a critical temperature exponentially sensitive to the impurity concentration.

The surface-induced spatial-temporal structures in confined binary alloys

NASA Astrophysics Data System (ADS)

Krasnyuk, Igor B.; Taranets, Roman M.; Chugunova, Marina

2014-12-01

This paper examines surface-induced ordering in confined binary alloys. The hyperbolic initial boundary value problem (IBVP) is used to describe a scenario of spatiotemporal ordering in a disordered phase for concentration of one component of binary alloy and order parameter with non-linear dynamic boundary conditions. This hyperbolic model consists of two coupled second order differential equations for order parameter and concentration. It also takes into account effects of the “memory” on the ordering of atoms and their densities in the alloy. The boundary conditions characterize surface velocities of order parameter and concentration changing which is due to surface (super)cooling on walls confining the binary alloy. It is shown that for large times there are three classes of dynamic non-linear boundary conditions which lead to three different types of attractor’s elements for the IBVP. Namely, the elements of attractor are the limit periodic simple shock waves with fronts of “discontinuities” Γ. If Γ is finite, then the attractor contains spatiotemporal functions of relaxation type. If Γ is infinite and countable then we observe the functions of pre-turbulent type. If Γ is infinite and uncountable then we obtain the functions of turbulent type.

Banding of NMR-derived Methyl Order Parameters: Implications for Protein Dynamics

PubMed Central

Sharp, Kim A.; Kasinath, Vignesh; Wand, A. Joshua

2014-01-01

Our understanding of protein folding, stability and function has begun to more explicitly incorporate dynamical aspects. Nuclear magnetic resonance has emerged as a powerful experimental method for obtaining comprehensive site-resolved insight into protein motion. It has been observed that methyl-group motion tends to cluster into three “classes” when expressed in terms of the popular Lipari-Szabo model-free squared generalized order parameter. Here the origins of the three classes or bands in the distribution of order parameters are examined. As a first step, a Bayesian based approach, which makes no a priori assumption about the existence or number of bands, is developed to detect the banding of O2axis values derived either from NMR experiments or molecular dynamics simulations. The analysis is applied to seven proteins with extensive molecular dynamics simulations of these proteins in explicit water to examine the relationship between O2 and fine details of the motion of methyl bearing side chains. All of the proteins studied display banding, with some subtle differences. We propose a very simple yet plausible physical mechanism for banding. Finally, our Bayesian method is used to analyze the measured distributions of methyl group motions in the catabolite activating protein and several of its mutants in various liganded states and discuss the functional implications of the observed banding to protein dynamics and function. PMID:24677353

Experiment design for pilot identification in compensatory tracking tasks

NASA Technical Reports Server (NTRS)

Wells, W. R.

1976-01-01

A design criterion for input functions in laboratory tracking tasks resulting in efficient parameter estimation is formulated. The criterion is that the statistical correlations between pairs of parameters be reduced in order to minimize the problem of nonuniqueness in the extraction process. The effectiveness of the method is demonstrated for a lower order dynamic system.

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higherorder dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Magnetic field effect on the structural properties of a peptide model: Molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Housaindokht, Mohammad Reza; Moosavi, Fatemeh

2018-06-01

The effect of magnetization on the properties of a system containing a peptide model is studied by molecular dynamics simulation at a range of 298-318 K. Two mole fractions of 0.001 and 0.002 of peptide were simulated and the variation of hydrogen bond number, orientational ordering parameter, gyration radius, mean square displacement, as well as radial distribution function, were under consideration. The results show that applying magnetic field will increase the number of hydrogen bonds between water molecules by clustering them and decreases the interaction of water and peptide. This reduction may cause more available free space and enhance the movement of the peptide. As a result, the diffusion coefficient of the peptide becomes greater and its conformation changes. Orientational ordering parameter besides radius of gyration demonstrates that peptide is expanded by static magnetic field and its orientational ordering parameter is affected.

X-ray microtomography study of the compaction process of rods under tapping.

PubMed

Fu, Yang; Xi, Yan; Cao, Yixin; Wang, Yujie

2012-05-01

We present an x-ray microtomography study of the compaction process of cylindrical rods under tapping. The process is monitored by measuring the evolution of the orientational order parameter, local, and overall packing densities as a function of the tapping number for different tapping intensities. The slow relaxation dynamics of the orientational order parameter can be well fitted with a stretched-exponential law with stretching exponents ranging from 0.9 to 1.6. The corresponding relaxation time versus tapping intensity follows an Arrhenius behavior which is reminiscent of the slow dynamics in thermal glassy systems. We also investigated the boundary effect on the ordering process and found that boundary rods order faster than interior ones. In searching for the underlying mechanism of the slow dynamics, we estimated the initial random velocities of the rods under tapping and found that the ordering process is compatible with a diffusion mechanism. The average coordination number as a function of the tapping number at different tapping intensities has also been measured, which spans a range from 6 to 8.

Controlling flexible structures with second order actuator dynamics

NASA Technical Reports Server (NTRS)

Inman, Daniel J.; Umland, Jeffrey W.; Bellos, John

1989-01-01

The control of flexible structures for those systems with actuators that are modeled by second order dynamics is examined. Two modeling approaches are investigated. First a stability and performance analysis is performed using a low order finite dimensional model of the structure. Secondly, a continuum model of the flexible structure to be controlled, coupled with lumped parameter second order dynamic models of the actuators performing the control is used. This model is appropriate in the modeling of the control of a flexible panel by proof-mass actuators as well as other beam, plate and shell like structural numbers. The model is verified with experimental measurements.

Radiation characteristics and implosion dynamics of Z-pinch dynamic hohlraums performed on PTS facility

NASA Astrophysics Data System (ADS)

Huang, Xian Bin; Ren, Xiao Dong; Dan, Jia Kun; Wang, Kun Lun; Xu, Qiang; Zhou, Shao Tong; Zhang, Si Qun; Cai, Hong Chun; Li, Jing; Wei, Bing; Ji, Ce; Feng, Shu Ping; Wang, Meng; Xie, Wei Ping; Deng, Jian Jun

2017-09-01

The preliminary experimental results of Z-pinch dynamic hohlraums conducted on the Primary Test Stand (PTS) facility are presented herein. Six different types of dynamic hohlraums were used in order to study the influence of load parameters on radiation characteristics and implosion dynamics, including dynamic hohlraums driven by single and nested arrays with different array parameters and different foams. The PTS facility can deliver a current of 6-8 MA in the peak current and 60-70 ns in the 10%-90% rising time to dynamic hohlraum loads. A set of diagnostics monitor the implosion dynamics of plasmas, the evolution of shock waves in the foam and the axial/radial X-ray radiation, giving the key parameters characterizing the features of dynamic hohlraums, such as the trajectory and related velocity of shock waves, radiation temperature, and so on. The experimental results presented here put our future study on Z-pinch dynamic hohlraums on the PTS facility on a firm basis.

Hierarchical Order Parameters for Macromolecular Assembly Simulations I: Construction and Dynamical Properties of Order Parameters

PubMed Central

Singharoy, Abhishek; Sereda, Yuriy

2012-01-01

Macromolecular assemblies often display a hierarchical organization of macromolecules or their sub-assemblies. To model this, we have formulated a space warping method that enables capturing overall macromolecular structure and dynamics via a set of coarse-grained order parameters (OPs). This article is the first of two describing the construction and computational implementation of an additional class of OPs that has built into them the hierarchical architecture of macromolecular assemblies. To accomplish this, first, the system is divided into subsystems, each of which is described via a representative set of OPs. Then, a global set of variables is constructed from these subsystem-centered OPs to capture overall system organization. Dynamical properties of the resulting OPs are compared to those of our previous nonhierarchical ones, and implied conceptual and computational advantages are discussed for a 100ns, 2 million atom solvated Human Papillomavirus-like particle simulation. In the second article, the hierarchical OPs are shown to enable a multiscale analysis that starts with the N-atom Liouville equation and yields rigorous Langevin equations of stochastic OP dynamics. The latter is demonstrated via a force-field based simulation algorithm that probes key structural transition pathways, simultaneously accounting for all-atom details and overall structure. PMID:22661911

Identification of dynamic systems, theory and formulation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1985-01-01

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Kibble-Zurek scaling and string-net coarsening in topologically ordered systems.

PubMed

Chandran, Anushya; Burnell, F J; Khemani, Vedika; Sondhi, S L

2013-10-09

We consider the non-equilibrium dynamics of topologically ordered systems 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 late stages of the process are seen to exhibit a slow, coarsening dynamics for the string-net that underlies the physics of the topological phase, a potentially interesting signature of topological order. We illustrate these phenomena in the context of particular phase transitions out of the Abelian Z2 topologically ordered phase of the toric code/Z2 gauge theory, and the non-Abelian SU(2)k ordered phases of the relevant Levin-Wen models.

Systematic expansion in the order parameter for replica theory of the dynamical glass transition.

PubMed

Jacquin, Hugo; Zamponi, Francesco

2013-03-28

It has been shown recently that predictions from mode-coupling theory for the glass transition of hard-spheres become increasingly bad when dimensionality increases, whereas replica theory predicts a correct scaling. Nevertheless if one focuses on the regime around the dynamical transition in three dimensions, mode-coupling results are far more convincing than replica theory predictions. It seems thus necessary to reconcile the two theoretic approaches in order to obtain a theory that interpolates between low-dimensional, mode-coupling results, and "mean-field" results from replica theory. Even though quantitative results for the dynamical transition issued from replica theory are not accurate in low dimensions, two different approximation schemes--small cage expansion and replicated hyper-netted-chain (RHNC)--provide the correct qualitative picture for the transition, namely, a discontinuous jump of a static order parameter from zero to a finite value. The purpose of this work is to develop a systematic expansion around the RHNC result in powers of the static order parameter, and to calculate the first correction in this expansion. Interestingly, this correction involves the static three-body correlations of the liquid. More importantly, we separately demonstrate that higher order terms in the expansion are quantitatively relevant at the transition, and that the usual mode-coupling kernel, involving two-body direct correlation functions of the liquid, cannot be recovered from static computations.

Thermal nanostructure: An order parameter multiscale ensemble approach

NASA Astrophysics Data System (ADS)

Cheluvaraja, S.; Ortoleva, P.

2010-02-01

Deductive all-atom multiscale techniques imply that many nanosystems can be understood in terms of the slow dynamics of order parameters that coevolve with the quasiequilibrium probability density for rapidly fluctuating atomic configurations. The result of this multiscale analysis is a set of stochastic equations for the order parameters whose dynamics is driven by thermal-average forces. We present an efficient algorithm for sampling atomistic configurations in viruses and other supramillion atom nanosystems. This algorithm allows for sampling of a wide range of configurations without creating an excess of high-energy, improbable ones. It is implemented and used to calculate thermal-average forces. These forces are then used to search the free-energy landscape of a nanosystem for deep minima. The methodology is applied to thermal structures of Cowpea chlorotic mottle virus capsid. The method has wide applicability to other nanosystems whose properties are described by the CHARMM or other interatomic force field. Our implementation, denoted SIMNANOWORLD™, achieves calibration-free nanosystem modeling. Essential atomic-scale detail is preserved via a quasiequilibrium probability density while overall character is provided via predicted values of order parameters. Applications from virology to the computer-aided design of nanocapsules for delivery of therapeutic agents and of vaccines for nonenveloped viruses are envisioned.

Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

NASA Astrophysics Data System (ADS)

Mata-Machuca, Juan L.; Aguilar-López, Ricardo

2018-01-01

This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

Determination of power system component parameters using nonlinear dead beat estimation method

NASA Astrophysics Data System (ADS)

Kolluru, Lakshmi

Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are introduced in the virtual test systems and the dynamic data obtained in each case is analyzed and recorded. Ideally, actual measurements are to be provided to the algorithm. As the measurements are not readily available the data obtained from simulations is fed into the determination algorithm as inputs. The obtained results are then compared to the original (or assumed) values of the parameters. The results obtained suggest that the algorithm is able to determine the parameters of a synchronous machine when crisp data is available.

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

PubMed Central

Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

2014-01-01

A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

A 3D generic inverse dynamic method using wrench notation and quaternion algebra.

PubMed

Dumas, R; Aissaoui, R; de Guise, J A

2004-06-01

In the literature, conventional 3D inverse dynamic models are limited in three aspects related to inverse dynamic notation, body segment parameters and kinematic formalism. First, conventional notation yields separate computations of the forces and moments with successive coordinate system transformations. Secondly, the way conventional body segment parameters are defined is based on the assumption that the inertia tensor is principal and the centre of mass is located between the proximal and distal ends. Thirdly, the conventional kinematic formalism uses Euler or Cardanic angles that are sequence-dependent and suffer from singularities. In order to overcome these limitations, this paper presents a new generic method for inverse dynamics. This generic method is based on wrench notation for inverse dynamics, a general definition of body segment parameters and quaternion algebra for the kinematic formalism.

The geometric field (gravity) as an electro-chemical potential in a Ginzburg-Landau theory of superconductivity

NASA Astrophysics Data System (ADS)

Atanasov, Victor

2017-07-01

We extend the superconductor's free energy to include an interaction of the order parameter with the curvature of space-time. This interaction leads to geometry dependent coherence length and Ginzburg-Landau parameter which suggests that the curvature of space-time can change the superconductor's type. The curvature of space-time doesn't affect the ideal diamagnetism of the superconductor but acts as chemical potential. In a particular circumstance, the geometric field becomes order-parameter dependent, therefore the superconductor's order parameter dynamics affects the curvature of space-time and electrical or internal quantum mechanical energy can be channelled into the curvature of space-time. Experimental consequences are discussed.

Approximate optimal guidance for the advanced launch system

NASA Technical Reports Server (NTRS)

Feeley, T. S.; Speyer, J. L.

1993-01-01

A real-time guidance scheme for the problem of maximizing the payload into orbit subject to the equations of motion for a rocket over a spherical, non-rotating earth is presented. An approximate optimal launch guidance law is developed based upon an asymptotic expansion of the Hamilton - Jacobi - Bellman or dynamic programming equation. The expansion is performed in terms of a small parameter, which is used to separate the dynamics of the problem into primary and perturbation dynamics. For the zeroth-order problem the small parameter is set to zero and a closed-form solution to the zeroth-order expansion term of Hamilton - Jacobi - Bellman equation is obtained. Higher-order terms of the expansion include the effects of the neglected perturbation dynamics. These higher-order terms are determined from the solution of first-order linear partial differential equations requiring only the evaluation of quadratures. This technique is preferred as a real-time, on-line guidance scheme to alternative numerical iterative optimization schemes because of the unreliable convergence properties of these iterative guidance schemes and because the quadratures needed for the approximate optimal guidance law can be performed rapidly and by parallel processing. Even if the approximate solution is not nearly optimal, when using this technique the zeroth-order solution always provides a path which satisfies the terminal constraints. Results for two-degree-of-freedom simulations are presented for the simplified problem of flight in the equatorial plane and compared to the guidance scheme generated by the shooting method which is an iterative second-order technique.

Nonequilibrium critical dynamics of the two-dimensional Ashkin-Teller model at the Baxter line

NASA Astrophysics Data System (ADS)

Fernandes, H. A.; da Silva, R.; Caparica, A. A.; de Felício, J. R. Drugowich

2017-04-01

We investigate the short-time universal behavior of the two-dimensional Ashkin-Teller model at the Baxter line by performing time-dependent Monte Carlo simulations. First, as preparatory results, we obtain the critical parameters by searching the optimal power-law decay of the magnetization. Thus, the dynamic critical exponents θm and θp, related to the magnetic and electric order parameters, as well as the persistence exponent θg, are estimated using heat-bath Monte Carlo simulations. In addition, we estimate the dynamic exponent z and the static critical exponents β and ν for both order parameters. We propose a refined method to estimate the static exponents that considers two different averages: one that combines an internal average using several seeds with another, which is taken over temporal variations in the power laws. Moreover, we also performed the bootstrapping method for a complementary analysis. Our results show that the ratio β /ν exhibits universal behavior along the critical line corroborating the conjecture for both magnetization and polarization.

15N CSA tensors and 15N-1H dipolar couplings of protein hydrophobic core residues investigated by static solid-state NMR

NASA Astrophysics Data System (ADS)

Vugmeyster, Liliya; Ostrovsky, Dmitry; Fu, Riqiang

2015-10-01

In this work, we assess the usefulness of static 15N NMR techniques for the determination of the 15N chemical shift anisotropy (CSA) tensor parameters and 15N-1H dipolar splittings in powder protein samples. By using five single labeled samples of the villin headpiece subdomain protein in a hydrated lyophilized powder state, we determine the backbone 15N CSA tensors at two temperatures, 22 and -35 °C, in order to get a snapshot of the variability across the residues and as a function of temperature. All sites probed belonged to the hydrophobic core and most of them were part of α-helical regions. The values of the anisotropy (which include the effect of the dynamics) varied between 130 and 156 ppm at 22 °C, while the values of the asymmetry were in the 0.32-0.082 range. The Leu-75 and Leu-61 backbone sites exhibited high mobility based on the values of their temperature-dependent anisotropy parameters. Under the assumption that most differences stem from dynamics, we obtained the values of the motional order parameters for the 15N backbone sites. While a simple one-dimensional line shape experiment was used for the determination of the 15N CSA parameters, a more advanced approach based on the ;magic sandwich; SAMMY pulse sequence (Nevzorov and Opella, 2003) was employed for the determination of the 15N-1H dipolar patterns, which yielded estimates of the dipolar couplings. Accordingly, the motional order parameters for the dipolar interaction were obtained. It was found that the order parameters from the CSA and dipolar measurements are highly correlated, validating that the variability between the residues is governed by the differences in dynamics. The values of the parameters obtained in this work can serve as reference values for developing more advanced magic-angle spinning recoupling techniques for multiple labeled samples.

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

PubMed

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

2016-01-01

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

Spin-Mechanical Inertia in Antiferromagnet

NASA Astrophysics Data System (ADS)

Cheng, Ran; Wu, Xiaochuan; Xiao, Di

Interplay between spin dynamics and mechanical motions is responsible for numerous striking phenomena, which has shaped a rapidly expanding field known as spin-mechanics. The guiding principle of this field has been the conservation of angular momentum that involves both quantum spins and classical mechanical rotations. However, in an antiferromagnet, the macroscopic magnetization vanishes while the order parameter (Néel order) does not carry an angular momentum. It is therefore not clear whether the order parameter dynamics has any mechanical consequence as its ferromagnetic counterparts. Here we demonstrate that the Néel order dynamics affects the mechanical motion of a rigid body by modifying its inertia tensor in the presence of strong magnetocrystalline anisotropy. This effect depends on temperature when magnon excitations are considered. Such a spin-mechanical inertia can produce measurable consequences at nanometer scales. Our discovery establishes spin-mechanical inertia as an essential ingredient to properly describe spin-mechanical effects in AFs, which supplements the known governing physics from angular momentum conservation. This work was supported by the DOE, Basic Energy Sciences, Grant No. DE-SC0012509. D.X. also acknowledges support from a Research Corporation for Science Advancement Cottrell Scholar Award.

Nonequilibrium lattice-driven dynamics of stripes in nickelates using time-resolved x-ray scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, W. S.; Kung, Y. F.; Moritz, B.

We investigate the lattice coupling to the spin and charge orders in the striped nickelate, La 1.75 Sr 0.25 NiO 4 , using time-resolved resonant x-ray scattering. Lattice-driven dynamics of both spin and charge orders are observed when the pump photon energy is tuned to that of an E u bond- stretching phonon. We present a likely scenario for the behavior of the spin and charge order parameters and its implications using a Ginzburg-Landau theory.

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

A Smoluchowski model of crystallization dynamics of small colloidal clusters

NASA Astrophysics Data System (ADS)

Beltran-Villegas, Daniel J.; Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.; Bevan, Michael A.

2011-10-01

We investigate the dynamics of colloidal crystallization in a 32-particle system at a fixed value of interparticle depletion attraction that produces coexisting fluid and solid phases. Free energy landscapes (FELs) and diffusivity landscapes (DLs) are obtained as coefficients of 1D Smoluchowski equations using as order parameters either the radius of gyration or the average crystallinity. FELs and DLs are estimated by fitting the Smoluchowski equations to Brownian dynamics (BD) simulations using either linear fits to locally initiated trajectories or global fits to unbiased trajectories using Bayesian inference. The resulting FELs are compared to Monte Carlo Umbrella Sampling results. The accuracy of the FELs and DLs for modeling colloidal crystallization dynamics is evaluated by comparing mean first-passage times from BD simulations with analytical predictions using the FEL and DL models. While the 1D models accurately capture dynamics near the free energy minimum fluid and crystal configurations, predictions near the transition region are not quantitatively accurate. A preliminary investigation of ensemble averaged 2D order parameter trajectories suggests that 2D models are required to capture crystallization dynamics in the transition region.

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Variational path integral molecular dynamics and hybrid Monte Carlo algorithms using a fourth order propagator with applications to molecular systems

NASA Astrophysics Data System (ADS)

Kamibayashi, Yuki; Miura, Shinichi

2016-08-01

In the present study, variational path integral molecular dynamics and associated hybrid Monte Carlo (HMC) methods have been developed on the basis of a fourth order approximation of a density operator. To reveal various parameter dependence of physical quantities, we analytically solve one dimensional harmonic oscillators by the variational path integral; as a byproduct, we obtain the analytical expression of the discretized density matrix using the fourth order approximation for the oscillators. Then, we apply our methods to realistic systems like a water molecule and a para-hydrogen cluster. In the HMC, we adopt two level description to avoid the time consuming Hessian evaluation. For the systems examined in this paper, the HMC method is found to be about three times more efficient than the molecular dynamics method if appropriate HMC parameters are adopted; the advantage of the HMC method is suggested to be more evident for systems described by many body interaction.

Mean field study of a propagation-turnover lattice model for the dynamics of histone marking

NASA Astrophysics Data System (ADS)

Yao, Fan; Li, FangTing; Li, TieJun

2017-02-01

We present a mean field study of a propagation-turnover lattice model, which was proposed by Hodges and Crabtree [Proc. Nat. Acad. Sci. 109, 13296 (2012)] for understanding how posttranslational histone marks modulate gene expression in mammalian cells. The kinetics of the lattice model consists of nucleation, propagation and turnover mechanisms, and exhibits second-order phase transition for the histone marking domain. We showed rigorously that the dynamics essentially depends on a non-dimensional parameter κ = k +/ k -, the ratio between the propagation and turnover rates, which has been observed in the simulations. We then studied the lowest order mean field approximation, and observed the phase transition with an analytically obtained critical parameter. The boundary layer analysis was utilized to investigate the structure of the decay profile of the mark density. We also studied the higher order mean field approximation to achieve sharper estimate of the critical transition parameter and more detailed features. The comparison between the simulation and theoretical results shows the validity of our theory.

Reduced-Order Models for the Aeroelastic Analysis of Ares Launch Vehicles

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Vatsa, Veer N.; Biedron, Robert T.

2010-01-01

This document presents the development and application of unsteady aerodynamic, structural dynamic, and aeroelastic reduced-order models (ROMs) for the ascent aeroelastic analysis of the Ares I-X flight test and Ares I crew launch vehicles using the unstructured-grid, aeroelastic FUN3D computational fluid dynamics (CFD) code. The purpose of this work is to perform computationally-efficient aeroelastic response calculations that would be prohibitively expensive via computation of multiple full-order aeroelastic FUN3D solutions. These efficient aeroelastic ROM solutions provide valuable insight regarding the aeroelastic sensitivity of the vehicles to various parameters over a range of dynamic pressures.

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

A data driven nonlinear stochastic model for blood glucose dynamics.

PubMed

Zhang, Yan; Holt, Tim A; Khovanova, Natalia

2016-03-01

The development of adequate mathematical models for blood glucose dynamics may improve early diagnosis and control of diabetes mellitus (DM). We have developed a stochastic nonlinear second order differential equation to describe the response of blood glucose concentration to food intake using continuous glucose monitoring (CGM) data. A variational Bayesian learning scheme was applied to define the number and values of the system's parameters by iterative optimisation of free energy. The model has the minimal order and number of parameters to successfully describe blood glucose dynamics in people with and without DM. The model accounts for the nonlinearity and stochasticity of the underlying glucose-insulin dynamic process. Being data-driven, it takes full advantage of available CGM data and, at the same time, reflects the intrinsic characteristics of the glucose-insulin system without detailed knowledge of the physiological mechanisms. We have shown that the dynamics of some postprandial blood glucose excursions can be described by a reduced (linear) model, previously seen in the literature. A comprehensive analysis demonstrates that deterministic system parameters belong to different ranges for diabetes and controls. Implications for clinical practice are discussed. This is the first study introducing a continuous data-driven nonlinear stochastic model capable of describing both DM and non-DM profiles. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Vowel selection and its effects on perturbation and nonlinear dynamic measures.

PubMed

Maccallum, Julia K; Zhang, Yu; Jiang, Jack J

2011-01-01

Acoustic analysis of voice is typically conducted on recordings of sustained vowel phonation. This study applied perturbation and nonlinear dynamic analyses to the vowels /a/, /i/, and /u/ in order to determine vowel selection effects on analysis. Forty subjects (20 males and 20 females) with normal voices participated in recording. Traditional parameters of fundamental frequency, signal-to-noise ratio, percent jitter, and percent shimmer were calculated for the signals using CSpeech. Nonlinear dynamic parameters of correlation dimension and second-order entropy were also calculated. Perturbation analysis results were largely incongruous in this study and in previous research. Fundamental frequency results corroborated previous work, indicating higher fundamental frequency for /i/ and /u/ and lower fundamental frequency for /a/. Signal-to-noise ratio results showed that /i/ and /u/ have greater harmonic levels than /a/. Results of nonlinear dynamic analysis suggested that more complex activity may be evident in /a/ than in /i/ or /u/. Percent jitter and percent shimmer may not be useful for description of acoustic differences between vowels. Fundamental frequency, signal-to-noise ratio, and nonlinear dynamic parameters may be applied to characterize /a/ as having lower frequency, higher noise, and greater nonlinear components than /i/ and /u/. Copyright © 2010 S. Karger AG, Basel.

Natural extension of fast-slow decomposition for dynamical systems

NASA Astrophysics Data System (ADS)

Rubin, J. E.; Krauskopf, B.; Osinga, H. M.

2018-01-01

Modeling and parameter estimation to capture the dynamics of physical systems are often challenging because many parameters can range over orders of magnitude and are difficult to measure experimentally. Moreover, selecting a suitable model complexity requires a sufficient understanding of the model's potential use, such as highlighting essential mechanisms underlying qualitative behavior or precisely quantifying realistic dynamics. We present an approach that can guide model development and tuning to achieve desired qualitative and quantitative solution properties. It relies on the presence of disparate time scales and employs techniques of separating the dynamics of fast and slow variables, which are well known in the analysis of qualitative solution features. We build on these methods to show how it is also possible to obtain quantitative solution features by imposing designed dynamics for the slow variables in the form of specified two-dimensional paths in a bifurcation-parameter landscape.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part I: Model development and observability analysis

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Fan, Guodong; Pan, Ke; Wei, Guo; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

The design of a lumped parameter battery model preserving physical meaning is especially desired by the automotive researchers and engineers due to the strong demand for battery system control, estimation, diagnosis and prognostics. In light of this, a novel simplified fractional order electrochemical model is developed for electric vehicle (EV) applications in this paper. In the model, a general fractional order transfer function is designed for the solid phase lithium ion diffusion approximation. The dynamic characteristics of the electrolyte concentration overpotential are approximated by a first-order resistance-capacitor transfer function in the electrolyte phase. The Ohmic resistances and electrochemical reaction kinetics resistance are simplified to a lumped Ohmic resistance parameter. Overall, the number of model parameters is reduced from 30 to 9, yet the accuracy of the model is still guaranteed. In order to address the dynamics of phase-change phenomenon in the active particle during charging and discharging, variable solid-state diffusivity is taken into consideration in the model. Also, the observability of the model is analyzed on two types of lithium ion batteries subsequently. Results show the fractional order model with variable solid-state diffusivity agrees very well with experimental data at various current input conditions and is suitable for electric vehicle applications.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

PubMed

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-09-21

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

A reduced adaptive observer for multivariable systems. [using reduced dynamic ordering

NASA Technical Reports Server (NTRS)

Carroll, R. L.; Lindorff, D. P.

1973-01-01

An adaptive observer for multivariable systems is presented for which the dynamic order of the observer is reduced, subject to mild restrictions. The observer structure depends directly upon the multivariable structure of the system rather than a transformation to a single-output system. The number of adaptive gains is at most the sum of the order of the system and the number of input parameters being adapted. Moreover, for the relatively frequent specific cases for which the number of required adaptive gains is less than the sum of system order and input parameters, the number of these gains is easily determined by inspection of the system structure. This adaptive observer possesses all the properties ascribed to the single-input single-output adpative observer. Like the other adaptive observers some restriction is required of the allowable system command input to guarantee convergence of the adaptive algorithm, but the restriction is more lenient than that required by the full-order multivariable observer. This reduced observer is not restricted to cycle systems.

Maximum Entropy/Optimal Projection (MEOP) control design synthesis: Optimal quantification of the major design tradeoffs

NASA Technical Reports Server (NTRS)

Hyland, D. C.; Bernstein, D. S.

1987-01-01

The underlying philosophy and motivation of the optimal projection/maximum entropy (OP/ME) stochastic modeling and reduced control design methodology for high order systems with parameter uncertainties are discussed. The OP/ME design equations for reduced-order dynamic compensation including the effect of parameter uncertainties are reviewed. The application of the methodology to several Large Space Structures (LSS) problems of representative complexity is illustrated.

Molecular dynamics simulations on PGLa using NMR orientational constraints.

PubMed

Sternberg, Ulrich; Witter, Raiker

2015-11-01

NMR data obtained by solid state NMR from anisotropic samples are used as orientational constraints in molecular dynamics simulations for determining the structure and dynamics of the PGLa peptide within a membrane environment. For the simulation the recently developed molecular dynamics with orientational constraints technique (MDOC) is used. This method introduces orientation dependent pseudo-forces into the COSMOS-NMR force field. Acting during a molecular dynamics simulation these forces drive molecular rotations, re-orientations and folding in such a way that the motional time-averages of the tensorial NMR properties are consistent with the experimentally measured NMR parameters. This MDOC strategy does not depend on the initial choice of atomic coordinates, and is in principle suitable for any flexible and mobile kind of molecule; and it is of course possible to account for flexible parts of peptides or their side-chains. MDOC has been applied to the antimicrobial peptide PGLa and a related dimer model. With these simulations it was possible to reproduce most NMR parameters within the experimental error bounds. The alignment, conformation and order parameters of the membrane-bound molecule and its dimer were directly derived with MDOC from the NMR data. Furthermore, this new approach yielded for the first time the distribution of segmental orientations with respect to the membrane and the order parameter tensors of the dimer systems. It was demonstrated the deuterium splittings measured at the peptide to lipid ratio of 1/50 are consistent with a membrane spanning orientation of the peptide.

Dynamic interaction of monowheel inclined vehicle-vibration platform coupled system with quadratic and cubic nonlinearities

NASA Astrophysics Data System (ADS)

Zhou, Shihua; Song, Guiqiu; Sun, Maojun; Ren, Zhaohui; Wen, Bangchun

2018-01-01

In order to analyze the nonlinear dynamics and stability of a novel design for the monowheel inclined vehicle-vibration platform coupled system (MIV-VPCS) with intermediate nonlinearity support subjected to a harmonic excitation, a multi-degree of freedom lumped parameter dynamic model taking into account the dynamic interaction of the MIV-VPCS with quadratic and cubic nonlinearities is presented. The dynamical equations of the coupled system are derived by applying the displacement relationship, interaction force relationship at the contact position and Lagrange's equation, which are further discretized into a set of nonlinear ordinary differential equations with coupled terms by Galerkin's truncation. Based on the mathematical model, the coupled multi-body nonlinear dynamics of the vibration system is investigated by numerical method, and the parameters influences of excitation amplitude, mass ratio and inclined angle on the dynamic characteristics are precisely analyzed and discussed by bifurcation diagram, Largest Lyapunov exponent and 3-D frequency spectrum. Depending on different ranges of system parameters, the results show that the different motions and jump discontinuity appear, and the coupled system enters into chaotic behavior through different routes (period-doubling bifurcation, inverse period-doubling bifurcation, saddle-node bifurcation and Hopf bifurcation), which are strongly attributed to the dynamic interaction of the MIV-VPCS. The decreasing excitation amplitude and inclined angle could reduce the higher order bifurcations, and effectively control the complicated nonlinear dynamic behaviors under the perturbation of low rotational speed. The first bifurcation and chaotic motion occur at lower value of inclined angle, and the chaotic behavior lasts for larger intervals with higher rotational speed. The investigation results could provide a better understanding of the nonlinear dynamic behaviors for the dynamic interaction of the MIV-VPCS.

Solar Dynamic Power System Stability Analysis and Control

NASA Technical Reports Server (NTRS)

Momoh, James A.; Wang, Yanchun

1996-01-01

The objective of this research is to conduct dynamic analysis, control design, and control performance test of solar power system. Solar power system consists of generation system and distribution network system. A bench mark system is used in this research, which includes a generator with excitation system and governor, an ac/dc converter, six DDCU's and forty-eight loads. A detailed model is used for modeling generator. Excitation system is represented by a third order model. DDCU is represented by a seventh order system. The load is modeled by the combination of constant power and constant impedance. Eigen-analysis and eigen-sensitivity analysis are used for system dynamic analysis. The effects of excitation system, governor, ac/dc converter control, and the type of load on system stability are discussed. In order to improve system transient stability, nonlinear ac/dc converter control is introduced. The direct linearization method is used for control design. The dynamic analysis results show that these controls affect system stability in different ways. The parameter coordination of controllers are recommended based on the dynamic analysis. It is concluded from the present studies that system stability is improved by the coordination of control parameters and the nonlinear ac/dc converter control stabilize system oscillation caused by the load change and system fault efficiently.

Model-order reduction of lumped parameter systems via fractional calculus

NASA Astrophysics Data System (ADS)

Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio

2018-04-01

This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.

Regular and Chaotic Quantum Dynamics of Two-Level Atoms in a Selfconsistent Radiation Field

NASA Technical Reports Server (NTRS)

Konkov, L. E.; Prants, S. V.

1996-01-01

Dynamics of two-level atoms interacting with their own radiation field in a single-mode high-quality resonator is considered. The dynamical system consists of two second-order differential equations, one for the atomic SU(2) dynamical-group parameter and another for the field strength. With the help of the maximal Lyapunov exponent for this set, we numerically investigate transitions from regularity to deterministic quantum chaos in such a simple model. Increasing the collective coupling constant b is identical with 8(pi)N(sub 0)(d(exp 2))/hw, we observed for initially unexcited atoms a usual sharp transition to chaos at b(sub c) approx. equal to 1. If we take the dimensionless individual Rabi frequency a = Omega/2w as a control parameter, then a sequence of order-to-chaos transitions has been observed starting with the critical value a(sub c) approx. equal to 0.25 at the same initial conditions.

On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

NASA Astrophysics Data System (ADS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

2017-10-01

With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

Nonequilibrium lattice-driven dynamics of stripes in nickelates using time-resolved x-ray scattering

DOE PAGES

Lee, W. S.; Kung, Y. F.; Moritz, B.; ...

2017-03-13

Here, we investigate the lattice coupling to the spin and charge orders in the striped nickelate, La 1.75 Sr 0.25 NiO 4, using time-resolved resonant x-ray scattering. Lattice-driven dynamics of both spin and charge orders are observed when the pump photon energy is tuned to that of an E u bond- stretching phonon. We present a likely scenario for the behavior of the spin and charge order parameters and its implications using a Ginzburg-Landau theory.

New multirate sampled-data control law structure and synthesis algorithm

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.; Yang, Gen-Sheng

1992-01-01

A new multirate sampled-data control law structure is defined and a new parameter-optimization-based synthesis algorithm for that structure is introduced. The synthesis algorithm can be applied to multirate, multiple-input/multiple-output, sampled-data control laws having a prescribed dynamic order and structure, and a priori specified sampling/update rates for all sensors, processor states, and control inputs. The synthesis algorithm is applied to design two-input, two-output tip position controllers of various dynamic orders for a sixth-order, two-link robot arm model.

Nonequilibrium lattice-driven dynamics of stripes in nickelates using time-resolved x-ray scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, W. S.; Kung, Y. F.; Moritz, B.

Here, we investigate the lattice coupling to the spin and charge orders in the striped nickelate, La 1.75 Sr 0.25 NiO 4, using time-resolved resonant x-ray scattering. Lattice-driven dynamics of both spin and charge orders are observed when the pump photon energy is tuned to that of an E u bond- stretching phonon. We present a likely scenario for the behavior of the spin and charge order parameters and its implications using a Ginzburg-Landau theory.

Non-linear dynamic analysis of geared systems, part 2

NASA Technical Reports Server (NTRS)

Singh, Rajendra; Houser, Donald R.; Kahraman, Ahmet

1990-01-01

A good understanding of the steady state dynamic behavior of a geared system is required in order to design reliable and quiet transmissions. This study focuses on a system containing a spur gear pair with backlash and periodically time-varying mesh stiffness, and rolling element bearings with clearance type non-linearities. A dynamic finite element model of the linear time-invariant (LTI) system is developed. Effects of several system parameters, such as torsional and transverse flexibilities of the shafts and prime mover/load inertias, on free and force vibration characteristics are investigated. Several reduced order LTI models are developed and validated by comparing their eigen solution with the finite element model results. Several key system parameters such as mean load and damping ratio are identified and their effects on the non-linear frequency response are evaluated quantitatively. Other fundamental issues such as the dynamic coupling between non-linear modes, dynamic interactions between component non-linearities and time-varying mesh stiffness, and the existence of subharmonic and chaotic solutions including routes to chaos have also been examined in depth.

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Optimization of hydraulic turbine governor parameters based on WPA

NASA Astrophysics Data System (ADS)

Gao, Chunyang; Yu, Xiangyang; Zhu, Yong; Feng, Baohao

2018-01-01

The parameters of hydraulic turbine governor directly affect the dynamic characteristics of the hydraulic unit, thus affecting the regulation capacity and the power quality of power grid. The governor of conventional hydropower unit is mainly PID governor with three adjustable parameters, which are difficult to set up. In order to optimize the hydraulic turbine governor, this paper proposes wolf pack algorithm (WPA) for intelligent tuning since the good global optimization capability of WPA. Compared with the traditional optimization method and PSO algorithm, the results show that the PID controller designed by WPA achieves a dynamic quality of hydraulic system and inhibits overshoot.

Semiclassical dynamics of spin density waves

NASA Astrophysics Data System (ADS)

Chern, Gia-Wei; Barros, Kipton; Wang, Zhentao; Suwa, Hidemaro; Batista, Cristian D.

2018-01-01

We present a theoretical framework for equilibrium and nonequilibrium dynamical simulation of quantum states with spin-density-wave (SDW) order. Within a semiclassical adiabatic approximation that retains electron degrees of freedom, we demonstrate that the SDW order parameter obeys a generalized Landau-Lifshitz equation. With the aid of an enhanced kernel polynomial method, our linear-scaling quantum Landau-Lifshitz dynamics (QLLD) method enables dynamical SDW simulations with N ≃105 lattice sites. Our real-space formulation can be used to compute dynamical responses, such as the dynamical structure factor, of complex and even inhomogeneous SDW configurations at zero or finite temperatures. Applying the QLLD to study the relaxation of a noncoplanar topological SDW under the excitation of a short pulse, we further demonstrate the crucial role of spatial correlations and fluctuations in the SDW dynamics.

Robust fixed order dynamic compensation for large space structure control

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Byrns, Edward V., Jr.

1989-01-01

A simple formulation for designing fixed order dynamic compensators which are robust to both uncertainty at the plant input and structured uncertainty in the plant dynamics is presented. The emphasis is on designing low order compensators for systems of high order. The formulation is done in an output feedback setting which exploits an observer canonical form to represent the compensator dynamics. The formulation also precludes the use of direct feedback of the plant output. The main contribution lies in defining a method for penalizing the states of the plant and of the compensator, and for choosing the distribution on initial conditions so that the loop transfer matrix approximates that of a full state design. To improve robustness to parameter uncertainty, the formulation avoids the introduction of sensitivity states, which has led to complex formulations in earlier studies where only structured uncertainty has been considered.

Computational Study of Chaotic and Ordered Solutions of the Kuramoto-Sivashinsky Equation

NASA Technical Reports Server (NTRS)

Smyrlis, Yiorgos S.; Papageorgiou, Demetrios T.

1996-01-01

We report the results of extensive numerical experiments on the Kuramoto-Sivashinsky equation in the strongly chaotic regime as the viscosity parameter is decreased and increasingly more linearly unstable modes enter the dynamics. General initial conditions are used and evolving states do not assume odd-parity. A large number of numerical experiments are employed in order to obtain quantitative characteristics of the dynamics. We report on different routes to chaos and provide numerical evidence and construction of strange attractors with self-similar characteristics. As the 'viscosity' parameter decreases the dynamics becomes increasingly more complicated and chaotic. In particular it is found that regular behavior in the form of steady state or steady state traveling waves is supported amidst the time-dependent and irregular motions. We show that multimodal steady states emerge and are supported on decreasing windows in parameter space. In addition we invoke a self-similarity property of the equation, to show that these profiles are obtainable from global fixed point attractors of the Kuramoto-Sivashinsky equation at much larger values of the viscosity.

Dynamical Quantum Phase Transitions in Spin Chains with Long-Range Interactions: Merging Different Concepts of Nonequilibrium Criticality

NASA Astrophysics Data System (ADS)

Žunkovič, Bojan; Heyl, Markus; Knap, Michael; Silva, Alessandro

2018-03-01

We theoretically study the dynamics of a transverse-field Ising chain with power-law decaying interactions characterized by an exponent α , which can be experimentally realized in ion traps. We focus on two classes of emergent dynamical critical phenomena following a quantum quench from a ferromagnetic initial state: The first one manifests in the time-averaged order parameter, which vanishes at a critical transverse field. We argue that such a transition occurs only for long-range interactions α ≤2 . The second class corresponds to the emergence of time-periodic singularities in the return probability to the ground-state manifold which is obtained for all values of α and agrees with the order parameter transition for α ≤2 . We characterize how the two classes of nonequilibrium criticality correspond to each other and give a physical interpretation based on the symmetry of the time-evolved quantum states.

Self-Organized Dynamic Flocking Behavior from a Simple Deterministic Map

NASA Astrophysics Data System (ADS)

Krueger, Wesley

2007-10-01

Coherent motion exhibiting large-scale order, such as flocking, swarming, and schooling behavior in animals, can arise from simple rules applied to an initial random array of self-driven particles. We present a completely deterministic dynamic map that exhibits emergent, collective, complex motion for a group of particles. Each individual particle is driven with a constant speed in two dimensions adopting the average direction of a fixed set of non-spatially related partners. In addition, the particle changes direction by π as it reaches a circular boundary. The dynamical patterns arising from these rules range from simple circular-type convective motion to highly sophisticated, complex, collective behavior which can be easily interpreted as flocking, schooling, or swarming depending on the chosen parameters. We present the results as a series of short movies and we also explore possible order parameters and correlation functions capable of quantifying the resulting coherence.

Derivation of a hydrodynamic theory for mesoscale dynamics in microswimmer suspensions

NASA Astrophysics Data System (ADS)

Reinken, Henning; Klapp, Sabine H. L.; Bär, Markus; Heidenreich, Sebastian

2018-02-01

In this paper, we systematically derive a fourth-order continuum theory capable of reproducing mesoscale turbulence in a three-dimensional suspension of microswimmers. We start from overdamped Langevin equations for a generic microscopic model (pushers or pullers), which include hydrodynamic interactions on both small length scales (polar alignment of neighboring swimmers) and large length scales, where the solvent flow interacts with the order parameter field. The flow field is determined via the Stokes equation supplemented by an ansatz for the stress tensor. In addition to hydrodynamic interactions, we allow for nematic pair interactions stemming from excluded-volume effects. The results here substantially extend and generalize earlier findings [S. Heidenreich et al., Phys. Rev. E 94, 020601 (2016), 10.1103/PhysRevE.94.020601], in which we derived a two-dimensional hydrodynamic theory. From the corresponding mean-field Fokker-Planck equation combined with a self-consistent closure scheme, we derive nonlinear field equations for the polar and the nematic order parameter, involving gradient terms of up to fourth order. We find that the effective microswimmer dynamics depends on the coupling between solvent flow and orientational order. For very weak coupling corresponding to a high viscosity of the suspension, the dynamics of mesoscale turbulence can be described by a simplified model containing only an effective microswimmer velocity.

Estimating short-period dynamics using an extended Kalman filter

NASA Technical Reports Server (NTRS)

Bauer, Jeffrey E.; Andrisani, Dominick

1990-01-01

An extended Kalman filter (EKF) is used to estimate the parameters of a low-order model from aircraft transient response data. The low-order model is a state space model derived from the short-period approximation of the longitudinal aircraft dynamics. The model corresponds to the pitch rate to stick force transfer function currently used in flying qualities analysis. Because of the model chosen, handling qualities information is also obtained. The parameters are estimated from flight data as well as from a six-degree-of-freedom, nonlinear simulation of the aircraft. These two estimates are then compared and the discrepancies noted. The low-order model is able to satisfactorily match both flight data and simulation data from a high-order computer simulation. The parameters obtained from the EKF analysis of flight data are compared to those obtained using frequency response analysis of the flight data. Time delays and damping ratios are compared and are in agreement. This technique demonstrates the potential to determine, in near real time, the extent of differences between computer models and the actual aircraft. Precise knowledge of these differences can help to determine the flying qualities of a test aircraft and lead to more efficient envelope expansion.

Characterizing hydrophobicity at the nanoscale: a molecular dynamics simulation study.

PubMed

Bandyopadhyay, Dibyendu; Choudhury, Niharendu

2012-06-14

We use molecular dynamics (MD) simulations of water near nanoscopic surfaces to characterize hydrophobic solute-water interfaces. By using nanoscopic paraffin like plates as model solutes, MD simulations in isothermal-isobaric ensemble have been employed to identify characteristic features of such an interface. Enhanced water correlation, density fluctuations, and position dependent compressibility apart from surface specific hydrogen bond distribution and molecular orientations have been identified as characteristic features of such interfaces. Tetrahedral order parameter that quantifies the degree of tetrahedrality in the water structure and an orientational order parameter, which quantifies the orientational preferences of the second solvation shell water around a central water molecule, have also been calculated as a function of distance from the plate surface. In the vicinity of the surface these two order parameters too show considerable sensitivity to the surface hydrophobicity. The potential of mean force (PMF) between water and the surface as a function of the distance from the surface has also been analyzed in terms of direct interaction and induced contribution, which shows unusual effect of plate hydrophobicity on the solvent induced PMF. In order to investigate hydrophobic nature of these plates, we have also investigated interplate dewetting when two such plates are immersed in water.

Noether symmetry approach in the cosmological alpha-attractors

NASA Astrophysics Data System (ADS)

Kaewkhao, Narakorn; Kanesom, Thanyagamon; Channuie, Phongpichit

2018-06-01

In cosmological framework, Noether symmetry technique has revealed a useful tool in order to examine exact solutions. In this work, we first introduce the Jordan-frame Lagrangian and apply the conformal transformation in order to obtain the Lagrangian equivalent to Einstein-frame form. We then analyze the dynamics of the field in the cosmological alpha-attractors using the Noether symmetry approach by focusing on the single field scenario in the Einstein-frame form. We show that with a Noether symmetry the corresponding dynamical system can be completely integrated and the potential exhibited by the symmetry can be exactly obtained. With the proper choice of parameters, the behavior of the scale factor displays an exponential (de Sitter) behavior at the present epoch. Moreover, we discover that the Hubble parameters strongly depends on the initial values of parameters exhibited by the Noether symmetry. Interestingly, it can retardedly evolve and becomes a constant in the present epoch in all cases.

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.

PubMed

Makni, Salima; Beckmann, Christian; Smith, Steve; Woolrich, Mark

2008-10-01

In Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993], a particular case of the Linear Dynamical Systems (LDSs) was used to model the dynamic behavior of the BOLD response in functional MRI. This state-space model, called bilinear dynamical system (BDS), is used to deconvolve the fMRI time series in order to estimate the neuronal response induced by the different stimuli of the experimental paradigm. The BDS model parameters are estimated using an expectation-maximization (EM) algorithm proposed by Ghahramani and Hinton [Ghahramani, Z., Hinton, G.E. 1996. Parameter Estimation for Linear Dynamical Systems. Technical Report, Department of Computer Science, University of Toronto]. In this paper we introduce modifications to the BDS model in order to explicitly model the spatial variations of the haemodynamic response function (HRF) in the brain using a non-parametric approach. While in Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993] the relationship between neuronal activation and fMRI signals is formulated as a first-order convolution with a kernel expansion using basis functions (typically two or three), in this paper, we argue in favor of a spatially adaptive GLM in which a local non-parametric estimation of the HRF is performed. Furthermore, in order to overcome the overfitting problem typically associated with simple EM estimates, we propose a full Variational Bayes (VB) solution to infer the BDS model parameters. We demonstrate the usefulness of our model which is able to estimate both the neuronal activity and the haemodynamic response function in every voxel of the brain. We first examine the behavior of this approach when applied to simulated data with different temporal and noise features. As an example we will show how this method can be used to improve interpretability of estimates from an independent component analysis (ICA) analysis of fMRI data. We finally demonstrate its use on real fMRI data in one slice of the brain.

Local order parameters for use in driving homogeneous ice nucleation with all-atom models of water

NASA Astrophysics Data System (ADS)

Reinhardt, Aleks; Doye, Jonathan P. K.; Noya, Eva G.; Vega, Carlos

2012-11-01

We present a local order parameter based on the standard Steinhardt-Ten Wolde approach that is capable both of tracking and of driving homogeneous ice nucleation in simulations of all-atom models of water. We demonstrate that it is capable of forcing the growth of ice nuclei in supercooled liquid water simulated using the TIP4P/2005 model using over-biassed umbrella sampling Monte Carlo simulations. However, even with such an order parameter, the dynamics of ice growth in deeply supercooled liquid water in all-atom models of water are shown to be very slow, and so the computation of free energy landscapes and nucleation rates remains extremely challenging.

Comparative Sensitivity Analysis of Muscle Activation Dynamics

PubMed Central

Günther, Michael; Götz, Thomas

2015-01-01

We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379

Transverse fields to tune an Ising-nematic quantum phase transition

NASA Astrophysics Data System (ADS)

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; Berg, Erez; Fernandes, Rafael M.; Fisher, Ian R.; Kivelson, Steven A.

2017-12-01

The paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated with spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.

Conformational Entropy of FK506 Binding to FKBP12 Determined by Nuclear Magnetic Resonance Relaxation and Molecular Dynamics Simulations.

PubMed

Solomentsev, Gleb; Diehl, Carl; Akke, Mikael

2018-03-06

FKBP12 (FK506 binding protein 12 kDa) is an important drug target. Nuclear magnetic resonance (NMR) order parameters, describing amplitudes of motion on the pico- to nanosecond time scale, can provide estimates of changes in conformational entropy upon ligand binding. Here we report backbone and methyl-axis order parameters of the apo and FK506-bound forms of FKBP12, based on 15 N and 2 H NMR relaxation. Binding of FK506 to FKBP12 results in localized changes in order parameters, notably for the backbone of residues E54 and I56 and the side chains of I56, I90, and I91, all positioned in the binding site. The order parameters increase slightly upon FK506 binding, indicating an unfavorable entropic contribution to binding of TΔ S = -18 ± 2 kJ/mol at 293 K. Molecular dynamics simulations indicate a change in conformational entropy, associated with all dihedral angles, of TΔ S = -26 ± 9 kJ/mol. Both these values are significant compared to the total entropy of binding determined by isothermal titration calorimetry and referenced to a reactant concentration of 1 mM ( TΔ S = -29 ± 1 kJ/mol). Our results reveal subtle differences in the response to ligand binding compared to that of the previously studied rapamycin-FKBP12 complex, despite the high degree of structural homology between the two complexes and their nearly identical ligand-FKBP12 interactions. These results highlight the delicate dependence of protein dynamics on drug interactions, which goes beyond the view provided by static structures, and reinforce the notion that protein conformational entropy can make important contributions to the free energy of ligand binding.

Higher-order rational solitons and rogue-like wave solutions of the (2 + 1)-dimensional nonlinear fluid mechanics equations

NASA Astrophysics Data System (ADS)

Wen, Xiao-Yong; Yan, Zhenya

2017-02-01

The novel generalized perturbation (n, M)-fold Darboux transformations (DTs) are reported for the (2 + 1)-dimensional Kadomtsev-Petviashvili (KP) equation and its extension by using the Taylor expansion of the Darboux matrix. The generalized perturbation (1 , N - 1) -fold DTs are used to find their higher-order rational solitons and rogue wave solutions in terms of determinants. The dynamics behaviors of these rogue waves are discussed in detail for different parameters and time, which display the interesting RW and soliton structures including the triangle, pentagon, heptagon profiles, etc. Moreover, we find that a new phenomenon that the parameter (a) can control the wave structures of the KP equation from the higher-order rogue waves (a ≠ 0) into higher-order rational solitons (a = 0) in (x, t)-space with y = const . These results may predict the corresponding dynamical phenomena in the models of fluid mechanics and other physically relevant systems.

Robust stability of second-order systems

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1995-01-01

It has been shown recently how virtual passive controllers can be designed for second-order dynamic systems to achieve robust stability. The virtual controllers were visualized as systems made up of spring, mass and damping elements. In this paper, a new approach emphasizing on the notion of positive realness to the same second-order dynamic systems is used. Necessary and sufficient conditions for positive realness are presented for scalar spring-mass-dashpot systems. For multi-input multi-output systems, we show how a mass-spring-dashpot system can be made positive real by properly choosing its output variables. In particular, sufficient conditions are shown for the system without output velocity. Furthermore, if velocity cannot be measured then the system parameters must be precise to keep the system positive real. In practice, system parameters are not always constant and cannot be measured precisely. Therefore, in order to be useful positive real systems must be robust to some degrees. This can be achieved with the design presented in this paper.

Excitonic magnet in external field: Complex order parameter and spin currents

NASA Astrophysics Data System (ADS)

Geffroy, D.; Hariki, A.; Kuneš, J.

2018-04-01

We investigate spin-triplet exciton condensation in the two-orbital Hubbard model close to half-filling by means of dynamical mean-field theory. Employing an impurity solver that handles complex off-diagonal hybridization functions, we study the behavior of excitonic condensate in stoichiometric and doped systems subject to external magnetic field. We find a general tendency of the triplet order parameter to lie perpendicular with the applied field and identify exceptions from this rule. For solutions exhibiting k -odd spin textures, we discuss the Bloch theorem, which, in the absence of spin-orbit coupling, forbids the appearance of spontaneous net spin current. We demonstrate that the Bloch theorem is not obeyed by the dynamical mean-field theory.

Topology and entanglement in quench dynamics

NASA Astrophysics Data System (ADS)

Chang, Po-Yao

2018-06-01

We classify the topology of the quench dynamics by homotopy groups. A relation between the topological invariant of a postquench order parameter and the topological invariant of a static Hamiltonian is shown in d +1 dimensions (d =1 ,2 ,3 ). The midgap states in the entanglement spectrum of the postquench states reveal their topological nature. When a trivial quantum state is under a sudden quench to a Chern insulator, the midgap states in the entanglement spectrum form rings. These rings are analogous to the boundary Fermi rings in the Hopf insulators. Finally, we show a postquench order parameter in 3+1 dimensions can be characterized by the second Chern number. The number of Dirac cones in the entanglement spectrum is equal to the second Chern number.

Analysis of helicopter flight dynamics through modeling and simulation of primary flight control actuation system

NASA Astrophysics Data System (ADS)

Nelson, Hunter Barton

A simplified second-order transfer function actuator model used in most flight dynamics applications cannot easily capture the effects of different actuator parameters. The present work integrates a nonlinear actuator model into a nonlinear state space rotorcraft model to determine the effect of actuator parameters on key flight dynamics. The completed actuator model was integrated with a swashplate kinematics where step responses were generated over a range of key hydraulic parameters. The actuator-swashplate system was then introduced into a nonlinear state space rotorcraft simulation where flight dynamics quantities such as bandwidth and phase delay analyzed. Frequency sweeps were simulated for unique actuator configurations using the coupled nonlinear actuator-rotorcraft system. The software package CIFER was used for system identification and compared directly to the linearized models. As the actuator became rate saturated, the effects on bandwidth and phase delay were apparent on the predicted handling qualities specifications.

Reduced-order dynamic output feedback control of uncertain discrete-time Markov jump linear systems

NASA Astrophysics Data System (ADS)

Morais, Cecília F.; Braga, Márcio F.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2017-11-01

This paper deals with the problem of designing reduced-order robust dynamic output feedback controllers for discrete-time Markov jump linear systems (MJLS) with polytopic state space matrices and uncertain transition probabilities. Starting from a full order, mode-dependent and polynomially parameter-dependent dynamic output feedback controller, sufficient linear matrix inequality based conditions are provided for the existence of a robust reduced-order dynamic output feedback stabilising controller with complete, partial or none mode dependency assuring an upper bound to the ? or the ? norm of the closed-loop system. The main advantage of the proposed method when compared to the existing approaches is the fact that the dynamic controllers are exclusively expressed in terms of the decision variables of the problem. In other words, the matrices that define the controller realisation do not depend explicitly on the state space matrices associated with the modes of the MJLS. As a consequence, the method is specially suitable to handle order reduction or cluster availability constraints in the context of ? or ? dynamic output feedback control of discrete-time MJLS. Additionally, as illustrated by means of numerical examples, the proposed approach can provide less conservative results than other conditions in the literature.

Catenaries in Drag

NASA Astrophysics Data System (ADS)

Chakrabarti, Brato; Hanna, James

2014-11-01

Dynamical equilibria of towed cables and sedimenting filaments have been the targets of much numerical work; here, we provide analytical expressions for the configurations of a translating and axially moving string subjected to a uniform body force and local, linear, anisotropic drag forces. Generically, these configurations comprise a five-parameter family of planar shapes determined by the ratio of tangential (axial) and normal drag coefficients, the angle between the translational velocity and the body force, the relative magnitudes of translational and axial drag forces with respect to the body force, and a scaling parameter. This five-parameter family of shapes is, in fact, a degenerate six-parameter family of equilibria in which inertial forces rescale the tension in the string without affecting its shape. Each configuration is represented by a first order dynamical system for the tangential angle of the body. Limiting cases include the dynamic catenaries with or without drag, and purely sedimenting or towed strings.

Nonequilibrium Phase Transitions in Supercooled Water

NASA Astrophysics Data System (ADS)

Limmer, David; Chandler, David

2012-02-01

We present results of a simulation study of water driven out of equilibrium. Using transition path sampling, we can probe stationary path distributions parameterize by order parameters that are extensive in space and time. We find that by coupling external fields to these parameters, we can drive water through a first order dynamical phase transition into amorphous ice. By varying the initial equilibrium distributions we can probe pathways for the creation of amorphous ices of low and high densities.

Modeling Coronal Mass Ejections with EUHFORIA: A Parameter Study of the Gibson-Low Flux Rope Model using Multi-Viewpoint Observations

NASA Astrophysics Data System (ADS)

Verbeke, C.; Asvestari, E.; Scolini, C.; Pomoell, J.; Poedts, S.; Kilpua, E.

2017-12-01

Coronal Mass Ejections (CMEs) are one of the big influencers on the coronal and interplanetary dynamics. Understanding their origin and evolution from the Sun to the Earth is crucial in order to determine the impact on our Earth and society. One of the key parameters that determine the geo-effectiveness of the coronal mass ejection is its internal magnetic configuration. We present a detailed parameter study of the Gibson-Low flux rope model. We focus on changes in the input parameters and how these changes affect the characteristics of the CME at Earth. Recently, the Gibson-Low flux rope model has been implemented into the inner heliosphere model EUHFORIA, a magnetohydrodynamics forecasting model of large-scale dynamics from 0.1 AU up to 2 AU. Coronagraph observations can be used to constrain the kinematics and morphology of the flux rope. One of the key parameters, the magnetic field, is difficult to determine directly from observations. In this work, we approach the problem by conducting a parameter study in which flux ropes with varying magnetic configurations are simulated. We then use the obtained dataset to look for signatures in imaging observations and in-situ observations in order to find an empirical way of constraining the parameters related to the magnetic field of the flux rope. In particular, we focus on events observed by at least two spacecraft (STEREO + L1) in order to discuss the merits of using observations from multiple viewpoints in constraining the parameters.

Wall Shear Stress Distribution in a Patient-Specific Cerebral Aneurysm Model using Reduced Order Modeling

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya

2016-11-01

We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.

Linear and nonlinear spectroscopy from quantum master equations.

PubMed

Fetherolf, Jonathan H; Berkelbach, Timothy C

2017-12-28

We investigate the accuracy of the second-order time-convolutionless (TCL2) quantum master equation for the calculation of linear and nonlinear spectroscopies of multichromophore systems. We show that even for systems with non-adiabatic coupling, the TCL2 master equation predicts linear absorption spectra that are accurate over an extremely broad range of parameters and well beyond what would be expected based on the perturbative nature of the approach; non-equilibrium population dynamics calculated with TCL2 for identical parameters are significantly less accurate. For third-order (two-dimensional) spectroscopy, the importance of population dynamics and the violation of the so-called quantum regression theorem degrade the accuracy of TCL2 dynamics. To correct these failures, we combine the TCL2 approach with a classical ensemble sampling of slow microscopic bath degrees of freedom, leading to an efficient hybrid quantum-classical scheme that displays excellent accuracy over a wide range of parameters. In the spectroscopic setting, the success of such a hybrid scheme can be understood through its separate treatment of homogeneous and inhomogeneous broadening. Importantly, the presented approach has the computational scaling of TCL2, with the modest addition of an embarrassingly parallel prefactor associated with ensemble sampling. The presented approach can be understood as a generalized inhomogeneous cumulant expansion technique, capable of treating multilevel systems with non-adiabatic dynamics.

Linear and nonlinear spectroscopy from quantum master equations

NASA Astrophysics Data System (ADS)

Fetherolf, Jonathan H.; Berkelbach, Timothy C.

2017-12-01

We investigate the accuracy of the second-order time-convolutionless (TCL2) quantum master equation for the calculation of linear and nonlinear spectroscopies of multichromophore systems. We show that even for systems with non-adiabatic coupling, the TCL2 master equation predicts linear absorption spectra that are accurate over an extremely broad range of parameters and well beyond what would be expected based on the perturbative nature of the approach; non-equilibrium population dynamics calculated with TCL2 for identical parameters are significantly less accurate. For third-order (two-dimensional) spectroscopy, the importance of population dynamics and the violation of the so-called quantum regression theorem degrade the accuracy of TCL2 dynamics. To correct these failures, we combine the TCL2 approach with a classical ensemble sampling of slow microscopic bath degrees of freedom, leading to an efficient hybrid quantum-classical scheme that displays excellent accuracy over a wide range of parameters. In the spectroscopic setting, the success of such a hybrid scheme can be understood through its separate treatment of homogeneous and inhomogeneous broadening. Importantly, the presented approach has the computational scaling of TCL2, with the modest addition of an embarrassingly parallel prefactor associated with ensemble sampling. The presented approach can be understood as a generalized inhomogeneous cumulant expansion technique, capable of treating multilevel systems with non-adiabatic dynamics.

Order parameter re-mapping algorithm for 3D phase field model of grain growth using FEM

DOE PAGES

Permann, Cody J.; Tonks, Michael R.; Fromm, Bradley; ...

2016-01-14

Phase field modeling (PFM) is a well-known technique for simulating microstructural evolution. To model grain growth using PFM, typically each grain is assigned a unique non-conserved order parameter and each order parameter field is evolved in time. Traditional approaches using a one-to-one mapping of grains to order parameters present a challenge when modeling large numbers of grains due to the computational expense of using many order parameters. This problem is exacerbated when using an implicit finite element method (FEM), as the global matrix size is proportional to the number of order parameters. While previous work has developed methods to reducemore » the number of required variables and thus computational complexity and run time, none of the existing approaches can be applied for an implicit FEM implementation of PFM. Here, we present a modular, dynamic, scalable reassignment algorithm suitable for use in such a system. Polycrystal modeling with grain growth and stress require careful tracking of each grain’s position and orientation which is lost when using a reduced order parameter set. In conclusion, the method presented in this paper maintains a unique ID for each grain even after reassignment, to allow the PFM to be tightly coupled to calculations of the stress throughout the polycrystal. Implementation details and comparative results of our approach are presented.« less

Changes in conformational dynamics of basic side chains upon protein–DNA association

PubMed Central

Esadze, Alexandre; Chen, Chuanying; Zandarashvili, Levani; Roy, Sourav; Pettitt, B. Montgometry; Iwahara, Junji

2016-01-01

Basic side chains play major roles in recognition of nucleic acids by proteins. However, dynamic properties of these positively charged side chains are not well understood. In this work, we studied changes in conformational dynamics of basic side chains upon protein–DNA association for the zinc-finger protein Egr-1. By nuclear magnetic resonance (NMR) spectroscopy, we characterized the dynamics of all side-chain cationic groups in the free protein and in the complex with target DNA. Our NMR order parameters indicate that the arginine guanidino groups interacting with DNA bases are strongly immobilized, forming rigid interfaces. Despite the strong short-range electrostatic interactions, the majority of the basic side chains interacting with the DNA phosphates exhibited high mobility, forming dynamic interfaces. In particular, the lysine side-chain amino groups exhibited only small changes in the order parameters upon DNA-binding. We found a similar trend in the molecular dynamics (MD) simulations for the free Egr-1 and the Egr-1–DNA complex. Using the MD trajectories, we also analyzed side-chain conformational entropy. The interfacial arginine side chains exhibited substantial entropic loss upon binding to DNA, whereas the interfacial lysine side chains showed relatively small changes in conformational entropy. These data illustrate different dynamic characteristics of the interfacial arginine and lysine side chains. PMID:27288446

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

1990-01-01

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

Inverse problem of HIV cell dynamics using Genetic Algorithms

NASA Astrophysics Data System (ADS)

González, J. A.; Guzmán, F. S.

2017-01-01

In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

PubMed Central

Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

2017-01-01

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors. PMID:28934163

Complex collective dynamics of active torque-driven colloids at interfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snezhko, Alexey

Modern self-assembly techniques aiming to produce complex structural order or functional diversity often rely on non-equilibrium conditions in the system. Light, electric, or magnetic fields are predominantly used to modify interaction profiles of colloidal particles during self-assembly or induce complex out-of-equilibrium dynamic ordering. The energy injection rate, properties of the environment are important control parameters that influence the outcome of active (dynamic) self-assembly. The current review is focused on a case of collective dynamics and self-assembly of particles with externally driven torques coupled to a liquid or solid interface. The complexity of interactions in such systems is further enriched bymore » strong hydrodynamic coupling between particles. Unconventionally ordered dynamic self-assembled patterns, spontaneous symmetry breaking phenomena, self-propulsion, and collective transport have been reported in torque-driven colloids. Some of the features of the complex collective behavior and dynamic pattern formation in those active systems have been successfully captured in simulations.« less

Dynamics and Instabilities of the Shastry-Sutherland Model

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Batista, Cristian D.

2018-06-01

We study the excitation spectrum in the dimer phase of the Shastry-Sutherland model by using an unbiased variational method that works in the thermodynamic limit. The method outputs dynamical correlation functions in all possible channels. This output is exploited to identify the order parameters with the highest susceptibility (single or multitriplon condensation in a specific channel) upon approaching a quantum phase transition in the magnetic field versus the J'/J phase diagram. We find four different instabilities: antiferro spin nematic, plaquette spin nematic, stripe magnetic order, and plaquette order, two of which have been reported in previous studies.

Diffusion of non-Gaussianity in heavy ion collisions

NASA Astrophysics Data System (ADS)

Kitazawa, Masakiyo; Asakawa, Masayuki; Ono, Hirosato

2014-05-01

We investigate the time evolution of higher order cumulants of bulk fluctuations of conserved charges in the hadronic stage in relativistic heavy ion collisions. The dynamical evolution of non-Gaussian fluctuations is modeled by the diffusion master equation. Using this model we predict that the fourth-order cumulant of net-electric charge is suppressed compared with the recently observed second-order one at ALICE for a reasonable parameter range. Significance of the measurements of various cumulants as functions of rapidity window to probe dynamical history of the hot medium created by heavy ion collisions is emphasized.

How do ensembles occupy space?

NASA Astrophysics Data System (ADS)

Daffertshofer, A.

2008-04-01

To find an answer to the title question, an attractiveness function between agents and locations is introduced yielding a phenomenological but generic model for the search for optimal distributions of agents over space. Agents can be seen as, e.g., members of biological populations like colonies of bacteria, swarms, and so on. The global attractiveness between agents and locations is maximized causing (self-propelled) `motion' of agents and, eventually, distinct distributions of agents over space. At the same token spontaneous changes or `decisions' are realized via competitions between agents as well as between locations. Hence, the model's solutions can be considered a sequence of decisions of agents during their search for a proper location. Depending on initial conditions both optimal as well as suboptimal configurations can be reached. For the latter early decision-making are important for avoiding possible conflicts: if the proper moment is missed, then only a few agents can find an optimal solution. Indeed, there is a delicate interplay between the values of the attractiveness function and the constraints as can be expressed by distinct terms of a potential function containing different Lagrange parameters. The model should be viewed as a top-down approach as it describes the dynamics of order parameters, i.e. macroscopic variables that reflect affiliations between agents and locations. The dynamics, however, is modified via so-called cost functions that are interpreted in terms of affinity levels. This interpretation can be seen as an original step towards an understanding of the dynamics at the underlying microscopic level. When focusing on the agent, one may say that the dynamics of an order parameter shows the evolution of an agent's intrinsic `map' for solving the problem of space occupation. Importantly, the dynamics does not necessarily distinguish between evolving (or moving) agents and evolving (or moving) locations though agents are more likely to be actors than the locations. Put differently, an order parameter describes an internal map which is linked to the expectation of an agent to find a certain location. Owing to the dynamical representation, we can therefore follow up the change of these maps over time leading from uncertainty to certainty.

Broadband dynamic phase matching of high-order harmonic generation by a high-peak-power soliton pump field in a gas-filled hollow photonic-crystal fiber.

PubMed

Serebryannikov, Evgenii E; von der Linde, Dietrich; Zheltikov, Aleksei M

2008-05-01

Hollow-core photonic-crystal fibers are shown to enable dynamically phase-matched high-order harmonic generation by a gigawatt soliton pump field. With a careful design of the waveguide structure and an appropriate choice of input-pulse and gas parameters, a remarkably broadband phase matching can be achieved for a soliton pump field and a large group of optical harmonics in the soft-x-ray-extreme-ultraviolet spectral range.

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

Anomalous critical slowdown at a first order phase transition in single polymer chains.

PubMed

Zhang, Shuangshuang; Qi, Shuanhu; Klushin, Leonid I; Skvortsov, Alexander M; Yan, Dadong; Schmid, Friederike

2017-08-14

Using Brownian dynamics, we study the dynamical behavior of a polymer grafted onto an adhesive surface close to the mechanically induced adsorption-stretching transition. Even though the transition is first order (in the infinite chain length limit, the stretching degree of the chain jumps discontinuously), the characteristic relaxation time is found to grow according to a power law as the transition point is approached. We present a dynamic effective interface model which reproduces these observations and provides an excellent quantitative description of the simulation data. The generic nature of the theoretical model suggests that the unconventional mixing of features that are characteristic for first-order transitions (a jump in an order parameter) and features that are characteristic of critical points (an anomalous slowdown) may be a common phenomenon in force-driven phase transitions of macromolecules.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Sang Beom; Dsilva, Carmeline J.; Debenedetti, Pablo G., E-mail: pdebene@princeton.edu

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories inmore » a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.« less

Far-from-equilibrium magnetic granular layers: dynamic patterns, magnetic order and self-assembled swimmers

NASA Astrophysics Data System (ADS)

Snezhko, Alexey

2010-03-01

Ensembles of interacting particles subject to an external periodic forcing often develop nontrivial collective behavior and self-assembled dynamic patterns. We study emergent phenomena in magnetic granular ensembles suspended at a liquid-air and liquid-liquid interfaces and subjected to a transversal alternating magnetic field. Experiments reveal a new type of nontrivially ordered dynamic self-assembled structures (in particular, ``magnetic snakes'', ``asters'', ``clams'') emerging in such systems in a certain range of excitation parameters. These non-equilibrium dynamic structures emerge as a result of the competition between magnetic and hydrodynamic forces and have complex magnetic ordering. Transition between different self-assembled phases with parameters of external driving magnetic field is observed. I will show that above some frequency threshold magnetic snakes spontaneously break the symmetry of the self-induced surface flows (symmetry breaking instability) and turn into swimmers. Self-induced surface flows symmetry can be also broken in a controlled fashion by introduction of a large bead to a magnetic snake (bead-snake hybrid), that transforms it into a robust self-locomoting entity. Some features of the self-localized structures can be understood in the framework of an amplitude equation for parametric waves coupled to the conservation law equation describing the evolution of the magnetic particle density and the Navier-Stokes equation for hydrodynamic flows.

Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.

PubMed

Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu

2018-04-23

This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Dynamic phase transitions and dynamic phase diagrams of the Blume-Emery-Griffiths model in an oscillating field: the effective-field theory based on the Glauber-type stochastic dynamics

NASA Astrophysics Data System (ADS)

Ertaş, Mehmet; Keskin, Mustafa

2015-06-01

Using the effective-field theory based on the Glauber-type stochastic dynamics (DEFT), we investigate dynamic phase transitions and dynamic phase diagrams of the Blume-Emery-Griffiths model under an oscillating magnetic field. We presented the dynamic phase diagrams in (T/J, h0/J), (D/J, T/J) and (K/J, T/J) planes, where T, h0, D, K and z are the temperature, magnetic field amplitude, crystal-field interaction, biquadratic interaction and the coordination number. The dynamic phase diagrams exhibit several ordered phases, coexistence phase regions and special critical points, as well as re-entrant behavior depending on interaction parameters. We also compare and discuss the results with the results of the same system within the mean-field theory based on the Glauber-type stochastic dynamics and find that some of the dynamic first-order phase lines and special dynamic critical points disappeared in the DEFT calculation.

Theoretical characterization of a model of aragonite crystal orientation in red abalone nacre

NASA Astrophysics Data System (ADS)

Coppersmith, S N; Gilbert, P U P A; Metzler, R A

2009-03-01

Nacre, commonly known as mother-of-pearl, is a remarkable biomineral that in red abalone consists of layers of 400 nm thick aragonite crystalline tablets confined by organic matrix sheets, with the [0 0 1] crystal axes of the aragonite tablets oriented to within ±12° from the normal to the layer planes. Recent experiments demonstrate that greater orientational order develops over a distance of tens of layers from the prismatic boundary at which nacre formation begins. Our previous simulations of a model in which the order develops because of differential tablet growth rates (oriented tablets growing faster than misoriented ones) yield patterns of tablets that agree qualitatively and quantitatively with the experimental measurements. This paper presents an analytical treatment of this model, focusing on how the dynamical development and eventual degree of order depend on model parameters. Dynamical equations for the probability distributions governing tablet orientations are introduced whose form can be determined from symmetry considerations and for which substantial analytic progress can be made. Numerical simulations are performed to relate the parameters used in the analytic theory to those in the microscopic growth model. The analytic theory demonstrates that the dynamical mechanism is able to achieve a much higher degree of order than naive estimates would indicate.

Photon Counting as a Probe of Superfluidity in a Two-Band Bose-Hubbard System Coupled to a Cavity Field

NASA Astrophysics Data System (ADS)

Rajaram, Sara; Trivedi, Nandini

2013-12-01

We show that photon number measurement can be used to detect superfluidity for a two-band Bose-Hubbard model coupled to a cavity field. The atom-photon coupling induces transitions between the two internal atomic levels and results in entangled polaritonic states. In the presence of a cavity field, we find different photon numbers in the Mott-insulating versus superfluid phases, providing a method of distinguishing the atomic phases by photon counting. Furthermore, we examine the dynamics of the photon field after a rapid quench to zero atomic hopping by increasing the well depth. We find a robust correlation between the field’s quench dynamics and the initial superfluid order parameter, thereby providing a novel and accurate method of determining the order parameter.

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.

A dynamical regularization algorithm for solving inverse source problems of elliptic partial differential equations

NASA Astrophysics Data System (ADS)

Zhang, Ye; Gong, Rongfang; Cheng, Xiaoliang; Gulliksson, Mårten

2018-06-01

This study considers the inverse source problem for elliptic partial differential equations with both Dirichlet and Neumann boundary data. The unknown source term is to be determined by additional boundary conditions. Unlike the existing methods found in the literature, which usually employ the first-order in time gradient-like system (such as the steepest descent methods) for numerically solving the regularized optimization problem with a fixed regularization parameter, we propose a novel method with a second-order in time dissipative gradient-like system and a dynamical selected regularization parameter. A damped symplectic scheme is proposed for the numerical solution. Theoretical analysis is given for both the continuous model and the numerical algorithm. Several numerical examples are provided to show the robustness of the proposed algorithm.

In situ determination of the static inductance and resistance of a plasma focus capacitor bank.

PubMed

Saw, S H; Lee, S; Roy, F; Chong, P L; Vengadeswaran, V; Sidik, A S M; Leong, Y W; Singh, A

2010-05-01

The static (unloaded) electrical parameters of a capacitor bank are of utmost importance for the purpose of modeling the system as a whole when the capacitor bank is discharged into its dynamic electromagnetic load. Using a physical short circuit across the electromagnetic load is usually technically difficult and is unnecessary. The discharge can be operated at the highest pressure permissible in order to minimize current sheet motion, thus simulating zero dynamic load, to enable bank parameters, static inductance L(0), and resistance r(0) to be obtained using lightly damped sinusoid equations given the bank capacitance C(0). However, for a plasma focus, even at the highest permissible pressure it is found that there is significant residual motion, so that the assumption of a zero dynamic load introduces unacceptable errors into the determination of the circuit parameters. To overcome this problem, the Lee model code is used to fit the computed current trace to the measured current waveform. Hence the dynamics is incorporated into the solution and the capacitor bank parameters are computed using the Lee model code, and more accurate static bank parameters are obtained.

In situ determination of the static inductance and resistance of a plasma focus capacitor bank

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saw, S. H.; Institute for Plasma Focus Studies, 32 Oakpark Drive, Chadstone, Victoria 3148; Lee, S.

2010-05-15

The static (unloaded) electrical parameters of a capacitor bank are of utmost importance for the purpose of modeling the system as a whole when the capacitor bank is discharged into its dynamic electromagnetic load. Using a physical short circuit across the electromagnetic load is usually technically difficult and is unnecessary. The discharge can be operated at the highest pressure permissible in order to minimize current sheet motion, thus simulating zero dynamic load, to enable bank parameters, static inductance L{sub 0}, and resistance r{sub 0} to be obtained using lightly damped sinusoid equations given the bank capacitance C{sub 0}. However, formore » a plasma focus, even at the highest permissible pressure it is found that there is significant residual motion, so that the assumption of a zero dynamic load introduces unacceptable errors into the determination of the circuit parameters. To overcome this problem, the Lee model code is used to fit the computed current trace to the measured current waveform. Hence the dynamics is incorporated into the solution and the capacitor bank parameters are computed using the Lee model code, and more accurate static bank parameters are obtained.« less

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Direct test of the Gaussian auxiliary field ansatz in nonconserved order parameter phase ordering dynamics

NASA Astrophysics Data System (ADS)

Yeung, Chuck

2018-06-01

The assumption that the local order parameter is related to an underlying spatially smooth auxiliary field, u (r ⃗,t ) , is a common feature in theoretical approaches to non-conserved order parameter phase separation dynamics. In particular, the ansatz that u (r ⃗,t ) is a Gaussian random field leads to predictions for the decay of the autocorrelation function which are consistent with observations, but distinct from predictions using alternative theoretical approaches. In this paper, the auxiliary field is obtained directly from simulations of the time-dependent Ginzburg-Landau equation in two and three dimensions. The results show that u (r ⃗,t ) is equivalent to the distance to the nearest interface. In two dimensions, the probability distribution, P (u ) , is well approximated as Gaussian except for small values of u /L (t ) , where L (t ) is the characteristic length-scale of the patterns. The behavior of P (u ) in three dimensions is more complicated; the non-Gaussian region for small u /L (t ) is much larger than that in two dimensions but the tails of P (u ) begin to approach a Gaussian form at intermediate times. However, at later times, the tails of the probability distribution appear to decay faster than a Gaussian distribution.

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

DOE PAGES

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; ...

2017-12-05

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

Numerical modeling of the transmission dynamics of drug-sensitive and drug-resistant HSV-2

NASA Astrophysics Data System (ADS)

Gumel, A. B.

2001-03-01

A competitive finite-difference method will be constructed and used to solve a modified deterministic model for the spread of herpes simplex virus type-2 (HSV-2) within a given population. The model monitors the transmission dynamics and control of drug-sensitive and drug-resistant HSV-2. Unlike the fourth-order Runge-Kutta method (RK4), which fails when the discretization parameters exceed certain values, the novel numerical method to be developed in this paper gives convergent results for all parameter values.

String order parameters for one-dimensional Floquet symmetry protected topological phases

NASA Astrophysics Data System (ADS)

Kumar, Ajesh; Dumitrescu, Philipp T.; Potter, Andrew C.

2018-06-01

Floquet symmetry protected topological (FSPT) phases are nonequilibrium topological phases enabled by time-periodic driving. FSPT phases of one-dimensional (1D) chains of bosons, spins, or qubits host dynamically protected edge states that can store quantum information without decoherence, making them promising for use as quantum memories. While FSPT order cannot be detected by any local measurement, here we construct nonlocal string order parameters that directly measure general 1D FSPT order. We propose a superconducting-qubit array based realization of the simplest Ising FSPT phase, which can be implemented with existing quantum computing hardware. We devise an interferometric scheme to directly measure the nonlocal string order using only simple one- and two-qubit operations and single-qubit measurements.

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

PubMed Central

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-01-01

Background We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems. PMID:17081289

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

PubMed

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-11-02

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps

NASA Astrophysics Data System (ADS)

Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.

2004-05-01

Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.

Comprehensive cosmographic analysis by Markov chain method

NASA Astrophysics Data System (ADS)

Capozziello, S.; Lazkoz, R.; Salzano, V.

2011-12-01

We study the possibility of extracting model independent information about the dynamics of the Universe by using cosmography. We intend to explore it systematically, to learn about its limitations and its real possibilities. Here we are sticking to the series expansion approach on which cosmography is based. We apply it to different data sets: Supernovae type Ia (SNeIa), Hubble parameter extracted from differential galaxy ages, gamma ray bursts, and the baryon acoustic oscillations data. We go beyond past results in the literature extending the series expansion up to the fourth order in the scale factor, which implies the analysis of the deceleration q0, the jerk j0, and the snap s0. We use the Markov chain Monte Carlo method (MCMC) to analyze the data statistically. We also try to relate direct results from cosmography to dark energy (DE) dynamical models parametrized by the Chevallier-Polarski-Linder model, extracting clues about the matter content and the dark energy parameters. The main results are: (a) even if relying on a mathematical approximate assumption such as the scale factor series expansion in terms of time, cosmography can be extremely useful in assessing dynamical properties of the Universe; (b) the deceleration parameter clearly confirms the present acceleration phase; (c) the MCMC method can help giving narrower constraints in parameter estimation, in particular for higher order cosmographic parameters (the jerk and the snap), with respect to the literature; and (d) both the estimation of the jerk and the DE parameters reflect the possibility of a deviation from the ΛCDM cosmological model.

Upper Pleistocene uplifted shorelines as tracers of (local rather than global) subduction dynamics

NASA Astrophysics Data System (ADS)

Henry, Hadrien; Regard, Vincent; Pedoja, Kevin; Husson, Laurent; Martinod, Joseph; Witt, Cesar; Heuret, Arnauld

2014-08-01

Past studies have shown that high coastal uplift rates are restricted to active areas, especially in a subduction context. The origin of coastal uplift in subduction zones, however, has not yet been globally investigated. Quaternary shorelines correlated to the last interglacial maximum (MIS 5e) were defined as a global tectonic benchmark (Pedoja et al., 2011). In order to investigate the relationships between the vertical motion and the subduction dynamic parameters, we cross-linked this coastal uplift database with the “geodynamical” databases from Heuret (2005), Conrad and Husson (2009) and Müller et al. (2008). Our statistical study shows that: (1) the most intuitive parameters one can think responsible for coastal uplift (e.g., subduction obliquity, trench motion, oceanic crust age, interplate friction and force, convergence variation, dynamic topography, overriding and subducted plate velocity) are not related with the uplift (and its magnitude); (2) the only intuitive parameter is the distance to the trench which shows in specific areas a decrease from the trench up to a distance of ˜300 km; (3) the slab dip (especially the deep slab dip), the position along the trench and the overriding plate tectonic regime are correlated with the coastal uplift, probably reflecting transient changes in subduction parameters. Finally we conclude that the first order parameter explaining coastal uplift is small-scale heterogeneities of the subducting plate, as for instance subducting aseismic ridges. The influence of large-scale geodynamic setting of subduction zones is secondary.

Discovering local order parameters in liquid water using machine learning

NASA Astrophysics Data System (ADS)

Soto, Adrian; Lu, Deyu; Yoo, Shinjae; Fernandez-Serra, Marivi

The local arrangement of water molecules in liquid phase is still being discussed and questioned. The prevailing view is that water is composed of a mixture of two structurally different liquids. One of the main challenges has been to find order parameters that are able to discriminate the complex structures of these distinct molecular environments. Several local order parameters have been proposed and studied in all sorts of atomistic simulations of liquid water but, to date, none has been able to capture the predicted dual character. This presents an ideal problem to treat with methods capable of unveiling information from complex data. In this talk we will discuss how local order parameters can be constructed from molecular dynamics trajectories by using machine learning and other related techniques. Work was partially supported by DOE Award No. DE-FG02-09ER16052, by DOE Early Career Award No. DE-SC0003871, by BNL LDRD 16-039 project and BNL Contract No. DE-SC0012704.

Motions and entropies in proteins as seen in NMR relaxation experiments and molecular dynamics simulations.

PubMed

Allnér, Olof; Foloppe, Nicolas; Nilsson, Lennart

2015-01-22

Molecular dynamics simulations of E. coli glutaredoxin1 in water have been performed to relate the dynamical parameters and entropy obtained in NMR relaxation experiments, with results extracted from simulated trajectory data. NMR relaxation is the most widely used experimental method to obtain data on dynamics of proteins, but it is limited to relatively short timescales and to motions of backbone amides or in some cases (13)C-H vectors. By relating the experimental data to the all-atom picture obtained in molecular dynamics simulations, valuable insights on the interpretation of the experiment can be gained. We have estimated the internal dynamics and their timescales by calculating the generalized order parameters (O) for different time windows. We then calculate the quasiharmonic entropy (S) and compare it to the entropy calculated from the NMR-derived generalized order parameter of the amide vectors. Special emphasis is put on characterizing dynamics that are not expressed through the motions of the amide group. The NMR and MD methods suffer from complementary limitations, with NMR being restricted to local vectors and dynamics on a timescale determined by the rotational diffusion of the solute, while in simulations, it may be difficult to obtain sufficient sampling to ensure convergence of the results. We also evaluate the amount of sampling obtained with molecular dynamics simulations and how it is affected by the length of individual simulations, by clustering of the sampled conformations. We find that two structural turns act as hinges, allowing the α helix between them to undergo large, long timescale motions that cannot be detected in the time window of the NMR dipolar relaxation experiments. We also show that the entropy obtained from the amide vector does not account for correlated motions of adjacent residues. Finally, we show that the sampling in a total of 100 ns molecular dynamics simulation can be increased by around 50%, by dividing the trajectory into 10 replicas with different starting velocities.

Dynamical susceptibility near a long-wavelength critical point with a nonconserved order parameter

NASA Astrophysics Data System (ADS)

Klein, Avraham; Lederer, Samuel; Chowdhury, Debanjan; Berg, Erez; Chubukov, Andrey

2018-04-01

We study the dynamic response of a two-dimensional system of itinerant fermions in the vicinity of a uniform (Q =0 ) Ising nematic quantum critical point of d - wave symmetry. The nematic order parameter is not a conserved quantity, and this permits a nonzero value of the fermionic polarization in the d - wave channel even for vanishing momentum and finite frequency: Π (q =0 ,Ωm)≠0 . For weak coupling between the fermions and the nematic order parameter (i.e., the coupling is small compared to the Fermi energy), we perturbatively compute Π (q =0 ,Ωm)≠0 over a parametrically broad range of frequencies where the fermionic self-energy Σ (ω ) is irrelevant, and use Eliashberg theory to compute Π (q =0 ,Ωm) in the non-Fermi-liquid regime at smaller frequencies, where Σ (ω )>ω . We find that Π (q =0 ,Ω ) is a constant, plus a frequency-dependent correction that goes as |Ω | at high frequencies, crossing over to |Ω| 1 /3 at lower frequencies. The |Ω| 1 /3 scaling holds also in a non-Fermi-liquid regime. The nonvanishing of Π (q =0 ,Ω ) gives rise to additional structure in the imaginary part of the nematic susceptibility χ″(q ,Ω ) at Ω >vFq , in marked contrast to the behavior of the susceptibility for a conserved order parameter. This additional structure may be detected in Raman scattering experiments in the d - wave geometry.

Coevolution of Glauber-like Ising dynamics and topology

NASA Astrophysics Data System (ADS)

Mandrà, Salvatore; Fortunato, Santo; Castellano, Claudio

2009-11-01

We study the coevolution of a generalized Glauber dynamics for Ising spins with tunable threshold and of the graph topology where the dynamics takes place. This simple coevolution dynamics generates a rich phase diagram in the space of the two parameters of the model, the threshold and the rewiring probability. The diagram displays phase transitions of different types: spin ordering, percolation, and connectedness. At variance with traditional coevolution models, in which all spins of each connected component of the graph have equal value in the stationary state, we find that, for suitable choices of the parameters, the system may converge to a state in which spins of opposite sign coexist in the same component organized in compact clusters of like-signed spins. Mean field calculations enable one to estimate some features of the phase diagram.

Changes in conformational dynamics of basic side chains upon protein-DNA association.

PubMed

Esadze, Alexandre; Chen, Chuanying; Zandarashvili, Levani; Roy, Sourav; Pettitt, B Montgometry; Iwahara, Junji

2016-08-19

Basic side chains play major roles in recognition of nucleic acids by proteins. However, dynamic properties of these positively charged side chains are not well understood. In this work, we studied changes in conformational dynamics of basic side chains upon protein-DNA association for the zinc-finger protein Egr-1. By nuclear magnetic resonance (NMR) spectroscopy, we characterized the dynamics of all side-chain cationic groups in the free protein and in the complex with target DNA. Our NMR order parameters indicate that the arginine guanidino groups interacting with DNA bases are strongly immobilized, forming rigid interfaces. Despite the strong short-range electrostatic interactions, the majority of the basic side chains interacting with the DNA phosphates exhibited high mobility, forming dynamic interfaces. In particular, the lysine side-chain amino groups exhibited only small changes in the order parameters upon DNA-binding. We found a similar trend in the molecular dynamics (MD) simulations for the free Egr-1 and the Egr-1-DNA complex. Using the MD trajectories, we also analyzed side-chain conformational entropy. The interfacial arginine side chains exhibited substantial entropic loss upon binding to DNA, whereas the interfacial lysine side chains showed relatively small changes in conformational entropy. These data illustrate different dynamic characteristics of the interfacial arginine and lysine side chains. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nonlinear observation of internal states of fuel cell cathode utilizing a high-order sliding-mode algorithm

NASA Astrophysics Data System (ADS)

Xu, Liangfei; Hu, Junming; Cheng, Siliang; Fang, Chuan; Li, Jianqiu; Ouyang, Minggao; Lehnert, Werner

2017-07-01

A scheme for designing a second-order sliding-mode (SOSM) observer that estimates critical internal states on the cathode side of a polymer electrolyte membrane (PEM) fuel cell system is presented. A nonlinear, isothermal dynamic model for the cathode side and a membrane electrolyte assembly are first described. A nonlinear observer topology based on an SOSM algorithm is then introduced, and equations for the SOSM observer deduced. Online calculation of the inverse matrix produces numerical errors, so a modified matrix is introduced to eliminate the negative effects of these on the observer. The simulation results indicate that the SOSM observer performs well for the gas partial pressures and air stoichiometry. The estimation results follow the simulated values in the model with relative errors within ± 2% at stable status. Large errors occur during the fast dynamic processes (<1 s). Moreover, the nonlinear observer shows good robustness against variations in the initial values of the internal states, but less robustness against variations in system parameters. The partial pressures are more sensitive than the air stoichiometry to system parameters. Finally, the order of effects of parameter uncertainties on the estimation results is outlined and analyzed.

Earth and ocean modeling

NASA Technical Reports Server (NTRS)

Knezovich, F. M.

1976-01-01

A modular structured system of computer programs is presented utilizing earth and ocean dynamical data keyed to finitely defined parameters. The model is an assemblage of mathematical algorithms with an inherent capability of maturation with progressive improvements in observational data frequencies, accuracies and scopes. The Eom in its present state is a first-order approach to a geophysical model of the earth's dynamics.

Nonlinear soil parameter effects on dynamic embedment of offshore pipeline on soft clay

NASA Astrophysics Data System (ADS)

Yu, Su Young; Choi, Han Suk; Lee, Seung Keon; Park, Kyu-Sik; Kim, Do Kyun

2015-06-01

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

Superslow relaxation in identical phase oscillators with random and frustrated interactions

NASA Astrophysics Data System (ADS)

Daido, H.

2018-04-01

This paper is concerned with the relaxation dynamics of a large population of identical phase oscillators, each of which interacts with all the others through random couplings whose parameters obey the same Gaussian distribution with the average equal to zero and are mutually independent. The results obtained by numerical simulation suggest that for the infinite-size system, the absolute value of Kuramoto's order parameter exhibits superslow relaxation, i.e., 1/ln t as time t increases. Moreover, the statistics on both the transient time T for the system to reach a fixed point and the absolute value of Kuramoto's order parameter at t = T are also presented together with their distribution densities over many realizations of the coupling parameters.

Toward a better understanding of helicopter stability derivatives

NASA Technical Reports Server (NTRS)

Hansen, R. S.

1982-01-01

An amended six degree of freedom helicopter stability and control derivative model was developed in which body acceleration and control rate derivatives were included in the Taylor series expansion. These additional derivatives were derived from consideration of the effects of the higher order rotor flapping dynamics, which are known to be inadequately represented in the conventional six degree of freedom, quasistatic stability derivative model. The amended model was a substantial improvement over the conventional model, effectively doubling the unsable bandwidth and providing a more accurate representation of the short period and cross axis characteristics. Further investigations assessed the applicability of the two stability derivative model structures for flight test parameter identification. Parameters were identified using simulation data generated from a higher order base line model having sixth order rotor tip path plane dynamics. Three lower order models were identified: one using the conventional stability derivative model structure, a second using the amended six degree of freedom model structure, and a third model having eight degrees of freedom that included a simplified rotor tip path plane tilt representation.

Nuclear magnetic resonance signal dynamics of liquids in the presence of distant dipolar fields, revisited

PubMed Central

Barros, Wilson; Gochberg, Daniel F.; Gore, John C.

2009-01-01

The description of the nuclear magnetic resonance magnetization dynamics in the presence of long-range dipolar interactions, which is based upon approximate solutions of Bloch–Torrey equations including the effect of a distant dipolar field, has been revisited. New experiments show that approximate analytic solutions have a broader regime of validity as well as dependencies on pulse-sequence parameters that seem to have been overlooked. In order to explain these experimental results, we developed a new method consisting of calculating the magnetization via an iterative formalism where both diffusion and distant dipolar field contributions are treated as integral operators incorporated into the Bloch–Torrey equations. The solution can be organized as a perturbative series, whereby access to higher order terms allows one to set better boundaries on validity regimes for analytic first-order approximations. Finally, the method legitimizes the use of simple analytic first-order approximations under less demanding experimental conditions, it predicts new pulse-sequence parameter dependencies for the range of validity, and clarifies weak points in previous calculations. PMID:19425789

Orbital Injection of the SEDSAT Satellite: Tethered Systems Dynamics and Flight Data Analysis

NASA Technical Reports Server (NTRS)

Lorenzini, Enrico C.; Gullahorn, Gordon E.; Cosmo, Mario L.; Ruiz, Manuel; Pelaez, Jesus

1996-01-01

This report deals with the following topics which are all related to the orbital injection of the SEDSAT satellite: Dynamics and Stability of Tether Oscillations after the First Cut. The dynamics of the tether after the first cut (i.e., without the Shuttle attached to it) is investigated. The tether oscillations with the free end are analyzed in order to assess the stability of the rectilinear configuration in between the two tether cuts; analysis of Unstable Modes. The unstable modes that appear for high libration angles are further investigated in order to determine their occurrences and the possible transition from bound librations to rotations; Orbital Release Strategies for SEDSAT. A parametric analysis of the orbital decay rate of the SEDSAT satellite after the two tether cuts has been carried out as a function of the following free parameters: libration amplitude at the end of deployment, deviation angle from LV at the first cut, and orbital anomaly at the second cut. The values of these parameters that provide a minimum orbital decay rate of the satellite (after the two cuts) have been computed; and Dynamics and Control of SEDSAT. The deployment control law has been modified to cope with the new ejection velocity of the satellite from the Shuttle cargo bay. New reference profiles have been derived as well as new control parameters. Timing errors at the satellite release as a function of the variations of the initial conditions and the tension model parameters have been estimated for the modified control law.

Influence of the model's degree of freedom on human body dynamics identification.

PubMed

Maita, Daichi; Venture, Gentiane

2013-01-01

In fields of sports and rehabilitation, opportunities of using motion analysis of the human body have dramatically increased. To analyze the motion dynamics, a number of subject specific parameters and measurements are required. For example the contact forces measurement and the inertial parameters of each segment of the human body are necessary to compute the joint torques. In this study, in order to perform accurate dynamic analysis we propose to identify the inertial parameters of the human body and to evaluate the influence of the model's number of degrees of freedom (DoF) on the results. We use a method to estimate the inertial parameters without torque sensor, using generalized coordinates of the base link, joint angles and external forces information. We consider a 34DoF model, a 58DoF model, as well as the case when the human is manipulating a tool (here a tennis racket). We compare the obtained in results in terms of contact force estimation.

Genetic algorithms for the application of Activated Sludge Model No. 1.

PubMed

Kim, S; Lee, H; Kim, J; Kim, C; Ko, J; Woo, H; Kim, S

2002-01-01

The genetic algorithm (GA) has been integrated into the IWA ASM No. 1 to calibrate important stoichiometric and kinetic parameters. The evolutionary feature of GA was used to configure the multiple local optima as well as the global optimum. The objective function of optimization was designed to minimize the difference between estimated and measured effluent concentrations at the activated sludge system. Both steady state and dynamic data of the simulation benchmark were used for calibration using denitrification layout. Depending upon the confidence intervals and objective functions, the proposed method provided distributions of parameter space. Field data have been collected and applied to validate calibration capacity of GA. Dynamic calibration was suggested to capture periodic variations of inflow concentrations. Also, in order to verify this proposed method in real wastewater treatment plant, measured data sets for substrate concentrations were obtained from Haeundae wastewater treatment plant and used to estimate parameters in the dynamic system. The simulation results with calibrated parameters matched well with the observed concentrations of effluent COD.

Phase transitions in single macromolecules: Loop-stretch transition versus loop adsorption transition in end-grafted polymer chains

NASA Astrophysics Data System (ADS)

Zhang, Shuangshuang; Qi, Shuanhu; Klushin, Leonid I.; Skvortsov, Alexander M.; Yan, Dadong; Schmid, Friederike

2018-01-01

We use Brownian dynamics simulations and analytical theory to compare two prominent types of single molecule transitions. One is the adsorption transition of a loop (a chain with two ends bound to an attractive substrate) driven by an attraction parameter ɛ and the other is the loop-stretch transition in a chain with one end attached to a repulsive substrate, driven by an external end-force F applied to the free end. Specifically, we compare the behavior of the respective order parameters of the transitions, i.e., the mean number of surface contacts in the case of the adsorption transition and the mean position of the chain end in the case of the loop-stretch transition. Close to the transition points, both the static behavior and the dynamic behavior of chains with different length N are very well described by a scaling ansatz with the scaling parameters (ɛ - ɛ*)Nϕ (adsorption transition) and (F - F*)Nν (loop-stretch transition), respectively, where ϕ is the crossover exponent of the adsorption transition and ν is the Flory exponent. We show that both the loop-stretch and the loop adsorption transitions provide an exceptional opportunity to construct explicit analytical expressions for the crossover functions which perfectly describe all simulation results on static properties in the finite-size scaling regime. Explicit crossover functions are based on the ansatz for the analytical form of the order parameter distributions at the respective transition points. In contrast to the close similarity in equilibrium static behavior, the dynamic relaxation at the two transitions shows qualitative differences, especially in the strongly ordered regimes. This is attributed to the fact that the surface contact dynamics in a strongly adsorbed chain is governed by local processes, whereas the end height relaxation of a strongly stretched chain involves the full spectrum of Rouse modes.

Charge and pairing dynamics in the attractive Hubbard model: Mode coupling and the validity of linear-response theory

NASA Astrophysics Data System (ADS)

Bünemann, Jörg; Seibold, Götz

2017-12-01

Pump-probe experiments have turned out as a powerful tool in order to study the dynamics of competing orders in a large variety of materials. The corresponding analysis of the data often relies on standard linear-response theory generalized to nonequilibrium situations. Here we examine the validity of such an approach for the charge and pairing response of systems with charge-density wave and (or) superconducting (SC) order. Our investigations are based on the attractive Hubbard model which we study within the time-dependent Hartree-Fock approximation. In particular, we calculate the quench and pump-probe dynamics for SC and charge order parameters in order to analyze the frequency spectra and the coupling of the probe field to the specific excitations. Our calculations reveal that the "linear-response assumption" is justified for small to moderate nonequilibrium situations (i.e., pump pulses) in the case of a purely charge-ordered ground state. However, the pump-probe dynamics on top of a superconducting ground state is determined by phase and amplitude modes which get coupled far from the equilibrium state indicating the failure of the linear-response assumption.

Demonstrative fractional order - PID controller based DC motor drive on digital platform.

PubMed

Khubalkar, Swapnil W; Junghare, Anjali S; Aware, Mohan V; Chopade, Amit S; Das, Shantanu

2017-09-21

In industrial drives applications, fractional order controllers can exhibit phenomenal impact due to realization through digital implementation. Digital fractional order controllers have created wide scope as it possess the inherent advantages like robustness against the plant parameter variation. This paper provides brief design procedure of fractional order proportional-integral-derivative (FO-PID) controller through the indirect approach of approximation using constant phase technique. The new modified dynamic particle swarm optimization (IdPSO) technique is proposed to find controller parameters. The FO-PID controller is implemented using floating point digital signal processor. The building blocks are designed and assembled with all peripheral components for the 1.5kW industrial DC motor drive. The robust operation for parametric variation is ascertained by testing the controller with two separately excited DC motors with the same rating but different parameters. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Hopf bifurcation and chaos in a third-order phase-locked loop

NASA Astrophysics Data System (ADS)

Piqueira, José Roberto C.

2017-01-01

Phase-locked loops (PLLs) are devices able to recover time signals in several engineering applications. The literature regarding their dynamical behavior is vast, specifically considering that the process of synchronization between the input signal, coming from a remote source, and the PLL local oscillation is robust. For high-frequency applications it is usual to increase the PLL order by increasing the order of the internal filter, for guarantying good transient responses; however local parameter variations imply structural instability, thus provoking a Hopf bifurcation and a route to chaos for the phase error. Here, one usual architecture for a third-order PLL is studied and a range of permitted parameters is derived, providing a rule of thumb for designers. Out of this range, a Hopf bifurcation appears and, by increasing parameters, the periodic solution originated by the Hopf bifurcation degenerates into a chaotic attractor, therefore, preventing synchronization.

State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps

PubMed Central

Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.

2017-01-01

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

Steering Dynamics of Tilting Narrow Track Vehicle with Passive Front Wheel Design

NASA Astrophysics Data System (ADS)

TAN, Jeffrey Too Chuan; ARAKAWA, Hiroki; SUDA, Yoshihiro

2016-09-01

In recent years, narrow track vehicle has been emerged as a potential candidate for the next generation of urban transportation system, which is greener and space effective. Vehicle body tilting has been a symbolic characteristic of such vehicle, with the purpose to maintain its stability with the narrow track body. However, the coordination between active steering and vehicle tilting requires considerable driving skill in order to achieve effective stability. In this work, we propose an alternative steering method with a passive front wheel that mechanically follows the vehicle body tilting. The objective of this paper is to investigate the steering dynamics of the vehicle under various design parameters of the passive front wheel. Modeling of a three-wheel tilting narrow track vehicle and multibody dynamics simulations were conducted to study the effects of two important front wheel design parameters, i.e. caster angle and trail toward the vehicle steering dynamics in steering response time, turning radius, steering stability and resiliency towards external disturbance. From the results of the simulation studies, we have verified the relationships of these two front wheel design parameters toward the vehicle steering dynamics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanz, Alejandro; Ezquerra, Tiberio A.; Nogales, Aurora, E-mail: aurora.nogales@csic.es

The dynamics of lower disorder-order temperature diblock copolymer leading to phase separation has been observed by X ray photon correlation spectroscopy. Two different modes have been characterized. A non-diffusive mode appears at temperatures below the disorder to order transition, which can be associated to compositional fluctuations, that becomes slower as the interaction parameter increases, in a similar way to the one observed for diblock copolymers exhibiting phase separation upon cooling. At temperatures above the disorder to order transition T{sub ODT}, the dynamics becomes diffusive, indicating that after phase separation in Lower Disorder-Order Transition (LDOT) diblock copolymers, the diffusion of chainmore » segments across the interface is the governing dynamics. As the segregation is stronger, the diffusive process becomes slower. Both observed modes have been predicted by the theory describing upper order-disorder transition systems, assuming incompressibility. However, the present results indicate that the existence of these two modes is more universal as they are present also in compressible diblock copolymers exhibiting a lower disorder-order transition. No such a theory describing the dynamics in LDOT block copolymers is available, and these experimental results may offer some hints to understanding the dynamics in these systems. The dynamics has also been studied in the ordered state, and for the present system, the non-diffusive mode disappears and only a diffusive mode is observed. This mode is related to the transport of segment in the interphase, due to the weak segregation on this system.« less

Glassy dynamics of dense particle assemblies on a spherical substrate.

PubMed

Vest, Julien-Piera; Tarjus, Gilles; Viot, Pascal

2018-04-28

We study by molecular dynamics simulation a dense one-component system of particles confined on a spherical substrate. We more specifically investigate the evolution of the structural and dynamical properties of the system when changing the control parameters, the temperature and the curvature of the substrate. We find that the dynamics become glassy at low temperature, with a strong slowdown of the relaxation and the emergence of dynamical heterogeneity. The prevalent local 6-fold order is frustrated by curvature and we analyze in detail the role of the topological defects in the statics and the dynamics of the particle assembly.

General high-order breathers and rogue waves in the (3 + 1) -dimensional KP-Boussinesq equation

NASA Astrophysics Data System (ADS)

Sun, Baonan; Wazwaz, Abdul-Majid

2018-11-01

In this work, we investigate the (3 + 1) -dimensional KP-Boussinesq equation, which can be used to describe the nonlinear dynamic behavior in scientific and engineering applications. We derive general high-order soliton solutions by using the Hirota's bilinear method combined with the perturbation expansion technique. We also obtain periodic solutions comprising of high-order breathers, periodic line waves, and mixed solutions consisting of breathers and periodic line waves upon selecting particular parameter constraints of the obtained soliton solutions. Furthermore, smooth rational solutions are generated by taking a long wave limit of the soliton solutions. These smooth rational solutions include high-order rogue waves, high-order lumps, and hybrid solutions consisting of lumps and line rogue waves. To better understand the dynamical behaviors of these solutions, we discuss some illustrative graphical analyses. It is expected that our results can enrich the dynamical behavior of the (3 + 1) -dimensional nonlinear evolution equations of other forms.

Neutron scattering studies of the ferroelectric distortion and spin dynamics in the type-1 multiferroic perovskite Sr 0.56 Ba 0.44 MnO 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratt, Daniel K.; Lynn, Jeffrey W.; Mais, James

2014-10-01

The magnetic order, spin dynamics, and crystal structure of the multiferroic Sr0.56Ba0.44MnO3 have been investigated using neutron and x-ray scattering. Ferroelectricity develops at T-C = 305 K with a polarization of 4.2 mu C/cm(2) associated with the displacements of the Mn ions, while the Mn4+ spins order below T-N approximate to 200 K into a simple G-type commensurate magnetic structure. Below TN the ferroelectric order decreases dramatically, demonstrating that the two order parameters are strongly coupled. The ground state spin dynamics is characterized by a spin gap of 4.6(5) meV and the magnon density of states peaking at 43 meV.more » Detailed spin wave simulations with a gap and isotropic exchange of J = 4.8(2) meV describe the excitation spectrum well. Above TN strong spin correlations coexist with robust ferroelectric order.« less

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Clustering promotes switching dynamics in networks of noisy neurons

NASA Astrophysics Data System (ADS)

Franović, Igor; Klinshov, Vladimir

2018-02-01

Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

Stereoisomeric effects on dynamic viscosity versus pressure and temperature for the system cis- + trans-decalin

NASA Astrophysics Data System (ADS)

Miyake, Yasufumi; Boned, Christian; Baylaucq, Antoine; Bessières, David; Zéberg-Mikkelsen, Claus K.; Galliéro, Guillaume; Ushiki, Hideharu

2007-07-01

In order to study the influence of stereoisomeric effects on the dynamic viscosity, an extensive experimental study of the viscosity of the binary system composed of the two stereoisomeric molecular forms of decalin - cis and trans - has been carried out for five different mixtures at three temperatures (303.15, 323.15 and 343.15) K and six isobars up to 100 MPa with a falling-body viscometer (a total of 90 points). The experimental relative uncertainty is estimated to be 2%. The variations of dynamic viscosity versus composition are discussed with respect to their behavior due to stereoisomerism. Four different models with a physical and theoretical background are studied in order to investigate how they take the stereoisomeric effect into account through their required model parameters. The evaluated models are based on the hard-sphere scheme, the concepts of the free-volume and the friction theory, and a model derived from molecular dynamics. Overall, a satisfactory representation of the viscosity of this binary system is found for the different models within the considered ( T, p) range taken into account their simplicity. All the models are able to distinguish between the two stereoisomeric decalin compounds. Further, based on the analysis of the model parameters performed on the pure compounds, it has been found that the use of simple mixing rules without introducing any binary interaction parameters are sufficient in order to predict the viscosity of cis + trans-decalin mixtures with the same accuracy in comparison with the experimental values as obtained for the pure compounds. In addition to these models, a semi-empirical self-referencing model and the simple mixing laws of Grunberg-Nissan and Katti-Chaudhri are also applied in the representation of the viscosity behavior of these systems.

Wire rope tension control of hoisting systems using a robust nonlinear adaptive backstepping control scheme.

PubMed

Zhu, Zhen-Cai; Li, Xiang; Shen, Gang; Zhu, Wei-Dong

2018-01-01

This paper concerns wire rope tension control of a double-rope winding hoisting system (DRWHS), which consists of a hoisting system employed to realize a transportation function and an electro-hydraulic servo system utilized to adjust wire rope tensions. A dynamic model of the DRWHS is developed in which parameter uncertainties and external disturbances are considered. A comparison between simulation results using the dynamic model and experimental results using a double-rope winding hoisting experimental system is given in order to demonstrate accuracy of the dynamic model. In order to improve the wire rope tension coordination control performance of the DRWHS, a robust nonlinear adaptive backstepping controller (RNABC) combined with a nonlinear disturbance observer (NDO) is proposed. Main features of the proposed combined controller are: (1) using the RNABC to adjust wire rope tensions with consideration of parameter uncertainties, whose parameters are designed online by adaptive laws derived from Lyapunov stability theory to guarantee the control performance and stability of the closed-loop system; and (2) introducing the NDO to deal with uncertain external disturbances. In order to demonstrate feasibility and effectiveness of the proposed controller, experimental studies have been conducted on the DRWHS controlled by an xPC rapid prototyping system. Experimental results verify that the proposed controller exhibits excellent performance on wire rope tension coordination control compared with a conventional proportional-integral (PI) controller and adaptive backstepping controller. Copyright © 2017 ISA. All rights reserved.

Determination of adsorption parameters in numerical simulation for polymer flooding

NASA Astrophysics Data System (ADS)

Bao, Pengyu; Li, Aifen; Luo, Shuai; Dang, Xu

2018-02-01

A study on the determination of adsorption parameters for polymer flooding simulation was carried out. The study mainly includes polymer static adsorption and dynamic adsorption. The law of adsorption amount changing with polymer concentration and core permeability was presented, and the one-dimensional numerical model of CMG was established under the support of a large number of experimental data. The adsorption laws of adsorption experiments were applied to the one-dimensional numerical model to compare the influence of two adsorption laws on the historical matching results. The results show that the static adsorption and dynamic adsorption abide by different rules, and differ greatly in adsorption. If the static adsorption results were directly applied to the numerical model, the difficulty of the historical matching will increase. Therefore, dynamic adsorption tests in the porous medium are necessary before the process of parameter adjustment in order to achieve the ideal history matching result.

Prethermalization and persistent order in the absence of a thermal phase transition

NASA Astrophysics Data System (ADS)

Halimeh, Jad C.; Zauner-Stauber, Valentin; McCulloch, Ian P.; de Vega, Inés; Schollwöck, Ulrich; Kastner, Michael

2017-01-01

We numerically study the dynamics after a parameter quench in the one-dimensional transverse-field Ising model with long-range interactions (∝1 /rα with distance r ), for finite chains and also directly in the thermodynamic limit. In nonequilibrium, i.e., before the system settles into a thermal state, we find a long-lived regime that is characterized by a prethermal value of the magnetization, which in general differs from its thermal value. We find that the ferromagnetic phase is stabilized dynamically: as a function of the quench parameter, the prethermal magnetization shows a transition between a symmetry-broken and a symmetric phase, even for those values of α for which no finite-temperature transition occurs in equilibrium. The dynamical critical point is shifted with respect to the equilibrium one, and the shift is found to depend on α as well as on the quench parameters.

An extended harmonic balance method based on incremental nonlinear control parameters

NASA Astrophysics Data System (ADS)

Khodaparast, Hamed Haddad; Madinei, Hadi; Friswell, Michael I.; Adhikari, Sondipon; Coggon, Simon; Cooper, Jonathan E.

2017-02-01

A new formulation for calculating the steady-state responses of multiple-degree-of-freedom (MDOF) non-linear dynamic systems due to harmonic excitation is developed. This is aimed at solving multi-dimensional nonlinear systems using linear equations. Nonlinearity is parameterised by a set of 'non-linear control parameters' such that the dynamic system is effectively linear for zero values of these parameters and nonlinearity increases with increasing values of these parameters. Two sets of linear equations which are formed from a first-order truncated Taylor series expansion are developed. The first set of linear equations provides the summation of sensitivities of linear system responses with respect to non-linear control parameters and the second set are recursive equations that use the previous responses to update the sensitivities. The obtained sensitivities of steady-state responses are then used to calculate the steady state responses of non-linear dynamic systems in an iterative process. The application and verification of the method are illustrated using a non-linear Micro-Electro-Mechanical System (MEMS) subject to a base harmonic excitation. The non-linear control parameters in these examples are the DC voltages that are applied to the electrodes of the MEMS devices.

Reflow dynamics of thin patterned viscous films

NASA Astrophysics Data System (ADS)

Leveder, T.; Landis, S.; Davoust, L.

2008-01-01

This letter presents a study of viscous smoothening dynamics of a nanopatterned thin film. Ultrathin film manufacturing processes appearing to be a key point of nanotechnology engineering and numerous studies have been recently led in order to exhibit driving parameters of this transient surface motion, focusing on time scale accuracy method. Based on nanomechanical analysis, this letter shows that controlled shape measurements provided much more detailed information about reflow mechanism. Control of reflow process of any complex surface shape, or measurement of material parameter as thin film viscosity, free surface energy, or even Hamaker constant are therefore possible.

Test of parameter-free local pseudopotential for the study of dynamical elastic constants - Cu as a prototype

NASA Astrophysics Data System (ADS)

Bhatia, K. G.; Vyas, S. M.; Patel, A. B.; Bhatt, N. K.; Vyas, P. R.; Gohel, V. B.

2018-05-01

Using parameter-free (first principles local) pseudopotential, in the present communication we have calculated dynamical elastic constants (C11, C12 and C44), bulk modulus (B), shear modulus (µp), Young's modulus (Y) and Poisson's ratio (σ) in long wavelength limit. Our computed results are well agreed for C44 and B with experiment and with other theoretical results obtained within framework of second order perturbation pseudopotential theory. From the present study we conclude that pseudopotential used contain s-p hybridization and no extra term is required to account core-core repulsion.

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Propagation of arbitrary initial wave packets in a quantum parametric oscillator: Instability zones for higher order moments

NASA Astrophysics Data System (ADS)

Biswas, Subhadip; Chattopadhyay, Rohitashwa; Bhattacharjee, Jayanta K.

2018-05-01

We consider the dynamics of a particle in a parametric oscillator with a view to exploring any quantum feature of the initial wave packet that shows divergent (in time) behaviour for parameter values where the classical motion dynamics of the mean position is bounded. We use Ehrenfest's theorem to explore the dynamics of nth order moment which reduces exactly to a linear non autonomous differential equation of order n + 1. It is found that while the width and skewness of the packet is unbounded exactly in the zones where the classical motion is unbounded, the kurtosis of an initially non-gaussian wave packet can become infinitely large in certain additional zones. This implies that the shape of the wave packet can change drastically with time in these zones.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Some new results concerning the dynamic behavior of annular turbulent seals

NASA Technical Reports Server (NTRS)

Massmann, H.; Nordmann, R.

1985-01-01

The dynamic characteristics of annular turbulent seals applied in high pressure turbopumps can be described by stiffness, damping, and inertia coefficients. An improved procedure is presented for determining these parameters by using measurements made with newly developed test equipment. The dynamic system seal, consisting of the fluid between the cylindrical surfaces of the rotating shaft and the housing, is excited by test forces (input), and the relative motion between the surfaces (output) is measured. Transformation of the input and output time signals into the frequency domain leads to frequency response functions. An analytical model, depending on the seal parameters, is fitted to the measured data in order to identify the dynamic coefficients. Some new results are reported that show the dependencies of these coefficients with respect to the axial and radial Reynolds numbers and the geometrical data of the seal.

Nonholonomic Hamiltonian Method for Molecular Dynamics Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Bass, Joseph

2015-06-01

Conventional molecular dynamics simulations of reacting shocks employ a holonomic Hamiltonian formulation: the breaking and forming of covalent bonds is described by potential functions. In general these potential functions: (a) are algebraically complex, (b) must satisfy strict smoothness requirements, and (c) contain many fitted parameters. In recent research the authors have developed a new noholonomic formulation of reacting molecular dynamics. In this formulation bond orders are determined by rate equations and the bonding-debonding process need not be described by differentiable functions. This simplifies the representation of complex chemistry and reduces the number of fitted model parameters. Example applications of the method show molecular level shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

Ergodicity breaking and ageing of underdamped Brownian dynamics with quenched disorder

NASA Astrophysics Data System (ADS)

Guo, Wei; Li, Yong; Song, Wen-Hua; Du, Lu-Chun

2018-03-01

The dynamics of an underdamped Brownian particle moving in one-dimensional quenched disorder under the action of an external force is investigated. Within the tailored parameter regime, the transiently anomalous diffusion and ergodicity breaking, spanning several orders of magnitude in time, have been obtained. The ageing nature of the system weakens as the dissipation of the system increases for other given parameters. Its origin is ascribed to the highly local heterogeneity of the disorder. Two kinds of approximations (in the stationary state), respectively, for large bias and large damping are derived. These results may be helpful in further understanding the nontrivial response of nonlinear dynamics, and also have potential applications to experiments and activities of biological processes.

Rapid characterizing of ferromagnetic materials using spin rectification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Xiaolong, E-mail: fanxiaolong@lzu.edu.cn; Wang, Wei; Wang, Yutian

2014-12-29

Spin rectification is a powerful tool for dc electric detections of spin dynamics and electromagnetic waves. Technically, elaborately designed on-chip microwave devices are needed in order to realize that effect. In this letter, we propose a rapid characterizing approach based on spin rectification. By directly sending dynamic current into ferromagnetic films with stripe shape, resonant dc voltages can be detected along the longitudinal or transversal directions. As an example, Fe (010) films with precise crystalline structure and magnetic parameters were used to testify the reliability of such method. We investigated not only the dynamic parameters and the precise anisotropy constantsmore » of the Fe crystals but also the principle of spin rectification in this method.« less

The Dynamic Response and Vibration of Functionally Graded Carbon Nanotube-Reinforced Composite (FG-CNTRC) Truncated Conical Shells Resting on Elastic Foundations

PubMed Central

Nguyen Dinh, Duc; Nguyen, Pham Dinh

2017-01-01

Based on the classical shell theory, the linear dynamic response of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) truncated conical shells resting on elastic foundations subjected to dynamic loads is presented. The truncated conical shells are reinforced by single-walled carbon nanotubes (SWCNTs) that vary according to the linear functions of the shell thickness. The motion equations are solved by the Galerkin method and the fourth-order Runge–Kutta method. In numerical results, the influences of geometrical parameters, elastic foundations, natural frequency parameters, and nanotube volume fraction of FG-CNTRC truncated conical shells are investigated. The proposed results are validated by comparing them with those of other authors. PMID:29057821

Crystal water dynamics of guanosine dihydrate: analysis of atomic displacement parameters, time profile of hydrogen-bonding probability, and translocation of water by MD simulation.

PubMed

Yoneda, Shigetaka; Sugawara, Yoko; Urabe, Hisako

2005-01-27

The dynamics of crystal water molecules of guanosine dihydrate are investigated in detail by molecular dynamics (MD) simulation. A 2 ns simulation is performed using a periodic boundary box composed of 4 x 5 x 8 crystallographic unit cells and using the particle-mesh Ewald method for calculation of electrostatic energy. The simulated average atomic positions and atomic displacement parameters are remarkably coincident with the experimental values determined by X-ray analysis, confirming the high accuracy of this simulation. The dynamics of crystal water are analyzed in terms of atomic displacement parameters, orientation vectors, order parameters, self-correlation functions of the orientation vectors, time profiles of hydrogen-bonding probability, and translocations. The simulation clarifies that the average structure is composed of various stable and transient structures of the molecules. The simulated guanosine crystal forms a layered structure, with four water sites per asymmetric unit, classified as either interlayer water or intralayer water. From a detailed analysis of the translocations of water molecules in the simulation, columns of intralayer water molecules along the c axis appear to represent a pathway for hydration and dehydration by a kind of molecular valve mechanism.

Study on Nonlinear Vibration Analysis of Gear System with Random Parameters

NASA Astrophysics Data System (ADS)

Tong, Cao; Liu, Xiaoyuan; Fan, Li

2018-03-01

In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.

Deterministic diffusion in flower-shaped billiards.

PubMed

Harayama, Takahisa; Klages, Rainer; Gaspard, Pierre

2002-08-01

We propose a flower-shaped billiard in order to study the irregular parameter dependence of chaotic normal diffusion. Our model is an open system consisting of periodically distributed obstacles in the shape of a flower, and it is strongly chaotic for almost all parameter values. We compute the parameter dependent diffusion coefficient of this model from computer simulations and analyze its functional form using different schemes, all generalizing the simple random walk approximation of Machta and Zwanzig. The improved methods we use are based either on heuristic higher-order corrections to the simple random walk model, on lattice gas simulation methods, or they start from a suitable Green-Kubo formula for diffusion. We show that dynamical correlations, or memory effects, are of crucial importance in reproducing the precise parameter dependence of the diffusion coefficent.

Dynamical models of happiness with fractional order

NASA Astrophysics Data System (ADS)

Song, Lei; Xu, Shiyun; Yang, Jianying

2010-03-01

This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.

Dynamic Monte Carlo Simulations of Phase Ordering in Br Electrosorption on Ag(100)

NASA Astrophysics Data System (ADS)

Mitchell, S. J.; Brown, G.; Rikvold, P. A.

2000-03-01

We study the dynamics of Br electrosorption on single-crystal Ag(100) by Monte Carlo simulation. The system has a second-order phase transition from a low-coverage disordered phase at more negative potentials to a doubly degenerate c(2× 2) ordered phase at more positive potentials.(B.M. Ocko, et al.), Phys. Rev. Lett. 79, 1511 (1997). Effective lateral interactions were estimated by fitting equilibrium Monte Carlo isotherms to experiments. These are well described by nearest-neighbor exclusion and repulsive 1/r^3 interactions.(M.T.M. Koper, J. Electroanal. Chem. 450), 189 (1997). Considering adsorption/desorption and diffusion with barriers estimated from ab-initio calculations,(A. Ignaczak and J.A.N.F. Gomes, J. Electroanal. Chem. 420), 71 (1997). we simulate the time dependent Br coverage, order parameter, and x-ray scattering intensity following sudden potential steps across the phase boundary. For steps far into the ordered phase, dynamical scaling is observed. For smaller steps, the dynamics are more complicated. We also analyze hysteresis in a simulated cyclic-voltammetry experiment. Movies at http://www.scri.fsu.edu/ ~mitchell/.

Bayesian dynamic modeling of time series of dengue disease case counts

PubMed Central

López-Quílez, Antonio; Torres-Prieto, Alexander

2017-01-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health. PMID:28671941

Dynamics of weakly inhomogeneous oscillator populations: perturbation theory on top of Watanabe-Strogatz integrability

NASA Astrophysics Data System (ADS)

Vlasov, Vladimir; Rosenblum, Michael; Pikovsky, Arkady

2016-08-01

As has been shown by Watanabe and Strogatz (WS) (1993 Phys. Rev. Lett. 70 2391), a population of identical phase oscillators, sine-coupled to a common field, is a partially integrable system: for any ensemble size its dynamics reduce to equations for three collective variables. Here we develop a perturbation approach for weakly nonidentical ensembles. We calculate corrections to the WS dynamics for two types of perturbations: those due to a distribution of natural frequencies and of forcing terms, and those due to small white noise. We demonstrate that in both cases, the complex mean field for which the dynamical equations are written is close to the Kuramoto order parameter, up to the leading order in the perturbation. This supports the validity of the dynamical reduction suggested by Ott and Antonsen (2008 Chaos 18 037113) for weakly inhomogeneous populations.

Higher-order spin and charge dynamics in a quantum dot-lead hybrid system.

PubMed

Otsuka, Tomohiro; Nakajima, Takashi; Delbecq, Matthieu R; Amaha, Shinichi; Yoneda, Jun; Takeda, Kenta; Allison, Giles; Stano, Peter; Noiri, Akito; Ito, Takumi; Loss, Daniel; Ludwig, Arne; Wieck, Andreas D; Tarucha, Seigo

2017-09-22

Understanding the dynamics of open quantum systems is important and challenging in basic physics and applications for quantum devices and quantum computing. Semiconductor quantum dots offer a good platform to explore the physics of open quantum systems because we can tune parameters including the coupling to the environment or leads. Here, we apply the fast single-shot measurement techniques from spin qubit experiments to explore the spin and charge dynamics due to tunnel coupling to a lead in a quantum dot-lead hybrid system. We experimentally observe both spin and charge time evolution via first- and second-order tunneling processes, and reveal the dynamics of the spin-flip through the intermediate state. These results enable and stimulate the exploration of spin dynamics in dot-lead hybrid systems, and may offer useful resources for spin manipulation and simulation of open quantum systems.

Nonlinear modeling and dynamic analysis of a hydro-turbine governing system in the process of sudden load increase transient

NASA Astrophysics Data System (ADS)

Li, Huanhuan; Chen, Diyi; Zhang, Hao; Wang, Feifei; Ba, Duoduo

2016-12-01

In order to study the nonlinear dynamic behaviors of a hydro-turbine governing system in the process of sudden load increase transient, we establish a novel nonlinear dynamic model of the hydro-turbine governing system which considers the elastic water-hammer model of the penstock and the second-order model of the generator. The six nonlinear dynamic transfer coefficients of the hydro-turbine are innovatively proposed by utilizing internal characteristics and analyzing the change laws of the characteristic parameters of the hydro-turbine governing system. Moreover, from the point of view of engineering, the nonlinear dynamic behaviors of the above system are exhaustively investigated based on bifurcation diagrams and time waveforms. More importantly, all of the above analyses supply theoretical basis for allowing a hydropower station to maintain a stable operation in the process of sudden load increase transient.

Non-linear dynamical classification of short time series of the rössler system in high noise regimes.

PubMed

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

PubMed Central

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E.; Poizner, Howard; Sejnowski, Terrence J.

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson’s disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to −30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A′ under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data. PMID:24379798

Spatial curvilinear path following control of underactuated AUV with multiple uncertainties.

PubMed

Miao, Jianming; Wang, Shaoping; Zhao, Zhiping; Li, Yuan; Tomovic, Mileta M

2017-03-01

This paper investigates the problem of spatial curvilinear path following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties. Firstly, in order to design the appropriate controller, path following error dynamics model is constructed in a moving Serret-Frenet frame, and the five degrees of freedom (DOFs) dynamic model with multiple uncertainties is established. Secondly, the proposed control law is separated into kinematic controller and dynamic controller via back-stepping technique. In the case of kinematic controller, to overcome the drawback of dependence on the accurate vehicle model that are present in a number of path following control strategies described in the literature, the unknown side-slip angular velocity and attack angular velocity are treated as uncertainties. Whereas in the case of dynamic controller, the model parameters perturbations, unknown external environmental disturbances and the nonlinear hydrodynamic damping terms are treated as lumped uncertainties. Both kinematic and dynamic uncertainties are estimated and compensated by designed reduced-order linear extended state observes (LESOs). Thirdly, feedback linearization (FL) based control law is implemented for the control model using the estimates generated by reduced-order LESOs. For handling the problem of computational complexity inherent in the conventional back-stepping method, nonlinear tracking differentiators (NTDs) are applied to construct derivatives of the virtual control commands. Finally, the closed loop stability for the overall system is established. Simulation and comparative analysis demonstrate that the proposed controller exhibits enhanced performance in the presence of internal parameter variations, external unknown disturbances, unmodeled nonlinear damping terms, and measurement noises. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Nonequilibrium Langevin dynamics: A demonstration study of shear flow fluctuations in a simple fluid

NASA Astrophysics Data System (ADS)

Belousov, Roman; Cohen, E. G. D.; Rondoni, Lamberto

2017-08-01

The present paper is based on a recent success of the second-order stochastic fluctuation theory in describing time autocorrelations of equilibrium and nonequilibrium physical systems. In particular, it was shown to yield values of the related deterministic parameters of the Langevin equation for a Couette flow in a microscopic molecular dynamics model of a simple fluid. In this paper we find all the remaining constants of the stochastic dynamics, which then is simulated numerically and compared directly with the original physical system. By using these data, we study in detail the accuracy and precision of a second-order Langevin model for nonequilibrium physical systems theoretically and computationally. We find an intriguing relation between an applied external force and cumulants of the resulting flow fluctuations. This is characterized by a linear dependence of an athermal cumulant ratio, an apposite quantity introduced here. In addition, we discuss how the order of a given Langevin dynamics can be raised systematically by introducing colored noise.

a Numerical Investigation of the Jamming Transition in Traffic Flow on Diluted Planar Networks

NASA Astrophysics Data System (ADS)

Achler, Gabriele; Barra, Adriano

In order to develop a toy model for car's traffic in cities, in this paper we analyze, by means of numerical simulations, the transition among fluid regimes and a congested jammed phase of the flow of kinetically constrained hard spheres in planar random networks similar to urban roads. In order to explore as timescales as possible, at a microscopic level we implement an event driven dynamics as the infinite time limit of a class of already existing model (Follow the Leader) on an Erdos-Renyi two-dimensional graph, the crossroads being accounted by standard Kirchoff density conservations. We define a dynamical order parameter as the ratio among the moving spheres versus the total number and by varying two control parameters (density of the spheres and coordination number of the network) we study the phase transition. At a mesoscopic level it respects an, again suitable, adapted version of the Lighthill-Whitham model, which belongs to the fluid-dynamical approach to the problem. At a macroscopic level, the model seems to display a continuous transition from a fluid phase to a jammed phase when varying the density of the spheres (the amount of cars in a city-like scenario) and a discontinuous jump when varying the connectivity of the underlying network.

Dynamic Control of Collapse in a Vortex Airy Beam

PubMed Central

Chen, Rui-Pin; Chew, Khian-Hooi; He, Sailing

2013-01-01

Here we study systematically the self-focusing dynamics and collapse of vortex Airy optical beams in a Kerr medium. The collapse is suppressed compared to a non-vortex Airy beam in a Kerr medium due to the existence of vortex fields. The locations of collapse depend sensitively on the initial power, vortex order, and modulation parameters. The collapse may occur in a position where the initial field is nearly zero, while no collapse appears in the region where the initial field is mainly distributed. Compared with a non-vortex Airy beam, the collapse of a vortex Airy beam can occur at a position away from the area of the initial field distribution. Our study shows the possibility of controlling and manipulating the collapse, especially the precise position of collapse, by purposely choosing appropriate initial power, vortex order or modulation parameters of a vortex Airy beam. PMID:23518858

Pairing induced superconductivity in holography

NASA Astrophysics Data System (ADS)

Bagrov, Andrey; Meszena, Balazs; Schalm, Koenraad

2014-09-01

We study pairing induced superconductivity in large N strongly coupled systems at finite density using holography. In the weakly coupled dual gravitational theory the mechanism is conventional BCS theory. An IR hard wall cut-off is included to ensure that we can controllably address the dynamics of a single confined Fermi surface. We address in detail the interplay between the scalar order parameter field and fermion pairing. Adding an explicitly dynamical scalar operator with the same quantum numbers as the fermion-pair, the theory experiences a BCS/BEC crossover controlled by the relative scaling dimensions. We find the novel result that this BCS/BEC crossover exposes resonances in the canonical expectation value of the scalar operator. This occurs not only when the scaling dimension is degenerate with the Cooper pair, but also with that of higher derivative paired operators. We speculate that a proper definition of the order parameter which takes mixing with these operators into account stays finite nevertheless.

AB INITIO Molecular Dynamics Simulations on Local Structure and Electronic Properties in Liquid Sb from 913 K to 1193 K

NASA Astrophysics Data System (ADS)

Hao, Qing-Hai; Li, Y. D.; Kong, Xiang-Shan; Liu, C. S.

2013-02-01

Ab initio molecular dynamics simulations on liquid Sb have been carried out at five different temperatures from 913 K to 1193 K. We have investigated the temperature dependence of structure properties including structural factor S(Q), pair correlation function g(r), bond-angle distribution function g3(θ), cluster properties and bond order parameter Q4 and Q6. A shoulder was reproduced in the high wave number side of the first peak in the S(Q) implying that the residual structure units of crystalline Sb remain in liquid Sb. There is a noticeable bend at around 1023 K in the temperature dependence of the first-peak height of S(Q), the cluster properties and bond order parameter Q4, respectively, indicating that an abnormal structural change may occur at 973-1023 K.

Transition to organized behavior on suspensions of concentrated bacteria

NASA Astrophysics Data System (ADS)

Ganguly, Sujoy; Cisneros, Luis; Kessler, John; Goldstein, Raymond

2008-11-01

Concentrated populations of the swimming bacterium Bacillus subtilis develop a collective phase, the Zooming BioNematic, that exhibits large-scale coherence analogous to the molecular alignment of nematic liquid crystals. Bacterial suspensions were prepared in order to experimentally measure the transition to organized behavior as a function of the cell number concentration. PIV analysis was used to obtain cell velocities and define an order parameter in order to characterize the dynamics of the system.

Effects of random initial conditions on the dynamical scaling behaviors of a fixed-energy Manna sandpile model in one dimension

NASA Astrophysics Data System (ADS)

Kwon, Sungchul; Kim, Jin Min

2015-01-01

For a fixed-energy (FE) Manna sandpile model in one dimension, we investigate the effects of random initial conditions on the dynamical scaling behavior of an order parameter. In the FE Manna model, the density ρ of total particles is conserved, and an absorbing phase transition occurs at ρc as ρ varies. In this work, we show that, for a given ρ , random initial distributions of particles lead to the domain structure in which domains with particle densities higher and lower than ρc alternate with each other. In the domain structure, the dominant length scale is the average domain length, which increases via the coalescence of adjacent domains. At ρc, the domain structure slows down the decay of an order parameter and also causes anomalous finite-size effects, i.e., power-law decay followed by an exponential one before the quasisteady state. As a result, the interplay of particle conservation and random initial conditions causes the domain structure, which is the origin of the anomalous dynamical scaling behaviors for random initial conditions.

Protein Conformational Entropy is Independent of Solvent

NASA Astrophysics Data System (ADS)

Nucci, Nathaniel; Moorman, Veronica; Gledhill, John; Valentine, Kathleen; Wand, A. Joshua

Proteins exhibit most of their conformational entropy in individual bond vector motions on the ps-ns timescale. These motions can be examined through determination of the Lipari-Szabo generalized squared order parameter (O2) using NMR spin relaxation measurements. It is often argued that most protein motions are intimately dependent on the nature of the solvating environment. Here the solvent dependence of the fast protein dynamics is directly assessed. Using the model protein ubiquitin, the order parameters of the backbone and methyl groups are shown to be generally unaffected by up to a six-fold increase in bulk viscosity or by encapsulation in the nanoscale interior of a reverse micelle. In addition, the reverse micelle condition permits direct comparison of protein dynamics to the mobility of the hydration layer; no correlation is observed. The dynamics of aromatic side chains are also assessed and provide an estimate of the length- and timescale of protein motions where solvent dependence is seen. These data demonstrate the solvent independence of conformational entropy, clarifying a long-held misconception in the fundamental behavior of biological macromolecules. Supported by the National Science Foundation.

Structure-dependent magnetoresistance and spin-transfer torque in antiferromagnetic Fe |MgO |FeMn |Cu tunnel junctions

NASA Astrophysics Data System (ADS)

Jia, Xingtao; Tang, Huimin; Wang, Shizhuo; Qin, Minghui

2017-02-01

We predict large magnetoresistance (MR) and spin transfer torque (STT) in antiferromagnetic Fe |MgO |FeMn |Cu tunnel junctions based on first-principles scattering theory. MR as large as ˜100 % is found in one junction. Magnetic dynamic simulations show that STT acting on the antiferromagnetic order parameter dominates the spin dynamics, and an electronic bias of order 10-1mV and current density of order 105Acm-2 can switches a junction of three-layer MgO, they are about one order smaller than that in Fe |MgO |Fe junction with the same barrier thickness, respectively. The multiple scattering in the antiferromagnetic region is considered to be responsible for the enhanced spin torque and smaller switching current density.

Fixed order dynamic compensation for multivariable linear systems

NASA Technical Reports Server (NTRS)

Kramer, F. S.; Calise, A. J.

1986-01-01

This paper considers the design of fixed order dynamic compensators for multivariable time invariant linear systems, minimizing a linear quadratic performance cost functional. Attention is given to robustness issues in terms of multivariable frequency domain specifications. An output feedback formulation is adopted by suitably augmenting the system description to include the compensator states. Either a controller or observer canonical form is imposed on the compensator description to reduce the number of free parameters to its minimal number. The internal structure of the compensator is prespecified by assigning a set of ascending feedback invariant indices, thus forming a Brunovsky structure for the nominal compensator.

Molecular dynamics on diffusive time scales from the phase-field-crystal equation.

PubMed

Chan, Pak Yuen; Goldenfeld, Nigel; Dantzig, Jon

2009-03-01

We extend the phase-field-crystal model to accommodate exact atomic configurations and vacancies by requiring the order parameter to be non-negative. The resulting theory dictates the number of atoms and describes the motion of each of them. By solving the dynamical equation of the model, which is a partial differential equation, we are essentially performing molecular dynamics simulations on diffusive time scales. To illustrate this approach, we calculate the two-point correlation function of a fluid.

Uncertainty in Damage Detection, Dynamic Propagation and Just-in-Time Networks

DTIC Science & Technology

2015-08-03

estimated parameter uncertainty in dynamic data sets; high order compact finite difference schemes for Helmholtz equations with discontinuous wave numbers...delay differential equations with a Gamma distributed delay. We found that with the same population size the histogram plots for the solution to the...schemes for Helmholtz equations with discontinuous wave numbers across interfaces. • We carried out numerical sensitivity analysis with respect to

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed Ising system within the effective-field theory and Glauber-type stochastic dynamics approach.

PubMed

Ertaş, Mehmet; Deviren, Bayram; Keskin, Mustafa

2012-11-01

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed spin-2 and spin-5/2 Ising system in the presence of a time-varying (sinusoidal) magnetic field are studied within the effective-field theory (EFT) with correlations. The time evolution of the system is described by using Glauber-type stochastic dynamics. The dynamic EFT equations are derived by employing the Glauber transition rates for two interpenetrating square lattices. We investigate the time dependence of the magnetizations for different interaction parameter values in order to find the phases in the system. We also study the thermal behavior of the dynamic magnetizations, the hysteresis loop area, and dynamic correlation. The dynamic phase diagrams are presented in the reduced magnetic field amplitude and reduced temperature plane and we observe that the system exhibits dynamic tricritical and reentrant behaviors. Moreover, the system also displays a double critical end point (B), a zero-temperature critical point (Z), a critical end point (E), and a triple point (TP). We also performed a comparison with the mean-field prediction in order to point out the effects of correlations and found that some of the dynamic first-order phase lines, which are artifacts of the mean-field approach, disappeared.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

PubMed

Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

2016-01-15

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.

Experimental investigation of dynamic impact of firearm with suppressor

NASA Astrophysics Data System (ADS)

Kilikevicius, Arturas; Skeivalas, Jonas; Jurevicius, Mindaugas; Turla, Vytautas; Kilikeviciene, Kristina; Bureika, Gintautas; Jakstas, Arunas

2017-09-01

The internal ballistics processes occur in the tube during firearm firing. They cause tremendous vibratory shock forces and robust sounds. The determination of these dynamic parameters is relevant in order to reasonably estimate the firearm ergonomic and noise reduction features. The objective of this study is to improve the reliability of the results of measuring a firearm suppressor's dynamic parameters. The analysis of indicator stability is based on an assessment of dynamic parameters and setting the correlation during experimental research. An examination of the spread of intensity of firearm with suppressor dynamic vibration and an analysis of its signals upon applying the theory of covariance functions are carried out in this paper. The results of measuring the intensity of vibrations in fixed points of a firearm and a shooter have been recorded on a time scale in the form of data arrays (matrices). The estimates of covariance functions between the arrays of digital results in measuring the intensity of firearm vibrations and the estimates of covariance functions of single arrays have been calculated upon changing the quantization interval on the time scale. Software Matlab 7 has been applied in the calculation. Finally, basic conclusions are given.

Spatiotemporal chaos of fractional order logistic equation in nonlinear coupled lattices

NASA Astrophysics Data System (ADS)

Zhang, Ying-Qian; Wang, Xing-Yuan; Liu, Li-Yan; He, Yi; Liu, Jia

2017-11-01

We investigate a new spatiotemporal dynamics with fractional order differential logistic map and spatial nonlinear coupling. The spatial nonlinear coupling features such as the higher percentage of lattices in chaotic behaviors for most of parameters and none periodic windows in bifurcation diagrams are held, which are more suitable for encryptions than the former adjacent coupled map lattices. Besides, the proposed model has new features such as the wider parameter range and wider range of state amplitude for ergodicity, which contributes a wider range of key space when applied in encryptions. The simulations and theoretical analyses are developed in this paper.

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

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

PubMed

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

2014-01-01

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

Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

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

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

DEAN: A program for dynamic engine analysis

NASA Technical Reports Server (NTRS)

Sadler, G. G.; Melcher, K. J.

1985-01-01

The Dynamic Engine Analysis program, DEAN, is a FORTRAN code implemented on the IBM/370 mainframe at NASA Lewis Research Center for digital simulation of turbofan engine dynamics. DEAN is an interactive program which allows the user to simulate engine subsystems as well as a full engine systems with relative ease. The nonlinear first order ordinary differential equations which define the engine model may be solved by one of four integration schemes, a second order Runge-Kutta, a fourth order Runge-Kutta, an Adams Predictor-Corrector, or Gear's method for still systems. The numerical data generated by the model equations are displayed at specified intervals between which the user may choose to modify various parameters affecting the model equations and transient execution. Following the transient run, versatile graphics capabilities allow close examination of the data. DEAN's modeling procedure and capabilities are demonstrated by generating a model of simple compressor rig.

Monge-Ampére simulation of fourth order PDEs in two dimensions with application to elastic-electrostatic contact problems

NASA Astrophysics Data System (ADS)

DiPietro, Kelsey L.; Lindsay, Alan E.

2017-11-01

We present an efficient moving mesh method for the simulation of fourth order nonlinear partial differential equations (PDEs) in two dimensions using the Parabolic Monge-Ampére (PMA) equation. PMA methods have been successfully applied to the simulation of second order problems, but not on systems with higher order equations which arise in many topical applications. Our main application is the resolution of fine scale behavior in PDEs describing elastic-electrostatic interactions. The PDE system considered has multiple parameter dependent singular solution modalities, including finite time singularities and sharp interface dynamics. We describe how to construct a dynamic mesh algorithm for such problems which incorporates known self similar or boundary layer scalings of the underlying equation to locate and dynamically resolve fine scale solution features in these singular regimes. We find a key step in using the PMA equation for mesh generation in fourth order problems is the adoption of a high order representation of the transformation from the computational to physical mesh. We demonstrate the efficacy of the new method on a variety of examples and establish several new results and conjectures on the nature of self-similar singularity formation in higher order PDEs.

Effects of uniaxial pressure on the quantum tunneling of magnetization in a high-symmetry Mn12 single-molecule magnet

NASA Astrophysics Data System (ADS)

Atkinson, James H.; Fournet, Adeline D.; Bhaskaran, Lakshmi; Myasoedov, Yuri; Zeldov, Eli; del Barco, Enrique; Hill, Stephen; Christou, George; Friedman, Jonathan R.

2017-05-01

The symmetry of single-molecule magnets dictates their spin quantum dynamics, influencing how such systems relax via quantum tunneling of magnetization (QTM). By reducing a system's symmetry, through the application of a magnetic field or uniaxial pressure, these dynamics can be modified. We report measurements of the magnetization dynamics of a crystalline sample of the high-symmetry [M n12O12(O2CMe) 16(Me OH ) 4].M e OH single-molecule magnet as a function of uniaxial pressure applied either parallel or perpendicular to the sample's "easy" magnetization axis. At temperatures between 1.8 and 3.3 K, magnetic hysteresis loops exhibit the characteristic steplike features that signal the occurrence of QTM. After applying uniaxial pressure to the sample in situ, both the magnitude and field position of the QTM steps changed. The step magnitudes were observed to grow as a function of pressure in both arrangements of pressure, while pressure applied along (perpendicular to) the sample's easy axis caused the resonant-tunneling fields to increase (decrease). These observations were compared with simulations in which the system's Hamiltonian parameters were changed. From these comparisons, we determined that parallel pressure induces changes to the second-order axial anisotropy parameter as well as either the fourth-order axial or fourth-order transverse parameter, or to both. In addition, we find that pressure applied perpendicular to the easy axis induces a rhombic anisotropy E ≈D /2000 per kbar that can be understood as deriving from a symmetry-breaking distortion of the molecule.

Modeling of crack growth under mixed-mode loading by a molecular dynamics method and a linear fracture mechanics approach

NASA Astrophysics Data System (ADS)

Stepanova, L. V.

2017-12-01

Atomistic simulations of the central crack growth process in an infinite plane medium under mixed-mode loading using Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), a classical molecular dynamics code, are performed. The inter-atomic potential used in this investigation is the Embedded Atom Method (EAM) potential. Plane specimens with an initial central crack are subjected to mixed-mode loadings. The simulation cell contains 400,000 atoms. The crack propagation direction angles under different values of the mixity parameter in a wide range of values from pure tensile loading to pure shear loading in a wide range of temperatures (from 0.1 K to 800 K) are obtained and analyzed. It is shown that the crack propagation direction angles obtained by molecular dynamics coincide with the crack propagation direction angles given by the multi-parameter fracture criteria based on the strain energy density and the multi-parameter description of the crack-tip fields. The multi-parameter fracture criteria are based on the multi-parameter stress field description taking into account the higher order terms of the Williams series expansion of the crack tip fields.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tien, C; Brewer, M; Studenski, M

Purpose: Dynamic-jaw tracking maximizes the area blocked by both jaw and MLC in RapidArc. We developed a method to quantify jaw tracking. Methods: An Eclipse Scripting API (ESAPI) was used to export beam parameters for each arc’s control points. The specific beam parameters extracted were: gantry angle, control point number, meterset, x-jaw positions, y-jaw positions, MLC bank-number, MLC leaf-number, and MLC leaf-position. Each arc contained 178 control points with 120 MLC positions. MATLAB routines were written to process these parameters in order to calculate both the beam aperture (unblocked) size for each control point. An average aperture size was weightedmore » by meterset. Jaw factor was defined as the ratio between dynamic-jaw to static-jaw aperture size. Jaw factor was determined for forty retrospectively replanned patients treated with static-jaw delivery sites including lung, brain, prostate, H&N, rectum, and bladder. Results: Most patients had multiple arcs and reduced-field boosts, resulting in 151 fields. Of these, the lowest (0.4722) and highest (0.9622) jaw factor was observed in prostate and rectal cases, respectively. The median jaw factor was 0.7917 meaning there is the potential unincreased blocking by 20%. Clinically, the dynamic-jaw tracking represents an area surrounding the target which would receive MLC-only leakage transmission of 1.68% versus 0.1% with jaws. Jaw-tracking was more pronounced at areas farther from the target. In prostate patients, the rectum and bladder had 5.5% and 6.3% lower mean dose, respectively; the structures closer to the prostate such as the rectum and bladder both had 1.4% lower mean dose. Conclusion: A custom ESAPI script was coupled with a MATLAB routine in order to extract beam parameters from static-jaw plans and their replanned dynamic-jaw deliveries. The effects were quantified using jaw factor which is the ratio between the meterset weighted aperture size for dynamic-jaw fields versus static-jaw fields.« less

Visualization in mechanics: the dynamics of an unbalanced roller

NASA Astrophysics Data System (ADS)

Cumber, Peter S.

2017-04-01

It is well known that mechanical engineering students often find mechanics a difficult area to grasp. This article describes a system of equations describing the motion of a balanced and an unbalanced roller constrained by a pivot arm. A wide range of dynamics can be simulated with the model. The equations of motion are embedded in a graphical user interface for its numerical solution in MATLAB. This allows a student's focus to be on the influence of different parameters on the system dynamics. The simulation tool can be used as a dynamics demonstrator in a lecture or as an educational tool driven by the imagination of the student. By way of demonstration the simulation tool has been applied to a range of roller-pivot arm configurations. In addition, approximations to the equations of motion are explored and a second-order model is shown to be accurate for a limited range of parameters.

Magnetostructural coupling behavior at the ferromagnetic transition in double-perovskite S r2FeMo O6

NASA Astrophysics Data System (ADS)

Yang, Dexin; Harrison, Richard J.; Schiemer, Jason A.; Lampronti, Giulio I.; Liu, Xueyin; Zhang, Fenghua; Ding, Hao; Liu, Yan'gai; Carpenter, Michael A.

2016-01-01

The ordered double-perovskite S r2FeMo O6 (SFMO) possesses remarkable room-temperature low-field colossal magnetoresistivity and transport properties which are related, at least in part, to combined structural and magnetic instabilities that are responsible for a cubic-tetragonal phase transition near 420 K. A formal strain analysis combined with measurements of elastic properties from resonant ultrasound spectroscopy reveal a system with weak biquadratic coupling between two order parameters belonging to Γ4+ and m Γ4+ of parent space group F m 3 ¯m . The observed softening of the shear modulus by ˜50% is due to the classical effects of strain/order parameter coupling at an improper ferroelastic (Γ4+) transition which is second order in character, while the ferromagnetic order parameter (m Γ4+ ) couples only with volume strain. The influence of a third order parameter, for ordering of Fe and Mo on crystallographic B sites, is to change the strength of coupling between the Γ4+ order parameter and the tetragonal shear strain due to the influence of changes in local strain heterogeneity at a unit cell scale. High anelastic loss below the transition point reveals the presence of mobile ferroelastic twin walls which become pinned by oxygen vacancies in a temperature interval near 340 K. The twin walls must be both ferroelastic and ferromagnetic, but due to the weak coupling between the magnetic and structural order parameters it should be possible to pull them apart with a weak magnetic field. These insights into the role of strain coupling and relaxational effects in a system with only weak coupling between three order parameters allow rationalization and prediction of how static and dynamic properties of the material might be tuned in thin film form by choice of strain contrast with a substrate.

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions.

PubMed

Omori, Toshiaki; Kuwatani, Tatsu; Okamoto, Atsushi; Hukushima, Koji

2016-09-01

It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Fisher information at the edge of chaos in random Boolean networks.

PubMed

Wang, X Rosalind; Lizier, Joseph T; Prokopenko, Mikhail

2011-01-01

We study the order-chaos phase transition in random Boolean networks (RBNs), which have been used as models of gene regulatory networks. In particular we seek to characterize the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximized near the order-chaos phase transitions in RBNs, since this is the region where the system is most sensitive to its parameters. Furthermore, we use this study of RBNs to clarify the relationship between Shannon and Fisher information measures.

Second-order sliding mode controller with model reference adaptation for automatic train operation

NASA Astrophysics Data System (ADS)

Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

2017-11-01

In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

Optimization of Protein Backbone Dihedral Angles by Means of Hamiltonian Reweighting

PubMed Central

2016-01-01

Molecular dynamics simulations depend critically on the accuracy of the underlying force fields in properly representing biomolecules. Hence, it is crucial to validate the force-field parameter sets in this respect. In the context of the GROMOS force field, this is usually achieved by comparing simulation data to experimental observables for small molecules. In this study, we develop new amino acid backbone dihedral angle potential energy parameters based on the widely used 54A7 parameter set by matching to experimental J values and secondary structure propensity scales. In order to find the most appropriate backbone parameters, close to 100 000 different combinations of parameters have been screened. However, since the sheer number of combinations considered prohibits actual molecular dynamics simulations for each of them, we instead predicted the values for every combination using Hamiltonian reweighting. While the original 54A7 parameter set fails to reproduce the experimental data, we are able to provide parameters that match significantly better. However, to ensure applicability in the context of larger peptides and full proteins, further studies have to be undertaken. PMID:27559757

Kinematic scaling relations of CALIFA galaxies: A dynamical mass proxy for galaxies across the Hubble sequence.

NASA Astrophysics Data System (ADS)

Aquino-Ortíz, E.; Valenzuela, O.; Sánchez, S. F.; Hernández-Toledo, H.; Ávila-Reese, V.; van de Ven, G.; Rodríguez-Puebla, A.; Zhu, L.; Mancillas, B.; Cano-Díaz, M.; García-Benito, R.

2018-06-01

We used ionized gas and stellar kinematics for 667 spatially resolved galaxies publicly available from the Calar Alto Legacy Integral Field Area survey (CALIFA) 3rd Data Release with the aim of studying kinematic scaling relations as the Tully & Fisher (TF) relation using rotation velocity, Vrot, the Faber & Jackson (FJ) relation using velocity dispersion, σ, and also a combination of Vrot and σ through the SK parameter defined as SK^2 = KV_{rot}^2 + σ ^2 with constant K. Late-type and early-type galaxies reproduce the TF and FJ relations. Some early-type galaxies also follow the TF relation and some late-type galaxies the FJ relation, but always with larger scatter. On the contrary, when we use the SK parameter, all galaxies, regardless of the morphological type, lie on the same scaling relation, showing a tight correlation with the total stellar mass, M⋆. Indeed, we find that the scatter in this relation is smaller or equal to that of the TF and FJ relations. We explore different values of the K parameter without significant differences (slope and scatter) in our final results with respect the case K = 0.5 besides than a small change in the zero point. We calibrate the kinematic SK^2 dynamical mass proxy in order to make it consistent with sophisticated published dynamical models within 0.15 dex. We show that the SK proxy is able to reproduce the relation between the dynamical mass and the stellar mass in the inner regions of galaxies. Our result may be useful in order to produce fast estimations of the central dynamical mass in galaxies and to study correlations in large galaxy surveys.

Dynamics of the GB3 loop regions from MD simulation: how much of it is real?

PubMed

Li, Tong; Jing, Qingqing; Yao, Lishan

2011-04-07

A total of 1.1 μs of molecular dynamics (MD) simulations were performed to study the structure and dynamics of protein GB3. The simulation motional amplitude of the loop regions is generally overestimated in comparison with the experimental backbone N-H order parameters S(2). Two-state behavior is observed for several residues in these regions, with the minor state population in the range of 3-13%. Further inspection suggests that the (φ, ψ) dihedral angles of the minor states deviate from the GB3 experimental values, implying the existence of nonnative states. After fitting the MD trajectories of these residues to the NMR RDCs, the minor state populations are significantly reduced by at least 80%, suggesting that MD simulations are strongly biased toward the minor states, thus overestimating the dynamics of the loop regions. The optimized trajectories produce intra, sequential H(N)-H(α) RDCs and intra (3)J(HNHα) that are not included in the trajectories fitting for these residues that are closer to the experimental data. Unlike GB3, 0.55 μs MD simulations of protein ubiquitin do not show distinctive minor states, and the derived NMR order parameters are better converged. Our findings indicate that the artifacts of the simulations depend on the specific system studied and that one should be cautious interpreting the enhanced dihedral dynamics from long MD simulations.

Coupling between corotation and Lindblad resonances in the presence of secular precession rates

NASA Astrophysics Data System (ADS)

El Moutamid, Maryame; Sicardy, Bruno; Renner, Stéfan

2014-03-01

We investigate the dynamics of two satellites with masses and orbiting a massive central planet in a common plane, near a first order mean motion resonance ( m integer). We consider only the resonant terms of first order in eccentricity in the disturbing potential of the satellites, plus the secular terms causing the orbital apsidal precessions. We obtain a two-degrees-of-freedom system, associated with the two critical resonant angles and , where and are the mean longitude and longitude of periapsis of , respectively, and where the primed quantities apply to . We consider the special case where (restricted problem). The symmetry between the two angles and is then broken, leading to two different kinds of resonances, classically referred to as corotation eccentric resonance (CER) and Lindblad eccentric Resonance (LER), respectively. We write the four reduced equations of motion near the CER and LER, that form what we call the CoraLin model. This model depends upon only two dimensionless parameters that control the dynamics of the system: the distance between the CER and LER, and a forcing parameter that includes both the mass and the orbital eccentricity of the disturbing satellite. Three regimes are found: for the system is integrable, for of order unity, it exhibits prominent chaotic regions, while for large compared to 2, the behavior of the system is regular and can be qualitatively described using simple adiabatic invariant arguments. We apply this model to three recently discovered small Saturnian satellites dynamically linked to Mimas through first order mean motion resonances: Aegaeon, Methone and Anthe. Poincaré surfaces of section reveal the dynamical structure of each orbit, and their proximity to chaotic regions. This work may be useful to explore various scenarii of resonant capture for those satellites.

Thermodynamic scaling of glassy dynamics and dynamic heterogeneities in metallic glass-forming liquid

NASA Astrophysics Data System (ADS)

Hu, Yuan-Chao; Shang, Bao-Shuang; Guan, Peng-Fei; Yang, Yong; Bai, Hai-Yang; Wang, Wei-Hua

2016-09-01

A ternary metallic glass-forming liquid is found to be not strongly correlating thermodynamically, but its average dynamics, dynamic heterogeneities including the high order dynamic correlation length, and static structure are still well described by thermodynamic scaling with the same scaling exponent γ. This may indicate that the metallic liquid could be treated as a single-parameter liquid. As an intrinsic material constant stemming from the fundamental interatomic interactions, γ is theoretically predicted from the thermodynamic fluctuations of the potential energy and the virial. Although γ is conventionally understood merely from the repulsive part of the inter-particle potentials, the strong correlation between γ and the Grüneisen parameter up to the accuracy of the Dulong-Petit approximation demonstrates the important roles of anharmonicity and attractive force of the interatomic potential in governing glass transition of metallic glassformers. These findings may shed light on how to understand metallic glass formation from the fundamental interatomic interactions.

Resonant Capture and Tidal Evolution in Circumbinary Systems: Testing the Case of Kepler-38

NASA Astrophysics Data System (ADS)

Zoppetti, F. A.; Beaugé, C.; Leiva, A. M.

2018-04-01

Circumbinary planets are thought to form far from the central binary and migrate inwards by interactions with the circumbinary disk, ultimately stopping near their present location either by a planetary trap near the disk inner edge or by resonance capture. Here, we analyze the second possibility, presenting a detailed numerical study on the capture process, resonant dynamics and tidal evolution of circumbinary planets in high-order mean-motion resonances (MMRs). Planetary migration was modeled as an external acceleration in an N-body code, while tidal effects were incorporated with a weak-friction equilibrium tide model. As a working example we chose Kepler-38, a highly evolved system with a planet in the vicinity of the 5/1 MMR. Our simulations show that resonance capture is a high-probability event under a large range of system parameters, although several different resonant configuration are possible. We identified three possible outcomes: aligned librations, anti-aligned librations and chaotic solutions. All were found to be dynamically stable, even after the dissipation of the disk, for time-spans of the order of the system's age. We found that while tidal evolution decreases the binary's separation, the semimajor axis of the planet is driven outwards. Although the net effect is a secular increase in the mean-motion ratio, the system requires a planetary tidal parameter of the order of unity to reproduce the observed orbital configuration. The results presented here open an interesting outlook into the complex dynamics of high-order resonances in circumbinary systems.

Resonant capture and tidal evolution in circumbinary systems: testing the case of Kepler-38

NASA Astrophysics Data System (ADS)

Zoppetti, F. A.; Beaugé, C.; Leiva, A. M.

2018-07-01

Circumbinary planets are thought to form far from the central binary and migrate inwards by interactions with the circumbinary disc, ultimately stopping near their present location either by a planetary trap near the disc inner edge or by resonance capture. Here, we analyse the second possibility, presenting a detailed numerical study on the capture process, resonant dynamics, and tidal evolution of circumbinary planets in high-order mean-motion resonances (MMRs). Planetary migration was modelled as an external acceleration in an N-body code, while tidal effects were incorporated with a weak-friction equilibrium tide model. As a working example, we chose Kepler-38, a highly evolved system with a planet in the vicinity of the 5/1 MMR. Our simulations show that resonance capture is a high-probability event under a large range of system parameters, although several different resonant configuration are possible. We identified three possible outcomes: aligned librations, anti-aligned librations, and chaotic solutions. All were found to be dynamically stable, even after the dissipation of the disc, for time spans of the order of the system's age. We found that while tidal evolution decreases the binary's separation, the semimajor axis of the planet is driven outwards. Although the net effect is a secular increase in the mean-motion ratio, the system requires a planetary tidal parameter of the order of unity to reproduce the observed orbital configuration. The results presented here open an interesting outlook into the complex dynamics of high-order resonances in circumbinary systems.

The role played by self-orientational properties in nematics of colloids with molecules axially symmetric.

PubMed

Alarcón-Waess, O

2010-04-14

The self-orientational structure factor as well as the short-time self-orientational diffusion coefficient is computed for colloids composed by nonspherical molecules. To compute the short-time dynamics the hydrodynamic interactions are not taken into account. The hard molecules with at least one symmetry axis considered are: rods, spherocylinders, and tetragonal parallelepipeds. Because both orientational properties in study are written in terms of the second and fourth order parameters, these automatically hold the features of the order parameters. That is, they present a discontinuity for first order transitions, determining in this way the spinodal line. In order to analyze the nematic phase only, we choose the appropriate values for the representative quantities that characterize the molecules. Different formalisms are used to compute the structural properties: de Gennes-Landau approach, Smoluchowski equation and computer simulations. Some of the necessary inputs are taken from literature. Our results show that the self-orientational properties play an important role in the characterization and the localization of axially symmetric phases. While the self-structure decreases throughout the nematics, the short-time self-diffusion does not decrease but rather increases. We study the evolution of the second and fourth order parameters; we find different responses for axial and biaxial nematics, predicting the possibility of a biaxial nematics in tetragonal parallelepiped molecules. By considering the second order in the axial-biaxial phase transition, with the support of the self-orientational structure factor, we are able to propose the density at which this occurs. The short-time dynamics is able to predict a different value in the axial and the biaxial phases. Because the different behavior of the fourth order parameter, the diffusion coefficient is lower for a biaxial phase than for an axial one. Therefore the self-structure factor is able to localize continuous phase transitions involving axially symmetric phases and the short-time self-orientational diffusion is able to distinguish the ordered phase by considering the degree of alignment, that is, axial or biaxial.

The internal dynamics of slowly rotating biological systems

NASA Technical Reports Server (NTRS)

Kessler, John O.

1992-01-01

The structure and the dynamics of biological systems are complex. Steady gravitational forces that act on organisms cause hydrostatic pressure gradients, stress in solid components, and ordering of movable subsystems according to density. Rotation induces internal motion; it also stresses and or deforms regions of attachment and containment. The disrupted gravitationally ordered layers of movable entities are replaced by their orbital movements. New ordering geometries may arise also, especially if fluids of various densities occur. One novel result obtained concerns the application of scheduled variation of clinostat rotation rates to the management of intracellular particle trajectories. Rotation and its consequences are discussed in terms of scaling factors for parameters such as time, derived from mathematical models for simple rotating mechanical systems.

Dipolar Spin Ice States with a Fast Monopole Hopping Rate in CdEr2X4 (X =Se , S)

NASA Astrophysics Data System (ADS)

Gao, Shang; Zaharko, O.; Tsurkan, V.; Prodan, L.; Riordan, E.; Lago, J.; Fâk, B.; Wildes, A. R.; Koza, M. M.; Ritter, C.; Fouquet, P.; Keller, L.; Canévet, E.; Medarde, M.; Blomgren, J.; Johansson, C.; Giblin, S. R.; Vrtnik, S.; Luzar, J.; Loidl, A.; Rüegg, Ch.; Fennell, T.

2018-03-01

Excitations in a spin ice behave as magnetic monopoles, and their population and mobility control the dynamics of a spin ice at low temperature. CdEr2 Se4 is reported to have the Pauling entropy characteristic of a spin ice, but its dynamics are three orders of magnitude faster than the canonical spin ice Dy2 Ti2 O7 . In this Letter we use diffuse neutron scattering to show that both CdEr2 Se4 and CdEr2 S4 support a dipolar spin ice state—the host phase for a Coulomb gas of emergent magnetic monopoles. These Coulomb gases have similar parameters to those in Dy2 Ti2 O7 , i.e., dilute and uncorrelated, and so cannot provide three orders faster dynamics through a larger monopole population alone. We investigate the monopole dynamics using ac susceptometry and neutron spin echo spectroscopy, and verify the crystal electric field Hamiltonian of the Er3 + ions using inelastic neutron scattering. A quantitative calculation of the monopole hopping rate using our Coulomb gas and crystal electric field parameters shows that the fast dynamics in CdEr2X4 (X =Se , S) are primarily due to much faster monopole hopping. Our work suggests that CdEr2X4 offer the possibility to study alternative spin ice ground states and dynamics, with equilibration possible at much lower temperatures than the rare earth pyrochlore examples.

Nonequilibrium phase transitions in isotropic Ashkin-Teller model

NASA Astrophysics Data System (ADS)

Akıncı, Ümit

2017-03-01

Dynamic behavior of an isotropic Ashkin-Teller model in the presence of a periodically oscillating magnetic field has been analyzed by means of the mean field approximation. The dynamic equation of motion has been constructed with the help of a Glauber type stochastic process and solved for a square lattice. After defining the possible dynamical phases of the system, phase diagrams have been given and the behavior of the hysteresis loops has been investigated in detail. The hysteresis loop for specific order parameter of isotropic Ashkin-Teller model has been defined and characteristics of this loop in different dynamical phases have been given.

Linear modeling of human hand-arm dynamics relevant to right-angle torque tool interaction.

PubMed

Ay, Haluk; Sommerich, Carolyn M; Luscher, Anthony F

2013-10-01

A new protocol was evaluated for identification of stiffness, mass, and damping parameters employing a linear model for human hand-arm dynamics relevant to right-angle torque tool use. Powered torque tools are widely used to tighten fasteners in manufacturing industries. While these tools increase accuracy and efficiency of tightening processes, operators are repetitively exposed to impulsive forces, posing risk of upper extremity musculoskeletal injury. A novel testing apparatus was developed that closely mimics biomechanical exposure in torque tool operation. Forty experienced torque tool operators were tested with the apparatus to determine model parameters and validate the protocol for physical capacity assessment. A second-order hand-arm model with parameters extracted in the time domain met model accuracy criterion of 5% for time-to-peak displacement error in 93% of trials (vs. 75% for frequency domain). Average time-to-peak handle displacement and relative peak handle force errors were 0.69 ms and 0.21%, respectively. Model parameters were significantly affected by gender and working posture. Protocol and numerical calculation procedures provide an alternative method for assessing mechanical parameters relevant to right-angle torque tool use. The protocol more closely resembles tool use, and calculation procedures demonstrate better performance of parameter extraction using time domain system identification methods versus frequency domain. Potential future applications include parameter identification for in situ torque tool operation and equipment development for human hand-arm dynamics simulation under impulsive forces that could be used for assessing torque tools based on factors relevant to operator health (handle dynamics and hand-arm reaction force).

A new data-driven model for post-transplant antibody dynamics in high risk kidney transplantation.

PubMed

Zhang, Yan; Briggs, David; Lowe, David; Mitchell, Daniel; Daga, Sunil; Krishnan, Nithya; Higgins, Robert; Khovanova, Natasha

2017-02-01

The dynamics of donor specific human leukocyte antigen antibodies during early stage after kidney transplantation are of great clinical interest as these antibodies are considered to be associated with short and long term clinical outcomes. The limited number of antibody time series and their diverse patterns have made the task of modelling difficult. Focusing on one typical post-transplant dynamic pattern with rapid falls and stable settling levels, a novel data-driven model has been developed for the first time. A variational Bayesian inference method has been applied to select the best model and learn its parameters for 39 time series from two groups of graft recipients, i.e. patients with and without acute antibody-mediated rejection (AMR) episodes. Linear and nonlinear dynamic models of different order were attempted to fit the time series, and the third order linear model provided the best description of the common features in both groups. Both deterministic and stochastic parameters are found to be significantly different in the AMR and no-AMR groups showing that the time series in the AMR group have significantly higher frequency of oscillations and faster dissipation rates. This research may potentially lead to better understanding of the immunological mechanisms involved in kidney transplantation. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Global dynamics for switching systems and their extensions by linear differential equations

NASA Astrophysics Data System (ADS)

Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

2018-03-01

Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

Material and morphology parameter sensitivity analysis in particulate composite materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyu; Oskay, Caglar

2017-12-01

This manuscript presents a novel parameter sensitivity analysis framework for damage and failure modeling of particulate composite materials subjected to dynamic loading. The proposed framework employs global sensitivity analysis to study the variance in the failure response as a function of model parameters. In view of the computational complexity of performing thousands of detailed microstructural simulations to characterize sensitivities, Gaussian process (GP) surrogate modeling is incorporated into the framework. In order to capture the discontinuity in response surfaces, the GP models are integrated with a support vector machine classification algorithm that identifies the discontinuities within response surfaces. The proposed framework is employed to quantify variability and sensitivities in the failure response of polymer bonded particulate energetic materials under dynamic loads to material properties and morphological parameters that define the material microstructure. Particular emphasis is placed on the identification of sensitivity to interfaces between the polymer binder and the energetic particles. The proposed framework has been demonstrated to identify the most consequential material and morphological parameters under vibrational and impact loads.

Global dynamics for switching systems and their extensions by linear differential equations.

PubMed

Huttinga, Zane; Cummins, Bree; Gedeon, Tomáš; Mischaikow, Konstantin

2018-03-15

Switching systems use piecewise constant nonlinearities to model gene regulatory networks. This choice provides advantages in the analysis of behavior and allows the global description of dynamics in terms of Morse graphs associated to nodes of a parameter graph. The parameter graph captures spatial characteristics of a decomposition of parameter space into domains with identical Morse graphs. However, there are many cellular processes that do not exhibit threshold-like behavior and thus are not well described by a switching system. We consider a class of extensions of switching systems formed by a mixture of switching interactions and chains of variables governed by linear differential equations. We show that the parameter graphs associated to the switching system and any of its extensions are identical. For each parameter graph node, there is an order-preserving map from the Morse graph of the switching system to the Morse graph of any of its extensions. We provide counterexamples that show why possible stronger relationships between the Morse graphs are not valid.

Understanding the transmission dynamics of respiratory syncytial virus using multiple time series and nested models.

PubMed

White, L J; Mandl, J N; Gomes, M G M; Bodley-Tickell, A T; Cane, P A; Perez-Brena, P; Aguilar, J C; Siqueira, M M; Portes, S A; Straliotto, S M; Waris, M; Nokes, D J; Medley, G F

2007-09-01

The nature and role of re-infection and partial immunity are likely to be important determinants of the transmission dynamics of human respiratory syncytial virus (hRSV). We propose a single model structure that captures four possible host responses to infection and subsequent reinfection: partial susceptibility, altered infection duration, reduced infectiousness and temporary immunity (which might be partial). The magnitude of these responses is determined by four homotopy parameters, and by setting some of these parameters to extreme values we generate a set of eight nested, deterministic transmission models. In order to investigate hRSV transmission dynamics, we applied these models to incidence data from eight international locations. Seasonality is included as cyclic variation in transmission. Parameters associated with the natural history of the infection were assumed to be independent of geographic location, while others, such as those associated with seasonality, were assumed location specific. Models incorporating either of the two extreme assumptions for immunity (none or solid and lifelong) were unable to reproduce the observed dynamics. Model fits with either waning or partial immunity to disease or both were visually comparable. The best fitting structure was a lifelong partial immunity to both disease and infection. Observed patterns were reproduced by stochastic simulations using the parameter values estimated from the deterministic models.

On the Relationship Between Transfer Function-derived Response Times and Hydrograph Analysis Timing Parameters: Are there Similarities?

NASA Astrophysics Data System (ADS)

Bansah, S.; Ali, G.; Haque, M. A.; Tang, V.

2017-12-01

The proportion of precipitation that becomes streamflow is a function of internal catchment characteristics - which include geology, landscape characteristics and vegetation - and influence overall storage dynamics. The timing and quantity of water discharged by a catchment are indeed embedded in event hydrographs. Event hydrograph timing parameters, such as the response lag and time of concentration, are important descriptors of how long it takes the catchment to respond to input precipitation and how long it takes the latter to filter through the catchment. However, the extent to which hydrograph timing parameters relate to average response times derived from fitting transfer functions to annual hydrographs is unknown. In this study, we used a gamma transfer function to determine catchment average response times as well as event-specific hydrograph parameters across a network of eight nested watersheds ranging from 0.19 km2 to 74.6 km2 prairie catchments located in south central Manitoba (Canada). Various statistical analyses were then performed to correlate average response times - estimated using the parameters of the fitted gamma transfer function - to event-specific hydrograph parameters. Preliminary results show significant interannual variations in response times and hydrograph timing parameters: the former were in the order of a few hours to days, while the latter ranged from a few days to weeks. Some statistically significant relationships were detected between response times and event-specific hydrograph parameters. Future analyses will involve the comparison of statistical distributions of event-specific hydrograph parameters with that of runoff response times and baseflow transit times in order to quantity catchment storage dynamics across a range of temporal scales.

The AmP project: Comparing species on the basis of dynamic energy budget parameters.

PubMed

Marques, Gonçalo M; Augustine, Starrlight; Lika, Konstadia; Pecquerie, Laure; Domingos, Tiago; Kooijman, Sebastiaan A L M

2018-05-01

We developed new methods for parameter estimation-in-context and, with the help of 125 authors, built the AmP (Add-my-Pet) database of Dynamic Energy Budget (DEB) models, parameters and referenced underlying data for animals, where each species constitutes one database entry. The combination of DEB parameters covers all aspects of energetics throughout the full organism's life cycle, from the start of embryo development to death by aging. The species-specific parameter values capture biodiversity and can now, for the first time, be compared between animals species. An important insight brought by the AmP project is the classification of animal energetics according to a family of related DEB models that is structured on the basis of the mode of metabolic acceleration, which links up with the development of larval stages. We discuss the evolution of metabolism in this context, among animals in general, and ray-finned fish, mollusks and crustaceans in particular. New DEBtool code for estimating DEB parameters from data has been written. AmPtool code for analyzing patterns in parameter values has also been created. A new web-interface supports multiple ways to visualize data, parameters, and implied properties from the entire collection as well as on an entry by entry basis. The DEB models proved to fit data well, the median relative error is only 0.07, for the 1035 animal species at 2018/03/12, including some extinct ones, from all large phyla and all chordate orders, spanning a range of body masses of 16 orders of magnitude. This study is a first step to include evolutionary aspects into parameter estimation, allowing to infer properties of species for which very little is known.

The AmP project: Comparing species on the basis of dynamic energy budget parameters

PubMed Central

Lika, Konstadia; Pecquerie, Laure; Kooijman, Sebastiaan A. L. M.

2018-01-01

We developed new methods for parameter estimation-in-context and, with the help of 125 authors, built the AmP (Add-my-Pet) database of Dynamic Energy Budget (DEB) models, parameters and referenced underlying data for animals, where each species constitutes one database entry. The combination of DEB parameters covers all aspects of energetics throughout the full organism’s life cycle, from the start of embryo development to death by aging. The species-specific parameter values capture biodiversity and can now, for the first time, be compared between animals species. An important insight brought by the AmP project is the classification of animal energetics according to a family of related DEB models that is structured on the basis of the mode of metabolic acceleration, which links up with the development of larval stages. We discuss the evolution of metabolism in this context, among animals in general, and ray-finned fish, mollusks and crustaceans in particular. New DEBtool code for estimating DEB parameters from data has been written. AmPtool code for analyzing patterns in parameter values has also been created. A new web-interface supports multiple ways to visualize data, parameters, and implied properties from the entire collection as well as on an entry by entry basis. The DEB models proved to fit data well, the median relative error is only 0.07, for the 1035 animal species at 2018/03/12, including some extinct ones, from all large phyla and all chordate orders, spanning a range of body masses of 16 orders of magnitude. This study is a first step to include evolutionary aspects into parameter estimation, allowing to infer properties of species for which very little is known. PMID:29742099

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

PubMed

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Lindemann histograms as a new method to analyse nano-patterns and phases

NASA Astrophysics Data System (ADS)

Makey, Ghaith; Ilday, Serim; Tokel, Onur; Ibrahim, Muhamet; Yavuz, Ozgun; Pavlov, Ihor; Gulseren, Oguz; Ilday, Omer

The detection, observation, and analysis of material phases and atomistic patterns are of great importance for understanding systems exhibiting both equilibrium and far-from-equilibrium dynamics. As such, there is intense research on phase transitions and pattern dynamics in soft matter, statistical and nonlinear physics, and polymer physics. In order to identify phases and nano-patterns, the pair correlation function is commonly used. However, this approach is limited in terms of recognizing competing patterns in dynamic systems, and lacks visualisation capabilities. In order to solve these limitations, we introduce Lindemann histogram quantification as an alternative method to analyse solid, liquid, and gas phases, along with hexagonal, square, and amorphous nano-pattern symmetries. We show that the proposed approach based on Lindemann parameter calculated per particle maps local number densities to material phase or particles pattern. We apply the Lindemann histogram method on dynamical colloidal self-assembly experimental data and identify competing patterns.

Nonlinear dynamic analysis of traveling wave-type ultrasonic motors.

PubMed

Nakagawa, Yosuke; Saito, Akira; Maeno, Takashi

2008-03-01

In this paper, nonlinear dynamic response of a traveling wave-type ultrasonic motor was investigated. In particular, understanding the transient dynamics of a bar-type ultrasonic motor, such as starting up and stopping, is of primary interest. First, the transient response of the bar-type ultrasonic motor at starting up and stopping was measured using a laser Doppler velocimeter, and its driving characteristics are discussed in detail. The motor is shown to possess amplitude-dependent nonlinearity that greatly influences the transient dynamics of the motor. Second, a dynamical model of the motor was constructed as a second-order nonlinear oscillator, which represents the dynamics of the piezoelectric ceramic, stator, and rotor. The model features nonlinearities caused by the frictional interface between the stator and the rotor, and cubic nonlinearity in the dynamics of the stator. Coulomb's friction model was employed for the interface model, and a stick-slip phenomenon is considered. Lastly, it was shown that the model is capable of representing the transient dynamics of the motor accurately. The critical parameters in the model were identified from measured results, and numerical simulations were conducted using the model with the identified parameters. Good agreement between the results of measurements and numerical simulations is observed.

Using spin-label W-band EPR to study membrane fluidity profiles in samples of small volume

NASA Astrophysics Data System (ADS)

Mainali, Laxman; Hyde, James S.; Subczynski, Witold K.

2013-01-01

Conventional and saturation-recovery (SR) EPR at W-band (94 GHz) using phosphatidylcholine spin labels (labeled at the alkyl chain [n-PC] and headgroup [T-PC]) to obtain profiles of membrane fluidity has been demonstrated. Dimyristoylphosphatidylcholine (DMPC) membranes with and without 50 mol% cholesterol have been studied, and the results have been compared with similar studies at X-band (9.4 GHz) (L. Mainali, J.B. Feix, J.S. Hyde, W.K. Subczynski, J. Magn. Reson. 212 (2011) 418-425). Profiles of the spin-lattice relaxation rate (T1-1) obtained from SR EPR measurements for n-PCs and T-PC were used as a convenient quantitative measure of membrane fluidity. Additionally, spectral analysis using Freed's MOMD (microscopic-order macroscopic-disorder) model (E. Meirovitch, J.H. Freed J. Phys. Chem. 88 (1984) 4995-5004) provided rotational diffusion coefficients (R⊥ and R||) and order parameters (S0). Spectral analysis at X-band provided one rotational diffusion coefficient, R⊥. T1-1, R⊥, and R|| profiles reflect local membrane dynamics of the lipid alkyl chain, while the order parameter shows only the amplitude of the wobbling motion of the lipid alkyl chain. Using these dynamic parameters, namely T1-1, R⊥, and R||, one can discriminate the different effects of cholesterol at different depths, showing that cholesterol has a rigidifying effect on alkyl chains to the depth occupied by the rigid steroid ring structure and a fluidizing effect at deeper locations. The nondynamic parameter, S0, shows that cholesterol has an ordering effect on alkyl chains at all depths. Conventional and SR EPR measurements with T-PC indicate that cholesterol has a fluidizing effect on phospholipid headgroups. EPR at W-band provides more detailed information about the depth-dependent dynamic organization of the membrane compared with information obtained at X-band. EPR at W-band has the potential to be a powerful tool for studying membrane fluidity in samples of small volume, ˜30 nL, compared with a representative sample volume of ˜3 μL at X-band.

Control of extreme events in the bubbling onset of wave turbulence.

PubMed

Galuzio, P P; Viana, R L; Lopes, S R

2014-04-01

We show the existence of an intermittent transition from temporal chaos to turbulence in a spatially extended dynamical system, namely, the forced and damped one-dimensional nonlinear Schrödinger equation. For some values of the forcing parameter, the system dynamics intermittently switches between ordered states and turbulent states, which may be seen as extreme events in some contexts. In a Fourier phase space, the intermittency takes place due to the loss of transversal stability of unstable periodic orbits embedded in a low-dimensional subspace. We mapped these transversely unstable regions and perturbed the system in order to significantly reduce the occurrence of extreme events of turbulence.

Empirical study on social groups in pedestrian evacuation dynamics

NASA Astrophysics Data System (ADS)

von Krüchten, Cornelia; Schadschneider, Andreas

2017-06-01

Pedestrian crowds often include social groups, i.e. pedestrians that walk together because of social relationships. They show characteristic configurations and influence the dynamics of the entire crowd. In order to investigate the impact of social groups on evacuations we performed an empirical study with pupils. Several evacuation runs with groups of different sizes and different interactions were performed. New group parameters are introduced which allow to describe the dynamics of the groups and the configuration of the group members quantitatively. The analysis shows a possible decrease of evacuation times for large groups due to self-ordering effects. Social groups can be approximated as ellipses that orientate along their direction of motion. Furthermore, explicitly cooperative behaviour among group members leads to a stronger aggregation of group members and an intermittent way of evacuation.

Evolution of short range order in Ar: Liquid to glass and solid transitions-A computational study

NASA Astrophysics Data System (ADS)

Shor, Stanislav; Yahel, Eyal; Makov, Guy

2018-04-01

The evolution of the short range order (SRO) as a function of temperature in a Lennard-Jones model liquid with Ar parameters was determined and juxtaposed with thermodynamic and kinetic properties obtained as the liquid was cooled (heated) and transformed between crystalline solid or glassy states and an undercooled liquid. The Lennard-Jones system was studied by non-equilibrium molecular dynamics simulations of large supercells (approximately 20000 atoms) rapidly cooled or heated at selected quenching rates and at constant pressure. The liquid to solid transition was identified by discontinuities in the atomic volume and molar enthalpy; the glass transition temperature range was identified from the temperature dependence of the self-diffusion. The SRO was studied within the quasi-crystalline model (QCM) framework and compared with the Steinhardt bond order parameters. Within the QCM it was found that the SRO evolves from a bcc-like order in the liquid through a bct-like short range order (c/a=1.2) in the supercooled liquid which persists into the glass and finally to a fcc-like ordering in the crystalline solid. The variation of the SRO that results from the QCM compares well with that obtained with Steinhardt's bond order parameters. The hypothesis of icosahedral order in liquids and glasses is not supported by our results.

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes

PubMed Central

Sharp, Kim A.; O’Brien, Evan; Kasinath, Vignesh; Wand, A. Joshua

2015-01-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O2NH) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O2NH < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O2axis. A calibration curve for backbone entropy vs. O2NH is developed which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O2NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, e.g. upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O2axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. PMID:25739366

Octahedral tilting instabilities in inorganic halide perovskites

NASA Astrophysics Data System (ADS)

Bechtel, Jonathon S.; Van der Ven, Anton

2018-02-01

Dynamic instabilities, stabilized by anharmonic interactions in cubic and tetragonal halide perovskites at high temperature, play a role in the electronic structure and optoelectronic properties of halide perovskites. In particular, inorganic and hybrid perovskite materials undergo structural phase transitions associated with octahedral tilts of the metal-halide octahedra. We investigate the structural instabilities present in inorganic Cs M X3 perovskites with Pb or Sn on the metal site and Br or I on the X site. Defining primary order parameters in terms of symmetry-adapted collective displacement modes and secondary order parameters in terms of symmetrized Hencky strain components, we unravel the coupling between octahedral tilt modes and macroscopic strains as well as the role of A -site displacements in perovskite phase stability. Symmetry-allowed secondary strain order parameters are enumerated for the 14 unique perovskite tilt systems. Using first-principles calculations to explore the Born-Oppenheimer energy surface in terms of symmetrized order parameters, we find coupling between octahedral tilting and A -site displacements is necessary to stabilize P n m a ground states. Additionally, we show that the relative stability of an inorganic halide perovskite tilt system correlates with the volume decrease from the high-symmetry cubic phase to the low-symmetry distorted phase.

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes.

PubMed

Sharp, Kim A; O'Brien, Evan; Kasinath, Vignesh; Wand, A Joshua

2015-05-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O(2) NH ) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O(2) NH  < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O(2) axis . A calibration curve for backbone entropy vs. O(2) NH is developed, which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O(2) NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, for example, upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O(2) axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. © 2015 Wiley Periodicals, Inc.

Universal behaviour in the stock market: Time dynamics of the electronic orderbook

NASA Astrophysics Data System (ADS)

Kızılersü, Ayşe; Kreer, Markus; Thomas, Anthony W.; Feindt, Michael

2016-07-01

A consequence of the digital revolution is that share trading at the stock exchange takes place via electronic order books which are accessed by traders and investors via the internet. Our empirical findings of the London Stock Exchange demonstrate that once ultra-high frequency manipulation on time scales less than around ten milliseconds is excluded, all relevant changes in the order book happen with time differences that are randomly distributed and well described by a left-truncated Weibull distribution with universal shape parameter (independent of time and same for all stocks). The universal shape parameter corresponds to maximum entropy of the distribution.

Joint min-max distribution and Edwards-Anderson's order parameter of the circular 1/f-noise model

NASA Astrophysics Data System (ADS)

Cao, Xiangyu; Le Doussal, Pierre

2016-05-01

We calculate the joint min-max distribution and the Edwards-Anderson's order parameter for the circular model of 1/f-noise. Both quantities, as well as generalisations, are obtained exactly by combining the freezing-duality conjecture and Jack-polynomial techniques. Numerical checks come with significantly improved control of finite-size effects in the glassy phase, and the results convincingly validate the freezing-duality conjecture. Application to diffusive dynamics is discussed. We also provide a formula for the pre-factor ratio of the joint/marginal Carpentier-Le Doussal tail for minimum/maximum which applies to any logarithmic random energy model.

Thermally and electrically controllable multiple high harmonics generation by harmonically driven quasi-two-dimensional electron gas

NASA Astrophysics Data System (ADS)

Maglevanny, I. I.; Smolar, V. A.; Karyakina, T. I.

2018-06-01

In this paper, we consider the activation processes in nonlinear meta-stable system based on a lateral (quasi-two-dimensional) superlattice and study the dynamics of such a system externally driven by a harmonic force. The internal control parameters are the longitudinal applied electric field and the sample temperature. The spontaneous transverse electric field is considered as an order parameter. The forced violations of order parameter are considered as a response of a system to periodic driving. We investigate the cooperative effects of self-organization and high harmonic forcing from the viewpoint of catastrophe theory and show the possibility of generation of third and higher odd harmonics in output signal that lead to distortion of its wave front. A higher harmonics detection strategy is further proposed and explained in detail by exploring the influences of system parameters on the response output of the system that are discussed through numerical simulations.

Perceptual multistability in figure-ground segregation using motion stimuli.

PubMed

Gori, Simone; Giora, Enrico; Pedersini, Riccardo

2008-11-01

In a series of experiments using ambiguous stimuli, we investigate the effects of displaying ordered, discrete series of images on the dynamics of figure-ground segregation. For low frame presentation speeds, the series were perceived as a sequence of discontinuous, static images, while for high speeds they were perceived as continuous. We conclude that using stimuli varying continuously along one parameter results in stronger hysteresis and reduces spontaneous switching compared to matched static stimuli with discontinuous parameter changes. The additional evidence that the size of the hysteresis effects depended on trial duration is consistent with the stochastic nature of the dynamics governing figure-ground segregation. The results showed that for continuously changing stimuli, alternative figure-ground organizations are resolved via low-level, dynamical competition. A second series of experiments confirmed these results with an ambiguous stimulus based on Petter's effect.

Effects of neutrino mass hierarchies on dynamical dark energy models

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Nunes, Rafael C.; Pan, Supriya; Mota, David F.

2017-05-01

We investigate how three different possibilities of neutrino mass hierarchies, namely normal, inverted, and degenerate, can affect the observational constraints on three well-known dynamical dark energy models, namely the Chevallier-Polarski-Linder, logarithmic, and the Jassal-Bagla-Padmanabhan parametrizations. In order to impose the observational constraints on the models, we performed a robust analysis using Planck 2015 temperature and polarization data, supernovae type Ia from the joint light curve analysis, baryon acoustic oscillation distance measurements, redshift space distortion characterized by f (z )σ8(z ) data, weak gravitational lensing data from the Canada-France-Hawaii Telescope Lensing Survey, and cosmic chronometer data plus the local value of the Hubble parameter. We find that different neutrino mass hierarchies return similar fits on almost all model parameters and mildly change the dynamical dark energy properties.

Entanglement analysis of a two-atom nonlinear Jaynes-Cummings model with nondegenerate two-photon transition, Kerr nonlinearity, and two-mode Stark shift

NASA Astrophysics Data System (ADS)

Baghshahi, H. R.; Tavassoly, M. K.; Faghihi, M. J.

2014-12-01

An entangled state, as an essential tool in quantum information processing, may be generated through the interaction between light and matter in cavity quantum electrodynamics. In this paper, we study the interaction between two two-level atoms and a two-mode field in an optical cavity enclosed by a medium with Kerr nonlinearity in the presence of a detuning parameter and Stark effect. It is assumed that the atom-field coupling and third-order susceptibility of the Kerr medium depend on the intensity of the light. In order to investigate the dynamics of the introduced system, we obtain the exact analytical form of the state vector of the considered atom-field system under initial conditions which may be prepared for the atoms (in a coherent superposition of their ground and upper states) and the fields (in a standard coherent state). Then, in order to evaluate the degree of entanglement between the subsystems, we investigate the dynamics of the entanglement by employing the entanglement of formation. Finally, we analyze in detail the influences of the Stark shift, the deformed Kerr medium, the intensity-dependent coupling, and also the detuning parameter on the behavior of this measure for different subsystems. The numerical results show that the amount of entanglement between the different subsystems can be controlled by choosing the evolved parameters appropriately.

Optimization of the structural and control system for LSS with reduced-order model

NASA Technical Reports Server (NTRS)

Khot, N. S.

1989-01-01

The objective is the simultaneous design of the structural and control system for space structures. The minimum weight of the structure is the objective function, and the constraints are placed on the closed loop distribution of the frequencies and the damping parameters. The controls approach used is linear quadratic regulator with constant feedback. A reduced-order control system is used. The effect of uncontrolled modes is taken into consideration by the model error sensitivity suppression (MESS) technique which modified the weighting parameters for the control forces. For illustration, an ACOSS-FOUR structure is designed for a different number of controlled modes with specified values for the closed loop damping parameters and frequencies. The dynamic response of the optimum designs for an initial disturbance is compared.

Delay-induced depinning of localized structures in a spatially inhomogeneous Swift-Hohenberg model

NASA Astrophysics Data System (ADS)

Tabbert, Felix; Schelte, Christian; Tlidi, Mustapha; Gurevich, Svetlana V.

2017-03-01

We report on the dynamics of localized structures in an inhomogeneous Swift-Hohenberg model describing pattern formation in the transverse plane of an optical cavity. This real order parameter equation is valid close to the second-order critical point associated with bistability. The optical cavity is illuminated by an inhomogeneous spatial Gaussian pumping beam and subjected to time-delayed feedback. The Gaussian injection beam breaks the translational symmetry of the system by exerting an attracting force on the localized structure. We show that the localized structure can be pinned to the center of the inhomogeneity, suppressing the delay-induced drift bifurcation that has been reported in the particular case where the injection is homogeneous, assuming a continuous wave operation. Under an inhomogeneous spatial pumping beam, we perform the stability analysis of localized solutions to identify different instability regimes induced by time-delayed feedback. In particular, we predict the formation of two-arm spirals, as well as oscillating and depinning dynamics caused by the interplay of an attracting inhomogeneity and destabilizing time-delayed feedback. The transition from oscillating to depinning solutions is investigated by means of numerical continuation techniques. Analytically, we use an order parameter approach to derive a normal form of the delay-induced Hopf bifurcation leading to an oscillating solution. Additionally we model the interplay of an attracting inhomogeneity and destabilizing time delay by describing the localized solution as an overdamped particle in a potential well generated by the inhomogeneity. In this case, the time-delayed feedback acts as a driving force. Comparing results from the later approach with the full Swift-Hohenberg model, we show that the approach not only provides an instructive description of the depinning dynamics, but also is numerically accurate throughout most of the parameter regime.

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

NASA Astrophysics Data System (ADS)

Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.

2011-01-01

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.

Model verification of mixed dynamic systems. [POGO problem in liquid propellant rockets

NASA Technical Reports Server (NTRS)

Chrostowski, J. D.; Evensen, D. A.; Hasselman, T. K.

1978-01-01

A parameter-estimation method is described for verifying the mathematical model of mixed (combined interactive components from various engineering fields) dynamic systems against pertinent experimental data. The model verification problem is divided into two separate parts: defining a proper model and evaluating the parameters of that model. The main idea is to use differences between measured and predicted behavior (response) to adjust automatically the key parameters of a model so as to minimize response differences. To achieve the goal of modeling flexibility, the method combines the convenience of automated matrix generation with the generality of direct matrix input. The equations of motion are treated in first-order form, allowing for nonsymmetric matrices, modeling of general networks, and complex-mode analysis. The effectiveness of the method is demonstrated for an example problem involving a complex hydraulic-mechanical system.

Phase behavior of charged colloids at a fluid interface

NASA Astrophysics Data System (ADS)

Kelleher, Colm P.; Guerra, Rodrigo E.; Hollingsworth, Andrew D.; Chaikin, Paul M.

2017-02-01

We study the phase behavior of a system of charged colloidal particles that are electrostatically bound to an almost flat interface between two fluids. We show that, despite the fact that our experimental system consists of only 103-104 particles, the phase behavior is consistent with the theory of melting due to Kosterlitz, Thouless, Halperin, Nelson, and Young. Using spatial and temporal correlations of the bond-orientational order parameter, we classify our samples into solid, isotropic fluid, and hexatic phases. We demonstrate that the topological defect structure we observe in each phase corresponds to the predictions of Kosterlitz-Thouless-Halperin-Nelson-Young theory. By measuring the dynamic Lindemann parameter γL(τ ) and the non-Gaussian parameter α2(τ ) of the displacements of the particles relative to their neighbors, we show that each of the phases displays distinctive dynamical behavior.

Molecular Dynamics Study on Nucleation Behavior and Lamellar Mergence of Polyethylene Globule Crystallization

NASA Astrophysics Data System (ADS)

Yang, Xiaozhen; Wang, Simiao

2012-02-01

The site order parameter (SOP) has been adopted to analyze various order structure formation and distribution during the crystallization of a multi-chain polyethylene globule simulated by molecular dynamics. We found that the nucleation relies on crystallinity fluctuation with increase of amplitude, and the baby nucleus in the fluctuation suddenly appears with different shape and increasing size. In the growth stage, a number of lamellar mergence was observed and their selective behaviors were suggested to be related to the orientation difference between the merging lamellae. We obtained that SOP distribution of all atoms in the system during crystallization appears with two peaks: one for the amorphous phase and the other for the crystalline phase. Mesomorphic structures with medium orders locate between the two peaks as an order promotion pathway. Obtained data show that the medium order structure fluctuates at the growth front and does not always be available; the medium order structure existing at the front is not always good for developing. It is possibly caused by chain entanglement.

Molecular ordering and molecular dynamics in isotactic-polypropylene characterized by solid state NMR.

PubMed

Miyoshi, Toshikazu; Mamun, Al; Hu, Wei

2010-01-14

The order-disorder phenomenon of local packing structures, space heterogeneity, and molecular dynamics and average lamellar thickness, , of the alpha form of isotactic polypropylene (iPP) crystallized at various supercooling temperatures, DeltaT, are investigated by solid-state (SS) NMR and SAXS, respectively. increases with lowering DeltaT, and extrapolations of (-1) versus averaged melting point, , gives an equilibrium melting temperature, T(m)(0) = 457 +/- 4 K. High-power TPPM decoupling with a field strength of 110 kHz extremely improves (13)C high-resolution SS-NMR spectral resolution of the ordered crystalline signals at various DeltaT. A high-resolution (13)C SS-NMR spectrum combined with a conventional spin-lattice relaxation time in the rotating frame (T(1rhoH)) filter easily accesses an order-disorder phenomenon for upward and downward orientations of stems and their packing in the crystalline region. It is found that ordered packing fraction, f(order), increases with lowering DeltaT and reaches a maximum value of 62% at DeltaT = 34 K. The ordering phenomenon of stem packing indicates that chain-folding direction changes from random in the disordered packing to order in the ordered packing along the a sin theta axis under a hypothesis of adjacent re-entry structures. It is also found that f(order) significantly increases prior to enhancement of lamellar thickness. Additionally, annealing experiments indicate that is significantly enhanced after a simultaneous process of partial melting and recrystallization/reorganization into the ordered packing at annealing temperature >/=423 K. Furthermore, the center-bands only detection of exchange (CODEX) NMR method demonstrates that time-kinetic parameters of helical jump motions are highly influenced by DeltaT. These dynamic constraints are interpreted in terms of increment of and packing ordering. Through these new results related to molecular structures and dynamics, roles of polymer chain trajectory and molecular dynamics for the lamellar thickening process are discussed.

Continuous-spin mixed-symmetry fields in AdS(5)

NASA Astrophysics Data System (ADS)

Metsaev, R. R.

2018-05-01

Free mixed-symmetry continuous-spin fields propagating in AdS(5) space and flat R(4,1) space are studied. In the framework of a light-cone gauge formulation of relativistic dynamics, we build simple actions for such fields. The realization of relativistic symmetries on the space of light-cone gauge mixed-symmetry continuous-spin fields is also found. Interrelations between constant parameters entering the light-cone gauge actions and eigenvalues of the Casimir operators of space-time symmetry algebras are obtained. Using these interrelations and requiring that the field dynamics in AdS(5) be irreducible and classically unitary, we derive restrictions on the constant parameters and eigenvalues of the second-order Casimir operator of the algebra.

Dynamics of elastic systems

NASA Astrophysics Data System (ADS)

Sankovich, Vladimir

1998-12-01

The goal of this paper is to build a consistent physical theory of the dynamics of the bat-ball interaction. This requires creating realistic models for both the softball bat and the softball. Some of the features of these models are known phenomenologically, from experiments conducted in our laboratory, others will be introduced and computed from first principles here for the first time. Both interacting objects are treated from the viewpoint of the theory of elasticity, and it is shown how a computer can be used to accurately calculate all the relevant characteristics of batball collisions. It is shown also how the major elastic parameters of the material constituting the interior of a softball can be determined using the existing experimental data. These parameters, such as the Young's modulus, the Poisson ratio and the damping coefficient are vital for the accurate description of the ball's dynamics. We are demonstrating how the existing theories of the elastic behavior of solid bars and hollow shells can be augmented to simplify the resulting equations and make the subsequent computer analysis feasible. The standard system of fourth-order PDE's is reduced to a system of the second order, because of the inclusion of the usually ignored effects of the shear forces in the bat.

Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations.

PubMed

Okimoto, Noriaki; Suenaga, Atsushi; Taiji, Makoto

2017-11-01

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein-ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski's equality was employed compared with the second-order cumulant expansion equation of Jarzynski's equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.

Chaos and Order in Weakly Coupled Systems of Nonlinear Oscillators

NASA Astrophysics Data System (ADS)

Bruhn, B.

1987-01-01

We consider in this paper perturbations of two degree of freedom Hamiltonian systems which contain periodic and heteroclinic orbits. The Melnikov-Keener condition is used to proof the existence of horseshoes in the dynamics. The same condition is applied to prove a high degree of order in the motion of the swinging Atwood's machine. For some selected parameter values the theoretical predictions are checked by numerical calculations.

Aeroelastic System Development Using Proper Orthogonal Decomposition and Volterra Theory

NASA Technical Reports Server (NTRS)

Lucia, David J.; Beran, Philip S.; Silva, Walter A.

2003-01-01

This research combines Volterra theory and proper orthogonal decomposition (POD) into a hybrid methodology for reduced-order modeling of aeroelastic systems. The out-come of the method is a set of linear ordinary differential equations (ODEs) describing the modal amplitudes associated with both the structural modes and the POD basis functions for the uid. For this research, the structural modes are sine waves of varying frequency, and the Volterra-POD approach is applied to the fluid dynamics equations. The structural modes are treated as forcing terms which are impulsed as part of the uid model realization. Using this approach, structural and uid operators are coupled into a single aeroelastic operator. This coupling converts a free boundary uid problem into an initial value problem, while preserving the parameter (or parameters) of interest for sensitivity analysis. The approach is applied to an elastic panel in supersonic cross ow. The hybrid Volterra-POD approach provides a low-order uid model in state-space form. The linear uid model is tightly coupled with a nonlinear panel model using an implicit integration scheme. The resulting aeroelastic model provides correct limit-cycle oscillation prediction over a wide range of panel dynamic pressure values. Time integration of the reduced-order aeroelastic model is four orders of magnitude faster than the high-order solution procedure developed for this research using traditional uid and structural solvers.

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; Hurtado, John E.

2011-01-01

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Modal identification of spindle-tool unit in high-speed machining

NASA Astrophysics Data System (ADS)

Gagnol, Vincent; Le, Thien-Phu; Ray, Pascal

2011-10-01

The accurate knowledge of high-speed motorised spindle dynamic behaviour during machining is important in order to ensure the reliability of machine tools in service and the quality of machined parts. More specifically, the prediction of stable cutting regions, which is a critical requirement for high-speed milling operations, requires the accurate estimation of tool/holder/spindle set dynamic modal parameters. These estimations are generally obtained through Frequency Response Function (FRF) measurements of the non-rotating spindle. However, significant changes in modal parameters are expected to occur during operation, due to high-speed spindle rotation. The spindle's modal variations are highlighted through an integrated finite element model of the dynamic high-speed spindle-bearing system, taking into account rotor dynamics effects. The dependency of dynamic behaviour on speed range is then investigated and determined with accuracy. The objective of the proposed paper is to validate these numerical results through an experiment-based approach. Hence, an experimental setup is elaborated to measure rotating tool vibration during the machining operation in order to determine the spindle's modal frequency variation with respect to spindle speed in an industrial environment. The identification of natural frequencies of the spindle under rotating conditions is challenging, due to the low number of sensors and the presence of many harmonics in the measured signals. In order to overcome these issues and to extract the characteristics of the system, the spindle modes are determined through a 3-step procedure. First, spindle modes are highlighted using the Frequency Domain Decomposition (FDD) technique, with a new formulation at the considered rotating speed. These extracted modes are then analysed through the value of their respective damping ratios in order to separate the harmonics component from structural spindle natural frequencies. Finally, the stochastic properties of the modes are also investigated by considering the probability density of the retained modes. Results show a good correlation between numerical and experiment-based identified frequencies. The identified spindle-tool modal properties during machining allow the numerical model to be considered as representative of the real dynamic properties of the system.

Experimental analysis of synchronization and dynamics in an automobile as a complex system

NASA Astrophysics Data System (ADS)

González-Cruz, C. A.; Jáuregui-Correa, J. C.; López-Cajún, C.; Sen, M.; Domínguez-González, A.

2015-08-01

A complex system is composed of many interacting elements, and its behavior, as a whole, can be quite different from that of the individual elements. An automobile is an example of a common mechanical system composed of a large number of individual elements. These elements are connected through soft and hard linkages that transmit motion to each other. This paper proposes a variety of analytical tools to study experimental data from complex systems using two elements of an automobile as an example. Accelerometer measurements were taken from two elements within an automobile: the door and the dashboard. Two types of data were collected: response to impact loading, and response to road excitation of the automobile driven at different speeds. The signals were processed via Fourier and wavelet transforms, cross-correlation coefficients, Hilbert transform, and Kuramoto order parameters. A new parameter, called the order-deficit parameter, is introduced. Considerable, but not complete, synchronization can be found between the accelerations measured at these two locations in the automobile, and the degree of synchronization is quantified using the order-deficit parameter.

Combined state and parameter identification of nonlinear structural dynamical systems based on Rao-Blackwellization and Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Abhinav, S.; Manohar, C. S.

2018-03-01

The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

Numerical and Experimental Investigations of Humping Phenomena in Laser Micro Welding

NASA Astrophysics Data System (ADS)

Otto, Andreas; Patschger, Andreas; Seiler, Michael

The Humping effect is a phenomenon which is observed approximately since 50 years in various welding procedures and is characterized by droplets due to a pile-up of the melt pool. It occurs within a broad range of process parameters. Particularly during micro welding, humping effect is critical due to typically high feed rates. In the past, essentially two approaches (fluid-dynamic approach of streaming melt within the molten pool and the Plateau-Rayleigh instability of a liquid jet) were discussed in order to explain the occurrence of the humping effect. But none of both can fully explain all observed effects. For this reason, experimental studies in micro welding of thin metal foils were performed in order to determine the influence of process parameters on the occurrence of humping effects. The experimental observations were compared with results from numerical multi-physical simulations (incorporating beam propagation, incoupling, heat transfer, fluid dynamics etc.) to provide a deeper understanding of the causes for hump formation.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Spatiotemporal dynamics in excitable homogeneous random networks composed of periodically self-sustained oscillation.

PubMed

Qian, Yu; Liu, Fei; Yang, Keli; Zhang, Ge; Yao, Chenggui; Ma, Jun

2017-09-19

The collective behaviors of networks are often dependent on the network connections and bifurcation parameters, also the local kinetics plays an important role in contributing the consensus of coupled oscillators. In this paper, we systematically investigate the influence of network structures and system parameters on the spatiotemporal dynamics in excitable homogeneous random networks (EHRNs) composed of periodically self-sustained oscillation (PSO). By using the dominant phase-advanced driving (DPAD) method, the one-dimensional (1D) Winfree loop is exposed as the oscillation source supporting the PSO, and the accurate wave propagation pathways from the oscillation source to the whole network are uncovered. Then, an order parameter is introduced to quantitatively study the influence of network structures and system parameters on the spatiotemporal dynamics of PSO in EHRNs. Distinct results induced by the network structures and the system parameters are observed. Importantly, the corresponding mechanisms are revealed. PSO influenced by the network structures are induced not only by the change of average path length (APL) of network, but also by the invasion of 1D Winfree loop from the outside linking nodes. Moreover, PSO influenced by the system parameters are determined by the excitation threshold and the minimum 1D Winfree loop. Finally, we confirmed that the excitation threshold and the minimum 1D Winfree loop determined PSO will degenerate as the system size is expanded.

Quantum trajectory phase transitions in the micromaser.

PubMed

Garrahan, Juan P; Armour, Andrew D; Lesanovsky, Igor

2011-08-01

We study the dynamics of the single-atom maser, or micromaser, by means of the recently introduced method of thermodynamics of quantum jump trajectories. We find that the dynamics of the micromaser displays multiple space-time phase transitions, i.e., phase transitions in ensembles of quantum jump trajectories. This rich dynamical phase structure becomes apparent when trajectories are classified by dynamical observables that quantify dynamical activity, such as the number of atoms that have changed state while traversing the cavity. The space-time transitions can be either first order or continuous, and are controlled not just by standard parameters of the micromaser but also by nonequilibrium "counting" fields. We discuss how the dynamical phase behavior relates to the better known stationary-state properties of the micromaser.

Numerical studies of identification in nonlinear distributed parameter systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Lo, C. K.; Reich, Simeon; Rosen, I. G.

1989-01-01

An abstract approximation framework and convergence theory for the identification of first and second order nonlinear distributed parameter systems developed previously by the authors and reported on in detail elsewhere are summarized and discussed. The theory is based upon results for systems whose dynamics can be described by monotone operators in Hilbert space and an abstract approximation theorem for the resulting nonlinear evolution system. The application of the theory together with numerical evidence demonstrating the feasibility of the general approach are discussed in the context of the identification of a first order quasi-linear parabolic model for one dimensional heat conduction/mass transport and the identification of a nonlinear dissipation mechanism (i.e., damping) in a second order one dimensional wave equation. Computational and implementational considerations, in particular, with regard to supercomputing, are addressed.

Mean-field analysis of an inductive reasoning game: Application to influenza vaccination

NASA Astrophysics Data System (ADS)

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination.

PubMed

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Multiscale modeling of dislocation-precipitate interactions in Fe: From molecular dynamics to discrete dislocations.

PubMed

Lehtinen, Arttu; Granberg, Fredric; Laurson, Lasse; Nordlund, Kai; Alava, Mikko J

2016-01-01

The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various pointlike defects such as precipitates or solute atoms. These defects act as obstacles for dislocation motion and hence affect the mechanical properties of the material. Here we combine molecular dynamics studies with three-dimensional discrete dislocation dynamics simulations in order to model the interaction between different kinds of precipitates and a 1/2〈111〉{110} edge dislocation in BCC iron. We have implemented immobile spherical precipitates into the ParaDis discrete dislocation dynamics code, with the dislocations interacting with the precipitates via a Gaussian potential, generating a normal force acting on the dislocation segments. The parameters used in the discrete dislocation dynamics simulations for the precipitate potential, the dislocation mobility, shear modulus, and dislocation core energy are obtained from molecular dynamics simulations. We compare the critical stresses needed to unpin the dislocation from the precipitate in molecular dynamics and discrete dislocation dynamics simulations in order to fit the two methods together and discuss the variety of the relevant pinning and depinning mechanisms.

Orientation dynamics in isotropic phases of model oligofluorenes: glass or liquid crystal.

PubMed

Somma, E; Chi, C; Loppinet, B; Grinshtein, J; Graf, R; Fytas, G; Spiess, H W; Wegner, G

2006-05-28

Orientation molecular dynamics were investigated in a series of "defect-free" oligofluorenes by depolarized dynamic light scattering and dynamic NMR spectroscopy. Typical liquid crystalline pretransitional dynamics were observed upon cooling the isotropic phase to the liquid crystalline phase with strong increase of the scattered intensity and slowing down of the characteristic time of the probed collective relaxation. This is well accounted for by the Landau-de Gennes theory, however, with a strong temperature dependence of the viscosity coefficient, reflecting the proximity of the glass transition. For the trimer the two transitions almost overlap and the molecular orientation coincide with the alpha-relaxation associated with the glass transition. The NMR measurements confirm that the time scale of the dynamics is completely governed by the glass process, yet the geometry of the motion is anisotropic, yielding order parameters ranging from 0.15 to 0.25 for the long axis in the liquid crystalline phase. The glass transition is therefore geometrically restricted with poorly ordered mesophase which is consistent with the weak transverse phonons in the light scattering experiment down to Tg+20 K.

Fragile-to-strong transition in liquid silica

NASA Astrophysics Data System (ADS)

Geske, Julian; Drossel, Barbara; Vogel, Michael

2016-03-01

We investigate anomalies in liquid silica with molecular dynamics simulations and present evidence for a fragile-to-strong transition at around 3100 K-3300 K. To this purpose, we studied the structure and dynamical properties of silica over a wide temperature range, finding four indicators of a fragile-to-strong transition. First, there is a density minimum at around 3000 K and a density maximum at 4700 K. The turning point is at 3400 K. Second, the local structure characterized by the tetrahedral order parameter changes dramatically around 3000 K from a higher-ordered, lower-density phase to a less ordered, higher-density phase. Third, the correlation time τ changes from an Arrhenius behavior below 3300 K to a Vogel-Fulcher-Tammann behavior at higher temperatures. Fourth, the Stokes-Einstein relation holds for temperatures below 3000 K, but is replaced by a fractional relation above this temperature. Furthermore, our data indicate that dynamics become again simple above 5000 K, with Arrhenius behavior and a classical Stokes-Einstein relation.

A time-dependent order parameter for ultrafast photoinduced phase transitions.

PubMed

Beaud, P; Caviezel, A; Mariager, S O; Rettig, L; Ingold, G; Dornes, C; Huang, S-W; Johnson, J A; Radovic, M; Huber, T; Kubacka, T; Ferrer, A; Lemke, H T; Chollet, M; Zhu, D; Glownia, J M; Sikorski, M; Robert, A; Wadati, H; Nakamura, M; Kawasaki, M; Tokura, Y; Johnson, S L; Staub, U

2014-10-01

Strongly correlated electron systems often exhibit very strong interactions between structural and electronic degrees of freedom that lead to complex and interesting phase diagrams. For technological applications of these materials it is important to learn how to drive transitions from one phase to another. A key question here is the ultimate speed of such phase transitions, and to understand how a phase transition evolves in the time domain. Here we apply time-resolved X-ray diffraction to directly measure the changes in long-range order during ultrafast melting of the charge and orbitally ordered phase in a perovskite manganite. We find that although the actual change in crystal symmetry associated with this transition occurs over different timescales characteristic of the many electronic and vibrational coordinates of the system, the dynamics of the phase transformation can be well described using a single time-dependent 'order parameter' that depends exclusively on the electronic excitation.

Study of dynamics of glucose-glucose oxidase-ferricyanide reaction

NASA Astrophysics Data System (ADS)

Nováková, A.; Schreiberová, L.; Schreiber, I.

2011-12-01

This work is focused on dynamics of the glucose-glucose oxidase-ferricyanide enzymatic reaction with or without sodium hydroxide in a continuous-flow stirred tank reactor (CSTR) and in a batch reactor. This reaction exhibits pH-variations having autocatalytic character and is reported to provide nonlinear dynamic behavior (bistability, excitability). The dynamical behavior of the reaction was examined within a wide range of inlet parameters. The main inlet parameters were the ratio of concentrations of sodium hydroxide and ferricyanide and the flow rate. In a batch reactor we observed an autocatalytic drop of pH from slightly basic to medium acidic values. In a CSTR our aim was to find bistability in the presence of sodium hydroxide. However, only a basic steady state was found. In order to reach an acidic steady state, we investigated the system in the absence of sodium hydroxide. Under these conditions the transition from the basic to the acidic steady state was observed when inlet glucose concentration was increased.

Visual-motor response of crewmen during a simulated 90-day space mission as measured by the critical task battery

NASA Technical Reports Server (NTRS)

Allen, R. W.; Jex, H. R.

1973-01-01

In order to test various components of a regenerative life support system and to obtain data on the physiological and psychological effects of long duration exposure to confinement in a space station atmosphere, four carefully screened young men were sealed in a space station simulator for 90 days and administered a tracking test battery. The battery included a clinical test (Critical Instability Task) designed to measure a subject's dynamic time delay, and a more conventional steady tracking task, during which dynamic response (describing functions) and performance measures were obtained. Good correlation was noted between the clinical critical instability scores and more detailed tracking parameters such as dynamic time delay and gain-crossover frequency. The levels of each parameter span the range observed with professional pilots and astronaut candidates tested previously. The chamber environment caused no significant decrement on the average crewman's dynamic response behavior, and the subjects continued to improve slightly in their tracking skills during the 90-day confinement period.

Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.

Modification of the SAS4A Safety Analysis Code for Integration with the ADAPT Discrete Dynamic Event Tree Framework.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jankovsky, Zachary Kyle; Denman, Matthew R.

It is difficult to assess the consequences of a transient in a sodium-cooled fast reactor (SFR) using traditional probabilistic risk assessment (PRA) methods, as numerous safety-related sys- tems have passive characteristics. Often there is significant dependence on the value of con- tinuous stochastic parameters rather than binary success/failure determinations. One form of dynamic PRA uses a system simulator to represent the progression of a transient, tracking events through time in a discrete dynamic event tree (DDET). In order to function in a DDET environment, a simulator must have characteristics that make it amenable to changing physical parameters midway through themore » analysis. The SAS4A SFR system analysis code did not have these characteristics as received. This report describes the code modifications made to allow dynamic operation as well as the linking to a Sandia DDET driver code. A test case is briefly described to demonstrate the utility of the changes.« less

Studying topology and dynamical phase transitions with ultracold quantum gases in optical lattices

NASA Astrophysics Data System (ADS)

Sengstock, Klaus

Topological properties lie at the heart of many fascinating phenomena in solid-state systems such as quantum Hall systems or Chern insulators. The topology of the bands can be captured by the distribution of Berry curvature, which describes the geometry of the eigenstates across the Brillouin zone. Using fermionic ultracold atoms in a hexagonal optical lattice, we engineered the Berry curvature of the Bloch bands using resonant driving and show a full momentum-resolved state tomography from which we obtain the Berry curvature and Chern number. Furthermore, we study the time-evolution of the many-body wavefunction after a sudden quench of the lattce parameters and observe the appearance, movement, and annihilation of vortices in reciprocal space. We identify their number as a dynamical topological order parameter, which suddenly changes its value at critical times. Our measurements constitute the first observation of a so called dynamical topological phase transition`, which we show to be a fruitful concept for the understanding of quantum dynamics far from equilibrium

Modeling behavior dynamics using computational psychometrics within virtual worlds.

PubMed

Cipresso, Pietro

2015-01-01

In case of fire in a building, how will people behave in the crowd? The behavior of each individual affects the behavior of others and, conversely, each one behaves considering the crowd as a whole and the individual others. In this article, I propose a three-step method to explore a brand new way to study behavior dynamics. The first step relies on the creation of specific situations with standard techniques (such as mental imagery, text, video, and audio) and an advanced technique [Virtual Reality (VR)] to manipulate experimental settings. The second step concerns the measurement of behavior in one, two, or many individuals focusing on parameters extractions to provide information about the behavior dynamics. Finally, the third step, which uses the parameters collected and measured in the previous two steps in order to simulate possible scenarios to forecast through computational models, understand, and explain behavior dynamics at the social level. An experimental study was also included to demonstrate the three-step method and a possible scenario.

Dynamic Statistical Characterization of Variation in Source Processes of Microseismic Events

NASA Astrophysics Data System (ADS)

Smith-Boughner, L.; Viegas, G. F.; Urbancic, T.; Baig, A. M.

2015-12-01

During a hydraulic fracture, water is pumped at high pressure into a formation. A proppant, typically sand is later injected in the hope that it will make its way into a fracture, keep it open and provide a path for the hydrocarbon to enter the well. This injection can create micro-earthquakes, generated by deformation within the reservoir during treatment. When these injections are monitored, thousands of microseismic events are recorded within several hundred cubic meters. For each well-located event, many source parameters are estimated e.g. stress drop, Savage-Wood efficiency and apparent stress. However, because we are evaluating outputs from a power-law process, the extent to which the failure is impacted by fluid injection or stress triggering is not immediately clear. To better detect differences in source processes, we use a set of dynamic statistical parameters which characterize various force balance assumptions using the average distance to the nearest event, event rate, volume enclosed by the events, cumulative moment and energy from a group of events. One parameter, the Fracability index, approximates the ratio of viscous to elastic forcing and highlights differences in the response time of a rock to changes in stress. These dynamic parameters are applied to a database of more than 90 000 events in a shale-gas play in the Horn River Basin to characterize spatial-temporal variations in the source processes. In order to resolve these differences, a moving window, nearest neighbour approach was used. First, the center of mass of the local distribution was estimated for several source parameters. Then, a set of dynamic parameters, which characterize the response of the rock were estimated. These techniques reveal changes in seismic efficiency and apparent stress and often coincide with marked changes in the Fracability index and other dynamic statistical parameters. Utilizing these approaches allowed for the characterization of fluid injection related processes.

Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons.

PubMed

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.

Earthquake Rupture Dynamics using Adaptive Mesh Refinement and High-Order Accurate Numerical Methods

NASA Astrophysics Data System (ADS)

Kozdon, J. E.; Wilcox, L.

2013-12-01

Our goal is to develop scalable and adaptive (spatial and temporal) numerical methods for coupled, multiphysics problems using high-order accurate numerical methods. To do so, we are developing an opensource, parallel library known as bfam (available at http://bfam.in). The first application to be developed on top of bfam is an earthquake rupture dynamics solver using high-order discontinuous Galerkin methods and summation-by-parts finite difference methods. In earthquake rupture dynamics, wave propagation in the Earth's crust is coupled to frictional sliding on fault interfaces. This coupling is two-way, required the simultaneous simulation of both processes. The use of laboratory-measured friction parameters requires near-fault resolution that is 4-5 orders of magnitude higher than that needed to resolve the frequencies of interest in the volume. This, along with earlier simulations using a low-order, finite volume based adaptive mesh refinement framework, suggest that adaptive mesh refinement is ideally suited for this problem. The use of high-order methods is motivated by the high level of resolution required off the fault in earlier the low-order finite volume simulations; we believe this need for resolution is a result of the excessive numerical dissipation of low-order methods. In bfam spatial adaptivity is handled using the p4est library and temporal adaptivity will be accomplished through local time stepping. In this presentation we will present the guiding principles behind the library as well as verification of code against the Southern California Earthquake Center dynamic rupture code validation test problems.

Rapid performance modeling and parameter regression of geodynamic models

NASA Astrophysics Data System (ADS)

Brown, J.; Duplyakin, D.

2016-12-01

Geodynamic models run in a parallel environment have many parameters with complicated effects on performance and scientifically-relevant functionals. Manually choosing an efficient machine configuration and mapping out the parameter space requires a great deal of expert knowledge and time-consuming experiments. We propose an active learning technique based on Gaussion Process Regression to automatically select experiments to map out the performance landscape with respect to scientific and machine parameters. The resulting performance model is then used to select optimal experiments for improving the accuracy of a reduced order model per unit of computational cost. We present the framework and evaluate its quality and capability using popular lithospheric dynamics models.

Identification of FOPDT and SOPDT process dynamics using closed loop test.

PubMed

Bajarangbali, Raghunath; Majhi, Somanath; Pandey, Saurabh

2014-07-01

In this paper, identification of stable and unstable first order, second order overdamped and underdamped process dynamics with time delay is presented. Relay with hysteresis is used to induce a limit cycle output and using this information, unknown process model parameters are estimated. State space based generalized analytical expressions are derived to achieve accurate results. To show the performance of the proposed method expressions are also derived for systems with a zero. In real time systems, measurement noise is an important issue during identification of process dynamics. A relay with hysteresis reduces the effect of measurement noise, in addition a new multiloop control strategy is proposed to recover the original limit cycle. Simulation results are included to validate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Homeostatic enhancement of sensory transduction

PubMed Central

Milewski, Andrew R.; Ó Maoiléidigh, Dáibhid; Salvi, Joshua D.; Hudspeth, A. J.

2017-01-01

Our sense of hearing boasts exquisite sensitivity, precise frequency discrimination, and a broad dynamic range. Experiments and modeling imply, however, that the auditory system achieves this performance for only a narrow range of parameter values. Small changes in these values could compromise hair cells’ ability to detect stimuli. We propose that, rather than exerting tight control over parameters, the auditory system uses a homeostatic mechanism that increases the robustness of its operation to variation in parameter values. To slowly adjust the response to sinusoidal stimulation, the homeostatic mechanism feeds back a rectified version of the hair bundle’s displacement to its adaptation process. When homeostasis is enforced, the range of parameter values for which the sensitivity, tuning sharpness, and dynamic range exceed specified thresholds can increase by more than an order of magnitude. Signatures in the hair cell’s behavior provide a means to determine through experiment whether such a mechanism operates in the auditory system. Robustness of function through homeostasis may be ensured in any system through mechanisms similar to those that we describe here. PMID:28760949

Complexity dynamics and Hopf bifurcation analysis based on the first Lyapunov coefficient about 3D IS-LM macroeconomics system

NASA Astrophysics Data System (ADS)

Ma, Junhai; Ren, Wenbo; Zhan, Xueli

2017-04-01

Based on the study of scholars at home and abroad, this paper improves the three-dimensional IS-LM model in macroeconomics, analyzes the equilibrium point of the system and stability conditions, focuses on the parameters and complex dynamic characteristics when Hopf bifurcation occurs in the three-dimensional IS-LM macroeconomics system. In order to analyze the stability of limit cycles when Hopf bifurcation occurs, this paper further introduces the first Lyapunov coefficient to judge the limit cycles, i.e. from a practical view of the business cycle. Numerical simulation results show that within the range of most of the parameters, the limit cycle of 3D IS-LM macroeconomics is stable, that is, the business cycle is stable; with the increase of the parameters, limit cycles becomes unstable, and the value range of the parameters in this situation is small. The research results of this paper have good guide significance for the analysis of macroeconomics system.

Galileo Station Keeping Strategy

NASA Technical Reports Server (NTRS)

Perez-Cambriles, Antonio; Bejar-Romero, Juan Antonio; Aguilar-Taboada, Daniel; Perez-Lopez, Fernando; Navarro, Daniel

2007-01-01

This paper presents analyses done for the design and implementation of the Maneuver Planning software of the Galileo Flight Dynamics Facility. The station keeping requirements of the constellation have been analyzed in order to identify the key parameters to be taken into account in the design and implementation of the software.

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

2015-01-01

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions. PMID:26579071

Microscopic insights into the NMR relaxation based protein conformational entropy meter

PubMed Central

Kasinath, Vignesh; Sharp, Kim A.; Wand, A. Joshua

2013-01-01

Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain. An empirical method that utilizes changes in conformational dynamics as a proxy for changes in conformational entropy has recently been introduced. Here we probe the microscopic origins of the link between conformational dynamics and conformational entropy using molecular dynamics simulations. Simulation of seven pro! teins gave an excellent correlation with measures of side-chain motion derived from NMR relaxation. The simulations show that the motion of methyl-bearing side-chains are sufficiently coupled to that of other side chains to serve as excellent reporters of the overall side-chain conformational entropy. These results tend to validate the use of experimentally accessible measures of methyl motion - the NMR-derived generalized order parameters - as a proxy from which to derive changes in protein conformational entropy. PMID:24007504

A simple dynamic subgrid-scale model for LES of particle-laden turbulence

NASA Astrophysics Data System (ADS)

Park, George Ilhwan; Bassenne, Maxime; Urzay, Javier; Moin, Parviz

2017-04-01

In this study, a dynamic model for large-eddy simulations is proposed in order to describe the motion of small inertial particles in turbulent flows. The model is simple, involves no significant computational overhead, contains no adjustable parameters, and is flexible enough to be deployed in any type of flow solvers and grids, including unstructured setups. The approach is based on the use of elliptic differential filters to model the subgrid-scale velocity. The only model parameter, which is related to the nominal filter width, is determined dynamically by imposing consistency constraints on the estimated subgrid energetics. The performance of the model is tested in large-eddy simulations of homogeneous-isotropic turbulence laden with particles, where improved agreement with direct numerical simulation results is observed in the dispersed-phase statistics, including particle acceleration, local carrier-phase velocity, and preferential-concentration metrics.

Social judgment theory based model on opinion formation, polarization and evolution

NASA Astrophysics Data System (ADS)

Chau, H. F.; Wong, C. Y.; Chow, F. K.; Fung, Chi-Hang Fred

2014-12-01

The dynamical origin of opinion polarization in the real world is an interesting topic that physical scientists may help to understand. To properly model the dynamics, the theory must be fully compatible with findings by social psychologists on microscopic opinion change. Here we introduce a generic model of opinion formation with homogeneous agents based on the well-known social judgment theory in social psychology by extending a similar model proposed by Jager and Amblard. The agents’ opinions will eventually cluster around extreme and/or moderate opinions forming three phases in a two-dimensional parameter space that describes the microscopic opinion response of the agents. The dynamics of this model can be qualitatively understood by mean-field analysis. More importantly, first-order phase transition in opinion distribution is observed by evolving the system under a slow change in the system parameters, showing that punctuated equilibria in public opinion can occur even in a fully connected social network.

Determination of eigenvalues of dynamical systems by symbolic computation

NASA Technical Reports Server (NTRS)

Howard, J. C.

1982-01-01

A symbolic computation technique for determining the eigenvalues of dynamical systems is described wherein algebraic operations, symbolic differentiation, matrix formulation and inversion, etc., can be performed on a digital computer equipped with a formula-manipulation compiler. An example is included that demonstrates the facility with which the system dynamics matrix and the control distribution matrix from the state space formulation of the equations of motion can be processed to obtain eigenvalue loci as a function of a system parameter. The example chosen to demonstrate the technique is a fourth-order system representing the longitudinal response of a DC 8 aircraft to elevator inputs. This simplified system has two dominant modes, one of which is lightly damped and the other well damped. The loci may be used to determine the value of the controlling parameter that satisfied design requirements. The results were obtained using the MACSYMA symbolic manipulation system.

Experiences with Probabilistic Analysis Applied to Controlled Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Giesy, Daniel P.

2004-01-01

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

DTIC Science & Technology

2015-03-16

sensitivity value was the maximum uncertainty in that value estimated by the Sobol method. 2.4. Global Sensitivity Analysis of the Reduced Order Coagulation...sensitivity analysis, using the variance-based method of Sobol , to estimate which parameters controlled the performance of the reduced order model [69]. We...Environment. Comput. Sci. Eng. 2007, 9, 90–95. 69. Sobol , I. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

Reduced-order model for dynamic optimization of pressure swing adsorption processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, A.; Biegler, L.; Zitney, S.

2007-01-01

Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the dynamic coupled PDE-based model of a two-bed four-step PSA process for separation of hydrogen from methane. Separate ROMs have been developed for each operating step with different POD modes for each of them. A significant reduction in the order of the number of states has been achieved. The gas-phase mole fraction, solid-state loading and temperature profiles from the low-order ROM and from the high-order simulations have been compared. Moreover, the profiles for a different set of inputs and parameter values fed to the same ROM were compared with the accurate profiles from the high-order simulations. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes. Moreover, deviations from the ROM for different set of inputs and parameters suggest that a recalibration of the model is required for the optimization studies. Results for these will also be presented with the aforementioned results.« less

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks.

PubMed

Scarpetta, Silvia; Giacco, Ferdinando

2013-04-01

We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stable precise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units.

Influence of fusion dynamics on fission observables: A multidimensional analysis

NASA Astrophysics Data System (ADS)

Schmitt, C.; Mazurek, K.; Nadtochy, P. N.

2018-01-01

An attempt to unfold the respective influence of the fusion and fission stages on typical fission observables, and namely the neutron prescission multiplicity, is proposed. A four-dimensional dynamical stochastic Langevin model is used to calculate the decay by fission of excited compound nuclei produced in a wide set of heavy-ion collisions. The comparison of the results from such a calculation and experimental data is discussed, guided by predictions of the dynamical deterministic HICOL code for the compound-nucleus formation time. While the dependence of the latter on the entrance-channel properties can straigthforwardly explain some observations, a complex interplay between the various parameters of the reaction is found to occur in other cases. A multidimensional analysis of the respective role of these parameters, including entrance-channel asymmetry, bombarding energy, compound-nucleus fissility, angular momentum, and excitation energy, is proposed. It is shown that, depending on the size of the system, apparent inconsistencies may be deduced when projecting onto specific ordering parameters. The work suggests the possibility of delicate compensation effects in governing the measured fission observables, thereby highlighting the necessity of a multidimensional discussion.

Confinement dynamics of a semiflexible chain inside nano-spheres

NASA Astrophysics Data System (ADS)

Fathizadeh, A.; Heidari, Maziar; Eslami-Mossallam, B.; Ejtehadi, M. R.

2013-07-01

We study the conformations of a semiflexible chain, confined in nano-scaled spherical cavities, under two distinct processes of confinement. Radial contraction and packaging are employed as two confining procedures. The former method is performed by gradually decreasing the diameter of a spherical shell which envelopes a confined chain. The latter procedure is carried out by injecting the chain inside a spherical shell through a hole on the shell surface. The chain is modeled with a rigid body molecular dynamics simulation and its parameters are adjusted to DNA base-pair elasticity. Directional order parameter is employed to analyze and compare the confined chain and the conformations of the chain for two different sizes of the spheres are studied in both procedures. It is shown that for the confined chains in the sphere sizes of our study, they appear in spiral or tennis-ball structures, and the tennis-ball structure is more likely to be observed in more compact confinements. Our results also show that the dynamical procedure of confinement and the rate of the confinement are influential parameters of the structure of the chain inside spherical cavities.

The system controlling the composition of clastic sediments

USGS Publications Warehouse

Johnsson, Mark J.

1993-01-01

The composition of clastic sediments and rocks is controlled by a complex suite of parameters operating during pedogenesis, erosion, transport, deposition, and burial. The principal first-order parameters include source rock composition, modification by chemical weathering, mechanical disaggregation and abrasion, authigenic inputs, hydrodynamic sorting, and diagenesis. Each of these first-order parameters is influenced to varying degrees by such factors as the tectonic settings of the source region, transportational system and depositional environment, climate, vegetation, relief, slope, and the nature and energy of transportational and depositional systems. These factors are not independent; rather a complicated web of interrelationships and feedback mechanisms causes many factors to be modulated by others. Accordingly, processes controlling the composition of clastic sediments are best viewed as constituting a system, and in evaluating compositional information the dynamics of the system must be considered as whole.

Warehouse stocking optimization based on dynamic ant colony genetic algorithm

NASA Astrophysics Data System (ADS)

Xiao, Xiaoxu

2018-04-01

In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

An accurate computational method for an order parameter with a Markov state model constructed using a manifold-learning technique

NASA Astrophysics Data System (ADS)

Ito, Reika; Yoshidome, Takashi

2018-01-01

Markov state models (MSMs) are a powerful approach for analyzing the long-time behaviors of protein motion using molecular dynamics simulation data. However, their quantitative performance with respect to the physical quantities is poor. We believe that this poor performance is caused by the failure to appropriately classify protein conformations into states when constructing MSMs. Herein, we show that the quantitative performance of an order parameter is improved when a manifold-learning technique is employed for the classification in the MSM. The MSM construction using the K-center method, which has been previously used for classification, has a poor quantitative performance.

Global dynamics of oscillator populations under common noise

NASA Astrophysics Data System (ADS)

Braun, W.; Pikovsky, A.; Matias, M. A.; Colet, P.

2012-07-01

Common noise acting on a population of identical oscillators can synchronize them. We develop a description of this process which is not limited to the states close to synchrony, but provides a global picture of the evolution of the ensembles. The theory is based on the Watanabe-Strogatz transformation, allowing us to obtain closed stochastic equations for the global variables. We show that at the initial stage, the order parameter grows linearly in time, while at the later stages the convergence to synchrony is exponentially fast. Furthermore, we extend the theory to nonidentical ensembles with the Lorentzian distribution of natural frequencies and determine the stationary values of the order parameter in dependence on driving noise and mismatch.

Ultrafast spin dynamics and switching via spin transfer torque in antiferromagnets with weak ferromagnetism

PubMed Central

Kim, Tae Heon; Grünberg, Peter; Han, Song Hee; Cho, Beongki

2016-01-01

The spin-torque driven dynamics of antiferromagnets with Dzyaloshinskii-Moriya interaction (DMI) were investigated based on the Landau-Lifshitz-Gilbert-Slonczewski equation with antiferromagnetic and ferromagnetic order parameters (l and m, respectively). We demonstrate that antiferromagnets including DMI can be described by a 2-dimensional pendulum model of l. Because m is coupled with l, together with DMI and exchange energy, close examination of m provides fundamental understanding of its dynamics in linear and nonlinear regimes. Furthermore, we discuss magnetization reversal as a function of DMI and anisotropy energy induced by a spin current pulse. PMID:27713522

Complexity and Hopf Bifurcation Analysis on a Kind of Fractional-Order IS-LM Macroeconomic System

NASA Astrophysics Data System (ADS)

Ma, Junhai; Ren, Wenbo

On the basis of our previous research, we deepen and complete a kind of macroeconomics IS-LM model with fractional-order calculus theory, which is a good reflection on the memory characteristics of economic variables, we also focus on the influence of the variables on the real system, and improve the analysis capabilities of the traditional economic models to suit the actual macroeconomic environment. The conditions of Hopf bifurcation in fractional-order system models are briefly demonstrated, and the fractional order when Hopf bifurcation occurs is calculated, showing the inherent complex dynamic characteristics of the system. With numerical simulation, bifurcation, strange attractor, limit cycle, waveform and other complex dynamic characteristics are given; and the order condition is obtained with respect to time. We find that the system order has an important influence on the running state of the system. The system has a periodic motion when the order meets the conditions of Hopf bifurcation; the fractional-order system gradually stabilizes with the change of the order and parameters while the corresponding integer-order system diverges. This study has certain significance to policy-making about macroeconomic regulation and control.

Full Two-Body Problem Mass Parameter Observability Explored Through Doubly Synchronous Systems

NASA Astrophysics Data System (ADS)

Davis, Alex Benjamin; Scheeres, Daniel

2018-04-01

The full two-body problem (F2BP) is often used to model binary asteroid systems, representing the bodies as two finite mass distributions whose dynamics are influenced by their mutual gravity potential. The emergent behavior of the F2BP is highly coupled translational and rotational mutual motion of the mass distributions. For these systems the doubly synchronous equilibrium occurs when both bodies are tidally-locked and in a circular co-orbit. Stable oscillations about this equilibrium can be shown, for the nonplanar system, to be combinations of seven fundamental frequencies of the system and the mutual orbit rate. The fundamental frequencies arise as the linear periods of center manifolds identified about the equilibrium which are heavily influenced by each body’s mass parameters. We leverage these eight dynamical constraints to investigate the observability of binary asteroid mass parameters via dynamical observations. This is accomplished by proving the nonsingularity of the relationship between the frequencies and mass parameters for doubly synchronous systems. Thus we can invert the relationship to show that given observations of the frequencies, we can solve for the mass parameters of a target system. In so doing we are able to predict the estimation covariance of the mass parameters based on observation quality and define necessary observation accuracies for desired mass parameter certainties. We apply these tools to 617 Patroclus, a doubly synchronous Trojan binary and flyby target of the LUCY mission, as well as the Pluto and Charon system in order to predict mutual behaviors of these doubly synchronous systems and to provide observational requirements for these systems’ mass parameters

Amino acids at water-vapor interfaces: surface activity and orientational ordering.

PubMed

Vöhringer-Martinez, Esteban; Toro-Labbé, Alejandro

2010-10-14

The surface activity and orientational ordering of amino acids at water-vapor interfaces were studied with molecular dynamics simulations in combination with thermodynamic integration and umbrella sampling. Asparagine, representing amino acids with polar side chains, displays no surface activity. Tryptophan, in contrast, with its hydrophobic indole ring as side chain unveils a free energy minimum at the water-vapor interface, which lies 6 kJ/mol under the hydration free energy. To study the orientational ordering of tryptophan along the interface, the order parameter was calculated. At the free energy minimum and at the Gibbs dividing surface, the order parameter reveals a parallel alignment of the indole ring with the water surface exposing the π-system to electrophiles in the hydrophobic phase and indicating polarization dependent spectroscopy. In the vicinity of this position a perpendicular orientation is obtained. The surface excess, calculated from the potential of mean force along the interface, is in excellent agreement with experimental measurements.

Correlating contact line capillarity and dynamic contact angle hysteresis in surfactant-nanoparticle based complex fluids

NASA Astrophysics Data System (ADS)

Harikrishnan, A. R.; Dhar, Purbarun; Agnihotri, Prabhat K.; Gedupudi, Sateesh; Das, Sarit K.

2018-04-01

Dynamic wettability and contact angle hysteresis can be correlated to shed insight onto any solid-liquid interaction. Complex fluids are capable of altering the expected hysteresis and dynamic wetting behavior due to interfacial interactions. We report the effect of capillary number on the dynamic advancing and receding contact angles of surfactant-based nanocolloidal solutions on hydrophilic, near hydrophobic, and superhydrophobic surfaces by performing forced wetting and de-wetting experiments by employing the embedded needle method. A segregated study is performed to infer the contributing effects of the constituents and effects of particle morphology. The static contact angle hysteresis is found to be a function of particle and surfactant concentrations and greatly depends on the nature of the morphology of the particles. An order of estimate of line energy and a dynamic flow parameter called spreading factor and the transient variations of these parameters are explored which sheds light on the dynamics of contact line movement and response to perturbation of three-phase contact. The Cox-Voinov-Tanner law was found to hold for hydrophilic and a weak dependency on superhydrophobic surfaces with capillary number, and even for the complex fluids, with a varying degree of dependency for different fluids.

Estimating the biophysical properties of neurons with intracellular calcium dynamics.

PubMed

Ye, Jingxin; Rozdeba, Paul J; Morone, Uriel I; Daou, Arij; Abarbanel, Henry D I

2014-06-01

We investigate the dynamics of a conductance-based neuron model coupled to a model of intracellular calcium uptake and release by the endoplasmic reticulum. The intracellular calcium dynamics occur on a time scale that is orders of magnitude slower than voltage spiking behavior. Coupling these mechanisms sets the stage for the appearance of chaotic dynamics, which we observe within certain ranges of model parameter values. We then explore the question of whether one can, using observed voltage data alone, estimate the states and parameters of the voltage plus calcium (V+Ca) dynamics model. We find the answer is negative. Indeed, we show that voltage plus another observed quantity must be known to allow the estimation to be accurate. We show that observing both the voltage time course V(t) and the intracellular Ca time course will permit accurate estimation, and from the estimated model state, accurate prediction after observations are completed. This sets the stage for how one will be able to use a more detailed model of V+Ca dynamics in neuron activity in the analysis of experimental data on individual neurons as well as functional networks in which the nodes (neurons) have these biophysical properties.

Estimating the biophysical properties of neurons with intracellular calcium dynamics

NASA Astrophysics Data System (ADS)

Ye, Jingxin; Rozdeba, Paul J.; Morone, Uriel I.; Daou, Arij; Abarbanel, Henry D. I.

2014-06-01

We investigate the dynamics of a conductance-based neuron model coupled to a model of intracellular calcium uptake and release by the endoplasmic reticulum. The intracellular calcium dynamics occur on a time scale that is orders of magnitude slower than voltage spiking behavior. Coupling these mechanisms sets the stage for the appearance of chaotic dynamics, which we observe within certain ranges of model parameter values. We then explore the question of whether one can, using observed voltage data alone, estimate the states and parameters of the voltage plus calcium (V+Ca) dynamics model. We find the answer is negative. Indeed, we show that voltage plus another observed quantity must be known to allow the estimation to be accurate. We show that observing both the voltage time course V (t) and the intracellular Ca time course will permit accurate estimation, and from the estimated model state, accurate prediction after observations are completed. This sets the stage for how one will be able to use a more detailed model of V+Ca dynamics in neuron activity in the analysis of experimental data on individual neurons as well as functional networks in which the nodes (neurons) have these biophysical properties.

Two-order-parameter description of liquid Al under five different pressures

NASA Astrophysics Data System (ADS)

Li, Y. D.; Hao, Qing-Hai; Cao, Qi-Long; Liu, C. S.

2008-11-01

In the present work, using the glue potential, the constant pressure molecular-dynamics simulations of liquid Al under five various pressures and a systematic analysis of the local atomic structures have been performed in order to test the two-order-parameter model proposed by Tanaka [Phys. Rev. Lett. 80, 5750 (1998)] originally for explaining the unusual behaviors of liquid water. The temperature dependence of the bond order parameter Q6 in liquid Al under five different pressures can be well fitted by the functional expression (Q6)/(1-Q6)=Q60exp((ΔE-PΔV)/(kBT)) which produces the energy gain ΔE and the volume change upon the formation of a locally favored structure: ΔE=0.025eV and ΔV=-0.27(Å)3 . ΔE is nearly equal to the difference between the average bond energy of the other type I bonds and the average bond energy of 1551 bonds (characterizing the icosahedronlike local structure); ΔV could be explained as the average volume occupied by one atom in icosahedra minus that occupied by one atom in other structures. With the obtained ΔE and ΔV , it is satisfactorily explained that the density of liquid Al displays a much weaker nonlinear dependence on temperature under lower pressures. So it is demonstrated that the behavior of liquid Al can be well described by the two-order-parameter model.

QCD-Electroweak First-Order Phase Transition in a Supercooled Universe.

PubMed

Iso, Satoshi; Serpico, Pasquale D; Shimada, Kengo

2017-10-06

If the electroweak sector of the standard model is described by classically conformal dynamics, the early Universe evolution can be substantially altered. It is already known that-contrarily to the standard model case-a first-order electroweak phase transition may occur. Here we show that, depending on the model parameters, a dramatically different scenario may happen: A first-order, six massless quark QCD phase transition occurs first, which then triggers the electroweak symmetry breaking. We derive the necessary conditions for this dynamics to occur, using the specific example of the classically conformal B-L model. In particular, relatively light weakly coupled particles are predicted, with implications for collider searches. This scenario is also potentially rich in cosmological consequences, such as renewed possibilities for electroweak baryogenesis, altered dark matter production, and gravitational wave production, as we briefly comment upon.

QCD-Electroweak First-Order Phase Transition in a Supercooled Universe

NASA Astrophysics Data System (ADS)

Iso, Satoshi; Serpico, Pasquale D.; Shimada, Kengo

2017-10-01

If the electroweak sector of the standard model is described by classically conformal dynamics, the early Universe evolution can be substantially altered. It is already known that—contrarily to the standard model case—a first-order electroweak phase transition may occur. Here we show that, depending on the model parameters, a dramatically different scenario may happen: A first-order, six massless quark QCD phase transition occurs first, which then triggers the electroweak symmetry breaking. We derive the necessary conditions for this dynamics to occur, using the specific example of the classically conformal B -L model. In particular, relatively light weakly coupled particles are predicted, with implications for collider searches. This scenario is also potentially rich in cosmological consequences, such as renewed possibilities for electroweak baryogenesis, altered dark matter production, and gravitational wave production, as we briefly comment upon.

Accelerated pharmacokinetic map determination for dynamic contrast enhanced MRI using frequency-domain based Tofts model.

PubMed

Vajuvalli, Nithin N; Nayak, Krupa N; Geethanath, Sairam

2014-01-01

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is widely used in the diagnosis of cancer and is also a promising tool for monitoring tumor response to treatment. The Tofts model has become a standard for the analysis of DCE-MRI. The process of curve fitting employed in the Tofts equation to obtain the pharmacokinetic (PK) parameters is time-consuming for high resolution scans. Current work demonstrates a frequency-domain approach applied to the standard Tofts equation to speed-up the process of curve-fitting in order to obtain the pharmacokinetic parameters. The results obtained show that using the frequency domain approach, the process of curve fitting is computationally more efficient compared to the time-domain approach.

Vibration of functionally graded plate resting on viscoelastic elastic foundation subjected to moving loads

NASA Astrophysics Data System (ADS)

Duy Hien, Ta; Lam, Nguyen Ngoc

2018-04-01

The dynamics of plates subjected to a moving load must be considered by engineering mechanics and design structures. This paper deals with the dynamic responses of functionally graded (FG) rectangular plates resting on a viscoelastic foundation under moving loads. It is assumed that material properties of the plate vary continuously in the thickness direction according to the power-law. The governing equations are derived by using Hamilton’s principle, which considers the effect of the higher-order shear deformation in the plate. Transient responses of simply supported FG rectangular plates are employed by using state-space methods. Several examples are given for displacement and stresses in the plates with various structural parameters, and the effects of these parameters are discussed.

Application of Fisher Information to Complex Dynamic Systems

EPA Science Inventory

Fisher information was developed by the statistician Ronald Fisher as a measure of the information obtainable from data being used to fit a related parameter. Starting from the work of Ronald Fisher1 and B. Roy Frieden2, we have developed Fisher information as a measure of order ...

Application of Fisher Information to Complex Dynamic Systems (Tucson)

EPA Science Inventory

Fisher information was developed by the statistician Ronald Fisher as a measure of the information obtainable from data being used to fit a related parameter. Starting from the work of Ronald Fisher1 and B. Roy Frieden2, we have developed Fisher information as a measure of order ...

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

NASA Astrophysics Data System (ADS)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

A multi-approach geophysical estimation of soil dynamic properties in settlements: a case study in Güzelbahce-İzmir (Western Anatolia)

NASA Astrophysics Data System (ADS)

Akgün, Mustafa; Gönenç, Tolga; Tunçel, Aykut; Pamukçu, Oya

2013-08-01

An earthquake is a natural disaster which cannot be predicted beforehand. The economic losses and casualties induced by earthquakes badly influence human life. In order to reduce these negative effects, buildings and structures should be designed to be earthquake resistant. In the design stage of earthquake-resistant structures, models of soil under dynamic conditions are used. The parameters that are required to account for soil dynamic models are shear wave velocity (Vs) values, stiffness, thickness, the number of layers, attenuation, rigidity and the depth to bedrock. These parameters are used to calculate an empirical transfer function, the bearing capacity of the soil and liquefaction. Within this context, these soil dynamic parameters should be obtained with the help of geophysical methods in situ, in the İzmir-Güzelbahçe region and its surrounds. The İzmir-Güzelbahçe region and its surrounds are located at the intersection point of two major faults (the İzmir fault and the Seferihisar fault). For this reason, soil dynamic parameters are variable in the lateral and vertical directions. These changes affect the soil Vs profiles. To identify the shear wave velocity (Vs) profile, common mid-point cross-correlation analysis of multi-channel surface-wave data (CMPCC MASW method), microtremor and microgravity methods can be used in common. As a result, when these three methods were evaluated together, it was concluded that the aforementioned region shows sudden lateral structure changes. Relying on these changes, the dynamic analyses that would be carried out to determine soil behavior at a possible earthquake site should be taken into consideration.

Cole-Cole law for critical dynamics in glass-forming liquids.

PubMed

Sperl, Matthias

2006-07-01

Within the mode-coupling theory (MCT) for glassy dynamics, the asymptotic low-frequency expansions for the dynamical susceptibilities at critical points are compared to the expansions for the dynamic moduli; this shows that the convergence properties of the two expansions can be quite different. In some parameter regions, the leading-order expansion formula for the modulus describes the solutions of the MCT equations of motion outside the transient regime successfully; at the same time, the leading- and next-to-leading-order expansion formulas for the susceptibility fail. In these cases, one can derive a Cole-Cole law for the susceptibilities; and this law accounts for the dynamics for frequencies below the band of microscopic excitations and above the high-frequency part of the alpha peak. It is shown that this scenario explains the optical-Kerr-effect data measured for salol and benzophenone (BZP). For BZP it is inferred that the depolarized light-scattering spectra exhibit a wing for the alpha peak within the Gigahertz band. This wing results from the crossover of the von Schweidler law part of the alpha peak to the high-frequency part of the Cole-Cole peak; and this crossover can be described quantitatively by the leading-order formulas of MCT for the modulus.

Solution to automatic generation control problem using firefly algorithm optimized I(λ)D(µ) controller.

PubMed

Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul

2014-03-01

Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust linear parameter-varying control of blood pressure using vasoactive drugs

NASA Astrophysics Data System (ADS)

Luspay, Tamas; Grigoriadis, Karolos

2015-10-01

Resuscitation of emergency care patients requires fast restoration of blood pressure to a target value to achieve hemodynamic stability and vital organ perfusion. A robust control design methodology is presented in this paper for regulating the blood pressure of hypotensive patients by means of the closed-loop administration of vasoactive drugs. To this end, a dynamic first-order delay model is utilised to describe the vasoactive drug response with varying parameters that represent intra-patient and inter-patient variability. The proposed framework consists of two components: first, an online model parameter estimation is carried out using a multiple-model extended Kalman-filter. Second, the estimated model parameters are used for continuously scheduling a robust linear parameter-varying (LPV) controller. The closed-loop behaviour is characterised by parameter-varying dynamic weights designed to regulate the mean arterial pressure to a target value. Experimental data of blood pressure response of anesthetised pigs to phenylephrine injection are used for validating the LPV blood pressure models. Simulation studies are provided to validate the online model estimation and the LPV blood pressure control using phenylephrine drug injection models representing patients showing sensitive, nominal and insensitive response to the drug.

Sensitivity analysis of a sediment dynamics model applied in a Mediterranean river basin: global change and management implications.

PubMed

Sánchez-Canales, M; López-Benito, A; Acuña, V; Ziv, G; Hamel, P; Chaplin-Kramer, R; Elorza, F J

2015-01-01

Climate change and land-use change are major factors influencing sediment dynamics. Models can be used to better understand sediment production and retention by the landscape, although their interpretation is limited by large uncertainties, including model parameter uncertainties. The uncertainties related to parameter selection may be significant and need to be quantified to improve model interpretation for watershed management. In this study, we performed a sensitivity analysis of the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) sediment retention model in order to determine which model parameters had the greatest influence on model outputs, and therefore require special attention during calibration. The estimation of the sediment loads in this model is based on the Universal Soil Loss Equation (USLE). The sensitivity analysis was performed in the Llobregat basin (NE Iberian Peninsula) for exported and retained sediment, which support two different ecosystem service benefits (avoided reservoir sedimentation and improved water quality). Our analysis identified the model parameters related to the natural environment as the most influential for sediment export and retention. Accordingly, small changes in variables such as the magnitude and frequency of extreme rainfall events could cause major changes in sediment dynamics, demonstrating the sensitivity of these dynamics to climate change in Mediterranean basins. Parameters directly related to human activities and decisions (such as cover management factor, C) were also influential, especially for sediment exported. The importance of these human-related parameters in the sediment export process suggests that mitigation measures have the potential to at least partially ameliorate climate-change driven changes in sediment exportation. Copyright © 2014 Elsevier B.V. All rights reserved.

A simple method for identifying parameter correlations in partially observed linear dynamic models.

PubMed

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a software packet.

Adaptive servo control for umbilical mating

NASA Technical Reports Server (NTRS)

Zia, Omar

1988-01-01

Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.

Efficient and stable exponential time differencing Runge-Kutta methods for phase field elastic bending energy models

NASA Astrophysics Data System (ADS)

Wang, Xiaoqiang; Ju, Lili; Du, Qiang

2016-07-01

The Willmore flow formulated by phase field dynamics based on the elastic bending energy model has been widely used to describe the shape transformation of biological lipid vesicles. In this paper, we develop and investigate some efficient and stable numerical methods for simulating the unconstrained phase field Willmore dynamics and the phase field Willmore dynamics with fixed volume and surface area constraints. The proposed methods can be high-order accurate and are completely explicit in nature, by combining exponential time differencing Runge-Kutta approximations for time integration with spectral discretizations for spatial operators on regular meshes. We also incorporate novel linear operator splitting techniques into the numerical schemes to improve the discrete energy stability. In order to avoid extra numerical instability brought by use of large penalty parameters in solving the constrained phase field Willmore dynamics problem, a modified augmented Lagrange multiplier approach is proposed and adopted. Various numerical experiments are performed to demonstrate accuracy and stability of the proposed methods.

Dynamic characterization of high damping viscoelastic materials from vibration test data

NASA Astrophysics Data System (ADS)

Martinez-Agirre, Manex; Elejabarrieta, María Jesús

2011-08-01

The numerical analysis and design of structural systems involving viscoelastic damping materials require knowledge of material properties and proper mathematical models. A new inverse method for the dynamic characterization of high damping and strong frequency-dependent viscoelastic materials from vibration test data measured by forced vibration tests with resonance is presented. Classical material parameter extraction methods are reviewed; their accuracy for characterizing high damping materials is discussed; and the bases of the new analysis method are detailed. The proposed inverse method minimizes the residue between the experimental and theoretical dynamic response at certain discrete frequencies selected by the user in order to identify the parameters of the material constitutive model. Thus, the material properties are identified in the whole bandwidth under study and not just at resonances. Moreover, the use of control frequencies makes the method insensitive to experimental noise and the efficiency is notably enhanced. Therefore, the number of tests required is drastically reduced and the overall process is carried out faster and more accurately. The effectiveness of the proposed method is demonstrated with the characterization of a CLD (constrained layer damping) cantilever beam. First, the elastic properties of the constraining layers are identified from the dynamic response of a metallic cantilever beam. Then, the viscoelastic properties of the core, represented by a four-parameter fractional derivative model, are identified from the dynamic response of a CLD cantilever beam.

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Synchronisation of chaos and its applications

NASA Astrophysics Data System (ADS)

Eroglu, Deniz; Lamb, Jeroen S. W.; Pereira, Tiago

2017-07-01

Dynamical networks are important models for the behaviour of complex systems, modelling physical, biological and societal systems, including the brain, food webs, epidemic disease in populations, power grids and many other. Such dynamical networks can exhibit behaviour in which deterministic chaos, exhibiting unpredictability and disorder, coexists with synchronisation, a classical paradigm of order. We survey the main theory behind complete, generalised and phase synchronisation phenomena in simple as well as complex networks and discuss applications to secure communications, parameter estimation and the anticipation of chaos.

Dynamical density functional theory analysis of the laning instability in sheared soft matter.

PubMed

Scacchi, A; Archer, A J; Brader, J M

2017-12-01

Using dynamical density functional theory (DDFT) methods we investigate the laning instability of a sheared colloidal suspension. The nonequilibrium ordering at the laning transition is driven by nonaffine particle motion arising from interparticle interactions. Starting from a DDFT which incorporates the nonaffine motion, we perform a linear stability analysis that enables identification of the regions of parameter space where lanes form. We illustrate our general approach by applying it to a simple one-component fluid of soft penetrable particles.

A model for oscillations and pattern formation in protoplasmic droplets of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Radszuweit, M.; Engel, H.; Bär, M.

2010-12-01

A mechano-chemical model for the spatiotemporal dynamics of free calcium and the thickness in protoplasmic droplets of the true slime mold Physarum polycephalum is derived starting from a physiologically detailed description of intracellular calcium oscillations proposed by Smith and Saldana (Biopys. J. 61, 368 (1992)). First, we have modified the Smith-Saldana model for the temporal calcium dynamics in order to reproduce the experimentally observed phase relation between calcium and mechanical tension oscillations. Then, we formulate a model for spatiotemporal dynamics by adding spatial coupling in the form of calcium diffusion and advection due to calcium-dependent mechanical contraction. In another step, the resulting reaction-diffusion model with mechanical coupling is simplified to a reaction-diffusion model with global coupling that approximates the mechanical part. We perform a bifurcation analysis of the local dynamics and observe a Hopf bifurcation upon increase of a biochemical activity parameter. The corresponding reaction-diffusion model with global coupling shows regular and chaotic spatiotemporal behaviour for parameters with oscillatory dynamics. In addition, we show that the global coupling leads to a long-wavelength instability even for parameters where the local dynamics possesses a stable spatially homogeneous steady state. This instability causes standing waves with a wavelength of twice the system size in one dimension. Simulations of the model in two dimensions are found to exhibit defect-mediated turbulence as well as various types of spiral wave patterns in qualitative agreement with earlier experimental observation by Takagi and Ueda (Physica D, 237, 420 (2008)).

Dynamic Transition and Resonance in Coupled Oscillators Under Symmetry-Breaking Fields

NASA Astrophysics Data System (ADS)

Choi, J.; Choi, M. Y.; Chung, M. S.; Yoon, B.-G.

2013-06-01

We investigate numerically the dynamic properties of a system of globally coupled oscillators driven by periodic symmetry-breaking fields in the presence of noise. The phase distribution of the oscillators is computed and a dynamic transition is disclosed. It is further found that the stochastic resonance is closely related to the behavior of the dynamic order parameter, which is in turn explained by the formation of a bi-cluster in the system. Here noise tends to symmetrize the motion of the oscillators, facilitating the bi-cluster formation. The observed resonance appears to be of the same class as the resonance present in the two-dimensional Ising model under oscillating fields.

Design and construction of miniature artificial ecosystem based on dynamic response optimization

NASA Astrophysics Data System (ADS)

Hu, Dawei; Liu, Hong; Tong, Ling; Li, Ming; Hu, Enzhu

The miniature artificial ecosystem (MAES) is a combination of man, silkworm, salad and mi-croalgae to partially regenerate O2 , sanitary water and food, simultaneously dispose CO2 and wastes, therefore it have a fundamental life support function. In order to enhance the safety and reliability of MAES and eliminate the influences of internal variations and external dis-turbances, it was necessary to configure MAES as a closed-loop control system, and it could be considered as a prototype for future bioregenerative life support system. However, MAES is a complex system possessing large numbers of parameters, intricate nonlinearities, time-varying factors as well as uncertainties, hence it is difficult to perfectly design and construct a prototype through merely conducting experiments by trial and error method. Our research presented an effective way to resolve preceding problem by use of dynamic response optimiza-tion. Firstly the mathematical model of MAES with first-order nonlinear ordinary differential equations including parameters was developed based on relevant mechanisms and experimental data, secondly simulation model of MAES was derived on the platform of MatLab/Simulink to perform model validation and further digital simulations, thirdly reference trajectories of de-sired dynamic response of system outputs were specified according to prescribed requirements, and finally optimization for initial values, tuned parameter and independent parameters was carried out using the genetic algorithm, the advanced direct search method along with parallel computing methods through computer simulations. The result showed that all parameters and configurations of MAES were determined after a series of computer experiments, and its tran-sient response performances and steady characteristics closely matched the reference curves. Since the prototype is a physical system that represents the mathematical model with reason-able accuracy, so the process of designing and constructing a prototype of MAES is the reverse of mathematical modeling, and must have prerequisite assists from these results of computer simulation.

Quantum criticality of a spin-1 XY model with easy-plane single-ion anisotropy via a two-time Green function approach avoiding the Anderson-Callen decoupling

NASA Astrophysics Data System (ADS)

Mercaldo, M. T.; Rabuffo, I.; De Cesare, L.; Caramico D'Auria, A.

2016-04-01

In this work we study the quantum phase transition, the phase diagram and the quantum criticality induced by the easy-plane single-ion anisotropy in a d-dimensional quantum spin-1 XY model in absence of an external longitudinal magnetic field. We employ the two-time Green function method by avoiding the Anderson-Callen decoupling of spin operators at the same sites which is of doubtful accuracy. Following the original Devlin procedure we treat exactly the higher order single-site anisotropy Green functions and use Tyablikov-like decouplings for the exchange higher order ones. The related self-consistent equations appear suitable for an analysis of the thermodynamic properties at and around second order phase transition points. Remarkably, the equivalence between the microscopic spin model and the continuous O(2) -vector model with transverse-Ising model (TIM)-like dynamics, characterized by a dynamic critical exponent z=1, emerges at low temperatures close to the quantum critical point with the single-ion anisotropy parameter D as the non-thermal control parameter. The zero-temperature critic anisotropy parameter Dc is obtained for dimensionalities d > 1 as a function of the microscopic exchange coupling parameter and the related numerical data for different lattices are found to be in reasonable agreement with those obtained by means of alternative analytical and numerical methods. For d > 2, and in particular for d=3, we determine the finite-temperature critical line ending in the quantum critical point and the related TIM-like shift exponent, consistently with recent renormalization group predictions. The main crossover lines between different asymptotic regimes around the quantum critical point are also estimated providing a global phase diagram and a quantum criticality very similar to the conventional ones.

Estimation of position and velocity for a low dynamic vehicle in near space using nonresolved photometric and astrometric data.

PubMed

Jing, Nan; Li, Chuang; Chong, Yaqin

2017-01-20

An estimation method for indirectly observable parameters for a typical low dynamic vehicle (LDV) is presented. The estimation method utilizes apparent magnitude, azimuth angle, and elevation angle to estimate the position and velocity of a typical LDV, such as a high altitude balloon (HAB). In order to validate the accuracy of the estimated parameters gained from an unscented Kalman filter, two sets of experiments are carried out to obtain the nonresolved photometric and astrometric data. In the experiments, a HAB launch is planned; models of the HAB dynamics and kinematics and observation models are built to use as time update and measurement update functions, respectively. When the HAB is launched, a ground-based optoelectronic detector is used to capture the object images, which are processed using aperture photometry technology to obtain the time-varying apparent magnitude of the HAB. Two sets of actual and estimated parameters are given to clearly indicate the parameter differences. Two sets of errors between the actual and estimated parameters are also given to show how the estimated position and velocity differ with respect to the observation time. The similar distribution curve results from the two scenarios, which agree within 3σ, verify that nonresolved photometric and astrometric data can be used to estimate the indirectly observable state parameters (position and velocity) for a typical LDV. This technique can be applied to small and dim space objects in the future.

The absence of intraband scattering in a consistent theory of Gilbert damping in pure metallic ferromagnets.

PubMed

Edwards, D M

2016-03-02

Damping of magnetization dynamics in a ferromagnetic metal, arising from spin-orbit coupling, is usually characterised by the Gilbert parameter α. Recent calculations of this quantity, using a formula due to Kambersky, find that it is infinite for a perfect crystal owing to an intraband scattering term which is of third order in the spin-orbit parameter ξ. This surprising result conflicts with recent work by Costa and Muniz who study damping numerically by direct calculation of the dynamical transverse susceptibility in the presence of spin-orbit coupling. We resolve this inconsistency by following the approach of Costa and Muniz for a slightly simplified model where it is possible to calculate α analytically. We show that to second order in ξ one retrieves the Kambersky result for α, but to higher order one does not obtain any divergent intraband terms. The present work goes beyond that of Costa and Muniz by pointing out the necessity of including the effect of long-range Coulomb interaction in calculating damping for large ξ. A direct derivation of the Kambersky formula is given which shows clearly the restriction of its validity to second order in ξ so that no intraband scattering terms appear. This restriction has an important effect on the damping over a substantial range of impurity content and temperature. The experimental situation is discussed.

Coarsening of stripe patterns: variations with quench depth and scaling.

PubMed

Tripathi, Ashwani K; Kumar, Deepak

2015-02-01

The coarsening of stripe patterns when the system is evolved from random initial states is studied by varying the quench depth ε, which is a measure of distance from the transition point of the stripe phase. The dynamics of the growth of stripe order, which is characterized by two length scales, depends on the quench depth. The growth exponents of the two length scales vary continuously with ε. The decay exponents for free energy, stripe curvature, and densities of defects like grain boundaries and dislocations also show similar variation. This implies a breakdown of the standard picture of nonequilibrium dynamical scaling. In order to understand the variations with ε we propose an additional scaling with a length scale dependent on ε. The main contribution to this length scale comes from the "pinning potential," which is unique to systems where the order parameter is spatially periodic. The periodic order parameter gives rise to an ε-dependent potential, which can pin defects like grain boundaries, dislocations, etc. This additional scaling provides a compact description of variations of growth exponents with quench depth in terms of just one exponent for each of the length scales. The relaxation of free energy, stripe curvature, and the defect densities have also been related to these length scales. The study is done at zero temperature using Swift-Hohenberg equation in two dimensions.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Optimal control of multiphoton ionization dynamics of small alkali aggregates

NASA Astrophysics Data System (ADS)

Lindinger, A.; Bartelt, A.; Lupulescu, C.; Vajda, S.; Woste, Ludger

2003-11-01

We have performed transient multi-photon ionization experiments on small alkali clusters of different size in order to probe their wave packet dynamics, structural reorientations, charge transfers and dissociative events in different vibrationally excited electronic states including their ground state. The observed processes were highly dependent on the irradiated pulse parameters like wavelength range or its phase and amplitude; an emphasis to employ a feedback control system for generating the optimum pulse shapes. Their spectral and temporal behavior reflects interesting properties about the investigated system and the irradiated photo-chemical process. First, we present the vibrational dynamics of bound electronically excited states of alkali dimers and trimers. The scheme for observing the wave packet dynamics in the electronic ground state using stimulated Raman-pumping is shown. Since the employed pulse parameters significantly influence the efficiency of the irradiated dynamic pathways photo-induced ioniziation experiments were carried out. The controllability of 3-photon ionization pathways is investigated on the model-like systems NaK and K2. A closed learning loop for adaptive feedback control is used to find the optimal fs pulse shape. Sinusoidal parameterizations of the spectral phase modulation are investigated in regard to the obtained optimal field. By reducing the number of parameters and thereby the complexity of the phase moduation, optimal pulse shapes can be generated that carry fingerprints of the molecule's dynamical properties. This enables to find "understandable" optimal pulse forms and offers the possiblity to gain insight into the photo-induced control process. Characteristic motions of the involved wave packets are proposed to explain the optimized dynamic dissociation pathways.

Dynamics of a feline virus with two transmission modes within exponentially growing host populations.

PubMed Central

Berthier, K; Langlais, M; Auger, P; Pontier, D

2000-01-01

Feline panleucopenia virus (FPLV) was introduced in 1977 on Marion Island (in the southern Indian Ocean) with the aim of eradicating the cat population and provoked a huge decrease in the host population within six years. The virus can be transmitted either directly through contacts between infected and healthy cats or indirectly between a healthy cat and the contaminated environment: a specific feature of the virus is its high rate of survival outside the host. In this paper, a model was designed in order to take these two modes of transmission into account. The results showed that a mass-action incidence assumption was more appropriate than a proportionate mixing one in describing the dynamics of direct transmission. Under certain conditions the virus was able to control the host population at a low density. The indirect transmission acted as a reservoir supplying the host population with a low but sufficient density of infected individuals which allowed the virus to persist. The dynamics of the infection were more affected by the demographic parameters of the healthy hosts than by the epidemiological ones. Thus, demographic parameters should be precisely measured in field studies in order to obtain accurate predictions. The predicted results of our model were in good agreement with observations. PMID:11416908

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Unsteady computational fluid dynamics in front crawl swimming.

PubMed

Samson, Mathias; Bernard, Anthony; Monnet, Tony; Lacouture, Patrick; David, Laurent

2017-05-01

The development of codes and power calculations currently allows the simulation of increasingly complex flows, especially in the turbulent regime. Swimming research should benefit from these technological advances to try to better understand the dynamic mechanisms involved in swimming. An unsteady Computational Fluid Dynamics (CFD) study is conducted in crawl, in order to analyse the propulsive forces generated by the hand and forearm. The k-ω SST turbulence model and an overset grid method have been used. The main objectives are to analyse the evolution of the hand-forearm propulsive forces and to explain this relative to the arm kinematics parameters. In order to validate our simulation model, the calculated forces and pressures were compared with several other experimental and numerical studies. A good agreement is found between our results and those of other studies. The hand is the segment that generates the most propulsive forces during the aquatic stroke. As the pressure component is the main source of force, the orientation of the hand-forearm in the absolute coordinate system is an important kinematic parameter in the swimming performance. The propulsive forces are biggest when the angles of attack are high. CFD appears as a very valuable tool to better analyze the mechanisms of swimming performance and offers some promising developments, especially for optimizing the performance from a parametric study.

Slow-roll approximation in loop quantum cosmology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luc, Joanna; Mielczarek, Jakub, E-mail: joanna.luc@uj.edu.pl, E-mail: jakub.mielczarek@uj.edu.pl

The slow-roll approximation is an analytical approach to study dynamical properties of the inflationary universe. In this article, systematic construction of the slow-roll expansion for effective loop quantum cosmology is presented. The analysis is performed up to the fourth order in both slow-roll parameters and the parameter controlling the strength of deviation from the classical case. The expansion is performed for three types of the slow-roll parameters: Hubble slow-roll parameters, Hubble flow parameters and potential slow-roll parameters. An accuracy of the approximation is verified by comparison with the numerical phase space trajectories for the case with a massive potential term.more » The results obtained in this article may be helpful in the search for the subtle quantum gravitational effects with use of the cosmological data.« less

Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow

NASA Astrophysics Data System (ADS)

Narsipur, Shreyas

Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering flap to model the effect of the separated boundary-layer. Unsteady RANS results for several pitch and plunge motions showed that the differences in aerodynamic loads between steady and unsteady flows can be attributed to the boundary-layer convection lag, which can be modeled by choosing an appropriate value of the time lag parameter, tau2. In order to provide appropriate viscous corrections to inviscid unsteady calculations, the non-linear decambering flap is applied with a time lag determined by the tau2 value, which was found to be independent of motion kinematics for a given airfoil and Reynolds number. The predictions of the aerodynamic loads, unsteady stall, hysteresis loops, and ow reattachment from the low-order model agree well with CFD and experimental results, both for individual cases and for trends between motions. The model was also found to perform as well as existing semi-empirical models while using only a single empirically defined parameter. Inclusion of LEV shedding capabilities and combining the resulting algorithm with phase one's trailing-edge separation model was the primary objective of phase two. Computational results at low and high Reynolds numbers were used to analyze the ow morphology of the LEV to identify the common surface signature associated with LEV initiation at both low and high Reynolds numbers and relate it to the critical leading-edge suction parameter (LESP ) to control the initiation and termination of LEV shedding in the low-order model. The critical LESP, like the tau2 parameter, was found to be independent of motion kinematics for a given airfoil and Reynolds number. Results from the final low-order model compared excellently with CFD and experimental solutions, both in terms of aerodynamic loads and vortex ow pattern predictions. Overall, the final combined dynamic stall model that resulted from the current research was successful in accurately modeling the physics of unsteady ow thereby helping restrict the number of empirical coefficients to just two variables while successfully modeling the aerodynamic forces and ow patterns in a simple and precise manner.

Various Attractors, Coexisting Attractors and Antimonotonicity in a Simple Fourth-Order Memristive Twin-T Oscillator

NASA Astrophysics Data System (ADS)

Zhou, Ling; Wang, Chunhua; Zhang, Xin; Yao, Wei

By replacing the resistor in a Twin-T network with a generalized flux-controlled memristor, this paper proposes a simple fourth-order memristive Twin-T oscillator. Rich dynamical behaviors can be observed in the dynamical system. The most striking feature is that this system has various periodic orbits and various chaotic attractors generated by adjusting parameter b. At the same time, coexisting attractors and antimonotonicity are also detected (especially, two full Feigenbaum remerging trees in series are observed in such autonomous chaotic systems). Their dynamical features are analyzed by phase portraits, Lyapunov exponents, bifurcation diagrams and basin of attraction. Moreover, hardware experiments on a breadboard are carried out. Experimental measurements are in accordance with the simulation results. Finally, a multi-channel random bit generator is designed for encryption applications. Numerical results illustrate the usefulness of the random bit generator.

Irregular vocal fold dynamics incited by asymmetric fluid loading in a model of recurrent laryngeal nerve paralysis

NASA Astrophysics Data System (ADS)

Sommer, David; Erath, Byron D.; Zanartu, Matias; Peterson, Sean D.

2011-11-01

Voiced speech is produced by dynamic fluid-structure interactions in the larynx. Traditionally, reduced order models of speech have relied upon simplified inviscid flow solvers to prescribe the fluid loadings that drive vocal fold motion, neglecting viscous flow effects that occur naturally in voiced speech. Viscous phenomena, such as skewing of the intraglottal jet, have the most pronounced effect on voiced speech in cases of vocal fold paralysis where one vocal fold loses some, or all, muscular control. The impact of asymmetric intraglottal flow in pathological speech is captured in a reduced order two-mass model of speech by coupling a boundary-layer estimation of the asymmetric pressures with asymmetric tissue parameters that are representative of recurrent laryngeal nerve paralysis. Nonlinear analysis identifies the emergence of irregular and chaotic vocal fold dynamics at values representative of pathological speech conditions.

Four dimensional chaos and intermittency in a mesoscopic model of the electroencephalogram.

PubMed

Dafilis, Mathew P; Frascoli, Federico; Cadusch, Peter J; Liley, David T J

2013-06-01

The occurrence of so-called four dimensional chaos in dynamical systems represented by coupled, nonlinear, ordinary differential equations is rarely reported in the literature. In this paper, we present evidence that Liley's mesoscopic theory of the electroencephalogram (EEG), which has been used to describe brain activity in a variety of clinically relevant contexts, possesses a chaotic attractor with a Kaplan-Yorke dimension significantly larger than three. This accounts for simple, high order chaos for a physiologically admissible parameter set. Whilst the Lyapunov spectrum of the attractor has only one positive exponent, the contracting dimensions are such that the integer part of the Kaplan-Yorke dimension is three, thus giving rise to four dimensional chaos. A one-parameter bifurcation analysis with respect to the parameter corresponding to extracortical input is conducted, with results indicating that the origin of chaos is due to an inverse period doubling cascade. Hence, in the vicinity of the high order, strange attractor, the model is shown to display intermittent behavior, with random alternations between oscillatory and chaotic regimes. This phenomenon represents a possible dynamical justification of some of the typical features of clinically established EEG traces, which can arise in the case of burst suppression in anesthesia and epileptic encephalopathies in early infancy.

Parameter tuning method for dither compensation of a pneumatic proportional valve with friction

NASA Astrophysics Data System (ADS)

Wang, Tao; Song, Yang; Huang, Leisheng; Fan, Wei

2016-05-01

In the practical application of pneumatic control devices, the nonlinearity of a pneumatic control valve become the main factor affecting the control effect, which comes mainly from the dynamic friction force. The dynamic friction inside the valve may cause hysteresis and a dead zone. In this paper, a dither compensation mechanism is proposed to reduce negative effects on the basis of analyzing the mechanism of friction force. The specific dither signal (using a sinusoidal signal) was superimposed on the control signal of the valve. Based on the relationship between the parameters of the dither signal and the inherent characteristics of the proportional servo valve, a parameter tuning method was proposed, which uses a displacement sensor to measure the maximum static friction inside the valve. According to the experimental results, the proper amplitude ranges are determined for different pressures. In order to get the optimal parameters of the dither signal, some dither compensation experiments have been carried out on different signal amplitude and gas pressure conditions. Optimal parameters are determined under two kinds of pressure conditions. Using tuning parameters the valve spool displacement experiment has been taken. From the experiment results, hysteresis of the proportional servo valve is significantly reduced. And through simulation and experiments, the cut-off frequency of the proportional valve has also been widened. Therefore after adding the dither signal, the static and dynamic characteristics of the proportional valve are both improved to a certain degree. This research proposes a parameter tuning method of dither signal, and the validity of the method is verified experimentally.

Dynamical cluster approximation plus semiclassical approximation study for a Mott insulator and d-wave pairing

NASA Astrophysics Data System (ADS)

Kim, SungKun; Lee, Hunpyo

2017-06-01

Via a dynamical cluster approximation with N c = 4 in combination with a semiclassical approximation (DCA+SCA), we study the doped two-dimensional Hubbard model. We obtain a plaquette antiferromagnetic (AF) Mott insulator, a plaquette AF ordered metal, a pseudogap (or d-wave superconductor) and a paramagnetic metal by tuning the doping concentration. These features are similar to the behaviors observed in copper-oxide superconductors and are in qualitative agreement with the results calculated by the cluster dynamical mean field theory with the continuous-time quantum Monte Carlo (CDMFT+CTQMC) approach. The results of our DCA+SCA differ from those of the CDMFT+CTQMC approach in that the d-wave superconducting order parameters are shown even in the high doped region, unlike the results of the CDMFT+CTQMC approach. We think that the strong plaquette AF orderings in the dynamical cluster approximation (DCA) with N c = 4 suppress superconducting states with increasing doping up to strongly doped region, because frozen dynamical fluctuations in a semiclassical approximation (SCA) approach are unable to destroy those orderings. Our calculation with short-range spatial fluctuations is initial research, because the SCA can manage long-range spatial fluctuations in feasible computational times beyond the CDMFT+CTQMC tool. We believe that our future DCA+SCA calculations should supply information on the fully momentum-resolved physical properties, which could be compared with the results measured by angle-resolved photoemission spectroscopy experiments.

Nanosecond electric modification of order parameters

NASA Astrophysics Data System (ADS)

Borshch, Volodymyr

In this Dissertation, we study a nanosecond electro-optic response of a nematic liquid crystal in a geometry where an applied electric field E modifies the tensor order parameter but does not change the orientation of the optic axis (director N̂). We use nematics with negative dielectric anisotropy with the electric field applied perpendicularly to N̂. The field changes the dielectric tensor at optical frequencies (optic tensor), due to the following mechanisms: (a) nanosecond creation of biaxial orientational order; (b) uniaxial modification of the orientational order that occurs over the timescales of tens of nanoseconds, and (c) quenching of director fluctuations with a wide range of characteristic times up to milliseconds. We develop a model to describe the dynamics of all three mechanisms. We design the experimental conditions to selectively suppress the contributions from the quenching of director fluctuations (c) and from the biaxial order effect (a) and thus, separate the contributions of the three mechanisms in the electro-optic response. As a result, the experimental data can be well fitted with the model parameters. The analysis provides a rather detailed physical picture of how the liquid crystal responds to a strong electric field, E ˜ 108 V/m, on a timescale of nanoseconds. This work provides a useful guide in the current search of the biaxial nematic phase. Namely, the temperature dependence of the biaxial susceptibility allows one to estimate the temperature of the potential uniaxial-to-biaxial phase transition. An analysis of the quenching of director fluctuations indicates that on a timescale of nanoseconds, the classic model with constant viscoelastic material parameters might reach its limit of validity. The effect of nanosecond electric modification of the order parameter (NEMOP) can be used in applications in which one needs to achieve ultrafast (nanosecond) changes of optical characteristics, such as birefringence.

Creation of Frustrated Systems by d-dot Array

NASA Astrophysics Data System (ADS)

Masahiko, Machida

2004-03-01

When a square shape dot of High-Tc superconductor is embedded in s-wave superconducting matrix, half quantized vortices are spontaneously generated at the corners of the dot. This feature gives the magnetic interactions between neighboring dots in array systems composed of sevaral dots of High-Tc superconductor and allows us to make magnetic interaction systems. We propose that we can create interesting frustrated systems like the spin-ice by setting the dots in various manners. In order to demonstrate which types of frustrated systems are possible, we perform numerical simulations for the time-dependent Ginzburg-Landau equation describing dynamics of the superconducting order parameters with d-wave and s-wave symmetries. The simulations reveal that the proposed system has two parameters originated from the magnetic interaction between emerged half vortices. We tune the parameters and show various patterns of half vortices from the Ising to the ice model.

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

PubMed

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

Sampling the isothermal-isobaric ensemble by Langevin dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Xingyu; Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094; CAEP Software Center for High Performance Numerical Simulation, Huayuan Road 6, Beijing 100088

2016-03-28

We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter’s splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling timemore » scales. The method and software implementation are carefully validated by a numerical example.« less

Dark solitons in the presence of higher-order effects.

PubMed

Horikis, Theodoros P; Frantzeskakis, Dimitrios J

2013-12-01

Dark soliton propagation is studied in the presence of higher-order effects, including third-order dispersion, self-steepening, linear/nonlinear gain/loss, and Raman scattering. It is found that for certain values of the parameters a stable evolution can exist for both the soliton and the relative continuous-wave background. Using a newly developed perturbation theory we show that the perturbing effects give rise to a shelf that accompanies the soliton in its propagation. Although, the stable solitons are not affected by the shelf it remains an integral part of the dynamics otherwise not considered so far in studies of higher-order nonlinear Schrödinger models.

Modulational instability and higher-order rogue waves with parameters modulation in a coupled integrable AB system via the generalized Darboux transformation.

PubMed

Wen, Xiao-Yong; Yan, Zhenya

2015-12-01

We study higher-order rogue wave (RW) solutions of the coupled integrable dispersive AB system (also called Pedlosky system), which describes the evolution of wave-packets in a marginally stable or unstable baroclinic shear flow in geophysical fluids. We propose its continuous-wave (CW) solutions and existent conditions for their modulation instability to form the rogue waves. A new generalized N-fold Darboux transformation (DT) is proposed in terms of the Taylor series expansion for the spectral parameter in the Darboux matrix and its limit procedure and applied to the CW solutions to generate multi-rogue wave solutions of the coupled AB system, which satisfy the general compatibility condition. The dynamical behaviors of these higher-order rogue wave solutions demonstrate both strong and weak interactions by modulating parameters, in which some weak interactions can generate the abundant triangle, pentagon structures, etc. Particularly, the trajectories of motion of peaks and depressions of profiles of the first-order RWs are explicitly analyzed. The generalized DT method used in this paper can be extended to other nonlinear integrable systems. These results may be useful for understanding the corresponding rogue-wave phenomena in fluid mechanics and related fields.

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Tian, Mingyan; Huang, Jiaqi; Zhang, Rui; Ma, Zhen

2015-09-01

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Metallic coatings of microelectromechanical structures at low temperatures: Stress, elasticity, and nonlinear dissipation

NASA Astrophysics Data System (ADS)

Collin, E.; Kofler, J.; Lakhloufi, S.; Pairis, S.; Bunkov, Yu. M.; Godfrin, H.

2010-06-01

We present mechanical measurements performed at low temperatures on cantilever-based microelectromechanical structures coated with a metallic layer. Two very different coatings are presented in order to illustrate the capabilities of the present approach, namely (soft) aluminum and (hard) niobium oxide. The temperature is used as a control parameter to access materials properties. We benefit from low temperature techniques to extract a phase-resolved measurement of the first mechanical resonance mode in cryogenic vacuum. By repeating the experiment on the same samples, after multiple metallic depositions, we can determine accurately the contribution of the coating layers to the mechanical properties in terms of surface stress, additional mass, additional elasticity, and damping. Analytic theoretical expressions are derived and used to fit the data. Taking advantage of the extremely broad dynamic range provided by the technique, we can measure the anelasticity of the thin metallic film. The key parameters describing the metals' dynamics are analyzed in an original way in order to provide new experimental grounds for future theoretical modelings of the underlying mechanisms.

Combining PALM and SOFI for quantitative imaging of focal adhesions in living cells

NASA Astrophysics Data System (ADS)

Deschout, Hendrik; Lukes, Tomas; Sharipov, Azat; Feletti, Lely; Lasser, Theo; Radenovic, Aleksandra

2017-02-01

Focal adhesions are complicated assemblies of hundreds of proteins that allow cells to sense their extracellular matrix and adhere to it. Although most focal adhesion proteins have been identified, their spatial organization in living cells remains challenging to observe. Photo-activated localization microscopy (PALM) is an interesting technique for this purpose, especially since it allows estimation of molecular parameters such as the number of fluorophores. However, focal adhesions are dynamic entities, requiring a temporal resolution below one minute, which is difficult to achieve with PALM. In order to address this problem, we merged PALM with super-resolution optical fluctuation imaging (SOFI) by applying both techniques to the same data. Since SOFI tolerates an overlap of single molecule images, it can improve the temporal resolution compared to PALM. Moreover, an adaptation called balanced SOFI (bSOFI) allows estimation of molecular parameters, such as the fluorophore density. We therefore performed simulations in order to assess PALM and SOFI for quantitative imaging of dynamic structures. We demonstrated the potential of our PALM-SOFI concept as a quantitative imaging framework by investigating moving focal adhesions in living cells.

Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats.

PubMed

Leander, Jacob; Almquist, Joachim; Ahlström, Christine; Gabrielsson, Johan; Jirstrand, Mats

2015-05-01

Inclusion of stochastic differential equations in mixed effects models provides means to quantify and distinguish three sources of variability in data. In addition to the two commonly encountered sources, measurement error and interindividual variability, we also consider uncertainty in the dynamical model itself. To this end, we extend the ordinary differential equation setting used in nonlinear mixed effects models to include stochastic differential equations. The approximate population likelihood is derived using the first-order conditional estimation with interaction method and extended Kalman filtering. To illustrate the application of the stochastic differential mixed effects model, two pharmacokinetic models are considered. First, we use a stochastic one-compartmental model with first-order input and nonlinear elimination to generate synthetic data in a simulated study. We show that by using the proposed method, the three sources of variability can be successfully separated. If the stochastic part is neglected, the parameter estimates become biased, and the measurement error variance is significantly overestimated. Second, we consider an extension to a stochastic pharmacokinetic model in a preclinical study of nicotinic acid kinetics in obese Zucker rats. The parameter estimates are compared between a deterministic and a stochastic NiAc disposition model, respectively. Discrepancies between model predictions and observations, previously described as measurement noise only, are now separated into a comparatively lower level of measurement noise and a significant uncertainty in model dynamics. These examples demonstrate that stochastic differential mixed effects models are useful tools for identifying incomplete or inaccurate model dynamics and for reducing potential bias in parameter estimates due to such model deficiencies.

Molecular dynamics study of lipid bilayers modeling the plasma membranes of mouse hepatocytes and hepatomas.

PubMed

Andoh, Yoshimichi; Aoki, Noriyuki; Okazaki, Susumu

2016-02-28

Molecular dynamics (MD) calculations of lipid bilayers modeling the plasma membranes of normal mouse hepatocytes and hepatomas in water have been performed under physiological isothermal-isobaric conditions (310.15 K and 1 atm). The changes in the membrane properties induced by hepatic canceration were investigated and were compared with previous MD calculations included in our previous study of the changes in membrane properties induced by murine thymic canceration. The calculated model membranes for normal hepatocytes and hepatomas comprised 23 and 24 kinds of lipids, respectively. These included phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, sphingomyelin, lysophospholipids, and cholesterol. We referred to previously published experimental values for the mole fraction of the lipids adopted in the present calculations. The calculated structural and dynamic properties of the membranes such as lateral structure, order parameters, lateral self-diffusion constants, and rotational correlation times all showed that hepatic canceration causes plasma membranes to become more ordered laterally and less fluid. Interestingly, this finding contrasts with the less ordered structure and increased fluidity of plasma membranes induced by thymic canceration observed in our previous MD study.

Molecular dynamics study of lipid bilayers modeling the plasma membranes of mouse hepatocytes and hepatomas

NASA Astrophysics Data System (ADS)

Andoh, Yoshimichi; Aoki, Noriyuki; Okazaki, Susumu

2016-02-01

Molecular dynamics (MD) calculations of lipid bilayers modeling the plasma membranes of normal mouse hepatocytes and hepatomas in water have been performed under physiological isothermal-isobaric conditions (310.15 K and 1 atm). The changes in the membrane properties induced by hepatic canceration were investigated and were compared with previous MD calculations included in our previous study of the changes in membrane properties induced by murine thymic canceration. The calculated model membranes for normal hepatocytes and hepatomas comprised 23 and 24 kinds of lipids, respectively. These included phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, sphingomyelin, lysophospholipids, and cholesterol. We referred to previously published experimental values for the mole fraction of the lipids adopted in the present calculations. The calculated structural and dynamic properties of the membranes such as lateral structure, order parameters, lateral self-diffusion constants, and rotational correlation times all showed that hepatic canceration causes plasma membranes to become more ordered laterally and less fluid. Interestingly, this finding contrasts with the less ordered structure and increased fluidity of plasma membranes induced by thymic canceration observed in our previous MD study.

Cookbook asymptotics for spiral and scroll waves in excitable media.

PubMed

Margerit, Daniel; Barkley, Dwight

2002-09-01

Algebraic formulas predicting the frequencies and shapes of waves in a reaction-diffusion model of excitable media are presented in the form of four recipes. The formulas themselves are based on a detailed asymptotic analysis (published elsewhere) of the model equations at leading order and first order in the asymptotic parameter. The importance of the first order contribution is stressed throughout, beginning with a discussion of the Fife limit, Fife scaling, and Fife regime. Recipes are given for spiral waves and detailed comparisons are presented between the asymptotic predictions and the solutions of the full reaction-diffusion equations. Recipes for twisted scroll waves with straight filaments are given and again comparisons are shown. The connection between the asymptotic results and filament dynamics is discussed, and one of the previously unknown coefficients in the theory of filament dynamics is evaluated in terms of its asymptotic expansion. (c) 2002 American Institute of Physics.

Cookbook asymptotics for spiral and scroll waves in excitable media

NASA Astrophysics Data System (ADS)

Margerit, Daniel; Barkley, Dwight

2002-09-01

Algebraic formulas predicting the frequencies and shapes of waves in a reaction-diffusion model of excitable media are presented in the form of four recipes. The formulas themselves are based on a detailed asymptotic analysis (published elsewhere) of the model equations at leading order and first order in the asymptotic parameter. The importance of the first order contribution is stressed throughout, beginning with a discussion of the Fife limit, Fife scaling, and Fife regime. Recipes are given for spiral waves and detailed comparisons are presented between the asymptotic predictions and the solutions of the full reaction-diffusion equations. Recipes for twisted scroll waves with straight filaments are given and again comparisons are shown. The connection between the asymptotic results and filament dynamics is discussed, and one of the previously unknown coefficients in the theory of filament dynamics is evaluated in terms of its asymptotic expansion.

Vibration of initially stressed carbon nanotubes under magneto-thermal environment for nanoparticle delivery via higher-order nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Farajpour, M. R.; Shahidi, A. R.; Tabataba'i-Nasab, F.; Farajpour, A.

2018-06-01

In this paper, the forced vibration of a single-walled carbon nanotube (SWCNT) under a moving nanoparticle is investigated based on the higher-order nonlocal strain gradient theory. The SWCNT is subjected to thermo-mechanical stresses and an external longitudinal magnetic field. The influences of higher-order stress gradients in conjunction with the strain gradient nonlocality are taken into account. Using Hamilton's principle and Maxwell's equations, the higher-order differential equations of motion are derived. An analytical solution is obtained for the dynamic deflection of SWCNTs using the Galerkin method. Furthermore, the governing differential equation is solved numerically using the precise integration method. The results of the two solution procedures are compared and an excellent agreement is found between them. Finally, the influences of various scale parameters, the velocity of the moving nanoparticle, the initial axial stress, the temperature change and longitudinal magnetic field on the dynamic response of SWCNTs are investigated.

Phase transition of Boolean networks with partially nested canalizing functions

NASA Astrophysics Data System (ADS)

Jansen, Kayse; Matache, Mihaela Teodora

2013-07-01

We generate the critical condition for the phase transition of a Boolean network governed by partially nested canalizing functions for which a fraction of the inputs are canalizing, while the remaining non-canalizing inputs obey a complementary threshold Boolean function. Past studies have considered the stability of fully or partially nested canalizing functions paired with random choices of the complementary function. In some of those studies conflicting results were found with regard to the presence of chaotic behavior. Moreover, those studies focus mostly on ergodic networks in which initial states are assumed equally likely. We relax that assumption and find the critical condition for the sensitivity of the network under a non-ergodic scenario. We use the proposed mathematical model to determine parameter values for which phase transitions from order to chaos occur. We generate Derrida plots to show that the mathematical model matches the actual network dynamics. The phase transition diagrams indicate that both order and chaos can occur, and that certain parameters induce a larger range of values leading to order versus chaos. The edge-of-chaos curves are identified analytically and numerically. It is shown that the depth of canalization does not cause major dynamical changes once certain thresholds are reached; these thresholds are fairly small in comparison to the connectivity of the nodes.

Asymmetry identification in rigid rotating bodies—Theory and experiment

NASA Astrophysics Data System (ADS)

Bucher, Izhak; Shomer, Ofer

2013-12-01

Asymmetry and anisotropy are important parameters in rotating devices that can cause instability; indicate a manufacturing defect or a developing fault. The present paper discusses an identification method capable of detecting minute levels of asymmetry by exploiting the unique dynamics of parametric excitation caused by asymmetry and rotation. The detection relies on rigid body dynamics without resorting to nonlinear vibration analysis, and the natural dynamics of elastically supported systems is exploited in order to increase the sensitivity to asymmetry. It is possible to isolate asymmetry from other rotation-induced phenomena like unbalance. An asymmetry detection machine which was built in the laboratory demonstrates the method alongside theoretical analysis.

Structure and dynamics of complex liquid water: Molecular dynamics simulation

NASA Astrophysics Data System (ADS)

S, Indrajith V.; Natesan, Baskaran

2015-06-01

We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

Chaotic dynamics of large-scale double-diffusive convection in a porous medium

NASA Astrophysics Data System (ADS)

Kondo, Shutaro; Gotoda, Hiroshi; Miyano, Takaya; Tokuda, Isao T.

2018-02-01

We have studied chaotic dynamics of large-scale double-diffusive convection of a viscoelastic fluid in a porous medium from the viewpoint of dynamical systems theory. A fifth-order nonlinear dynamical system modeling the double-diffusive convection is theoretically obtained by incorporating the Darcy-Brinkman equation into transport equations through a physical dimensionless parameter representing porosity. We clearly show that the chaotic convective motion becomes much more complicated with increasing porosity. The degree of dynamic instability during chaotic convective motion is quantified by two important measures: the network entropy of the degree distribution in the horizontal visibility graph and the Kaplan-Yorke dimension in terms of Lyapunov exponents. We also present an interesting on-off intermittent phenomenon in the probability distribution of time intervals exhibiting nearly complete synchronization.

Magnetoelectric antiferromagnets as platforms for the manipulation of solitons

NASA Astrophysics Data System (ADS)

Zarzuela, Ricardo; Kim, Se Kwon; Tserkovnyak, Yaroslav

2018-01-01

We study the magnetic dynamics of magnetoelectric antiferromagnetic thin films, where an unconventional boundary ferromagnetism coexists with the bulk Néel phase below the Néel temperature. The spin exchange between the two order parameters yields an effective low-energy theory that is formally equivalent to that of a ferrimagnet. Dynamics of domain walls and skyrmions are analyzed within the collective-variable approach, from which we conclude that they behave as massive particles moving in a viscous medium subjected to a gyrotropic force. We find that the film thickness can be used as a control parameter for the motion of these solitons. In this regard, it is shown that an external magnetic field can drive the dynamics of domain walls, whose terminal velocity is tunable with the sample thickness. Furthermore, the classification of the skyrmion dynamics is sensitive to the spatial modulation of the sample thickness, which can be easily engineered with the present (thin-film) deposition techniques. Current-driven spin transfer can trigger drifting orbits of skyrmions, which can be utilized as racetracks for these magnetic textures.

Parameter identification and optimization of slide guide joint of CNC machine tools

NASA Astrophysics Data System (ADS)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Research on the Dynamic Hysteresis Loop Model of the Residence Times Difference (RTD)-Fluxgate

PubMed Central

Wang, Yanzhang; Wu, Shujun; Zhou, Zhijian; Cheng, Defu; Pang, Na; Wan, Yunxia

2013-01-01

Based on the core hysteresis features, the RTD-fluxgate core, while working, is repeatedly saturated with excitation field. When the fluxgate simulates, the accurate characteristic model of the core may provide a precise simulation result. As the shape of the ideal hysteresis loop model is fixed, it cannot accurately reflect the actual dynamic changing rules of the hysteresis loop. In order to improve the fluxgate simulation accuracy, a dynamic hysteresis loop model containing the parameters which have actual physical meanings is proposed based on the changing rule of the permeability parameter when the fluxgate is working. Compared with the ideal hysteresis loop model, this model has considered the dynamic features of the hysteresis loop, which makes the simulation results closer to the actual output. In addition, other hysteresis loops of different magnetic materials can be explained utilizing the described model for an example of amorphous magnetic material in this manuscript. The model has been validated by the output response comparison between experiment results and fitting results using the model. PMID:24002230

The study on dynamic properties of monolithic ball end mills with various slenderness

NASA Astrophysics Data System (ADS)

Wojciechowski, Szymon; Tabaszewski, Maciej; Krolczyk, Grzegorz M.; Maruda, Radosław W.

2017-10-01

The reliable determination of modal mass, damping and stiffness coefficient (modal parameters) for the particular machine-toolholder-tool system is essential for the accurate estimation of vibrations, stability and thus the machined surface finish formed during the milling process. Therefore, this paper focuses on the analysis of ball end mill's dynamical properties. The tools investigated during this study are monolithic ball end mills with different slenderness values, made of coated cemented carbide. These kinds of tools are very often applied during the precise milling of curvilinear surfaces. The research program included the impulse test carried out for the investigated tools clamped in the hydraulic toolholder. The obtained modal parameters were further applied in the developed tool's instantaneous deflection model, in order to estimate the tool's working part vibrations during precise milling. The application of the proposed dynamics model involved also the determination of instantaneous cutting forces on the basis of the mechanistic approach. The research revealed that ball end mill's slenderness can be considered as an important milling dynamics and machined surface quality indicator.

Geometrical shock dynamics, formation of singularities and topological bifurcations of converging shock fronts

NASA Astrophysics Data System (ADS)

Suramlishvili, Nugzar; Eggers, Jens; Fontelos, Marco

2014-11-01

We are concerned with singularities of the shock fronts of converging perturbed shock waves. Our considerations are based on Whitham's theory of geometrical shock dynamics. The recently developed method of local analysis is applied in order to determine generic singularities. In this case the solutions of partial differential equations describing the geometry of the shock fronts are presented as families of smooth maps with state variables and the set of control parameters dependent on Mach number, time and initial conditions. The space of control parameters of the singularities is analysed, the unfoldings describing the deformations of the canonical germs of shock front singularities are found and corresponding bifurcation diagrams are constructed. Research is supported by the Leverhulme Trust, Grant Number RPG-2012-568.

Studying flow close to an interface by total internal reflection fluorescence cross-correlation spectroscopy: Quantitative data analysis

NASA Astrophysics Data System (ADS)

Schmitz, R.; Yordanov, S.; Butt, H. J.; Koynov, K.; Dünweg, B.

2011-12-01

Total internal reflection fluorescence cross-correlation spectroscopy (TIR-FCCS) has recently [S. Yordanov , Optics ExpressOPEXFF1094-408710.1364/OE.17.021149 17, 21149 (2009)] been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence occurs only for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions provide only rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. First, Brownian dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Second, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.

Impact of fitting algorithms on errors of parameter estimates in dynamic contrast-enhanced MRI

NASA Astrophysics Data System (ADS)

Debus, C.; Floca, R.; Nörenberg, D.; Abdollahi, A.; Ingrisch, M.

2017-12-01

Parameter estimation in dynamic contrast-enhanced MRI (DCE MRI) is usually performed by non-linear least square (NLLS) fitting of a pharmacokinetic model to a measured concentration-time curve. The two-compartment exchange model (2CXM) describes the compartments ‘plasma’ and ‘interstitial volume’ and their exchange in terms of plasma flow and capillary permeability. The model function can be defined by either a system of two coupled differential equations or a closed-form analytical solution. The aim of this study was to compare these two representations in terms of accuracy, robustness and computation speed, depending on parameter combination and temporal sampling. The impact on parameter estimation errors was investigated by fitting the 2CXM to simulated concentration-time curves. Parameter combinations representing five tissue types were used, together with two arterial input functions, a measured and a theoretical population based one, to generate 4D concentration images at three different temporal resolutions. Images were fitted by NLLS techniques, where the sum of squared residuals was calculated by either numeric integration with the Runge-Kutta method or convolution. Furthermore two example cases, a prostate carcinoma and a glioblastoma multiforme patient, were analyzed in order to investigate the validity of our findings in real patient data. The convolution approach yields improved results in precision and robustness of determined parameters. Precision and stability are limited in curves with low blood flow. The model parameter ve shows great instability and little reliability in all cases. Decreased temporal resolution results in significant errors for the differential equation approach in several curve types. The convolution excelled in computational speed by three orders of magnitude. Uncertainties in parameter estimation at low temporal resolution cannot be compensated by usage of the differential equations. Fitting with the convolution approach is superior in computational time, with better stability and accuracy at the same time.

Photo-responsive surface topology in chiral nematic media

NASA Astrophysics Data System (ADS)

Liu, Danqing; Bastiaansen, Cees W. M.; Toonder, Jaap. M. J.; Broer, Dirk J.

2012-03-01

We report on the design and fabrication of 'smart surfaces' that exhibit dynamic changes in their surface topology in response to exposure to light. The principle is based on anisotropic geometric changes of a liquid crystal network upon a change of the molecular order parameter. The photomechanical property of the coating is induced by incorporating an azobenzene moiety into the liquid crystal network. The responsive surface topology consists of regions with two different types of molecular order: planar chiral-nematic areas and homeotropic. Under flood exposure with 365 nm light the surfaces deform from flat to one with a surface relief. The height of the relief structures is of the order of 1 um corresponding to strain difference of around 20%. Furthermore, we demonstrate surface reliefs can form either convex or concave structures upon exposure to UV light corresponding to the decrease or increase molecular order parameter, respectively, related to the isomeric state of the azobenzene crosslinker. The reversible deformation to the initial flat state occurs rapidly after removing the light source.

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

PubMed

Du, Bin; Zielinski, Daniel C; Kavvas, Erol S; Dräger, Andreas; Tan, Justin; Zhang, Zhen; Ruggiero, Kayla E; Arzumanyan, Garri A; Palsson, Bernhard O

2016-06-06

The mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question. In this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations. Overall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches.

Chaotic Dynamical Ferromagnetic Phase Induced by Nonequilibrium Quantum Fluctuations

NASA Astrophysics Data System (ADS)

Lerose, Alessio; Marino, Jamir; Žunkovič, Bojan; Gambassi, Andrea; Silva, Alessandro

2018-03-01

We investigate the robustness of a dynamical phase transition against quantum fluctuations by studying the impact of a ferromagnetic nearest-neighbor spin interaction in one spatial dimension on the nonequilibrium dynamical phase diagram of the fully connected quantum Ising model. In particular, we focus on the transient dynamics after a quantum quench and study the prethermal state via a combination of analytic time-dependent spin wave theory and numerical methods based on matrix product states. We find that, upon increasing the strength of the quantum fluctuations, the dynamical critical point fans out into a chaotic dynamical phase within which the asymptotic ordering is characterized by strong sensitivity to the parameters and initial conditions. We argue that such a phenomenon is general, as it arises from the impact of quantum fluctuations on the mean-field out of equilibrium dynamics of any system which exhibits a broken discrete symmetry.

Chaotic Dynamical Ferromagnetic Phase Induced by Nonequilibrium Quantum Fluctuations.

PubMed

Lerose, Alessio; Marino, Jamir; Žunkovič, Bojan; Gambassi, Andrea; Silva, Alessandro

2018-03-30

We investigate the robustness of a dynamical phase transition against quantum fluctuations by studying the impact of a ferromagnetic nearest-neighbor spin interaction in one spatial dimension on the nonequilibrium dynamical phase diagram of the fully connected quantum Ising model. In particular, we focus on the transient dynamics after a quantum quench and study the prethermal state via a combination of analytic time-dependent spin wave theory and numerical methods based on matrix product states. We find that, upon increasing the strength of the quantum fluctuations, the dynamical critical point fans out into a chaotic dynamical phase within which the asymptotic ordering is characterized by strong sensitivity to the parameters and initial conditions. We argue that such a phenomenon is general, as it arises from the impact of quantum fluctuations on the mean-field out of equilibrium dynamics of any system which exhibits a broken discrete symmetry.

Minimum of the order parameter fluctuations of seismicity before major earthquakes in Japan.

PubMed

Sarlis, Nicholas V; Skordas, Efthimios S; Varotsos, Panayiotis A; Nagao, Toshiyasu; Kamogawa, Masashi; Tanaka, Haruo; Uyeda, Seiya

2013-08-20

It has been shown that some dynamic features hidden in the time series of complex systems can be uncovered if we analyze them in a time domain called natural time χ. The order parameter of seismicity introduced in this time domain is the variance of χ weighted for normalized energy of each earthquake. Here, we analyze the Japan seismic catalog in natural time from January 1, 1984 to March 11, 2011, the day of the M9 Tohoku earthquake, by considering a sliding natural time window of fixed length comprised of the number of events that would occur in a few months. We find that the fluctuations of the order parameter of seismicity exhibit distinct minima a few months before all of the shallow earthquakes of magnitude 7.6 or larger that occurred during this 27-y period in the Japanese area. Among the minima, the minimum before the M9 Tohoku earthquake was the deepest. It appears that there are two kinds of minima, namely precursory and nonprecursory, to large earthquakes.

Resummed memory kernels in generalized system-bath master equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

2014-08-07

Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between themore » two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.« less

Variations in leaf growth parameters within the tree structure of adult Coffea arabica in relation to seasonal growth, water availability and air carbon dioxide concentration.

PubMed

Rakocevic, Miroslava; Matsunaga, Fabio Takeshi

2018-04-05

Dynamics in branch and leaf growth parameters, such as the phyllochron, duration of leaf expansion, leaf life span and bud mortality, determine tree architecture and canopy foliage distribution. We aimed to estimate leaf growth parameters in adult Arabica coffee plants based on leaf supporter axis order and position along the vertical profile, considering their modifications related to seasonal growth, air [CO2] and water availability. Growth and mortality of leaves and terminal buds of adult Arabica coffee trees were followed in two independent field experiments in two sub-tropical climate regions of Brazil, Londrina-PR (Cfa) and Jaguariúna-SP (Cwa). In the Cwa climate, coffee trees were grown under a FACE (free air CO2 enrichment) facility, where half of those had been irrigated. Plants were observed at a 15-30 d frequency for 1 year. Leaf growth parameters were estimated on five axes orders and expressed as functions of accumulated thermal time (°Cd per leaf). The phyllochron and duration of leaf expansion increased with axis order, from the seond to the fourth. The phyllochron and life span during the reduced vegetative seasonal growth were greater than during active growth. It took more thermal time for leaves from the first- to fourth-order axes to expand their blades under irrigation compared with rainfed conditions. The compensation effects of high [CO2] for low water availability were observed on leaf retention on the second and third axes orders, and duration of leaf expansion on the first- and fourth-order axes. The second-degree polynomials modelled leaf growth parameter distribution in the vertical tree profile, and linear regressions modelled the proportion of terminal bud mortality. Leaf growth parameters in coffee plants were determined by axis order. The duration of leaf expansion contributed to phyllochron determination. Leaf growth parameters varied according the position of the axis supporter along the vertical profile, suggesting an effect of axes age and micro-environmental light modulations.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

NASA Technical Reports Server (NTRS)

Juang, J. N.; Pappa, R. S.

1985-01-01

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Supercritical nonlinear parametric dynamics of Timoshenko microbeams

NASA Astrophysics Data System (ADS)

Farokhi, Hamed; Ghayesh, Mergen H.

2018-06-01

The nonlinear supercritical parametric dynamics of a Timoshenko microbeam subject to an axial harmonic excitation force is examined theoretically, by means of different numerical techniques, and employing a high-dimensional analysis. The time-variant axial load is assumed to consist of a mean value along with harmonic fluctuations. In terms of modelling, a continuous expression for the elastic potential energy of the system is developed based on the modified couple stress theory, taking into account small-size effects; the kinetic energy of the system is also modelled as a continuous function of the displacement field. Hamilton's principle is employed to balance the energies and to obtain the continuous model of the system. Employing the Galerkin scheme along with an assumed-mode technique, the energy terms are reduced, yielding a second-order reduced-order model with finite number of degrees of freedom. A transformation is carried out to convert the second-order reduced-order model into a double-dimensional first order one. A bifurcation analysis is performed for the system in the absence of the axial load fluctuations. Moreover, a mean value for the axial load is selected in the supercritical range, and the principal parametric resonant response, due to the time-variant component of the axial load, is obtained - as opposed to transversely excited systems, for parametrically excited system (such as our problem here), the nonlinear resonance occurs in the vicinity of twice any natural frequency of the linear system; this is accomplished via use of the pseudo-arclength continuation technique, a direct time integration, an eigenvalue analysis, and the Floquet theory for stability. The natural frequencies of the system prior to and beyond buckling are also determined. Moreover, the effect of different system parameters on the nonlinear supercritical parametric dynamics of the system is analysed, with special consideration to the effect of the length-scale parameter.

From boiling point to glass transition temperature: transport coefficients in molecular liquids follow three-parameter scaling.

PubMed

Schmidtke, B; Petzold, N; Kahlau, R; Hofmann, M; Rössler, E A

2012-10-01

The phenomenon of the glass transition is an unresolved problem in condensed matter physics. Its prominent feature, the super-Arrhenius temperature dependence of the transport coefficients, remains a challenge to be described over the full temperature range. For a series of molecular glass formers, we combined τ(T) collected from dielectric spectroscopy and dynamic light scattering covering a range 10(-12) s < τ(T) < 10(2) s. Describing the dynamics in terms of an activation energy E(T), we distinguish a high-temperature regime characterized by an Arrhenius law with a constant activation energy E(∞) and a low-temperature regime for which E(coop)(T) ≡ E(T)-E(∞) increases exponentially while cooling. A scaling is introduced, specifically E(coop)(T)/E(∞) [proportionality] exp[-λ(T/T(A)-1)], where λ is a fragility parameter and T(A) a reference temperature proportional to E(∞). In order to describe τ(T) still the attempt time τ(∞) has to be specified. Thus, a single interaction parameter E(∞) describing the high-temperature regime together with λ controls the temperature dependence of low-temperature cooperative dynamics.

Force-field parametrization and molecular dynamics simulations of Congo red

NASA Astrophysics Data System (ADS)

Król, Marcin; Borowski, Tomasz; Roterman, Irena; Piekarska, Barbara; Stopa, Barbara; Rybarska, Joanna; Konieczny, Leszek

2004-01-01

Congo red, a diazo dye widely used in medical diagnosis, is known to form supramolecular systems in solution. Such a supramolecular system may interact with various proteins. In order to examine the nature of such complexes empirical force field parameters for the Congo red molecule were developed. The parametrization of bonding terms closely followed the methodology used in the development of the charmm22 force field, except for the calculation of charges. Point charges were calculated from a fit to a quantum mechanically derived electrostatic potential using the CHELP-BOW method. Obtained parameters were tested in a series of molecular dynamics simulations of both a single molecule and a micelle composed of Congo red molecules. It is shown that newly developed parameters define a stable minimum on the hypersurface of the potential energy and crystal and ab initio geometries and rotational barriers are well reproduced. Furthermore, rotations around C-N bonds are similar to torsional vibrations observed in crystals of diphenyl-diazene, which confirms that the flexibility of the molecule is correct. Comparison of results obtained from micelles molecular dynamics simulations with experimental data shows that the thermal dependence of micelle creation is well reproduced.

Modeling of human operator dynamics in simple manual control utilizing time series analysis. [tracking (position)

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Osafo-Charles, F.; Oneill, W. D.; Gottlieb, G. L.

1982-01-01

Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

Competitive Modes for the Detection of Chaotic Parameter Regimes in the General Chaotic Bilinear System of Lorenz Type

NASA Astrophysics Data System (ADS)

Mallory, Kristina; van Gorder, Robert A.

We study chaotic behavior of solutions to the bilinear system of Lorenz type developed by Celikovsky and Vanecek [1994] through an application of competitive modes. This bilinear system of Lorenz type is one possible canonical form holding the Lorenz equation as a special case. Using a competitive modes analysis, which is a completely analytical method allowing one to identify parameter regimes for which chaos may occur, we are able to demonstrate a number of parameter regimes which admit a variety of distinct chaotic behaviors. Indeed, we are able to draw some interesting conclusions which relate the behavior of the mode frequencies arising from writing the state variables for the Celikovsky-Vanecek model as coupled oscillators, and the types of emergent chaotic behaviors observed. The competitive modes analysis is particularly useful if all but one of the model parameters are fixed, and the remaining free parameter is used to modify the chaos observed, in a manner analogous to a bifurcation parameter. Through a thorough application of the method, we are able to identify several parameter regimes which give new dynamics (such as specific forms of chaos) which were not observed or studied previously in the Celikovsky-Vanecek model. Therefore, the results demonstrate the advantage of the competitive modes approach for detecting new parameter regimes leading to chaos in third-order dynamical systems.

Effect of correlations on the polarizability of the one component plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carini, P.R.

Correlational effects on the dynamical polarizability ..cap alpha..(k,..omega..) of the one component plasma (OCP) are investigated in both the weak (..gamma.. < 1) and strong (..gamma.. < 1) coupling regions (..gamma.. is the plasma parameter, ..gamma.. = k/sup 3//4..pi..n where k/sup -1/ is the Debye length and n is the number density. In the weak coupling region a numerical solution is presented over a wide range of frequencies of the complete first order (in ..gamma..) correction to the dynamical polarizability which fully accounts for dynamical screening effects and is exact in the long wavelength and weak coupling limits (k ..-->..more » 0, ..gamma.. ..-->.. 0). This complete result is compared with a similar numerical solution for the dynamical polarizability obtained from the Golden-Kalman (GK) dynamical theory for strongly coupled plasmas. Contrary to previous results reported in the literature it was found that both theories predict the change in the dispersion of the long wavelength plasmons due to finite ..gamma.. effects to be that the slope of the plasmon dispersion curve decreases from its Bohm-Gross value as the plasma parameter increases from 0. In the strong coupling region two hydrodynamical model solutions of the GK dynamical theory for the polarizability are presented.« less

Impact of leakage delay on bifurcation in high-order fractional BAM neural networks.

PubMed

Huang, Chengdai; Cao, Jinde

2018-02-01

The effects of leakage delay on the dynamics of neural networks with integer-order have lately been received considerable attention. It has been confirmed that fractional neural networks more appropriately uncover the dynamical properties of neural networks, but the results of fractional neural networks with leakage delay are relatively few. This paper primarily concentrates on the issue of bifurcation for high-order fractional bidirectional associative memory(BAM) neural networks involving leakage delay. The first attempt is made to tackle the stability and bifurcation of high-order fractional BAM neural networks with time delay in leakage terms in this paper. The conditions for the appearance of bifurcation for the proposed systems with leakage delay are firstly established by adopting time delay as a bifurcation parameter. Then, the bifurcation criteria of such system without leakage delay are successfully acquired. Comparative analysis wondrously detects that the stability performance of the proposed high-order fractional neural networks is critically weakened by leakage delay, they cannot be overlooked. Numerical examples are ultimately exhibited to attest the efficiency of the theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Effects of soil properties on the stabilization process of cadmium in Cd alone and Cd-Pb contaminated soils].

PubMed

Wu, Man; Xu, Ming-Gang; Zhang, Wen-Ju; Wu, Hai-Wen

2012-07-01

In order to clarify the effects of soil properties on the stabilization process of the cadmium (Cd) added, 11 different soils were collected and incubated under a moisture content of 65%-70% at 25 degrees C. The changes of available Cd contents with incubation time (in 360 days) in Cd and Cd-Pb contaminated treatments were determined. The stabilization process was simulated using dynamic equations. The results showed that after 1.0 mg x kg(-1) Cd or 500 mg x kg(-1) Pb + 1.0 mg x kg(-1) Cd were added into the soil, the available Cd content decreased rapidly during the first 15 days, and then the decreasing rate slowed down, with an equilibrium content reached after 60 days' incubation. In Cd-Pb contaminated soils, the presence of Pb increased the content of available Cd. The stabilization process of Cd could be well described by the second-order equation and the first order exponential decay; meanwhile, dynamic parameters including equilibrium content and stabilization velocity were used to characterize the stabilization process of Cd. These two key dynamic parameters were significantly affected by soil properties. Correlation analysis and stepwise regression suggested that high pH and high cation exchange capacity (CEC) significantly retarded the availability of Cd. High pH had the paramount effect on the equilibrium content. The stabilization velocity of Cd was influenced by the soil texture. It took shorter time for Cd to get stabilized in sandy soil than in the clay.

A Generalized Framework for Reduced-Order Modeling of a Wind Turbine Wake

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, Nicholas; Viggiano, Bianca; Calaf, Marc

A reduced-order model for a wind turbine wake is sought from large eddy simulation data. Fluctuating velocity fields are combined in the correlation tensor to form the kernel of the proper orthogonal decomposition (POD). Proper orthogonal decomposition modes resulting from the decomposition represent the spatially coherent turbulence structures in the wind turbine wake; eigenvalues delineate the relative amount of turbulent kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces dynamic coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a seriesmore » of polynomial parameters that quantify mode interaction and the evolution of each POD mode coefficients. The resulting system of ordinary differential equations models the wind turbine wake composed only of the large-scale turbulent dynamics identified by the POD. Tikhonov regularization is used to recalibrate the dynamical system by adding additional constraints to the minimization seeking polynomial parameters, reducing error in the modeled mode coefficients. The wakeROM is periodically reinitialized with new initial conditions found by relating the incoming turbulent velocity to the POD mode coefficients through a series of open-loop transfer functions. The wakeROM reproduces mode coefficients to within 25.2%, quantified through the normalized root-mean-square error. A high-level view of the modeling approach is provided as a platform to discuss promising research directions, alternate processes that could benefit stability and efficiency, and desired extensions of the wakeROM.« less

A theoretical investigation of chirp insonification of ultrasound contrast agents.

PubMed

Barlow, Euan; Mulholland, Anthony J; Gachagan, Anthony; Nordon, Alison

2011-08-01

A theoretical investigation of second harmonic imaging of an Ultrasound Contrast Agent (UCA) under chirp insonification is considered. By solving the UCA's dynamical equation analytically, the effect that the chirp signal parameters and the UCA shell parameters have on the amplitude of the second harmonic frequency are examined. This allows optimal parameter values to be identified which maximise the UCA's second harmonic response. A relationship is found for the chirp parameters which ensures that a signal can be designed to resonate a UCA for a given set of shell parameters. It is also shown that the shell thickness, shell viscosity and shell elasticity parameter should be as small as realistically possible in order to maximise the second harmonic amplitude. Keller-Herring, Second Harmonic, Chirp, Ultrasound Contrast Agent. Copyright © 2011 Elsevier B.V. All rights reserved.

Sensitivity of grounding line dynamics to basal conditions

NASA Astrophysics Data System (ADS)

Gagliardini, O.; Brondex, J.; Chauveau, G.; Gillet-chaulet, F.; Durand, G.

2017-12-01

In the context of a warming climate, the dynamical contribution of Antarctica to future sea level rise is still tainted by high uncertainties. Among the processes entering these uncertainties is the link between basal hydrology, friction and grounding line dynamics. Recent works have shown how sensitive is the response of the grounding line retreat to the choice of the form of the friction law. Indeed, starting from the same initial state, grounding line retreat rates can range over almost two orders of magnitude depending on the friction law formulation.Here, we use a phenomenological law that depends on the water pressure and allows a continuous transition from a Weertman-type friction at low water pressure to a Coulomb-type friction at high water pressure. This friction law depends on two main parameters that control the Weertman and Coulomb regimes. The range of values for these two parameters is only weakly physically constrained, and it can be shown that, for a given basal shear stress, different couples of parameters can conduct to the same sliding velocity. In addition, we show that close to the grounding line where basal water pressure is high, determining these two parameters might conduct to an ill-posed inverse problem with no solution.The aim of this presentation is to discuss a methodology to guide the choice of the two friction parameters and explore the sensitivity of the grounding line dynamics to this initial choice. We present results obtained both on a synthetic configuration used by the Marine Ice Sheet Model Intercomparison exercise and for the Amundsen sea sector using the experiments proposed by InitMIP-Antarctica, the first exercise in a series of ISMIP6 ice-sheet model intercomparison activities.

Numerical Treatment of the Boltzmann Equation for Self-Propelled Particle Systems

NASA Astrophysics Data System (ADS)

Thüroff, Florian; Weber, Christoph A.; Frey, Erwin

2014-10-01

Kinetic theories constitute one of the most promising tools to decipher the characteristic spatiotemporal dynamics in systems of actively propelled particles. In this context, the Boltzmann equation plays a pivotal role, since it provides a natural translation between a particle-level description of the system's dynamics and the corresponding hydrodynamic fields. Yet, the intricate mathematical structure of the Boltzmann equation substantially limits the progress toward a full understanding of this equation by solely analytical means. Here, we propose a general framework to numerically solve the Boltzmann equation for self-propelled particle systems in two spatial dimensions and with arbitrary boundary conditions. We discuss potential applications of this numerical framework to active matter systems and use the algorithm to give a detailed analysis to a model system of self-propelled particles with polar interactions. In accordance with previous studies, we find that spatially homogeneous isotropic and broken-symmetry states populate two distinct regions in parameter space, which are separated by a narrow region of spatially inhomogeneous, density-segregated moving patterns. We find clear evidence that these three regions in parameter space are connected by first-order phase transitions and that the transition between the spatially homogeneous isotropic and polar ordered phases bears striking similarities to liquid-gas phase transitions in equilibrium systems. Within the density-segregated parameter regime, we find a novel stable limit-cycle solution of the Boltzmann equation, which consists of parallel lanes of polar clusters moving in opposite directions, so as to render the overall symmetry of the system's ordered state nematic, despite purely polar interactions on the level of single particles.

Currents and Flows in Distant Magnetospheres

NASA Technical Reports Server (NTRS)

Kivelson, Margaret Galland

2000-01-01

Space scientists have explored, described, and explained the terrestrial magnetosphere for four decades. Rarely do they point out that the planetary and solar wind parameters controlling the size, shape, and activity of Earth's magnetosphere map out only a small portion of the space of dimensionless parameters that govern magnetospheric properties. With the discovery of Ganymede's magnetosphere, the range of parameters relevant to magnetospheric studies has grown by orders of magnitude. Consider the extremes of Ganymede's and Jupiter's magnetospheres. Jupiter's magnetosphere forms within a plasma flowing at super-Alfvenic speed, whereas Ganymede's forms in a sub-Alfvenic flow. The scale sizes of these magnetospheres, characterized by distances to the magnetopause of order 7x10(exp 6) km and 5x10(exp 3) km, respectively, differ by three orders of magnitude, ranging from 100 to 0.1 times the scale of Earth's magnetosphere. The current systems that control the structure and dynamics of a magnetosphere depend on specific plasma and field properties. Magnetopause currents at Ganymede differ greatly from the forms familiar for Earth and Jupiter, principally because the Mach number of the ambient plasma flow greatly influences the shape of the magnetosphere. A magnetodisk current, present at Jupiter because of its rapid rotation, is absent at Earth and Ganymede. The ring current, extensively investigated at Earth, is probably unimportant at Ganymede because the dynamical variations of the external flow are slow. The ring current is subsumed within the magnetodisk current at Jupiter. This paper describes and contrasts aspects of these and other current systems for the three bodies.

Multiple scales and phases in discrete chains with application to folded proteins

NASA Astrophysics Data System (ADS)

Sinelnikova, A.; Niemi, A. J.; Nilsson, Johan; Ulybyshev, M.

2018-05-01

Chiral heteropolymers such as large globular proteins can simultaneously support multiple length scales. The interplay between the different scales brings about conformational diversity, determines the phase properties of the polymer chain, and governs the structure of the energy landscape. Most importantly, multiple scales produce complex dynamics that enable proteins to sustain live matter. However, at the moment there is incomplete understanding of how to identify and distinguish the various scales that determine the structure and dynamics of a complex protein. Here we address this impending problem. We develop a methodology with the potential to systematically identify different length scales, in the general case of a linear polymer chain. For this we introduce and analyze the properties of an order parameter that can both reveal the presence of different length scales and can also probe the phase structure. We first develop our concepts in the case of chiral homopolymers. We introduce a variant of Kadanoff's block-spin transformation to coarse grain piecewise linear chains, such as the C α backbone of a protein. We derive analytically, and then verify numerically, a number of properties that the order parameter can display, in the case of a chiral polymer chain. In particular, we propose that in the case of a chiral heteropolymer the order parameter can reveal traits of several different phases, contingent on the length scale at which it is scrutinized. We confirm that this is the case with crystallographic protein structures in the Protein Data Bank. Thus our results suggest relations between the scales, the phases, and the complexity of folding pathways.

Synchronization transmission of laser pattern signal within uncertain switched network

NASA Astrophysics Data System (ADS)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

Isobaric molecular dynamics version of the generalized replica exchange method (gREM): Liquid–vapor equilibrium

DOE PAGES

Malolepsza, Edyta; Secor, Maxim; Keyes, Tom

2015-09-23

A prescription for sampling isobaric generalized ensembles with molecular dynamics is presented and applied to the generalized replica exchange method (gREM), which was designed for simulating first-order phase transitions. The properties of the isobaric gREM ensemble are discussed and a study is presented of the liquid-vapor equilibrium of the guest molecules given for gas hydrate formation with the mW water model. As a result, phase diagrams, critical parameters, and a law of corresponding states are obtained.

Experiments and modelling of rate-dependent transition delay in a stochastic subcritical bifurcation

NASA Astrophysics Data System (ADS)

Bonciolini, Giacomo; Ebi, Dominik; Boujo, Edouard; Noiray, Nicolas

2018-03-01

Complex systems exhibiting critical transitions when one of their governing parameters varies are ubiquitous in nature and in engineering applications. Despite a vast literature focusing on this topic, there are few studies dealing with the effect of the rate of change of the bifurcation parameter on the tipping points. In this work, we consider a subcritical stochastic Hopf bifurcation under two scenarios: the bifurcation parameter is first changed in a quasi-steady manner and then, with a finite ramping rate. In the latter case, a rate-dependent bifurcation delay is observed and exemplified experimentally using a thermoacoustic instability in a combustion chamber. This delay increases with the rate of change. This leads to a state transition of larger amplitude compared with the one that would be experienced by the system with a quasi-steady change of the parameter. We also bring experimental evidence of a dynamic hysteresis caused by the bifurcation delay when the parameter is ramped back. A surrogate model is derived in order to predict the statistic of these delays and to scrutinize the underlying stochastic dynamics. Our study highlights the dramatic influence of a finite rate of change of bifurcation parameters upon tipping points, and it pinpoints the crucial need of considering this effect when investigating critical transitions.

Experiments and modelling of rate-dependent transition delay in a stochastic subcritical bifurcation

PubMed Central

Noiray, Nicolas

2018-01-01

Complex systems exhibiting critical transitions when one of their governing parameters varies are ubiquitous in nature and in engineering applications. Despite a vast literature focusing on this topic, there are few studies dealing with the effect of the rate of change of the bifurcation parameter on the tipping points. In this work, we consider a subcritical stochastic Hopf bifurcation under two scenarios: the bifurcation parameter is first changed in a quasi-steady manner and then, with a finite ramping rate. In the latter case, a rate-dependent bifurcation delay is observed and exemplified experimentally using a thermoacoustic instability in a combustion chamber. This delay increases with the rate of change. This leads to a state transition of larger amplitude compared with the one that would be experienced by the system with a quasi-steady change of the parameter. We also bring experimental evidence of a dynamic hysteresis caused by the bifurcation delay when the parameter is ramped back. A surrogate model is derived in order to predict the statistic of these delays and to scrutinize the underlying stochastic dynamics. Our study highlights the dramatic influence of a finite rate of change of bifurcation parameters upon tipping points, and it pinpoints the crucial need of considering this effect when investigating critical transitions. PMID:29657803

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

PubMed

Benoussaad, Mourad; Poignet, Philippe; Hayashibe, Mitsuhiro; Azevedo-Coste, Christine; Fattal, Charles; Guiraud, David

2013-06-01

We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

Critical space-time networks and geometric phase transitions from frustrated edge antiferromagnetism

NASA Astrophysics Data System (ADS)

Trugenberger, Carlo A.

2015-12-01

Recently I proposed a simple dynamical network model for discrete space-time that self-organizes as a graph with Hausdorff dimension dH=4 . The model has a geometric quantum phase transition with disorder parameter (dH-ds) , where ds is the spectral dimension of the dynamical graph. Self-organization in this network model is based on a competition between a ferromagnetic Ising model for vertices and an antiferromagnetic Ising model for edges. In this paper I solve a toy version of this model defined on a bipartite graph in the mean-field approximation. I show that the geometric phase transition corresponds exactly to the antiferromagnetic transition for edges, the dimensional disorder parameter of the former being mapped to the staggered magnetization order parameter of the latter. The model has a critical point with long-range correlations between edges, where a continuum random geometry can be defined, exactly as in Kazakov's famed 2D random lattice Ising model but now in any number of dimensions.

Theoretical analysis for the specific heat and thermal parameters of solid C60

NASA Astrophysics Data System (ADS)

Soto, J. R.; Calles, A.; Castro, J. J.

1997-08-01

We present the results of a theoretical analysis for the thermal parameters and phonon contribution to the specific heat in solid C60. The phonon contribution to the specific heat is calculated through the solution of the corresponding dynamical matrix, for different points in the Brillouin zone, and the construccion of the partial and generalized phonon density of states. The force constants are obtained from a first principle calculation, using a SCF Hartree-Fock wave function from the Gaussian 92 program. The thermal parameters reported are the effective temperatures and vibrational amplitudes as a function of temperature. Using this model we present a parametization scheme in order to reproduce the general behaviour of the experimental specific heat for these materials.

Case study: Optimizing fault model input parameters using bio-inspired algorithms

NASA Astrophysics Data System (ADS)

Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

2017-07-01

We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

Coalescence of two spinning black holes: An effective one-body approach

NASA Astrophysics Data System (ADS)

Damour, Thibault

2001-12-01

We generalize to the case of spinning black holes a recently introduced ``effective one-body'' approach to the general relativistic dynamics of binary systems. We show how to approximately map the conservative part of the third post-Newtonian (3PN) dynamics of two spinning black holes of masses m1, m2 and spins S1, S2 onto the dynamics of a non-spinning particle of mass μ≡m1m2/(m1+m2) in a certain effective metric geffμν(xλM,ν,a) which can be viewed either as a spin deformation [with the deformation parameter a≡Seff/M] of the recently constructed 3PN effective metric geffμν(xλM,ν), or as a ν deformation [with the comparable-mass deformation parameter ν≡m1m2/(m1+m2)2] of a Kerr metric of mass M≡m1+m2 and (effective) spin Seff≡[1+3m2/(4m1)]S1+[1+3m1/(4m2)]S2. The combination of the effective one-body approach, and of a Padé definition of the crucial effective radial functions, is shown to define a dynamics with much improved post-Newtonian convergence properties, even for black hole separations of the order of 6 GM/c2. The complete (conservative) phase-space evolution equations of binary spinning black hole systems are written down and their exact and approximate first integrals are discussed. This leads to the approximate existence of a two-parameter family of ``spherical orbits'' (with constant radius), and of a corresponding one-parameter family of ``last stable spherical orbits'' (LSSO). These orbits are of special interest for forthcoming LIGO-VIRGO-GEO gravitational wave observations. The binding energy and total angular momentum of LSSO's are studied in some detail. It is argued that for most (but not all) of the parameter space of two spinning holes the approximate (leading-order) effective one-body approach introduced here gives a reliable analytical tool for describing the dynamics of the last orbits before coalescence. This tool predicts, in a quantitative way, how certain spin orientations increase the binding energy of the LSSO. This leads to a detection bias, in LIGO-VIRGO-GEO observations, favoring spinning black hole systems, and makes it urgent to complete the conservative effective one-body dynamics given here by adding (resummed) radiation reaction effects, and by constructing gravitational waveform templates that include spin effects. Finally, our approach predicts that the spin of the final hole formed by the coalescence of two arbitrarily spinning holes never approaches extremality.

Comparison of gating dynamics of different IP3R channels with immune algorithm searching for channel parameter distributions

NASA Astrophysics Data System (ADS)

Cai, Xiuhong; Li, Xiang; Qi, Hong; Wei, Fang; Chen, Jianyong; Shuai, Jianwei

2016-10-01

The gating properties of the inositol 1, 4, 5-trisphosphate (IP3) receptor (IP3R) are determined by the binding and unbinding capability of Ca2+ ions and IP3 messengers. With the patch clamp experiments, the stationary properties have been discussed for Xenopus oocyte type-1 IP3R (Oo-IP3R1), type-3 IP3R (Oo-IP3R3) and Spodoptera frugiperda IP3R (Sf-IP3R). In this paper, in order to provide insights about the relation between the observed gating characteristics and the gating parameters in different IP3Rs, we apply the immune algorithm to fit the parameters of a modified DeYoung-Keizer model. By comparing the fitting parameter distributions of three IP3Rs, we suggest that the three types of IP3Rs have the similar open sensitivity in responding to IP3. The Oo-IP3R3 channel is easy to open in responding to low Ca2+ concentration, while Sf-IP3R channel is easily inhibited in responding to high Ca2+ concentration. We also show that the IP3 binding rate is not a sensitive parameter for stationary gating dynamics for three IP3Rs, but the inhibitory Ca2+ binding/unbinding rates are sensitive parameters for gating dynamics for both Oo-IP3R1 and Oo-IP3R3 channels. Such differences may be important in generating the spatially and temporally complex Ca2+ oscillations in cells. Our study also demonstrates that the immune algorithm can be applied for model parameter searching in biological systems.

A general multiscroll Lorenz system family and its realization via digital signal processors.

PubMed

Yu, Simin; Lü, Jinhu; Tang, Wallace K S; Chen, Guanrong

2006-09-01

This paper proposes a general multiscroll Lorenz system family by introducing a novel parameterized nth-order polynomial transformation. Some basic dynamical behaviors of this general multiscroll Lorenz system family are then investigated, including bifurcations, maximum Lyapunov exponents, and parameters regions. Furthermore, the general multiscroll Lorenz attractors are physically verified by using digital signal processors.

Observation of the Kibble-Zurek Mechanism in Microscopic Acoustic Crackling Noises (Open Access Publisher’s Version)

DTIC Science & Technology

2016-02-15

the definite continuous S-W transition, we have also recognized events with an abrupt change in the order parameter that is characteristic of a first... Cosmological experiments in superfluid helium? Nature 317, 505–508 (1985). 9. del Campo, A. & Zurek, W. H. Universality of phase transition dynamics

On the integrability of some generalized Lotka-Volterra systems

NASA Astrophysics Data System (ADS)

Bier, M.; Hijmans, J.; Bountis, T. C.

1983-08-01

Several integrable systems of nonlinear ordinary differential equations of the Lotka-Volterra type are identified by the Painleveproperty and completely integrated. One such integrable case of N first order ode's is found, with N-2 free parameters and N arbitrary. The concept of integrability of a general dynamical system, not necessarily derived from a Hamiltonian, is also discussed.

An asymptotic solution to a passive biped walker model

NASA Astrophysics Data System (ADS)

Yudaev, Sergey A.; Rachinskii, Dmitrii; Sobolev, Vladimir A.

2017-02-01

We consider a simple model of a passive dynamic biped robot walker with point feet and legs without knee. The model is a switched system, which includes an inverted double pendulum. Robot’s gait and its stability depend on parameters such as the slope of the ramp, the length of robot’s legs, and the mass distribution along the legs. We present an asymptotic solution of the model. The first correction to the zero order approximation is shown to agree with the numerical solution for a limited parameter range.

From qualitative data to quantitative models: analysis of the phage shock protein stress response in Escherichia coli

PubMed Central

2011-01-01

Background Bacteria have evolved a rich set of mechanisms for sensing and adapting to adverse conditions in their environment. These are crucial for their survival, which requires them to react to extracellular stresses such as heat shock, ethanol treatment or phage infection. Here we focus on studying the phage shock protein (Psp) stress response in Escherichia coli induced by a phage infection or other damage to the bacterial membrane. This system has not yet been theoretically modelled or analysed in silico. Results We develop a model of the Psp response system, and illustrate how such models can be constructed and analyzed in light of available sparse and qualitative information in order to generate novel biological hypotheses about their dynamical behaviour. We analyze this model using tools from Petri-net theory and study its dynamical range that is consistent with currently available knowledge by conditioning model parameters on the available data in an approximate Bayesian computation (ABC) framework. Within this ABC approach we analyze stochastic and deterministic dynamics. This analysis allows us to identify different types of behaviour and these mechanistic insights can in turn be used to design new, more detailed and time-resolved experiments. Conclusions We have developed the first mechanistic model of the Psp response in E. coli. This model allows us to predict the possible qualitative stochastic and deterministic dynamic behaviours of key molecular players in the stress response. Our inferential approach can be applied to stress response and signalling systems more generally: in the ABC framework we can condition mathematical models on qualitative data in order to delimit e.g. parameter ranges or the qualitative system dynamics in light of available end-point or qualitative information. PMID:21569396

Non-local Second Order Closure Scheme for Boundary Layer Turbulence and Convection

NASA Astrophysics Data System (ADS)

Meyer, Bettina; Schneider, Tapio

2017-04-01

There has been scientific consensus that the uncertainty in the cloud feedback remains the largest source of uncertainty in the prediction of climate parameters like climate sensitivity. To narrow down this uncertainty, not only a better physical understanding of cloud and boundary layer processes is required, but specifically the representation of boundary layer processes in models has to be improved. General climate models use separate parameterisation schemes to model the different boundary layer processes like small-scale turbulence, shallow and deep convection. Small scale turbulence is usually modelled by local diffusive parameterisation schemes, which truncate the hierarchy of moment equations at first order and use second-order equations only to estimate closure parameters. In contrast, the representation of convection requires higher order statistical moments to capture their more complex structure, such as narrow updrafts in a quasi-steady environment. Truncations of moment equations at second order may lead to more accurate parameterizations. At the same time, they offer an opportunity to take spatially correlated structures (e.g., plumes) into account, which are known to be important for convective dynamics. In this project, we study the potential and limits of local and non-local second order closure schemes. A truncation of the momentum equations at second order represents the same dynamics as a quasi-linear version of the equations of motion. We study the three-dimensional quasi-linear dynamics in dry and moist convection by implementing it in a LES model (PyCLES) and compare it to a fully non-linear LES. In the quasi-linear LES, interactions among turbulent eddies are suppressed but nonlinear eddy—mean flow interactions are retained, as they are in the second order closure. In physical terms, suppressing eddy—eddy interactions amounts to suppressing, e.g., interactions among convective plumes, while retaining interactions between plumes and the environment (e.g., entrainment and detrainment). In a second part, we employ the possibility to include non-local statistical correlations in a second-order closure scheme. Such non-local correlations allow to directly incorporate the spatially coherent structures that occur in the form of convective updrafts penetrating the boundary layer. This allows us to extend the work that has been done using assumed-PDF schemes for parameterising boundary layer turbulence and shallow convection in a non-local sense.

Dynamics of Change and Change in Dynamics

PubMed Central

Boker, Steven M.; Staples, Angela D.; Hu, Yueqin

2017-01-01

A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self–regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within–person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models’ feasibility within a chosen experimental design. PMID:29046764

On-line training of recurrent neural networks with continuous topology adaptation.

PubMed

Obradovic, D

1996-01-01

This paper presents an online procedure for training dynamic neural networks with input-output recurrences whose topology is continuously adjusted to the complexity of the target system dynamics. This is accomplished by changing the number of the elements of the network hidden layer whenever the existing topology cannot capture the dynamics presented by the new data. The training mechanism is based on the suitably altered extended Kalman filter (EKF) algorithm which is simultaneously used for the network parameter adjustment and for its state estimation. The network consists of a single hidden layer with Gaussian radial basis functions (GRBF), and a linear output layer. The choice of the GRBF is induced by the requirements of the online learning. The latter implies the network architecture which permits only local influence of the new data point in order not to forget the previously learned dynamics. The continuous topology adaptation is implemented in our algorithm to avoid memory and computational problems of using a regular grid of GRBF'S which covers the network input space. Furthermore, we show that the resulting parameter increase can be handled "smoothly" without interfering with the already acquired information. If the target system dynamics are changing over time, we show that a suitable forgetting factor can be used to "unlearn" the no longer-relevant dynamics. The quality of the recurrent network training algorithm is demonstrated on the identification of nonlinear dynamic systems.

Short-Time Dynamics of the Random n-Vector Model

NASA Astrophysics Data System (ADS)

Chen, Yuan; Li, Zhi-Bing; Fang, Hai; He, Shun-Shan; Situ, Shu-Ping

2001-11-01

Short-time critical behavior of the random n-vector model is studied by the theoretic renormalization-group approach. Asymptotic scaling laws are studied in a frame of the expansion in ɛ=4-d for n≠1 and {√ɛ} for n=1 respectively. In d<4, the initial slip exponents θ‧ for the order parameter and θ for the response function are calculated up to the second order in ɛ=4-d for n≠1 and {√ɛ} for n=1 at the random fixed point respectively. Our results show that the random impurities exert a strong influence on the short-time dynamics for d<4 and n

Dissecting cross-impact on stock markets: an empirical analysis

NASA Astrophysics Data System (ADS)

Benzaquen, M.; Mastromatteo, I.; Eisler, Z.; Bouchaud, J.-P.

2017-02-01

The vast majority of market impact studies assess each product individually, and the interactions between the different order flows are disregarded. This strong approximation may lead to an underestimation of trading costs and possible contagion effects. Transactions in fact mediate a significant part of the correlation between different instruments. In turn, liquidity shares the sectorial structure of market correlations, which can be encoded as a set of eigenvalues and eigenvectors. We introduce a multivariate linear propagator model that successfully describes such a structure, and accounts for a significant fraction of the covariance of stock returns. We dissect the various dynamical mechanisms that contribute to the joint dynamics of assets. We also define two simplified models with substantially less parameters in order to reduce overfitting, and show that they have superior out-of-sample performance.

Study of the fractional order proportional integral controller for the permanent magnet synchronous motor based on the differential evolution algorithm.

PubMed

Zheng, Weijia; Pi, Youguo

2016-07-01

A tuning method of the fractional order proportional integral speed controller for a permanent magnet synchronous motor is proposed in this paper. Taking the combination of the integral of time and absolute error and the phase margin as the optimization index, the robustness specification as the constraint condition, the differential evolution algorithm is applied to search the optimal controller parameters. The dynamic response performance and robustness of the obtained optimal controller are verified by motor speed-tracking experiments on the motor speed control platform. Experimental results show that the proposed tuning method can enable the obtained control system to achieve both the optimal dynamic response performance and the robustness to gain variations. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

NASA Astrophysics Data System (ADS)

Xavier, Marcelo A.; Trimboli, M. Scott

2015-07-01

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models.

Computational methods and traveling wave solutions for the fourth-order nonlinear Ablowitz-Kaup-Newell-Segur water wave dynamical equation via two methods and its applications

NASA Astrophysics Data System (ADS)

Ali, Asghar; Seadawy, Aly R.; Lu, Dianchen

2018-05-01

The aim of this article is to construct some new traveling wave solutions and investigate localized structures for fourth-order nonlinear Ablowitz-Kaup-Newell-Segur (AKNS) water wave dynamical equation. The simple equation method (SEM) and the modified simple equation method (MSEM) are applied in this paper to construct the analytical traveling wave solutions of AKNS equation. The different waves solutions are derived by assigning special values to the parameters. The obtained results have their importance in the field of physics and other areas of applied sciences. All the solutions are also graphically represented. The constructed results are often helpful for studying several new localized structures and the waves interaction in the high-dimensional models.

On the modeling and nonlinear dynamics of autonomous Silva-Young type chaotic oscillators with flat power spectrum

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kengne, Jacques; Kenmogne, Fabien

2014-12-15

The nonlinear dynamics of fourth-order Silva-Young type chaotic oscillators with flat power spectrum recently introduced by Tamaseviciute and collaborators is considered. In this type of oscillators, a pair of semiconductor diodes in an anti-parallel connection acts as the nonlinear component necessary for generating chaotic oscillations. Based on the Shockley diode equation and an appropriate selection of the state variables, a smooth mathematical model (involving hyperbolic sine and cosine functions) is derived for a better description of both the regular and chaotic dynamics of the system. The complex behavior of the oscillator is characterized in terms of its parameters by usingmore » time series, bifurcation diagrams, Lyapunov exponents' plots, Poincaré sections, and frequency spectra. It is shown that the onset of chaos is achieved via the classical period-doubling and symmetry restoring crisis scenarios. Some PSPICE simulations of the nonlinear dynamics of the oscillator are presented in order to confirm the ability of the proposed mathematical model to accurately describe/predict both the regular and chaotic behaviors of the oscillator.« less

Microgravity Foam Structure and Rheology

NASA Technical Reports Server (NTRS)

Durian, Douglas J.

1997-01-01

To exploit rheological and multiple-light scattering techniques, and ultimately microgravity conditions, in order to quantify and elucidate the unusual elastic character of foams in terms of their underlying microscopic structure and dynamics. Special interest is in determining how this elastic character vanishes, i.e. how the foam melts into a simple viscous liquid, as a function of both increasing liquid content and shear strain rate. The unusual elastic character of foams will be quantified macroscopically by measurement of the shear stress as a function of static shear strain, shear strain rate, and time following a step strain; such data will be analyzed in terms of a yield stress, a static shear modulus, and dynamical time scales. Microscopic information about bubble packing and rearrangement dynamics, from which these macroscopic non-Newtonian properties presumably arise, will be obtained non-invasively by novel multiple-light scattering diagnostics such as Diffusing-Wave Spectroscopy (DWS). Quantitative trends with materials parameters, such as average bubble size, and liquid content, will be sought in order to elucidate the fundamental connection between the microscopic structure and dynamics and the macroscopic rheology.

Molecular dynamics study of the isotropic-nematic quench.

PubMed

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.

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri

2014-01-01

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

A dynamical model on deposit and loan of banking: A bifurcation analysis

NASA Astrophysics Data System (ADS)

Sumarti, Novriana; Hasmi, Abrari Noor

2015-09-01

A dynamical model, which is one of sophisticated techniques using mathematical equations, can determine the observed state, for example bank profits, for all future times based on the current state. It will also show small changes in the state of the system create either small or big changes in the future depending on the model. In this research we develop a dynamical system of the form: d/D d t =f (D ,L ,rD,rL,r ), d/L d t =g (D ,L ,rD,rL,r ), Here D and rD are the volume of deposit and its rate, L and rL are the volume of loan and its rate, and r is the interbank market rate. There are parameters required in this model which give connections between two variables or between two derivative functions. In this paper we simulate the model for several parameters values. We do bifurcation analysis on the dynamics of the system in order to identify the appropriate parameters that control the stability behaviour of the system. The result shows that the system will have a limit cycle for small value of interest rate of loan, so the deposit and loan volumes are fluctuating and oscillating extremely. If the interest rate of loan is too high, the loan volume will be decreasing and vanish and the system will converge to its carrying capacity.

Forecasting financial asset processes: stochastic dynamics via learning neural networks.

PubMed

Giebel, S; Rainer, M

2010-01-01

Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

Robustness of a cellular automata model for the HIV infection

NASA Astrophysics Data System (ADS)

Figueirêdo, P. H.; Coutinho, S.; Zorzenon dos Santos, R. M.

2008-11-01

An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R.M. Zorzenon dos Santos, S. Coutinho, Phys. Rev. Lett. 87 (2001) 168102]. The analysis focused on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model’s stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were approximately the same when lattice symmetry varied, but there was a significant variation when dimensionality changed from two to three. The dynamics of the three-dimensional model was also shown to be insensitive to variations of the deterministic parameters related to cell resistance to the infection, and the necessary time lag to mount the specific immune response to HIV variants. The robustness of the model demonstrated in this work reinforce that its basic hypothesis are consistent with the three-stage dynamic of the HIV infection observed in patients.

Highly dynamic animal contact network and implications on disease transmission

PubMed Central

Chen, Shi; White, Brad J.; Sanderson, Michael W.; Amrine, David E.; Ilany, Amiyaal; Lanzas, Cristina

2014-01-01

Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2). PMID:24667241

The dynamical crossover phenomenon in bulk water, confined water and protein hydration water.

PubMed

Mallamace, Francesco; Corsaro, Carmelo; Baglioni, Piero; Fratini, Emiliano; Chen, Sow-Hsin

2012-02-15

We discuss a phenomenon regarding water that was until recently a subject of scientific controversy, i.e. the dynamical crossover from fragile-to-strong glass-forming material, for both bulk and protein hydration water. Such a crossover is characterized by a temperature T(L) at which significant dynamical changes occur, such as violation of the Stokes-Einstein relation and changes of behaviour of homologous transport parameters such as the density relaxation time and the viscosity. In this respect we will consider carefully the dynamic properties of water-protein systems. More precisely, we will study proteins and their hydration water as far as bulk and confined water. In order to clarify the controversy we will discuss in a comparative way many previous and new experimental data that have emerged using different techniques and molecular dynamic simulation (MD). We point out the reasons for the different dynamical findings from the use of different experimental techniques.

Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

PubMed

Yu, Theodore; Cauwenberghs, Gert

2009-01-01

We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

Temperature dependence of fast carbonyl backbone dynamics in chicken villin headpiece subdomain

PubMed Central

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

Dynamics of a quantum phase transition in the Bose-Hubbard model: Kibble-Zurek mechanism and beyond

NASA Astrophysics Data System (ADS)

Shimizu, Keita; Kuno, Yoshihito; Hirano, Takahiro; Ichinose, Ikuo

2018-03-01

In this paper, we study the dynamics of the Bose-Hubbard model by using time-dependent Gutzwiller methods. In particular, we vary the parameters in the Hamiltonian as a function of time, and investigate the temporal behavior of the system from the Mott insulator to the superfluid (SF) crossing a second-order phase transition. We first solve a time-dependent Schrödinger equation for the experimental setup recently done by Braun et al. [Proc. Natl. Acad. Sci. USA 112, 3641 (2015)] and show that the numerical and experimental results are in fairly good agreement. However, these results disagree with the Kibble-Zurek scaling. From our numerical study, we reveal a possible source of the discrepancy. Next, we calculate the critical exponents of the correlation length and vortex density in addition to the SF order parameter for a Kibble-Zurek protocol. We show that beside the "freeze" time t ̂, there exists another important time, teq, at which an oscillating behavior of the SF amplitude starts. From calculations of the exponents of the correlation length and vortex density with respect to a quench time τQ, we obtain a physical picture of a coarsening process. Finally, we study how the system evolves after the quench. We give a global picture of dynamics of the Bose-Hubbard model.

Modulational instability and dynamics of implicit higher-order rogue wave solutions for the Kundu equation

NASA Astrophysics Data System (ADS)

Wen, Xiao-Yong; Zhang, Guoqiang

2018-01-01

Under investigation in this paper is the Kundu equation, which may be used to describe the propagation process of ultrashort optical pulses in nonlinear optics. The modulational instability of the plane-wave for the possible reason of the formation of the rogue wave (RW) is studied for the system. Based on our proposed generalized perturbation (n,N - n)-fold Darboux transformation (DT), some new higher-order implicit RW solutions in terms of determinants are obtained by means of the generalized perturbation (1,N - 1)-fold DT, when choosing different special parameters, these results will reduce to the RW solutions of the Kaup-Newell (KN) equation, Chen-Lee-Liu (CLL) equation and Gerjikov-Ivanov (GI) equation, respectively. The relevant wave structures are shown graphically, which display abundant interesting wave structures. The dynamical behaviors and propagation stability of the first-order and second-order RW solutions are discussed by using numerical simulations, the higher-order nonlinear terms for the Kundu equation have an impact on the propagation instability of the RW. The method can also be extended to find the higher-order RW or rational solutions of other integrable nonlinear equations.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Dynamic analysis of a pumped-storage hydropower plant with random power load

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Xu, Beibei; Patelli, Edoardo; Tolo, Silvia

2018-02-01

This paper analyzes the dynamic response of a pumped-storage hydropower plant in generating mode. Considering the elastic water column effects in the penstock, a linearized reduced order dynamic model of the pumped-storage hydropower plant is used in this paper. As the power load is always random, a set of random generator electric power output is introduced to research the dynamic behaviors of the pumped-storage hydropower plant. Then, the influences of the PI gains on the dynamic characteristics of the pumped-storage hydropower plant with the random power load are analyzed. In addition, the effects of initial power load and PI parameters on the stability of the pumped-storage hydropower plant are studied in depth. All of the above results will provide theoretical guidance for the study and analysis of the pumped-storage hydropower plant.

Pressure Dynamic Characteristics of Pressure Controlled Ventilation System of a Lung Simulator

PubMed Central

Shi, Yan; Ren, Shuai; Cai, Maolin; Xu, Weiqing; Deng, Qiyou

2014-01-01

Mechanical ventilation is an important life support treatment of critically ill patients, and air pressure dynamics of human lung affect ventilation treatment effects. In this paper, in order to obtain the influences of seven key parameters of mechanical ventilation system on the pressure dynamics of human lung, firstly, mechanical ventilation system was considered as a pure pneumatic system, and then its mathematical model was set up. Furthermore, to verify the mathematical model, a prototype mechanical ventilation system of a lung simulator was proposed for experimental study. Last, simulation and experimental studies on the air flow dynamic of the mechanical ventilation system were done, and then the pressure dynamic characteristics of the mechanical system were obtained. The study can be referred to in the pulmonary diagnostics, treatment, and design of various medical devices or diagnostic systems. PMID:25197318

Single neuron modeling and data assimilation in BNST neurons

NASA Astrophysics Data System (ADS)

Farsian, Reza

Neurons, although tiny in size, are vastly complicated systems, which are responsible for the most basic yet essential functions of any nervous system. Even the most simple models of single neurons are usually high dimensional, nonlinear, and contain many parameters and states which are unobservable in a typical neurophysiological experiment. One of the most fundamental problems in experimental neurophysiology is the estimation of these parameters and states, since knowing their values is essential in identification, model construction, and forward prediction of biological neurons. Common methods of parameter and state estimation do not perform well for neural models due to their high dimensionality and nonlinearity. In this dissertation, two alternative approaches for parameters and state estimation of biological neurons have been demonstrated: dynamical parameter estimation (DPE) and a Markov Chain Monte Carlo (MCMC) method. The first method uses elements of chaos control and synchronization theory for parameter and state estimation. MCMC is a statistical approach which uses a path integral formulation to evaluate a mean and an error bound for these unobserved parameters and states. These methods have been applied to biological system of neurons in Bed Nucleus of Stria Termialis neurons (BNST) of rats. State and parameters of neurons in both systems were estimated, and their value were used for recreating a realistic model and predicting the behavior of the neurons successfully. The knowledge of biological parameters can ultimately provide a better understanding of the internal dynamics of a neuron in order to build robust models of neuron networks.

Chaos and crises in a model for cooperative hunting: a symbolic dynamics approach.

PubMed

Duarte, Jorge; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2009-12-01

In this work we investigate the population dynamics of cooperative hunting extending the McCann and Yodzis model for a three-species food chain system with a predator, a prey, and a resource species. The new model considers that a given fraction sigma of predators cooperates in prey's hunting, while the rest of the population 1-sigma hunts without cooperation. We use the theory of symbolic dynamics to study the topological entropy and the parameter space ordering of the kneading sequences associated with one-dimensional maps that reproduce significant aspects of the dynamics of the species under several degrees of cooperative hunting. Our model also allows us to investigate the so-called deterministic extinction via chaotic crisis and transient chaos in the framework of cooperative hunting. The symbolic sequences allow us to identify a critical boundary in the parameter spaces (K,C(0)) and (K,sigma) which separates two scenarios: (i) all-species coexistence and (ii) predator's extinction via chaotic crisis. We show that the crisis value of the carrying capacity K(c) decreases at increasing sigma, indicating that predator's populations with high degree of cooperative hunting are more sensitive to the chaotic crises. We also show that the control method of Dhamala and Lai [Phys. Rev. E 59, 1646 (1999)] can sustain the chaotic behavior after the crisis for systems with cooperative hunting. We finally analyze and quantify the inner structure of the target regions obtained with this control method for wider parameter values beyond the crisis, showing a power law dependence of the extinction transients on such critical parameters.

Light scattering from liquid crystal director fluctuations in steady magnetic fields up to 25 tesla.

PubMed

Challa, Pavan K; Curtiss, O; Williams, J C; Twieg, R; Toth, J; McGill, S; Jákli, A; Gleeson, J T; Sprunt, S N

2012-07-01

We report on homodyne dynamic light scattering measurements of orientational fluctuation modes in both calamitic and bent-core nematic liquid crystals, carried out in the new split-helix resistive magnet at the National High Magnetic Field Laboratory. The relaxation rate and inverse scattered intensity of director fluctuations exhibit a linear dependence on field-squared up to 25 tesla, which is consistent with strictly lowest order coupling of the tensor order parameter Q to field (Q(αβ)B(α)B(β)) in the nematic free energy. However, we also observe evidence of field dependence of certain nematic material parameters, an effect which may be expected from the mean field scaling of these quantities with the magnitude of Q and the predicted variation of Q with field.

Initialization of a fractional order identification algorithm applied for Lithium-ion battery modeling in time domain

NASA Astrophysics Data System (ADS)

Nasser Eddine, Achraf; Huard, Benoît; Gabano, Jean-Denis; Poinot, Thierry

2018-06-01

This paper deals with the initialization of a non linear identification algorithm used to accurately estimate the physical parameters of Lithium-ion battery. A Randles electric equivalent circuit is used to describe the internal impedance of the battery. The diffusion phenomenon related to this modeling is presented using a fractional order method. The battery model is thus reformulated into a transfer function which can be identified through Levenberg-Marquardt algorithm to ensure the algorithm's convergence to the physical parameters. An initialization method is proposed in this paper by taking into account previously acquired information about the static and dynamic system behavior. The method is validated using noisy voltage response, while precision of the final identification results is evaluated using Monte-Carlo method.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian B; Purba, Victor; Jafarpour, Saber

Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loopmore » for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.« less

Membrane fluidity profiles as deduced by saturation-recovery EPR measurements of spin-lattice relaxation times of spin labels

NASA Astrophysics Data System (ADS)

Mainali, Laxman; Feix, Jimmy B.; Hyde, James S.; Subczynski, Witold K.

2011-10-01

There are no easily obtainable EPR spectral parameters for lipid spin labels that describe profiles of membrane fluidity. The order parameter, which is most often used as a measure of membrane fluidity, describes the amplitude of wobbling motion of alkyl chains relative to the membrane normal and does not contain explicitly time or velocity. Thus, this parameter can be considered as nondynamic. The spin-lattice relaxation rate ( T1-1) obtained from saturation-recovery EPR measurements of lipid spin labels in deoxygenated samples depends primarily on the rotational correlation time of the nitroxide moiety within the lipid bilayer. Thus, T1-1 can be used as a convenient quantitative measure of membrane fluidity that reflects local membrane dynamics. T1-1 profiles obtained for 1-palmitoyl-2-( n-doxylstearoyl)phosphatidylcholine ( n-PC) spin labels in dimyristoylphosphatidylcholine (DMPC) membranes with and without 50 mol% cholesterol are presented in parallel with profiles of the rotational diffusion coefficient, R⊥, obtained from simulation of EPR spectra using Freed's model. These profiles are compared with profiles of the order parameter obtained directly from EPR spectra and with profiles of the order parameter obtained from simulation of EPR spectra. It is shown that T1-1 and R⊥ profiles reveal changes in membrane fluidity that depend on the motional properties of the lipid alkyl chain. We find that cholesterol has a rigidifying effect only to the depth occupied by the rigid steroid ring structure and a fluidizing effect at deeper locations. These effects cannot be differentiated by profiles of the order parameter. All profiles in this study were obtained at X-band (9.5 GHz).

NMR studies of the backbone flexibility and structure of human growth hormone: a comparison of high and low pH conformations.

PubMed

Kasimova, Marina R; Kristensen, Søren M; Howe, Peter W A; Christensen, Thorkild; Matthiesen, Finn; Petersen, Jørgen; Sørensen, Hans H; Led, Jens J

2002-05-03

(15)N NMR relaxation parameters and amide (1)H/(2)H-exchange rates have been used to characterize the structural flexibility of human growth hormone (rhGH) at neutral and acidic pH. Our results show that the rigidity of the molecule is strongly affected by the solution conditions. At pH 7.0 the backbone dynamics parameters of rhGH are uniform along the polypeptide chain and their values are similar to those of other folded proteins. In contrast, at pH 2.7 the overall backbone flexibility increases substantially compared to neutral pH and the average order parameter approaches the lower limit expected for a folded protein. However, a significant variation of the backbone dynamics through the molecule indicates that under acidic conditions the mobility of the residues becomes more dependent on their location within the secondary structure units. In particular, the order parameters of certain loop regions decrease dramatically and become comparable to those found in unfolded proteins. Furthermore, the HN-exchange rates at low pH reveal that the residues most protected from exchange are clustered at one end of the helical bundle, forming a stable nucleus. We suggest that this nucleus maintains the overall fold of the protein under destabilizing conditions. We therefore conclude that the acid state of rhGH consists of a structurally conserved, but dynamically more flexible helical core surrounded by an aura of highly mobile, unstructured loops. However, in spite of its prominent flexibility the acid state of rhGH cannot be considered a "molten globule" state because of its high stability. It appears from our work that under certain conditions, a protein can tolerate a considerable increase in flexibility of its backbone, along with an increased penetration of water into its core, while still maintaining a stable folded conformation.

Dynamics of modulated beams in spectral domain

DOE PAGES

Yampolsky, Nikolai A.

2017-07-16

General formalism for describing dynamics of modulated beams along linear beamlines is developed. We describe modulated beams with spectral distribution function which represents Fourier transform of the conventional beam distribution function in the 6-dimensional phase space. The introduced spectral distribution function is localized in some region of the spectral domain for nearly monochromatic modulations. It can be characterized with a small number of typical parameters such as the lowest order moments of the spectral distribution. We study evolution of the modulated beams in linear beamlines and find that characteristic spectral parameters transform linearly. The developed approach significantly simplifies analysis ofmore » various schemes proposed for seeding X-ray free electron lasers. We use this approach to study several recently proposed schemes and find the bandwidth of the output bunching in each case.« less

Recruitment dynamics in adaptive social networks

NASA Astrophysics Data System (ADS)

Shkarayev, Maxim; Shaw, Leah; Schwartz, Ira

2011-03-01

We model recruitment in social networks in the presence of birth and death processes. The recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. The recruiting nodes may adapt their connections in order to improve recruitment capabilities, thus changing the network structure. We develop a mean-field theory describing the system dynamics. Using mean-field theory we characterize the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment dynamics, as well as on network topology. The theoretical predictions are confirmed by the direct simulations of the full system.

Nonequilibrium optical control of dynamical states in superconducting nanowire circuits.

PubMed

Madan, Ivan; Buh, Jože; Baranov, Vladimir V; Kabanov, Viktor V; Mrzel, Aleš; Mihailovic, Dragan

2018-03-01

Optical control of states exhibiting macroscopic phase coherence in condensed matter systems opens intriguing possibilities for materials and device engineering, including optically controlled qubits and photoinduced superconductivity. Metastable states, which in bulk materials are often associated with the formation of topological defects, are of more practical interest. Scaling to nanosize leads to reduced dimensionality, fundamentally changing the system's properties. In one-dimensional superconducting nanowires, vortices that are present in three-dimensional systems are replaced by fluctuating topological defects of the phase. These drastically change the dynamical behavior of the superconductor and introduce dynamical periodic long-range ordered states when the current is driven through the wire. We report the control and manipulation of transitions between different dynamically stable states in superconducting δ 3 -MoN nanowire circuits by ultrashort laser pulses. Not only can the transitions between different dynamically stable states be precisely controlled by light, but we also discovered new photoinduced hidden states that cannot be reached under near-equilibrium conditions, created while laser photoexcited quasi-particles are outside the equilibrium condition. The observed switching behavior can be understood in terms of dynamical stabilization of various spatiotemporal periodic trajectories of the order parameter in the superconductor nanowire, providing means for the optical control of the superconducting phase with subpicosecond control of timing.

Nonequilibrium optical control of dynamical states in superconducting nanowire circuits

PubMed Central

Madan, Ivan; Baranov, Vladimir V.

2018-01-01

Optical control of states exhibiting macroscopic phase coherence in condensed matter systems opens intriguing possibilities for materials and device engineering, including optically controlled qubits and photoinduced superconductivity. Metastable states, which in bulk materials are often associated with the formation of topological defects, are of more practical interest. Scaling to nanosize leads to reduced dimensionality, fundamentally changing the system’s properties. In one-dimensional superconducting nanowires, vortices that are present in three-dimensional systems are replaced by fluctuating topological defects of the phase. These drastically change the dynamical behavior of the superconductor and introduce dynamical periodic long-range ordered states when the current is driven through the wire. We report the control and manipulation of transitions between different dynamically stable states in superconducting δ3-MoN nanowire circuits by ultrashort laser pulses. Not only can the transitions between different dynamically stable states be precisely controlled by light, but we also discovered new photoinduced hidden states that cannot be reached under near-equilibrium conditions, created while laser photoexcited quasi-particles are outside the equilibrium condition. The observed switching behavior can be understood in terms of dynamical stabilization of various spatiotemporal periodic trajectories of the order parameter in the superconductor nanowire, providing means for the optical control of the superconducting phase with subpicosecond control of timing. PMID:29670935

Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

PubMed

Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

2018-01-01

A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

Observation of dynamical vortices after quenches in a system with topology

NASA Astrophysics Data System (ADS)

Fläschner, N.; Vogel, D.; Tarnowski, M.; Rem, B. S.; Lühmann, D.-S.; Heyl, M.; Budich, J. C.; Mathey, L.; Sengstock, K.; Weitenberg, C.

2018-03-01

Topological phases constitute an exotic form of matter characterized by non-local properties rather than local order parameters1. The paradigmatic Haldane model on a hexagonal lattice features such topological phases distinguished by an integer topological invariant known as the first Chern number2. Recently, the identification of non-equilibrium signatures of topology in the dynamics of such systems has attracted particular attention3-6. Here, we experimentally study the dynamical evolution of the wavefunction using time- and momentum-resolved full state tomography for spin-polarized fermionic atoms in driven optical lattices7. We observe the appearance, movement and annihilation of dynamical vortices in momentum space after sudden quenches close to the topological phase transition. These dynamical vortices can be interpreted as dynamical Fisher zeros of the Loschmidt amplitude8, which signal a so-called dynamical phase transition9,10. Our results pave the way to a deeper understanding of the connection between topological phases and non-equilibrium dynamics.

Baryonic matter perturbations in decaying vacuum cosmology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marttens, R.F. vom; Zimdahl, W.; Hipólito-Ricaldi, W.S., E-mail: rodrigovonmarttens@gmail.com, E-mail: wiliam.ricaldi@ufes.br, E-mail: winfried.zimdahl@pq.cnpq.br

2014-08-01

We consider the perturbation dynamics for the cosmic baryon fluid and determine the corresponding power spectrum for a Λ(t)CDM model in which a cosmological term decays into dark matter linearly with the Hubble rate. The model is tested by a joint analysis of data from supernovae of type Ia (SNIa) (Constitution and Union 2.1), baryonic acoustic oscillations (BAO), the position of the first peak of the anisotropy spectrum of the cosmic microwave background (CMB) and large-scale-structure (LSS) data (SDSS DR7). While the homogeneous and isotropic background dynamics is only marginally influenced by the baryons, there are modifications on the perturbativemore » level if a separately conserved baryon fluid is included. Considering the present baryon fraction as a free parameter, we reproduce the observed abundance of the order of 5% independently of the dark-matter abundance which is of the order of 32% for this model. Generally, the concordance between background and perturbation dynamics is improved if baryons are explicitly taken into account.« less

In Situ XRD Studies of the Process Dynamics During Annealing in Cold-Rolled Copper

NASA Astrophysics Data System (ADS)

Dey, Santu; Gayathri, N.; Bhattacharya, M.; Mukherjee, P.

2016-12-01

The dynamics of the release of stored energy during annealing along two different crystallographic planes, i.e., {111} and {220}, in deformed copper have been investigated using in situ X-ray diffraction measurements at 458 K and 473 K (185 °C and 200 °C). The study has been carried out on 50 and 80 pct cold-rolled Cu sheets. The microstructures of the rolled samples have been characterized using optical microscopy and electron backscattered diffraction measurements. The microstructural parameters were evaluated from the X-ray diffractogram using the Scherrer equation and the modified Rietveld method. The stored energy along different planes was determined using the modified Stibitz formula from the X-ray peak broadening, and the bulk stored energy was evaluated using differential scanning calorimetry. The process dynamics of recovery and recrystallization as observed through the release of stored energy have been modeled as the second-order and first-order processes, respectively.

Extraordinary variability and sharp transitions in a maximally frustrated dynamic network

NASA Astrophysics Data System (ADS)

Liu, Wenjia; Schmittmann, Beate; Zia, R. K. P.

2013-03-01

Most previous studies of complex networks have focused on single, static networks. However, in the real world, networks are dynamic and interconnected. Inspired by the presence of extroverts and introverts in the general population, we investigate a highly simplified model of a social network, involving two types of nodes: one preferring the highest degree possible, and one preferring no connections whatsoever. There are only two control parameters in the model: the number of ``introvert'' and ``extrovert'' nodes, NI and NE. Our key findings are as follows: As a function of NI and NE, the system exhibits a highly unusual transition, displaying extraordinary fluctuations (as in 2nd order transitions) and discontinuous jumps (characteristic of 1st order transitions). Most remarkably, the system can be described by an Ising-like Hamiltonian with long-range multi-spin interactions and some of its properties can be obtained analytically. This is in stark contrast with other dynamic network models which rely almost exclusively on simulations. NSF-DMR-1005417/1244666 and and ICTAS Virginia Tech

Molecular dynamics simulations of a DMSO/water mixture using the AMBER force field.

PubMed

Stachura, Slawomir S; Malajczuk, Chris J; Mancera, Ricardo L

2018-06-25

Due to its protective properties of biological samples at low temperatures and under desiccation, dimethyl sulfoxide (DMSO) in aqueous solutions has been studied widely by many experimental approaches and molecular dynamics (MD) simulations. In the case of the latter, AMBER is among the most commonly used force fields for simulations of biomolecular systems; however, the parameters for DMSO published by Fox and Kollman in 1998 have only been tested for pure liquid DMSO. We have conducted an MD simulation study of DMSO in a water mixture and computed several structural and dynamical properties such as of the mean density, self-diffusion coefficient, hydrogen bonding and DMSO and water ordering. The AMBER force field of DMSO is seen to reproduce well most of the experimental properties of DMSO in water, with the mixture displaying strong and specific water ordering, as observed in experiments and multiple other MD simulations with other non-polarizable force fields. Graphical abstract Hydration structure within hydrogen-bonding distance around a DMSOmolecule.

Quantifying the biophysical characteristics of Plasmodium-falciparum-parasitized red blood cells in microcirculation

PubMed Central

Fedosov, D. A.; Caswell, B.; Suresh, S.; Karniadakis, G. E.

2011-01-01

The pathogenicity of Plasmodium falciparum (Pf) malaria results from the stiffening of red blood cells (RBCs) and its ability to adhere to endothelial cells (cytoadherence). The dynamics of Pf-parasitized RBCs is studied by three-dimensional mesoscopic simulations of flow in cylindrical capillaries in order to predict the flow resistance enhancement at different parasitemia levels. In addition, the adhesive dynamics of Pf-RBCs is explored for various parameters revealing several types of cell dynamics such as firm adhesion, very slow slipping along the wall, and intermittent flipping. The parasite inside the RBC is modeled explicitly in order to capture phenomena such as “hindered tumbling” motion of the RBC and the sudden transition from firm RBC cytoadherence to flipping on the endothelial surface. These predictions are in quantitative agreement with recent experimental observations, and thus the three-dimensional modeling method presented here provides new capabilities for guiding and interpreting future in vitro and in vivo studies of malaria. PMID:21173269

Fractional viscoelasticity of soft elastomers and auxetic foams

NASA Astrophysics Data System (ADS)

Solheim, Hannah; Stanisauskis, Eugenia; Miles, Paul; Oates, William

2018-03-01

Dielectric elastomers are commonly implemented in adaptive structures due to their unique capabilities for real time control of a structure's shape, stiffness, and damping. These active polymers are often used in applications where actuator control or dynamic tunability are important, making an accurate understanding of the viscoelastic behavior critical. This challenge is complicated as these elastomers often operate over a broad range of deformation rates. Whereas research has demonstrated success in applying a nonlinear viscoelastic constitutive model to characterize the behavior of Very High Bond (VHB) 4910, robust predictions of the viscoelastic response over the entire range of time scales is still a significant challenge. An alternative formulation for viscoelastic modeling using fractional order calculus has shown significant improvement in predictive capabilities. While fractional calculus has been explored theoretically in the field of linear viscoelasticity, limited experimental validation and statistical evaluation of the underlying phenomena have been considered. In the present study, predictions across several orders of magnitude in deformation rates are validated against data using a single set of model parameters. Moreover, we illustrate the fractional order is material dependent by running complementary experiments and parameter estimation on the elastomer VHB 4949 as well as an auxetic foam. All results are statistically validated using Bayesian uncertainty methods to obtain posterior densities for the fractional order as well as the hyperelastic parameters.

Fractional Order Spatiotemporal Chaos with Delay in Spatial Nonlinear Coupling

NASA Astrophysics Data System (ADS)

Zhang, Yingqian; Wang, Xingyuan; Liu, Liyan; Liu, Jia

We investigate the spatiotemporal dynamics with fractional order differential logistic map with delay under nonlinear chaotic maps for spatial coupling connections. Here, the coupling methods between lattices are the nonlinear chaotic map coupling of lattices. The fractional order differential logistic map with delay breaks the limits of the range of parameter μ ∈ [3.75, 4] in the classical logistic map for chaotic states. The Kolmogorov-Sinai entropy density and universality, and bifurcation diagrams are employed to investigate the chaotic behaviors of the proposed model in this paper. The proposed model can also be applied for cryptography, which is verified in a color image encryption scheme in this paper.

Optimal fixed-finite-dimensional compensator for Burgers' equation with unbounded input/output operators

NASA Technical Reports Server (NTRS)

Burns, John A.; Marrekchi, Hamadi

1993-01-01

The problem of using reduced order dynamic compensators to control a class of nonlinear parabolic distributed parameter systems was considered. Concentration was on a system with unbounded input and output operators governed by Burgers' equation. A linearized model was used to compute low-order-finite-dimensional control laws by minimizing certain energy functionals. Then these laws were applied to the nonlinear model. Standard approaches to this problem employ model/controller reduction techniques in conjunction with linear quadratic Gaussian (LQG) theory. The approach used is based on the finite dimensional Bernstein/Hyland optimal projection theory which yields a fixed-finite-order controller.

Computer program documentation for the dynamic analysis of a noncontacting mechanical face seal

NASA Technical Reports Server (NTRS)

Auer, B. M.; Etsion, I.

1980-01-01

A computer program is presented which achieves a numerical solution for the equations of motion of a noncontacting mechanical face seal. The flexibly-mounted primary seal ring motion is expressed by a set of second order differential equations for three degrees of freedom. These equations are reduced to a set of first order equations and the GEAR software package is used to solve the set of first order equations. Program input includes seal design parameters and seal operating conditions. Output from the program includes velocities and displacements of the seal ring about the axis of an inertial reference system. One example problem is described.

Exact closed-form solutions of a fully nonlinear asymptotic two-fluid model

NASA Astrophysics Data System (ADS)

Cheviakov, Alexei F.

2018-05-01

A fully nonlinear model of Choi and Camassa (1999) describing one-dimensional incompressible dynamics of two non-mixing fluids in a horizontal channel, under a shallow water approximation, is considered. An equivalence transformation is presented, leading to a special dimensionless form of the system, involving a single dimensionless constant physical parameter, as opposed to five parameters present in the original model. A first-order dimensionless ordinary differential equation describing traveling wave solutions is analyzed. Several multi-parameter families of physically meaningful exact closed-form solutions of the two-fluid model are derived, corresponding to periodic, solitary, and kink-type bidirectional traveling waves; specific examples are given, and properties of the exact solutions are analyzed.

Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research.

PubMed

Wu, Hulin; Xue, Hongqi; Kumar, Arun

2012-06-01

Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches. © 2012, The International Biometric Society.

Guidelines for reducing dynamic loads in two-bladed teetering-hub downwind wind turbines

NASA Astrophysics Data System (ADS)

Wright, A. D.; Bir, G. S.; Butterfield, C. D.

1995-06-01

A major goal of the federal Wind Energy Program is the rapid development and validation of structural models to determine loads and response for a wide variety of different wind turbine configurations operating under extreme conditions. Such codes are crucial to the successful design of future advanced wind turbines. In previous papers the authors described steps they took to develop a model of a two-bladed teetering-hub downwind wind turbine using ADAMS (Automatic Dynamic Analysis of Mechanical Systems), as well as comparison of model predictions to test data. In this paper they show the use of this analytical model to study the influence of various turbine parameters on predicted system loads. They concentrate their study on turbine response in the frequency range of six to ten times the rotor rotational frequency (6P to 10P). Their goal is to identify the most important parameters which influence the response of this type of machine in this frequency range and give turbine designers some general design guidelines for designing two-bladed teetering-hub machines to be less susceptible to vibration. They study the effects of such parameters as blade edgewise and flapwise stiffness, tower top stiffness, blade tip-brake mass, low-speed shaft stiffness, nacelle mass momenta of inertia, and rotor speed. They show which parameters can be varied in order to make the turbine less responsive to such atmospheric inputs as wind shear and tower shadow. They then give designers a set of design guidelines in order to show how these machines can be designed to be less responsive to these inputs.

Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

NASA Astrophysics Data System (ADS)

Perdigão, R. A. P.

2017-12-01

Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

[Indicators of dynamic work tolerability in healthy subjects].

PubMed

Capodaglio, E M; Capodaglio, P

1997-01-01

This paper reports a study on the dynamics of tolerability in performing dynamic cycling in healthy subjects. Data on individually tolerable levels (power x duration) was obtained from 9 subjects by means of three submaximal tests on an ergometric bicycle lasting < or = 40 minutes, with constant load (50%, 65% and 80% of maximum VO2 reached during a previous test of increasing difficulty within the limits of the symptoms). During performance of the test we monitored heart rate and subjective perception of fatigue (Borg's 10-point scale). We then defined the individual functions of "isoperception", which expressed the individual trend of the product "power x duration" at identical subjective perception score. On the basis of the metabolic parameters monitored, the individual isoperceptive functions at a "moderate" level of fatigue (3 on the Borg scale) were defined as "tolerability) threshold" for prolonged dynamic cycling. The product "power x duration" defined by the isoperceptive curves at a "moderate" level of fatigue does in fact reflect the individual aerobic capacity that can be sustained for prolonged dynamic activity (under 60 minutes). In order to validate the hypothesis of tolerability of the functions identified, three further short tests were performed (duration < or = 8.5 minutes) on an ergometric bicycle, with measurement of ventilatory and metabolic parameters.

A fractional-order accumulative regularization filter for force reconstruction

NASA Astrophysics Data System (ADS)

Wensong, Jiang; Zhongyu, Wang; Jing, Lv

2018-02-01

The ill-posed inverse problem of the force reconstruction comes from the influence of noise to measured responses and results in an inaccurate or non-unique solution. To overcome this ill-posedness, in this paper, the transfer function of the reconstruction model is redefined by a Fractional order Accumulative Regularization Filter (FARF). First, the measured responses with noise are refined by a fractional-order accumulation filter based on a dynamic data refresh strategy. Second, a transfer function, generated by the filtering results of the measured responses, is manipulated by an iterative Tikhonov regularization with a serious of iterative Landweber filter factors. Third, the regularization parameter is optimized by the Generalized Cross-Validation (GCV) to improve the ill-posedness of the force reconstruction model. A Dynamic Force Measurement System (DFMS) for the force reconstruction is designed to illustrate the application advantages of our suggested FARF method. The experimental result shows that the FARF method with r = 0.1 and α = 20, has a PRE of 0.36% and an RE of 2.45%, is superior to other cases of the FARF method and the traditional regularization methods when it comes to the dynamic force reconstruction.

Simulating Bilayers of Nonionic Surfactants with the GROMOS-Compatible 2016H66 Force Field.

PubMed

Senac, Caroline; Urbach, Wladimir; Kurtisovski, Erol; Hünenberger, Philippe H; Horta, Bruno A C; Taulier, Nicolas; Fuchs, Patrick F J

2017-10-03

Polyoxyethylene glycol alkyl ether amphiphiles (C i E j ) are important nonionic surfactants, often used for biophysical and membrane protein studies. In this work, we extensively test the GROMOS-compatible 2016H66 force field in molecular dynamics simulations involving the lamellar phase of a series of C i E j surfactants, namely C 12 E 2 , C 12 E 3 , C 12 E 4 , C 12 E 5 , and C 14 E 4 . The simulations reproduce qualitatively well the monitored structural properties and their experimental trends along the surfactant series, although some discrepancies remain, in particular in terms of the area per surfactant, the equilibrium phase of C 12 E 5 , and the order parameters of C 12 E 3 , C 12 E 4 , and C 12 E 5 . The polar head of the C i E j surfactants is highly hydrated, almost like a single polyethyleneoxide (PEO) molecule at full hydration, resulting in very compact conformations. Within the bilayer, all C i E j surfactants flip-flop spontaneously within tens of nanoseconds. Water-permeation is facilitated, and the bending rigidity is 4 to 5 times lower than that of typical phospholipid bilayers. In line with another recent theoretical study, the simulations show that the lamellar phase of C i E j contains large hydrophilic pores. These pores should be abundant in order to reproduce the comparatively low NMR order parameters. We show that their contour length is directly correlated to the order parameters, and we estimate that they should occupy approximately 7-10% of the total membrane area. Due to their highly dynamic nature (rapid flip-flops, high water permeability, observed pore formation), C i E j surfactant bilayers are found to represent surprisingly challenging systems in terms of modeling. Given this difficulty, the results presented here show that the 2016H66 parameters, optimized independently considering pure-liquid as well as polar and nonpolar solvation properties of small organic molecules, represent a good starting point for simulating these systems.

Error estimation for CFD aeroheating prediction under rarefied flow condition

NASA Astrophysics Data System (ADS)

Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian

2014-12-01

Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.

On a Model of a Nonlinear Feedback System for River Flow Prediction

NASA Astrophysics Data System (ADS)

Ozaki, T.

1980-02-01

A nonlinear system with feedback is proposed as a dynamic model for the hydrological system, whose input is the rainfall and whose output is the discharge of river flow. Parameters and orders of the model are estimated using Akaike's information criterion. Its application to the prediction of daily discharges of Kanna River and Bird Creek is discussed.

Parameters of the Future Food Service World of Work. A Report.

ERIC Educational Resources Information Center

Powers, Thomas F.; Swinton, John R.

The document is a study of the food service industry intended for use as a reference by food service teachers and curriculum planners. The purpose of the study is to map the economic and technological territory of the industry, to identify the dynamics shaping the industry today, and to consider questions crucial to an orderly consideration of the…

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1987-01-01

The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.