Membrane Capacitive Memory Alters Spiking in Neurons Described by the Fractional-Order Hodgkin-Huxley Model

PubMed Central

Weinberg, Seth H.

2015-01-01

Excitable cells and cell membranes are often modeled by the simple yet elegant parallel resistor-capacitor circuit. However, studies have shown that the passive properties of membranes may be more appropriately modeled with a non-ideal capacitor, in which the current-voltage relationship is given by a fractional-order derivative. Fractional-order membrane potential dynamics introduce capacitive memory effects, i.e., dynamics are influenced by a weighted sum of the membrane potential prior history. However, it is not clear to what extent fractional-order dynamics may alter the properties of active excitable cells. In this study, we investigate the spiking properties of the neuronal membrane patch, nerve axon, and neural networks described by the fractional-order Hodgkin-Huxley neuron model. We find that in the membrane patch model, as fractional-order decreases, i.e., a greater influence of membrane potential memory, peak sodium and potassium currents are altered, and spike frequency and amplitude are generally reduced. In the nerve axon, the velocity of spike propagation increases as fractional-order decreases, while in a neural network, electrical activity is more likely to cease for smaller fractional-order. Importantly, we demonstrate that the modulation of the peak ionic currents that occurs for reduced fractional-order alone fails to reproduce many of the key alterations in spiking properties, suggesting that membrane capacitive memory and fractional-order membrane potential dynamics are important and necessary to reproduce neuronal electrical activity. PMID:25970534

Finite element dynamic analysis of soft tissues using state-space model.

PubMed

Iorga, Lucian N; Shan, Baoxiang; Pelegri, Assimina A

2009-04-01

A finite element (FE) model is employed to investigate the dynamic response of soft tissues under external excitations, particularly corresponding to the case of harmonic motion imaging. A solid 3D mixed 'u-p' element S8P0 is implemented to capture the near-incompressibility inherent in soft tissues. Two important aspects in structural modelling of these tissues are studied; these are the influence of viscous damping on the dynamic response and, following FE-modelling, a developed state-space formulation that valuates the efficiency of several order reduction methods. It is illustrated that the order of the mathematical model can be significantly reduced, while preserving the accuracy of the observed system dynamics. Thus, the reduced-order state-space representation of soft tissues for general dynamic analysis significantly reduces the computational cost and provides a unitary framework for the 'forward' simulation and 'inverse' estimation of soft tissues. Moreover, the results suggest that damping in soft-tissue is significant, effectively cancelling the contribution of all but the first few vibration modes.

Analysis of propulsion system dynamics in the validation of a high-order state space model of the UH-60

NASA Technical Reports Server (NTRS)

Kim, Frederick D.

1992-01-01

Frequency responses generated from a high-order linear model of the UH-60 Black Hawk have shown that the propulsion system influences significantly the vertical and yaw dynamics of the aircraft at frequencies important to high-bandwidth control law designs. The inclusion of the propulsion system comprises the latest step in the development of a high-order linear model of the UH-60 that models additionally the dynamics of the fuselage, rotor, and inflow. A complete validation study of the linear model is presented in the frequency domain for both on-axis and off-axis coupled responses in the hoverflight condition, and on-axis responses for forward speeds of 80 and 120 knots.

Reduced-Order Aerothermoelastic Analysis of Hypersonic Vehicle Structures

NASA Astrophysics Data System (ADS)

Falkiewicz, Nathan J.

Design and simulation of hypersonic vehicles require consideration of a variety of disciplines due to the highly coupled nature of the flight regime. In order to capture all of the potential effects on vehicle dynamics, one must consider the aerodynamics, aerodynamic heating, heat transfer, and structural dynamics as well as the interactions between these disciplines. The problem is further complicated by the large computational expense involved in capturing all of these effects and their interactions in a full-order sense. While high-fidelity modeling techniques exist for each of these disciplines, the use of such techniques is computationally infeasible in a vehicle design and control system simulation setting for such a highly coupled problem. Early in the design stage, many iterations of analyses may need to be carried out as the vehicle design matures, thus requiring quick analysis turnaround time. Additionally, the number of states used in the analyses must be small enough to allow for efficient control simulation and design. As a result, alternatives to full-order models must be considered. This dissertation presents a fully coupled, reduced-order aerothermoelastic framework for the modeling and analysis of hypersonic vehicle structures. The reduced-order transient thermal solution is a modal solution based on the proper orthogonal decomposition. The reduced-order structural dynamic model is based on projection of the equations of motion onto a Ritz modal subspace that is identified a priori. The reduced-order models are assembled into a time-domain aerothermoelastic simulation framework which uses a partitioned time-marching scheme to account for the disparate time scales of the associated physics. The aerothermoelastic modeling framework is outlined and the formulations associated with the unsteady aerodynamics, aerodynamic heating, transient thermal, and structural dynamics are outlined. Results demonstrate the accuracy of the reduced-order transient thermal and structural dynamic models under variation in boundary conditions and flight conditions. The framework is applied to representative hypersonic vehicle control surface structures and a variety of studies are conducted to assess the impact of aerothermoelastic effects on hypersonic vehicle dynamics. The results presented in this dissertation demonstrate the ability of the proposed framework to perform efficient aerothermoelastic analysis.

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.

Identification of Dynamic Simulation Models for Variable Speed Pumped Storage Power Plants

NASA Astrophysics Data System (ADS)

Moreira, C.; Fulgêncio, N.; Silva, B.; Nicolet, C.; Béguin, A.

2017-04-01

This paper addresses the identification of reduced order models for variable speed pump-turbine plants, including the representation of the dynamic behaviour of the main components: hydraulic system, turbine governors, electromechanical equipment and power converters. A methodology for the identification of appropriated reduced order models both for turbine and pump operating modes is presented and discussed. The methodological approach consists of three main steps: 1) detailed pumped-storage power plant modelling in SIMSEN; 2) reduced order models identification and 3) specification of test conditions for performance evaluation.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

PubMed

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

High-order dynamic modeling and parameter identification of structural discontinuities in Timoshenko beams by using reflection coefficients

NASA Astrophysics Data System (ADS)

Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue

2013-02-01

Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.

Experimental and theoretical investigation of the first-order hyperpolarizability of a class of triarylamine derivatives

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

Silva, Daniel L., E-mail: dlsilva.physics@gmail.com, E-mail: deboni@ifsc.usp.br; Instituto de Física, Universidade de São Paulo, CP 66318, 05314-970 São Paulo, SP; Fonseca, Ruben D.

2015-02-14

This paper reports on the static and dynamic first-order hyperpolarizabilities of a class of push-pull octupolar triarylamine derivatives dissolved in toluene. We have combined hyper-Rayleigh scattering experiment and the coupled perturbed Hartree-Fock method implemented at the Density Functional Theory (DFT) level of theory to determine the static and dynamic (at 1064 nm) first-order hyperpolarizability (β{sub HRS}) of nine triarylamine derivatives with distinct electron-withdrawing groups. In four of these derivatives, an azoaromatic unit is inserted and a pronounceable increase of the first-order hyperpolarizability is reported. Based on the theoretical results, the dipolar/octupolar character of the derivatives is determined. By using amore » polarizable continuum model in combination with the DFT calculations, it was found that although solvated in an aprotic and low dielectric constant solvent, due to solvent-induced polarization and the frequency dispersion effect, the environment substantially affects the first-order hyperpolarizability of all derivatives investigated. This statement is supported due to the solvent effects to be essential for the better agreement between theoretical results and experimental data concerning the dynamic first-order hyperpolarizability of the derivatives. The first-order hyperpolarizability of the derivatives was also modeled using the two- and three-level models, where the relationship between static and dynamic first hyperpolarizabilities is given by a frequency dispersion model. Using this approach, it was verified that the dynamic first hyperpolarizability of the derivatives is satisfactorily reproduced by the two-level model and that, in the case of the derivatives with an azoaromatic unit, the use of a damped few-level model is essential for, considering also the molecular size of such derivatives, a good quantitative agreement between theoretical results and experimental data to be observed.« less

A hierarchy for modeling high speed propulsion systems

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Deabreu, Alex

1991-01-01

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery, such as inlets, ramjets, and scramjets. The discussion is separated into four areas: (1) computational fluid dynamics models for the entire nonlinear system or high order nonlinear models; (2) high order linearized models derived from fundamental physics; (3) low order linear models obtained from the other high order models; and (4) low order nonlinear models (order here refers to the number of dynamic states). Included in the discussion are any special considerations based on the relevant control system designs. The methods discussed are for the quasi-one-dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, including moving normal shocks, hammershocks, simple subsonic combustion via heat addition, temperature dependent gases, detonations, and thermal choking. The report also contains a comprehensive list of papers and theses generated by this grant.

Ordered and disordered dynamics in monolayers of rolling particles.

PubMed

Kim, Byungsoo; Putkaradze, Vakhtang

2010-12-10

We consider the ordered and disordered dynamics for monolayers of rolling self-interacting particles modeling water molecules. The rolling constraint represents a simplified model of a strong, but rapidly decaying bond with the surface. We show the existence and nonlinear stability of ordered lattice states, as well as disturbance propagation through and chaotic vibrations of these states. We study the dynamics of disordered gas states and show that there is a surprising and universal linear connection between distributions of angular and linear velocity, allowing definition of temperature.

A modeling of dynamic storage assignment for order picking in beverage warehousing with Drive-in Rack system

NASA Astrophysics Data System (ADS)

Hadi, M. Z.; Djatna, T.; Sugiarto

2018-04-01

This paper develops a dynamic storage assignment model to solve storage assignment problem (SAP) for beverages order picking in a drive-in rack warehousing system to determine the appropriate storage location and space for each beverage products dynamically so that the performance of the system can be improved. This study constructs a graph model to represent drive-in rack storage position then combine association rules mining, class-based storage policies and an arrangement rule algorithm to determine an appropriate storage location and arrangement of the product according to dynamic orders from customers. The performance of the proposed model is measured as rule adjacency accuracy, travel distance (for picking process) and probability a product become expiry using Last Come First Serve (LCFS) queue approach. Finally, the proposed model is implemented through computer simulation and compare the performance for different storage assignment methods as well. The result indicates that the proposed model outperforms other storage assignment methods.

Low-order nonlinear dynamic model of IC engine-variable pitch propeller system for general aviation aircraft

NASA Technical Reports Server (NTRS)

Richard, Jacques C.

1995-01-01

This paper presents a dynamic model of an internal combustion engine coupled to a variable pitch propeller. The low-order, nonlinear time-dependent model is useful for simulating the propulsion system of general aviation single-engine light aircraft. This model is suitable for investigating engine diagnostics and monitoring and for control design and development. Furthermore, the model may be extended to provide a tool for the study of engine emissions, fuel economy, component effects, alternative fuels, alternative engine cycles, flight simulators, sensors, and actuators. Results show that the model provides a reasonable representation of the propulsion system dynamics from zero to 10 Hertz.

Modeling and simulation of continuous wave velocity radar based on third-order DPLL

NASA Astrophysics Data System (ADS)

Di, Yan; Zhu, Chen; Hong, Ma

2015-02-01

Second-order digital phase-locked-loop (DPLL) is widely used in traditional Continuous wave (CW) velocity radar with poor performance in high dynamic conditions. Using the third-order DPLL can improve the performance. Firstly, the echo signal model of CW radar is given. Secondly, theoretical derivations of the tracking performance in different velocity conditions are given. Finally, simulation model of CW radar is established based on Simulink tool. Tracking performance of the two kinds of DPLL in different acceleration and jerk conditions is studied by this model. The results show that third-order PLL has better performance in high dynamic conditions. This model provides a platform for further research of CW radar.

First order coupled dynamic model of flexible space structures with time-varying configurations

NASA Astrophysics Data System (ADS)

Wang, Jie; Li, Dongxu; Jiang, Jianping

2017-03-01

This paper proposes a first order coupled dynamic modeling method for flexible space structures with time-varying configurations for the purpose of deriving the characteristics of the system. The model considers the first time derivative of the coordinate transformation matrix between the platform's body frame and the appendage's floating frame. As a result it can accurately predict characteristics of the system even if flexible appendages rotate with complex trajectory relative to the rigid part. In general, flexible appendages are fixed on the rigid platform or forced to rotate with a slow angular velocity. So only the zero order of the transformation matrix is considered in conventional models. However, due to neglecting of time-varying terms of the transformation matrix, these models introduce severe error when appendages, like antennas, for example, rotate with a fast speed relative to the platform. The first order coupled dynamic model for flexible space structures proposed in this paper resolve this problem by introducing the first time derivative of the transformation matrix. As a numerical example, a central core with a rotating solar panel is considered and the results are compared with those given by the conventional model. It has been shown that the first order terms are of great importance on the attitude of the rigid body and dynamic response of the flexible appendage.

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

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

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

Equilibrium pricing in an order book environment: Case study for a spin model

NASA Astrophysics Data System (ADS)

Meudt, Frederik; Schmitt, Thilo A.; Schäfer, Rudi; Guhr, Thomas

2016-07-01

When modeling stock market dynamics, the price formation is often based on an equilibrium mechanism. In real stock exchanges, however, the price formation is governed by the order book. It is thus interesting to check if the resulting stylized facts of a model with equilibrium pricing change, remain the same or, more generally, are compatible with the order book environment. We tackle this issue in the framework of a case study by embedding the Bornholdt-Kaizoji-Fujiwara spin model into the order book dynamics. To this end, we use a recently developed agent based model that realistically incorporates the order book. We find realistic stylized facts. We conclude for the studied case that equilibrium pricing is not needed and that the corresponding assumption of a ;fundamental; price may be abandoned.

Technical report series on global modeling and data assimilation. Volume 5: Documentation of the AIRES/GEOS dynamical core, version 2

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Takacs, Lawrence L.

1995-01-01

A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems

PubMed Central

Koumoutsakos, Petros

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse. PMID:29795631

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

PubMed

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

PubMed Central

Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

The confluence model: birth order as a within-family or between-family dynamic?

PubMed

Zajonc, R B; Sulloway, Frank J

2007-09-01

The confluence model explains birth-order differences in intellectual performance by quantifying the changing dynamics within the family. Wichman, Rodgers, and MacCallum (2006) claimed that these differences are a between-family phenomenon--and hence are not directly related to birth order itself. The study design and analyses presented by Wichman et al. nevertheless suffer from crucial shortcomings, including their use of unfocused tests, which cause statistically significant trends to be overlooked. In addition, Wichman et al. treated birth-order effects as a linear phenomenon thereby ignoring the confluence model's prediction that these two samples may manifest opposing results based on age. This article cites between- and within-family data that demonstrate systematic birth-order effects as predicted by the confluence model. The corpus of evidence invoked here offers strong support for the assumption of the confluence model that birth-order differences in intellectual performance are primarily a within-family phenomenon.

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

A multi agent model for the limit order book dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.

2010-11-01

In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.

Pilot modeling and closed-loop analysis of flexible aircraft in the pitch tracking task

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

The issue addressed in the appropriate modeling technique for pilot vehicle analysis of large flexible aircraft, when the frequency separation between the rigid-body mode and the dynamic aeroelastic modes is reduced. This situation was shown to have significant effects on pitch-tracking performance and subjective rating of the task, obtained via fixed base simulation. Further, the dynamics in these cases are not well modeled with a rigid-body-like model obtained by including only 'static elastic' effects, for example. It is shown that pilot/vehicle analysis of this data supports the hypothesis that an appropriate pilot-model structure is an optimal-control pilot model of full order. This is in contrast to the contention that a representative model is of reduced order when the subject is controlling high-order dynamics as in a flexible vehicle. The key appears to be in the correct assessment of the pilot's objective of attempting to control 'rigid-body' vehicle response, a response that must be estimated by the pilot from observations contaminated by aeroelastic dynamics. Finally, a model-based metric is shown to correlate well with the pilot's subjective ratings.

Convergence of high order perturbative expansions in open system quantum dynamics.

PubMed

Xu, Meng; Song, Linze; Song, Kai; Shi, Qiang

2017-02-14

We propose a new method to directly calculate high order perturbative expansion terms in open system quantum dynamics. They are first written explicitly in path integral expressions. A set of differential equations are then derived by extending the hierarchical equation of motion (HEOM) approach. As two typical examples for the bosonic and fermionic baths, specific forms of the extended HEOM are obtained for the spin-boson model and the Anderson impurity model. Numerical results are then presented for these two models. General trends of the high order perturbation terms as well as the necessary orders for the perturbative expansions to converge are analyzed.

Control-structure interaction study for the Space Station solar dynamic power module

NASA Technical Reports Server (NTRS)

Cheng, J.; Ianculescu, G.; Ly, J.; Kim, M.

1991-01-01

The authors investigate the feasibility of using a conventional PID (proportional plus integral plus derivative) controller design to perform the pointing and tracking functions for the Space Station Freedom solar dynamic power module. Using this simple controller design, the control/structure interaction effects were also studied without assuming frequency bandwidth separation. From the results, the feasibility of a simple solar dynamic control solution with a reduced-order model, which satisfies the basic system pointing and stability requirements, is suggested. However, the conventional control design approach is shown to be very much influenced by the order of reduction of the plant model, i.e., the number of the retained elastic modes from the full-order model. This suggests that, for complex large space structures, such as the Space Station Freedom solar dynamic, the conventional control system design methods may not be adequate.

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.

Dynamic decoupling and local atomic order of a model multicomponent metallic glass-former.

PubMed

Kim, Jeongmin; Sung, Bong June

2015-06-17

The dynamics of multicomponent metallic alloys is spatially heterogeneous near glass transition. The diffusion coefficient of one component of the metallic alloys may also decouple from those of other components, i.e., the diffusion coefficient of each component depends differently on the viscosity of metallic alloys. In this work we investigate the dynamic heterogeneity and decoupling of a model system for multicomponent Pd43Cu27Ni10P20 melts by using a hard sphere model that considers the size disparity of alloys but does not take chemical effects into account. We also study how such dynamic behaviors would relate to the local atomic structure of metallic alloys. We find, from molecular dynamics simulations, that the smallest component P of multicomponent Pd43Cu27Ni10P20 melts becomes dynamically heterogeneous at a translational relaxation time scale and that the largest major component Pd forms a slow subsystem, which has been considered mainly responsible for the stabilization of amorphous state of alloys. The heterogeneous dynamics of P atoms accounts for the breakdown of Stokes-Einstein relation and also leads to the dynamic decoupling of P and Pd atoms. The dynamically heterogeneous P atoms decrease the lifetime of the local short-range atomic orders of both icosahedral and close-packed structures by orders of magnitude.

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.

Dynamical simulation of E-ELT segmented primary mirror

NASA Astrophysics Data System (ADS)

Sedghi, B.; Muller, M.; Bauvir, B.

2011-09-01

The dynamical behavior of the primary mirror (M1) has an important impact on the control of the segments and the performance of the telescope. Control of large segmented mirrors with a large number of actuators and sensors and multiple control loops in real life is a challenging problem. In virtual life, modeling, simulation and analysis of the M1 bears similar difficulties and challenges. In order to capture the dynamics of the segment subunits (high frequency modes) and the telescope back structure (low frequency modes), high order dynamical models with a very large number of inputs and outputs need to be simulated. In this paper, different approaches for dynamical modeling and simulation of the M1 segmented mirror subject to various perturbations, e.g. sensor noise, wind load, vibrations, earthquake are presented.

Utilizing the Upcoming Gravity Measurements from Cassini's Proximal Orbits for Studying the Atmospheric Dynamics of Saturn - How Deep Do the Winds Penetrate?

NASA Astrophysics Data System (ADS)

Kaspi, Y.; Galanti, E.

2014-12-01

At the end of the Cassini mission, the spacecraft will descend into close-by proximal orbits around Saturn. During those proximal orbits, Cassini will obtain high precision gravity measurements of the planet. In this talk, we will discuss how this data can be used to estimate the depth of the observed flows on the planet. This can be done in several ways: 1. measurements of the high order even harmonics which beyond J10 are dominated by the dynamics; 2. measurements of odd gravity harmonics which have no contribution from a static planet, and therefore are a pure signature of dynamics; 3. upper limits on the depth can be obtained by comparing low order even harmonics from dynamical models to the difference between the measured low order even harmonics and the largest possible values of a static planet; 4. direct latitudinally varying measurements of the gravity field exerted on the spacecraft. We will discuss how these methods may be applied and show that given the expected sensitivity of Cassini the odd harmonics J3 and J5 will have the best sensitivity to deep dynamics, allowing detection of winds reaching only O(100km) deep, if those exist on Saturn. We use a hierarchy of dynamical models ranging from full 3D dynamical circulation models to simplified dynamical models where the sensitivity of the gravity field to the dynamics can be explored. In order to invert the gravity field to be measured by Cassini into the depth dependent circulation, an adjoint inverse model is constructed for the dynamical models, thus allowing backward integration of the dynamical model. This tool can be used for examination of various scenarios, including cases in which the depth of the wind depends on latitudinal position. In summary, we expect that the very end of Cassini's tour holds an opportunity for gravity measurements that may finally allow answering one of the long-lasting puzzles in planetary science regarding the depth of the zonal jets on the gas giants. In fact, as Juno will be performing similar measurements we hope to be able to build a picture of the dynamics for both Jupiter and Saturn. Answering this puzzle, will likely help explain the origin of the multiple jet streams and strong equatorial superrotation on the gas giants.

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.

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.

POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation

NASA Astrophysics Data System (ADS)

Ştefănescu, R.; Sandu, A.; Navon, I. M.

2015-08-01

This work studies reduced order modeling (ROM) approaches to speed up the solution of variational data assimilation problems with large scale nonlinear dynamical models. It is shown that a key requirement for a successful reduced order solution is that reduced order Karush-Kuhn-Tucker conditions accurately represent their full order counterparts. In particular, accurate reduced order approximations are needed for the forward and adjoint dynamical models, as well as for the reduced gradient. New strategies to construct reduced order based are developed for proper orthogonal decomposition (POD) ROM data assimilation using both Galerkin and Petrov-Galerkin projections. For the first time POD, tensorial POD, and discrete empirical interpolation method (DEIM) are employed to develop reduced data assimilation systems for a geophysical flow model, namely, the two dimensional shallow water equations. Numerical experiments confirm the theoretical framework for Galerkin projection. In the case of Petrov-Galerkin projection, stabilization strategies must be considered for the reduced order models. The new reduced order shallow water data assimilation system provides analyses similar to those produced by the full resolution data assimilation system in one tenth of the computational time.

Complex Sequencing Rules of Birdsong Can be Explained by Simple Hidden Markov Processes

PubMed Central

Katahira, Kentaro; Suzuki, Kenta; Okanoya, Kazuo; Okada, Masato

2011-01-01

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors such as human speech and musical performance, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical properties of the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable labeles, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model; GMM), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex behavioral sequences with higher-order dependencies. PMID:21915345

Haptics-based dynamic implicit solid modeling.

PubMed

Hua, Jing; Qin, Hong

2004-01-01

This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.

Modeling Climate Dynamically

ERIC Educational Resources Information Center

Walsh, Jim; McGehee, Richard

2013-01-01

A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

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.

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.

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

Model-based control strategies for systems with constraints of the program type

NASA Astrophysics Data System (ADS)

Jarzębowska, Elżbieta

2006-08-01

The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

Higher-Order Extended Lagrangian Born–Oppenheimer Molecular Dynamics for Classical Polarizable Models

DOE PAGES

Albaugh, Alex; Head-Gordon, Teresa; Niklasson, Anders M. N.

2018-01-09

Generalized extended Lagrangian Born−Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate “shadow” potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential tomore » any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.« less

Higher-Order Extended Lagrangian Born-Oppenheimer Molecular Dynamics for Classical Polarizable Models.

PubMed

Albaugh, Alex; Head-Gordon, Teresa; Niklasson, Anders M N

2018-02-13

Generalized extended Lagrangian Born-Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate "shadow" potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential to any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.

Higher-Order Extended Lagrangian Born–Oppenheimer Molecular Dynamics for Classical Polarizable Models

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

Albaugh, Alex; Head-Gordon, Teresa; Niklasson, Anders M. N.

Generalized extended Lagrangian Born−Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate “shadow” potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential tomore » any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.« less

Variable threshold algorithm for division of labor analyzed as a dynamical system.

PubMed

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Navarro, Iñaki; Caamaño-Martín, Estefanía; Monasterio-Huelin, Félix; Gutiérrez, Álvaro

2014-12-01

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Modeling Multi-Agent Self-Organization through the Lens of Higher Order Attractor Dynamics.

PubMed

Butner, Jonathan E; Wiltshire, Travis J; Munion, A K

2017-01-01

Social interaction occurs across many time scales and varying numbers of agents; from one-on-one to large-scale coordination in organizations, crowds, cities, and colonies. These contexts, are characterized by emergent self-organization that implies higher order coordinated patterns occurring over time that are not due to the actions of any particular agents, but rather due to the collective ordering that occurs from the interactions of the agents. Extant research to understand these social coordination dynamics (SCD) has primarily examined dyadic contexts performing rhythmic tasks. To advance this area of study, we elaborate on attractor dynamics, our ability to depict them visually, and quantitatively model them. Primarily, we combine difference/differential equation modeling with mixture modeling as a way to infer the underlying topological features of the data, which can be described in terms of attractor dynamic patterns. The advantage of this approach is that we are able to quantify the self-organized dynamics that agents exhibit, link these dynamics back to activity from individual agents, and relate it to other variables central to understanding the coordinative functionality of a system's behavior. We present four examples that differ in the number of variables used to depict the attractor dynamics (1, 2, and 6) and range from simulated to non-simulated data sources. We demonstrate that this is a flexible method that advances scientific study of SCD in a variety of multi-agent systems.

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.

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

A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

NASA Astrophysics Data System (ADS)

Zou, Changfu; Zhang, Lei; Hu, Xiaosong; Wang, Zhenpo; Wik, Torsten; Pecht, Michael

2018-06-01

Electrochemical energy storage systems play an important role in diverse applications, such as electrified transportation and integration of renewable energy with the electrical grid. To facilitate model-based management for extracting full system potentials, proper mathematical models are imperative. Due to extra degrees of freedom brought by differentiation derivatives, fractional-order models may be able to better describe the dynamic behaviors of electrochemical systems. This paper provides a critical overview of fractional-order techniques for managing lithium-ion batteries, lead-acid batteries, and supercapacitors. Starting with the basic concepts and technical tools from fractional-order calculus, the modeling principles for these energy systems are presented by identifying disperse dynamic processes and using electrochemical impedance spectroscopy. Available battery/supercapacitor models are comprehensively reviewed, and the advantages of fractional types are discussed. Two case studies demonstrate the accuracy and computational efficiency of fractional-order models. These models offer 15-30% higher accuracy than their integer-order analogues, but have reasonable complexity. Consequently, fractional-order models can be good candidates for the development of advanced battery/supercapacitor management systems. Finally, the main technical challenges facing electrochemical energy storage system modeling, state estimation, and control in the fractional-order domain, as well as future research directions, are highlighted.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

NASA Astrophysics Data System (ADS)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are applied in the training phase for calibrating model errors to achieve optimal imperfect model parameters; and total statistical energy dynamics are introduced to improve the model sensitivity in the prediction phase especially when strong external perturbations are exerted. The validity of reduced-order models for predicting statistical responses and intermittency is demonstrated on a series of instructive models with increasing complexity, including the stochastic triad model, the Lorenz '96 model, and models for barotropic and baroclinic turbulence. The skillful low-order modeling methods developed here should also be useful for other applications such as efficient algorithms for data assimilation.

Design of distributed PID-type dynamic matrix controller for fractional-order systems

NASA Astrophysics Data System (ADS)

Wang, Dawei; Zhang, Ridong

2018-01-01

With the continuous requirements for product quality and safety operation in industrial production, it is difficult to describe the complex large-scale processes with integer-order differential equations. However, the fractional differential equations may precisely represent the intrinsic characteristics of such systems. In this paper, a distributed PID-type dynamic matrix control method based on fractional-order systems is proposed. First, the high-order approximate model of integer order is obtained by utilising the Oustaloup method. Then, the step response model vectors of the plant is obtained on the basis of the high-order model, and the online optimisation for multivariable processes is transformed into the optimisation of each small-scale subsystem that is regarded as a sub-plant controlled in the distributed framework. Furthermore, the PID operator is introduced into the performance index of each subsystem and the fractional-order PID-type dynamic matrix controller is designed based on Nash optimisation strategy. The information exchange among the subsystems is realised through the distributed control structure so as to complete the optimisation task of the whole large-scale system. Finally, the control performance of the designed controller in this paper is verified by an example.

Robust controller designs for second-order dynamic system: A virtual passive approach

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1990-01-01

A robust controller design is presented for second-order dynamic systems. The controller is model-independent and itself is a virtual second-order dynamic system. Conditions on actuator and sensor placements are identified for controller designs that guarantee overall closed-loop stability. The dynamic controller can be viewed as a virtual passive damping system that serves to stabilize the actual dynamic system. The control gains are interpreted as virtual mass, spring, and dashpot elements that play the same roles as actual physical elements in stability analysis. Position, velocity, and acceleration feedback are considered. Simple examples are provided to illustrate the physical meaning of this controller design.

Censored Glauber Dynamics for the Mean Field Ising Model

NASA Astrophysics Data System (ADS)

Ding, Jian; Lubetzky, Eyal; Peres, Yuval

2009-11-01

We study Glauber dynamics for the Ising model on the complete graph on n vertices, known as the Curie-Weiss Model. It is well known that at high temperature ( β<1) the mixing time is Θ( nlog n), whereas at low temperature ( β>1) it is exp ( Θ( n)). Recently, Levin, Luczak and Peres considered a censored version of this dynamics, which is restricted to non-negative magnetization. They proved that for fixed β>1, the mixing-time of this model is Θ( nlog n), analogous to the high-temperature regime of the original dynamics. Furthermore, they showed cutoff for the original dynamics for fixed β<1. The question whether the censored dynamics also exhibits cutoff remained unsettled. In a companion paper, we extended the results of Levin et al. into a complete characterization of the mixing-time for the Curie-Weiss model. Namely, we found a scaling window of order 1/sqrt{n} around the critical temperature β c =1, beyond which there is cutoff at high temperature. However, determining the behavior of the censored dynamics outside this critical window seemed significantly more challenging. In this work we answer the above question in the affirmative, and establish the cutoff point and its window for the censored dynamics beyond the critical window, thus completing its analogy to the original dynamics at high temperature. Namely, if β=1+ δ for some δ>0 with δ 2 n→∞, then the mixing-time has order ( n/ δ)log ( δ 2 n). The cutoff constant is (1/2+[2(ζ2 β/ δ-1)]-1), where ζ is the unique positive root of g( x)=tanh ( β x)- x, and the cutoff window has order n/ δ.

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.

A two-scale model for dynamic damage evolution

NASA Astrophysics Data System (ADS)

Keita, Oumar; Dascalu, Cristian; François, Bertrand

2014-03-01

This paper presents a new micro-mechanical damage model accounting for inertial effect. The two-scale damage model is fully deduced from small-scale descriptions of dynamic micro-crack propagation under tensile loading (mode I). An appropriate micro-mechanical energy analysis is combined with homogenization based on asymptotic developments in order to obtain the macroscopic evolution law for damage. Numerical simulations are presented in order to illustrate the ability of the model to describe known behaviors like size effects for the structural response, strain-rate sensitivity, brittle-ductile transition and wave dispersion.

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.

General order parameter based correlation analysis of protein backbone motions between experimental NMR relaxation measurements and molecular dynamics simulations

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

Liu, Qing; Shi, Chaowei; Yu, Lu

Internal backbone dynamic motions are essential for different protein functions and occur on a wide range of time scales, from femtoseconds to seconds. Molecular dynamic (MD) simulations and nuclear magnetic resonance (NMR) spin relaxation measurements are valuable tools to gain access to fast (nanosecond) internal motions. However, there exist few reports on correlation analysis between MD and NMR relaxation data. Here, backbone relaxation measurements of {sup 15}N-labeled SH3 (Src homology 3) domain proteins in aqueous buffer were used to generate general order parameters (S{sup 2}) using a model-free approach. Simultaneously, 80 ns MD simulations of SH3 domain proteins in amore » defined hydrated box at neutral pH were conducted and the general order parameters (S{sup 2}) were derived from the MD trajectory. Correlation analysis using the Gromos force field indicated that S{sup 2} values from NMR relaxation measurements and MD simulations were significantly different. MD simulations were performed on models with different charge states for three histidine residues, and with different water models, which were SPC (simple point charge) water model and SPC/E (extended simple point charge) water model. S{sup 2} parameters from MD simulations with charges for all three histidines and with the SPC/E water model correlated well with S{sup 2} calculated from the experimental NMR relaxation measurements, in a site-specific manner. - Highlights: • Correlation analysis between NMR relaxation measurements and MD simulations. • General order parameter (S{sup 2}) as common reference between the two methods. • Different protein dynamics with different Histidine charge states in neutral pH. • Different protein dynamics with different water models.« less

Phase ordering in disordered and inhomogeneous systems

NASA Astrophysics Data System (ADS)

Corberi, Federico; Zannetti, Marco; Lippiello, Eugenio; Burioni, Raffaella; Vezzani, Alessandro

2015-06-01

We study numerically the coarsening dynamics of the Ising model on a regular lattice with random bonds and on deterministic fractal substrates. We propose a unifying interpretation of the phase-ordering processes based on two classes of dynamical behaviors characterized by different growth laws of the ordered domain size, namely logarithmic or power law, respectively. It is conjectured that the interplay between these dynamical classes is regulated by the same topological feature that governs the presence or the absence of a finite-temperature phase transition.

POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation

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

Ştefănescu, R., E-mail: rstefane@vt.edu; Sandu, A., E-mail: sandu@cs.vt.edu; Navon, I.M., E-mail: inavon@fsu.edu

2015-08-15

This work studies reduced order modeling (ROM) approaches to speed up the solution of variational data assimilation problems with large scale nonlinear dynamical models. It is shown that a key requirement for a successful reduced order solution is that reduced order Karush–Kuhn–Tucker conditions accurately represent their full order counterparts. In particular, accurate reduced order approximations are needed for the forward and adjoint dynamical models, as well as for the reduced gradient. New strategies to construct reduced order based are developed for proper orthogonal decomposition (POD) ROM data assimilation using both Galerkin and Petrov–Galerkin projections. For the first time POD, tensorialmore » POD, and discrete empirical interpolation method (DEIM) are employed to develop reduced data assimilation systems for a geophysical flow model, namely, the two dimensional shallow water equations. Numerical experiments confirm the theoretical framework for Galerkin projection. In the case of Petrov–Galerkin projection, stabilization strategies must be considered for the reduced order models. The new reduced order shallow water data assimilation system provides analyses similar to those produced by the full resolution data assimilation system in one tenth of the computational time.« less

A novel condition for stable nonlinear sampled-data models using higher-order discretized approximations with zero dynamics.

PubMed

Zeng, Cheng; Liang, Shan; Xiang, Shuwen

2017-05-01

Continuous-time systems are usually modelled by the form of ordinary differential equations arising from physical laws. However, the use of these models in practice and utilizing, analyzing or transmitting these data from such systems must first invariably be discretized. More importantly, for digital control of a continuous-time nonlinear system, a good sampled-data model is required. This paper investigates the new consistency condition which is weaker than the previous similar results presented. Moreover, given the stability of the high-order approximate model with stable zero dynamics, the novel condition presented stabilizes the exact sampled-data model of the nonlinear system for sufficiently small sampling periods. An insightful interpretation of the obtained results can be made in terms of the stable sampling zero dynamics, and the new consistency condition is surprisingly associated with the relative degree of the nonlinear continuous-time system. Our controller design, based on the higher-order approximate discretized model, extends the existing methods which mainly deal with the Euler approximation. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Fractional discrete-time consensus models for single- and double-summator dynamics

NASA Astrophysics Data System (ADS)

Wyrwas, Małgorzata; Mozyrska, Dorota; Girejko, Ewa

2018-04-01

The leader-following consensus problem of fractional-order multi-agent discrete-time systems is considered. In the systems, interactions between opinions are defined like in Krause and Cucker-Smale models but the memory is included by taking the fractional-order discrete-time operator on the left-hand side of the nonlinear systems. In this paper, we investigate fractional-order models of opinions for the single- and double-summator dynamics of discrete-time by analytical methods as well as by computer simulations. The necessary and sufficient conditions for the leader-following consensus are formulated by proposing a consensus control law for tracking the virtual leader.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters: Preprint

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

Johnson, Brian B; Purba, Victor; Jafarpour, Saber

Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute 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 pointmore » of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model 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. That is, 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 an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.« less

Vibrational properties of the amide group in acetanilide: A molecular-dynamics study

NASA Astrophysics Data System (ADS)

Campa, Alessandro; Giansanti, Andrea; Tenenbaum, Alexander

1987-09-01

A simplified classical model of acetanilide crystal is built in order to study the mechanisms of vibrational energy transduction in a hydrogen-bonded solid. The intermolecular hydrogen bond is modeled by an electrostatic interaction between neighboring excess charges on hydrogen and oxygen atoms. The intramolecular interaction in the peptide group is provided by a dipole-charge interaction. Forces are calculated up to second-order terms in the atomic displacements from equilibrium positions; the model is thus a chain of nonlinear coupled oscillators. Numerical molecular-dynamics experiments are performed on chain segments of five molecules. The dynamics is ordered, at all temperatures. Energy is widely exchanged between the stretching and the bending of the N-H bond, with characteristic times of the order of 0.2 ps. Energy transduction through the H bond is somewhat slower and of smaller amplitude, and is strongly reduced when the energies of the two bound molecules are very different: This could reduce the dissipation of localized energy fluctuations.

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.

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.

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

Explicit filtering in large eddy simulation using a discontinuous Galerkin method

NASA Astrophysics Data System (ADS)

Brazell, Matthew J.

The discontinuous Galerkin (DG) method is a formulation of the finite element method (FEM). DG provides the ability for a high order of accuracy in complex geometries, and allows for highly efficient parallelization algorithms. These attributes make the DG method attractive for solving the Navier-Stokes equations for large eddy simulation (LES). The main goal of this work is to investigate the feasibility of adopting an explicit filter in the numerical solution of the Navier-Stokes equations with DG. Explicit filtering has been shown to increase the numerical stability of under-resolved simulations and is needed for LES with dynamic sub-grid scale (SGS) models. The explicit filter takes advantage of DG's framework where the solution is approximated using a polyno- mial basis where the higher modes of the solution correspond to a higher order polynomial basis. By removing high order modes, the filtered solution contains low order frequency content much like an explicit low pass filter. The explicit filter implementation is tested on a simple 1-D solver with an initial condi- tion that has some similarity to turbulent flows. The explicit filter does restrict the resolution as well as remove accumulated energy in the higher modes from aliasing. However, the ex- plicit filter is unable to remove numerical errors causing numerical dissipation. A second test case solves the 3-D Navier-Stokes equations of the Taylor-Green vortex flow (TGV). The TGV is useful for SGS model testing because it is initially laminar and transitions into a fully turbulent flow. The SGS models investigated include the constant coefficient Smagorinsky model, dynamic Smagorinsky model, and dynamic Heinz model. The constant coefficient Smagorinsky model is over dissipative, this is generally not desirable however it does add stability. The dynamic Smagorinsky model generally performs better, especially during the laminar-turbulent transition region as expected. The dynamic Heinz model which is based on an improved model, handles the laminar-turbulent transition region well while also showing additional robustness.

Influence of model order reduction methods on dynamical-optical simulations

NASA Astrophysics Data System (ADS)

Störkle, Johannes; Eberhard, Peter

2017-04-01

In this work, the influence of model order reduction (MOR) methods on optical aberrations is analyzed within a dynamical-optical simulation of a high precision optomechanical system. Therefore, an integrated modeling process and new methods have to be introduced for the computation and investigation of the overall dynamical-optical behavior. For instance, this optical system can be a telescope optic or a lithographic objective. In order to derive a simplified mechanical model for transient time simulations with low computational cost, the method of elastic multibody systems in combination with MOR methods can be used. For this, software tools and interfaces are defined and created. Furthermore, mechanical and optical simulation models are derived and implemented. With these, on the one hand, the mechanical sensitivity can be investigated for arbitrary external excitations and on the other hand, the related optical behavior can be predicted. In order to clarify these methods, academic examples are chosen and the influences of the MOR methods and simulation strategies are analyzed. Finally, the systems are investigated with respect to the mechanical-optical frequency responses, and in conclusion, some recommendations for the application of reduction methods are given.

Phase transitions in a multistate majority-vote model on complex networks

NASA Astrophysics Data System (ADS)

Chen, Hanshuang; Li, Guofeng

2018-06-01

We generalize the original majority-vote (MV) model from two states to arbitrary p states and study the order-disorder phase transitions in such a p -state MV model on complex networks. By extensive Monte Carlo simulations and a mean-field theory, we show that for p ≥3 the order of phase transition is essentially different from a continuous second-order phase transition in the original two-state MV model. Instead, for p ≥3 the model displays a discontinuous first-order phase transition, which is manifested by the appearance of the hysteresis phenomenon near the phase transition. Within the hysteresis loop, the ordered phase and disordered phase are coexisting, and rare flips between the two phases can be observed due to the finite-size fluctuation. Moreover, we investigate the type of phase transition under a slightly modified dynamics [Melo et al., J. Stat. Mech. (2010) P11032, 10.1088/1742-5468/2010/11/P11032]. We find that the order of phase transition in the three-state MV model depends on the degree heterogeneity of networks. For p ≥4 , both dynamics produce the first-order phase transitions.

Nano-confined water in the interlayers of hydrocalumite: Reorientational dynamics probed by neutron spectroscopy and molecular dynamics computer simulations

NASA Astrophysics Data System (ADS)

Kalinichev, A. G.; Faraone, A.; Udovic, T.; Kolesnikov, A. I.; de Souza, N. R.; Reinholdt, M. X.; Kirkpatrick, R.

2008-12-01

Layered double hydroxides (LDHs, anionic clays) represent excellent model systems for detailed molecular- level studies of the structure, dynamics, and energetics of nano-confined water in mineral interlayers and nano-pores, because LDH interlayers can have a well-defined structures and contain H2O molecules and a wide variety of anions in structurally well-defined positions and coordinations. [Ca2Al(OH)6]Cl·2H2O, also known as hydrocalumite or Friedel's salt, has a well- ordered Ca,Al distribution in the hydroxide layer and a very high degree of H2O,Cl ordering in the interlayer. It is also one of the only LDH phase for which a single crystal structure refinement is available. Thus, it is currently the best model compound for understanding the structure and dynamical behavior of interlayer and surface species in other, less-ordered, LDHs. We investigated the structural and dynamic behavior of water in the interlayers of hydrocalumite using inelastic (INS) and quasielastic (QENS) neutron scattering and molecular dynamics computer simulations. The comperehensive neutron scattering studies were performed for one fully hydrated and one dehydrated sample of hydrocalumite using several complementary instruments (HFBS, DCS and FANS at NCNR; HRMECS and QENS at IPNS) at temperatures above and below the previously discovered order-disorder interlayer phase transition. Together the experimental and molecular modeling results capture the important details of the dynamics of nano-confined water and the effects of the orientational ordering of H2O molecules above and below the phase transition. They provide otherwise unobtainable experimental information about the transformation of H2O librational and diffusional modes across the order-disorder phase transition and significantly add to our current understanding of the structure and dynamics of water in LDH phases based on the earlier NMR, IR, X-ray, and calorimetric measurements. The approach can now be extended to probe the dynamics of nano-confined and interfacial water in more disordered phases (LDH, clays, cement, etc.), for which much less initial structural information is available.

Fixed gain and adaptive techniques for rotorcraft vibration control

NASA Technical Reports Server (NTRS)

Roy, R. H.; Saberi, H. A.; Walker, R. A.

1985-01-01

The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

An Empirical Validation of a Dynamic Systems Model of Interaction: Do Children of Different Sociometric Statuses Differ in Their Dyadic Play?

ERIC Educational Resources Information Center

Steenbeek, Henderien; van Geert, Paul

2008-01-01

Studying short-term dynamic processes and change mechanisms in interaction yields important knowledge that contributes to understanding long-term social development of children. In order to get a grip on this short-term dynamics of interaction processes, the authors made a dynamic systems model of dyadic interaction of children during one play…

A tone mapping operator based on neural and psychophysical models of visual perception

NASA Astrophysics Data System (ADS)

Cyriac, Praveen; Bertalmio, Marcelo; Kane, David; Vazquez-Corral, Javier

2015-03-01

High dynamic range imaging techniques involve capturing and storing real world radiance values that span many orders of magnitude. However, common display devices can usually reproduce intensity ranges only up to two to three orders of magnitude. Therefore, in order to display a high dynamic range image on a low dynamic range screen, the dynamic range of the image needs to be compressed without losing details or introducing artefacts, and this process is called tone mapping. A good tone mapping operator must be able to produce a low dynamic range image that matches as much as possible the perception of the real world scene. We propose a two stage tone mapping approach, in which the first stage is a global method for range compression based on a gamma curve that equalizes the lightness histogram the best, and the second stage performs local contrast enhancement and color induction using neural activity models for the visual cortex.

High-Order Model and Dynamic Filtering for Frame Rate Up-Conversion.

PubMed

Bao, Wenbo; Zhang, Xiaoyun; Chen, Li; Ding, Lianghui; Gao, Zhiyong

2018-08-01

This paper proposes a novel frame rate up-conversion method through high-order model and dynamic filtering (HOMDF) for video pixels. Unlike the constant brightness and linear motion assumptions in traditional methods, the intensity and position of the video pixels are both modeled with high-order polynomials in terms of time. Then, the key problem of our method is to estimate the polynomial coefficients that represent the pixel's intensity variation, velocity, and acceleration. We propose to solve it with two energy objectives: one minimizes the auto-regressive prediction error of intensity variation by its past samples, and the other minimizes video frame's reconstruction error along the motion trajectory. To efficiently address the optimization problem for these coefficients, we propose the dynamic filtering solution inspired by video's temporal coherence. The optimal estimation of these coefficients is reformulated into a dynamic fusion of the prior estimate from pixel's temporal predecessor and the maximum likelihood estimate from current new observation. Finally, frame rate up-conversion is implemented using motion-compensated interpolation by pixel-wise intensity variation and motion trajectory. Benefited from the advanced model and dynamic filtering, the interpolated frame has much better visual quality. Extensive experiments on the natural and synthesized videos demonstrate the superiority of HOMDF over the state-of-the-art methods in both subjective and objective comparisons.

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.

Modelling dynamics in protein crystal structures by ensemble refinement

PubMed Central

Burnley, B Tom; Afonine, Pavel V; Adams, Paul D; Gros, Piet

2012-01-01

Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated Rfree values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships. DOI: http://dx.doi.org/10.7554/eLife.00311.001 PMID:23251785

Coupled orbit-attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

NASA Astrophysics Data System (ADS)

Misra, Gaurav; Izadi, Maziar; Sanyal, Amit; Scheeres, Daniel

2016-04-01

The effects of dynamical coupling between the rotational (attitude) and translational (orbital) motion of spacecraft near small Solar System bodies is investigated. This coupling arises due to the weak gravity of these bodies, as well as solar radiation pressure. The traditional approach assumes a point-mass spacecraft model to describe the translational motion of the spacecraft, while the attitude motion is considered to be completely decoupled from the translational motion. The model used here to describe the rigid-body spacecraft dynamics includes the non-uniform rotating gravity field of the small body up to second degree and order along with the attitude dependent terms, solar tide, and solar radiation pressure. This model shows that the second degree and order gravity terms due to the small body affect the dynamics of the spacecraft to the same extent as the orbit-attitude coupling due to the primary gravity (zeroth order) term. Variational integrators are used to simulate the dynamics of both the rigid spacecraft and the point mass. The small bodies considered here are modeled after Near-Earth Objects (NEO) 101955 Bennu, and 25143 Itokawa, and are assumed to be triaxial ellipsoids with uniform density. Differences in the numerically obtained trajectories of a rigid spacecraft and a point mass are then compared, to illustrate the impact of the orbit-attitude coupling on spacecraft dynamics in proximity of small bodies. Possible implications on the performance of model-based spacecraft control and on the station-keeping budget, if the orbit-attitude coupling is not accounted for in the model of the dynamics, are also discussed. An almost globally asymptotically stable motion estimation scheme based solely on visual/optical feedback that estimates the relative motion of the asteroid with respect to the spacecraft is also obtained. This estimation scheme does not require a model of the dynamics of the asteroid, which makes it perfectly suited for asteroids whose properties are not well known.

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.

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.

Anomalous diffusion with linear reaction dynamics: from continuous time random walks to fractional reaction-diffusion equations.

PubMed

Henry, B I; Langlands, T A M; Wearne, S L

2006-09-01

We have revisited the problem of anomalously diffusing species, modeled at the mesoscopic level using continuous time random walks, to include linear reaction dynamics. If a constant proportion of walkers are added or removed instantaneously at the start of each step then the long time asymptotic limit yields a fractional reaction-diffusion equation with a fractional order temporal derivative operating on both the standard diffusion term and a linear reaction kinetics term. If the walkers are added or removed at a constant per capita rate during the waiting time between steps then the long time asymptotic limit has a standard linear reaction kinetics term but a fractional order temporal derivative operating on a nonstandard diffusion term. Results from the above two models are compared with a phenomenological model with standard linear reaction kinetics and a fractional order temporal derivative operating on a standard diffusion term. We have also developed further extensions of the CTRW model to include more general reaction dynamics.

Building a kinetic Monte Carlo model with a chosen accuracy.

PubMed

Bhute, Vijesh J; Chatterjee, Abhijit

2013-06-28

The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached.

High-Order Shock-Capturing Methods for Modeling Dynamics of the Solar Atmosphere

NASA Technical Reports Server (NTRS)

Bryson, Steve; Kosovichev, Alexander; Levy, Doron

2004-01-01

We use one-dimensional high-order central shock capturing numerical methods to study the response of various model solar atmospheres to forcing at the solar surface. The dynamics of the atmosphere is modeled with the Euler equations in a variable-sized flux tube in the presence of gravity. We study dynamics of the atmosphere suggestive of spicule formation and coronal oscillations. These studies are performed on observationally-derived model atmospheres above the quiet sun and above sunspots. To perform these simulations, we provide a new extension of existing second- and third- order shock-capturing methods to irregular grids. We also solve the problem of numerically maintaining initial hydrostatic balance via the introduction of new variables in the model equations and a careful initialization mechanism. We find several striking results: all model atmospheres respond to a single impulsive perturbation with several strong shock waves consistent with the rebound-shock model. These shock waves lift material and the transition region well into the initial corona, and the sensitivity of this lift to the initial impulse depends non-linearly on the details of the atmosphere model. We also reproduce an observed 3-minute coronal oscillation above sunspots compared to 5-minute oscillations above the quiet sun.

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.

Piloting Changes to Changing Aircraft Dynamics: What Do Pilots Need to Know?

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2011-01-01

An experiment was conducted to quantify the effects of changing dynamics on a subject s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. The data will be used to identify primary aircraft dynamics variables that influence changes in pilot s response and produce a simplified pilot model that incorporates this relationship. Each run incorporated a different set of second-order aircraft dynamics representing short period transfer function pitch attitude response: damping ratio, frequency, gain, zero location, and time delay. The subject s ability to conduct the tracking task was the greatest source of root mean square error tracking variability. As for the aircraft dynamics, the factors that affected the subjects ability to conduct the tracking were the time delay, frequency, and zero location. In addition to creating a simplified pilot model, the results of the experiment can be utilized in an advisory capacity. A situation awareness/prediction aid based on the pilot behavior and aircraft dynamics may help tailor pilot s inputs more quickly so that PIO or an upset condition can be avoided.

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.

Disturbance rejection control for vibration suppression of piezoelectric laminated thin-walled structures

NASA Astrophysics Data System (ADS)

Zhang, S. Q.; Li, H. N.; Schmidt, R.; Müller, P. C.

2014-02-01

Thin-walled piezoelectric integrated smart structures are easily excited to vibrate by unknown disturbances. In order to design and simulate a control strategy, firstly, an electro-mechanically coupled dynamic finite element (FE) model of smart structures is developed based on first-order shear deformation (FOSD) hypothesis. Linear piezoelectric constitutive equations and the assumption of constant electric field through the thickness are considered. Based on the dynamic FE model, a disturbance rejection (DR) control with proportional-integral (PI) observer using step functions as the fictitious model of disturbances is developed for vibration suppression of smart structures. In order to achieve a better dynamic behavior of the fictitious model of disturbances, the PI observer is extended to generalized proportional-integral (GPI) observer, in which sine or polynomial functions can be used to represent disturbances resulting in better dynamics. Therefore the disturbances can be estimated either by PI or GPI observer, and then the estimated signals are fed back to the controller. The DR control is validated by various kinds of unknown disturbances, and compared with linear-quadratic regulator (LQR) control. The results illustrate that the vibrations are better suppressed by the proposed DR control.

Development of an end-of-life vehicle recovery model using system dynamics and future research needs

NASA Astrophysics Data System (ADS)

Mohamad-Ali, N.; Ghazilla, R. A. R.; Abdul-Rashid, S. H.; Sakundarini, N.; Ahmad-Yazid, A.; Stephenie, L.

2017-06-01

The implementation of end-of-life vehicle (ELV) recovery policy in Malaysia has led vehicle manufacturers to look at different ways to improve design and development of vehicles. Nowadays, it is crucial to incorporate end-of-life (EOL) design strategies into the vehicle design in order to enhance the effectiveness of the ELV recovery network. Although recent studies have shown that product design has a significant effect on the product recovery rate, there is a lack of studies on how EOL design strategies affects the effectiveness of ELV recovery, particularly when there are dynamic changes in the behaviour of the product recovery network. Thus, in this study, we developed a preliminary model based on the system dynamics approach in order to predict the effectiveness of ELV recovery in response to dynamic changes of various factors (including EOL design strategies) in the business environment. We developed this model based on preliminary data that we had gathered from unstructured interviews with the key stakeholders of ELV management in Malaysia. We believe that our model will greatly benefit product designers in incorporating the appropriate EOL design strategies in order to boost ELV recovery effectiveness in Malaysia.

Stochastic dynamics of melt ponds and sea ice-albedo climate feedback

NASA Astrophysics Data System (ADS)

Sudakov, Ivan

Evolution of melt ponds on the Arctic sea surface is a complicated stochastic process. We suggest a low-order model with ice-albedo feedback which describes stochastic dynamics of melt ponds geometrical characteristics. The model is a stochastic dynamical system model of energy balance in the climate system. We describe the equilibria in this model. We conclude the transition in fractal dimension of melt ponds affects the shape of the sea ice albedo curve.

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.

Memory in a fractional-order cardiomyocyte model alters properties of alternans and spontaneous activity

NASA Astrophysics Data System (ADS)

Comlekoglu, T.; Weinberg, S. H.

2017-09-01

Cardiac memory is the dependence of electrical activity on the prior history of one or more system state variables, including transmembrane potential (Vm), ionic current gating, and ion concentrations. While prior work has represented memory either phenomenologically or with biophysical detail, in this study, we consider an intermediate approach of a minimal three-variable cardiomyocyte model, modified with fractional-order dynamics, i.e., a differential equation of order between 0 and 1, to account for history-dependence. Memory is represented via both capacitive memory, due to fractional-order Vm dynamics, that arises due to non-ideal behavior of membrane capacitance; and ionic current gating memory, due to fractional-order gating variable dynamics, that arises due to gating history-dependence. We perform simulations for varying Vm and gating variable fractional-orders and pacing cycle length and measure action potential duration (APD) and incidence of alternans, loss of capture, and spontaneous activity. In the absence of ionic current gating memory, we find that capacitive memory, i.e., decreased Vm fractional-order, typically shortens APD, suppresses alternans, and decreases the minimum cycle length (MCL) for loss of capture. However, in the presence of ionic current gating memory, capacitive memory can prolong APD, promote alternans, and increase MCL. Further, we find that reduced Vm fractional order (typically less than 0.75) can drive phase 4 depolarizations that promote spontaneous activity. Collectively, our results demonstrate that memory reproduced by a fractional-order model can play a role in alternans formation and pacemaking, and in general, can greatly increase the range of electrophysiological characteristics exhibited by a minimal model.

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

Local dynamic subgrid-scale models in channel flow

NASA Technical Reports Server (NTRS)

Cabot, William H.

1994-01-01

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

Mathematical modeling of alignment dynamics in active motor-filament systems

NASA Astrophysics Data System (ADS)

Swaminathan, Sumanth

The formation of the cytoskeleton, via motor-mediated microtubule self-organization, is an important subject of study in the biological sciences as well as in nonequilibrium, soft matter physics. Accurate modeling of the dynamics is a formidable task as it involves intrinsic nonlinearities, structural anisotropies, nonequilibrium processes, and a broad window of time scales, length scales, and densities. In this thesis, we study the ordering dynamics and pattern formations arising from motor-mediated microtubule self-organization in dilute and semi-dilute filament solutions. In the dilute case, we use a probabilistic model in which microtubules interact through motor induced, inelastic binary collisions. This model shows that initially disordered filament solutions exhibit an ordering transition resulting in the emergence of well aligned rod bundles. We study the existence and dynamic interaction of microtubule bundles analytically and numerically. Our results show a long term attraction and coalescing of bundles indicating a clear coarsening in the system; microtubule bundles concentrate into fewer orientations on a slow logarithmic time scale. In the semi-dilute case, multiple motors can bind a filament to several others and, for a critical motor density, induce a transition to an ordered state with a nonzero mean orientation. We develop a spatially homogeneous, mean-field theory that explicitly accounts for motor forcing and thermal fluctuations which enter into the model as multiplicative and additive noises respectively. Our model further incorporates a force-dependent detachment rate of motors, which in turn affects the mean and the fluctuations of the net force acting on a filament. We demonstrate that the transition to the oriented state changes from second order to first order when the force-dependent detachment becomes important. In our final analysis, we add complex spatial inhomogeneities to our mean field theory. The revised model consists of a system of stochastic differential equations governing the time evolution of the orientation and center of mass of each filament; microtubules translate and rotate under the influence of motor forces and intrinsic thermal fluctuations. We show through a molecular dynamics type stochastic simulation that initially disordered systems of microtubules exhibit an ordering transition resulting in the formation of bundles and vortices. This finding is compared with previous binary interaction and hydrodynamic models and shown to be consistent with in vitro experiments on motor-mediated self-organization of microtubules and actin filaments.

Extreme learning machine for reduced order modeling of turbulent geophysical flows.

PubMed

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

NASA Astrophysics Data System (ADS)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

An individual-based model of zebrafish population dynamics accounting for energy dynamics.

PubMed

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

PubMed Central

Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409

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.

Modeling of thin-walled structures interacting with acoustic media as constrained two-dimensional continua

NASA Astrophysics Data System (ADS)

Rabinskiy, L. N.; Zhavoronok, S. I.

2018-04-01

The transient interaction of acoustic media and elastic shells is considered on the basis of the transition function approach. The three-dimensional hyperbolic initial boundary-value problem is reduced to a two-dimensional problem of shell theory with integral operators approximating the acoustic medium effect on the shell dynamics. The kernels of these integral operators are determined by the elementary solution of the problem of acoustic waves diffraction at a rigid obstacle with the same boundary shape as the wetted shell surface. The closed-form elementary solution for arbitrary convex obstacles can be obtained at the initial interaction stages on the background of the so-called “thin layer hypothesis”. Thus, the shell–wave interaction model defined by integro-differential dynamic equations with analytically determined kernels of integral operators becomes hence two-dimensional but nonlocal in time. On the other hand, the initial interaction stage results in localized dynamic loadings and consequently in complex strain and stress states that require higher-order shell theories. Here the modified theory of I.N.Vekua–A.A.Amosov-type is formulated in terms of analytical continuum dynamics. The shell model is constructed on a two-dimensional manifold within a set of field variables, Lagrangian density, and constraint equations following from the boundary conditions “shifted” from the shell faces to its base surface. Such an approach allows one to construct consistent low-order shell models within a unified formal hierarchy. The equations of the N th-order shell theory are singularly perturbed and contain second-order partial derivatives with respect to time and surface coordinates whereas the numerical integration of systems of first-order equations is more efficient. Such systems can be obtained as Hamilton–de Donder–Weyl-type equations for the Lagrangian dynamical system. The Hamiltonian formulation of the elementary N th-order shell theory is here briefly described.

Mining the Dynamics of Student Utility and Strategy Use during Vocabulary Learning

ERIC Educational Resources Information Center

Pavlik, Philip I., Jr.

2013-01-01

This paper describes the development of a dynamical systems model of motivation and metacognition during learning, which explains some of the practically and theoretically important relationships among three student engagement constructs and performance metrics during learning. In order to better calibrate and understand the model, the model was…

Reduced order modeling and active flow control of an inlet duct

NASA Astrophysics Data System (ADS)

Ge, Xiaoqing

Many aerodynamic applications require the modeling of compressible flows in or around a body, e.g., the design of aircraft, inlet or exhaust duct, wind turbines, or tall buildings. Traditional methods use wind tunnel experiments and computational fluid dynamics (CFD) to investigate the spatial and temporal distribution of the flows. Although they provide a great deal of insight into the essential characteristics of the flow field, they are not suitable for control analysis and design due to the high physical/computational cost. Many model reduction methods have been studied to reduce the complexity of the flow model. There are two main approaches: linearization based input/output modeling and proper orthogonal decomposition (POD) based model reduction. The former captures mostly the local behavior near a steady state, which is suitable to model laminar flow dynamics. The latter obtains a reduced order model by projecting the governing equation onto an "optimal" subspace and is able to model complex nonlinear flow phenomena. In this research we investigate various model reduction approaches and compare them in flow modeling and control design. We propose an integrated model-based control methodology and apply it to the reduced order modeling and active flow control of compressible flows within a very aggressive (length to exit diameter ratio, L/D, of 1.5) inlet duct and its upstream contraction section. The approach systematically applies reduced order modeling, estimator design, sensor placement and control design to improve the aerodynamic performance. The main contribution of this work is the development of a hybrid model reduction approach that attempts to combine the best features of input/output model identification and POD method. We first identify a linear input/output model by using a subspace algorithm. We next project the difference between CFD response and the identified model response onto a set of POD basis. This trajectory is fit to a nonlinear dynamical model to augment the linear input/output model. Thus, the full system is decomposed into a dominant linear subsystem and a low order nonlinear subsystem. The hybrid model is then used for control design and compared with other modeling methods in CFD simulations. Numerical results indicate that the hybrid model accurately predicts the nonlinear behavior of the flow for a 2D diffuser contraction section model. It also performs best in terms of feedback control design and learning control. Since some outputs of interest (e.g., the AIP pressure recovery) are not observable during normal operations, static and dynamic estimators are designed to recreate the information from available sensor measurements. The latter also provides a state estimation for feedback controller. Based on the reduced order models and estimators, different controllers are designed to improve the aerodynamic performance of the contraction section and inlet duct. The integrated control methodology is evaluated with CFD simulations. Numerical results demonstrate the feasibility and efficacy of the active flow control based on reduced order models. Our reduced order models not only generate a good approximation of the nonlinear flow dynamics over a wide input range, but also help to design controllers that significantly improve the flow response. The tools developed for model reduction, estimator and control design can also be applied to wind tunnel experiment.

Nonlinear identification of the total baroreflex arc: higher-order nonlinearity

PubMed Central

Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru

2016-01-01

The total baroreflex arc is the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP). The nonlinear dynamics of this system were recently characterized. First, Gaussian white noise CSP stimulation was employed in open-loop conditions in normotensive and hypertensive rats with sectioned vagal and aortic depressor nerves. Nonparametric system identification was then applied to measured CSP and AP to establish a second-order nonlinear Uryson model. The aim in this study was to assess the importance of higher-order nonlinear dynamics via development and evaluation of a third-order nonlinear model of the total arc using the same experimental data. Third-order Volterra and Uryson models were developed by employing nonparametric and parametric identification methods. The R2 values between the AP predicted by the best third-order Volterra model and measured AP in response to Gaussian white noise CSP not utilized in developing the model were 0.69 ± 0.03 and 0.70 ± 0.03 for normotensive and hypertensive rats, respectively. The analogous R2 values for the best third-order Uryson model were 0.71 ± 0.03 and 0.73 ± 0.03. These R2 values were not statistically different from the corresponding values for the previously established second-order Uryson model, which were both 0.71 ± 0.03 (P > 0.1). Furthermore, none of the third-order models predicted well-known nonlinear behaviors including thresholding and saturation better than the second-order Uryson model. Additional experiments suggested that the unexplained AP variance was partly due to higher brain center activity. In conclusion, the second-order Uryson model sufficed to represent the sympathetically mediated total arc under the employed experimental conditions. PMID:27629885

A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring.

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

Roettgen, Dan; Seegar, Ben; Tai, Wei Che

Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then theymore » are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.« less

A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint

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

Roettgen, Dan; Seeger, Benjamin; Tai, Wei Che

Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then theymore » are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.« less

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.

How to turn a genetic circuit into a synthetic tunable oscillator, or a bistable switch.

PubMed

Marucci, Lucia; Barton, David A W; Cantone, Irene; Ricci, Maria Aurelia; Cosma, Maria Pia; Santini, Stefania; di Bernardo, Diego; di Bernardo, Mario

2009-12-07

Systems and Synthetic Biology use computational models of biological pathways in order to study in silico the behaviour of biological pathways. Mathematical models allow to verify biological hypotheses and to predict new possible dynamical behaviours. Here we use the tools of non-linear analysis to understand how to change the dynamics of the genes composing a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-engineering and Modelling Assessment (IRMA). Guided by previous theoretical results that make the dynamics of a biological network depend on its topological properties, through the use of simulation and continuation techniques, we found that the network can be easily turned into a robust and tunable synthetic oscillator or a bistable switch. Our results provide guidelines to properly re-engineering in vivo the network in order to tune its dynamics.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

In order to better understand the dynamic processes of a real game system, we need an appropriate dynamics model, so to evaluate the validity of a model is not a trivial task. Here, we demonstrate an approach, considering the dynamical macroscope patterns of angular momentum and speed as the measurement variables, to evaluate the validity of various dynamics models. Using the data in real time Rock-Paper-Scissors (RPS) games experiments, we obtain the experimental dynamic patterns, and then derive the related theoretical dynamic patterns from a series of typical dynamics models respectively. By testing the goodness-of-fit between the experimental and theoretical patterns, the validity of the models can be evaluated. One of the results in our study case is that, among all the nonparametric models tested, the best-known Replicator dynamics model performs almost worst, while the Projection dynamics model performs best. Besides providing new empirical macroscope patterns of social dynamics, we demonstrate that the approach can be an effective and rigorous tool to test game dynamics models. Fundamental Research Funds for the Central Universities (SSEYI2014Z) and the National Natural Science Foundation of China (Grants No. 61503062).

Higher-Order Hurst Signatures: Dynamical Information in Time Series

NASA Astrophysics Data System (ADS)

Ferenbaugh, Willis

2005-10-01

Understanding and comparing time series from different systems requires characteristic measures of the dynamics embedded in the series. The Hurst exponent is a second-order dynamical measure of a time series which grew up within the blossoming fractal world of Mandelbrot. This characteristic measure is directly related to the behavior of the autocorrelation, the power-spectrum, and other second-order things. And as with these other measures, the Hurst exponent captures and quantifies some but not all of the intrinsic nature of a series. The more elusive characteristics live in the phase spectrum and the higher-order spectra. This research is a continuing quest to (more) fully characterize the dynamical information in time series produced by plasma experiments or models. The goal is to supplement the series information which can be represented by a Hurst exponent, and we would like to develop supplemental techniques in analogy with Hurst's original R/S analysis. These techniques should be another way to plumb the higher-order dynamics.

MCore: A High-Order Finite-Volume Dynamical Core for Atmospheric General Circulation Models

NASA Astrophysics Data System (ADS)

Ullrich, P.; Jablonowski, C.

2011-12-01

The desire for increasingly accurate predictions of the atmosphere has driven numerical models to smaller and smaller resolutions, while simultaneously exponentially driving up the cost of existing numerical models. Even with the modern rapid advancement of computational performance, it is estimated that it will take more than twenty years before existing models approach the scales needed to resolve atmospheric convection. However, smarter numerical methods may allow us to glimpse the types of results we would expect from these fine-scale simulations while only requiring a fraction of the computational cost. The next generation of atmospheric models will likely need to rely on both high-order accuracy and adaptive mesh refinement in order to properly capture features of interest. We present our ongoing research on developing a set of ``smart'' numerical methods for simulating the global non-hydrostatic fluid equations which govern atmospheric motions. We have harnessed a high-order finite-volume based approach in developing an atmospheric dynamical core on the cubed-sphere. This type of method is desirable for applications involving adaptive grids, since it has been shown that spuriously reflected wave modes are intrinsically damped out under this approach. The model further makes use of an implicit-explicit Runge-Kutta-Rosenbrock (IMEX-RKR) time integrator for accurate and efficient coupling of the horizontal and vertical model components. We survey the algorithmic development of the model and present results from idealized dynamical core test cases, as well as give a glimpse at future work with our model.

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.

Effects of distribution of infection rate on epidemic models

NASA Astrophysics Data System (ADS)

Lachiany, Menachem; Louzoun, Yoram

2016-08-01

A goal of many epidemic models is to compute the outcome of the epidemics from the observed infected early dynamics. However, often, the total number of infected individuals at the end of the epidemics is much lower than predicted from the early dynamics. This discrepancy is argued to result from human intervention or nonlinear dynamics not incorporated in standard models. We show that when variability in infection rates is included in standard susciptible-infected-susceptible (SIS ) and susceptible-infected-recovered (SIR ) models the total number of infected individuals in the late dynamics can be orders lower than predicted from the early dynamics. This discrepancy holds for SIS and SIR models, where the assumption that all individuals have the same sensitivity is eliminated. In contrast with network models, fixed partnerships are not assumed. We derive a moment closure scheme capturing the distribution of sensitivities. We find that the shape of the sensitivity distribution does not affect R0 or the number of infected individuals in the early phases of the epidemics. However, a wide distribution of sensitivities reduces the total number of removed individuals in the SIR model and the steady-state infected fraction in the SIS model. The difference between the early and late dynamics implies that in order to extrapolate the expected effect of the epidemics from the initial phase of the epidemics, the rate of change in the average infectivity should be computed. These results are supported by a comparison of the theoretical model to the Ebola epidemics and by numerical simulation.

Asymmetric statistics of order books: The role of discreteness and evidence for strategic order placement

NASA Astrophysics Data System (ADS)

Zaccaria, A.; Cristelli, M.; Alfi, V.; Ciulla, F.; Pietronero, L.

2010-06-01

We show that the statistics of spreads in real order books is characterized by an intrinsic asymmetry due to discreteness effects for even or odd values of the spread. An analysis of data from the New York Stock Exchange (NYSE) order book points out that traders’ strategies contribute to this asymmetry. We also investigate this phenomenon in the framework of a microscopic model and, by introducing a nonuniform deposition mechanism for limit orders, we are able to quantitatively reproduce the asymmetry found in the experimental data. Simulations of our model also show a realistic dynamics with a sort of intermittent behavior characterized by long periods in which the order book is compact and liquid interrupted by volatile configurations. The order placement strategies produce a nontrivial behavior of the spread relaxation dynamics which is similar to the one observed in real markets.

Stability analysis and wave dynamics of an extended hybrid traffic flow model

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Li, Wei-Kang; Yan, Bo-Wen; Jia, Bin; Wang, Ji-Xin

2018-02-01

The stability analysis and wave dynamic properties of an extended hybrid traffic flow model, WZY model, are intensively studied in this paper. The linear stable condition obtained by the linear stability analysis is presented. Besides, by means of analyzing Korteweg-de Vries equation, we present soliton waves in the metastable region. Moreover, the multiscale perturbation technique is applied to derive the traveling wave solution of the model. Furthermore, by means of performing Darboux transformation, the first-order and second-order doubly-periodic solutions and rational solutions are presented. It can be found that analytical solutions match well with numerical simulations.

Two degree of freedom internal model control-PID design for LFC of power systems via logarithmic approximations.

PubMed

Singh, Jay; Chattterjee, Kalyan; Vishwakarma, C B

2018-01-01

Load frequency controller has been designed for reduced order model of single area and two-area reheat hydro-thermal power system through internal model control - proportional integral derivative (IMC-PID) control techniques. The controller design method is based on two degree of freedom (2DOF) internal model control which combines with model order reduction technique. Here, in spite of taking full order system model a reduced order model has been considered for 2DOF-IMC-PID design and the designed controller is directly applied to full order system model. The Logarithmic based model order reduction technique is proposed to reduce the single and two-area high order power systems for the application of controller design.The proposed IMC-PID design of reduced order model achieves good dynamic response and robustness against load disturbance with the original high order system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

PubMed

Russo, Michael F; Garrison, Barbara J

2006-10-15

Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

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

Hybrid RANS-LES using high order numerical methods

NASA Astrophysics Data System (ADS)

Henry de Frahan, Marc; Yellapantula, Shashank; Vijayakumar, Ganesh; Knaus, Robert; Sprague, Michael

2017-11-01

Understanding the impact of wind turbine wake dynamics on downstream turbines is particularly important for the design of efficient wind farms. Due to their tractable computational cost, hybrid RANS/LES models are an attractive framework for simulating separation flows such as the wake dynamics behind a wind turbine. High-order numerical methods can be computationally efficient and provide increased accuracy in simulating complex flows. In the context of LES, high-order numerical methods have shown some success in predictions of turbulent flows. However, the specifics of hybrid RANS-LES models, including the transition region between both modeling frameworks, pose unique challenges for high-order numerical methods. In this work, we study the effect of increasing the order of accuracy of the numerical scheme in simulations of canonical turbulent flows using RANS, LES, and hybrid RANS-LES models. We describe the interactions between filtering, model transition, and order of accuracy and their effect on turbulence quantities such as kinetic energy spectra, boundary layer evolution, and dissipation rate. This work was funded by the U.S. Department of Energy, Exascale Computing Project, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.

Langevin Dynamics, Large Deviations and Instantons for the Quasi-Geostrophic Model and Two-Dimensional Euler Equations

NASA Astrophysics Data System (ADS)

Bouchet, Freddy; Laurie, Jason; Zaboronski, Oleg

2014-09-01

We investigate a class of simple models for Langevin dynamics of turbulent flows, including the one-layer quasi-geostrophic equation and the two-dimensional Euler equations. Starting from a path integral representation of the transition probability, we compute the most probable fluctuation paths from one attractor to any state within its basin of attraction. We prove that such fluctuation paths are the time reversed trajectories of the relaxation paths for a corresponding dual dynamics, which are also within the framework of quasi-geostrophic Langevin dynamics. Cases with or without detailed balance are studied. We discuss a specific example for which the stationary measure displays either a second order (continuous) or a first order (discontinuous) phase transition and a tricritical point. In situations where a first order phase transition is observed, the dynamics are bistable. Then, the transition paths between two coexisting attractors are instantons (fluctuation paths from an attractor to a saddle), which are related to the relaxation paths of the corresponding dual dynamics. For this example, we show how one can analytically determine the instantons and compute the transition probabilities for rare transitions between two attractors.

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.

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.

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.

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.

Integrated Model Reduction and Control of Aircraft with Flexible Wings

NASA Technical Reports Server (NTRS)

Swei, Sean Shan-Min; Zhu, Guoming G.; Nguyen, Nhan T.

2013-01-01

This paper presents an integrated approach to the modeling and control of aircraft with exible wings. The coupled aircraft rigid body dynamics with a high-order elastic wing model can be represented in a nite dimensional state-space form. Given a set of desired output covariance, a model reduction process is performed by using the weighted Modal Cost Analysis (MCA). A dynamic output feedback controller, which is designed based on the reduced-order model, is developed by utilizing output covariance constraint (OCC) algorithm, and the resulting OCC design weighting matrix is used for the next iteration of the weighted cost analysis. This controller is then validated for full-order evaluation model to ensure that the aircraft's handling qualities are met and the uttering motion of the wings suppressed. An iterative algorithm is developed in CONDUIT environment to realize the integration of model reduction and controller design. The proposed integrated approach is applied to NASA Generic Transport Model (GTM) for demonstration.

Application of partial differential equation modeling of the control/structural dynamics of flexible spacecraft

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr.; Rajiyah, H.

1991-01-01

Partial differential equations for modeling the structural dynamics and control systems of flexible spacecraft are applied here in order to facilitate systems analysis and optimization of these spacecraft. Example applications are given, including the structural dynamics of SCOLE, the Solar Array Flight Experiment, the Mini-MAST truss, and the LACE satellite. The development of related software is briefly addressed.

Instantaneous nonlinear assessment of complex cardiovascular dynamics by Laguerre-Volterra point process models.

PubMed

Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

2013-01-01

We report an exemplary study of instantaneous assessment of cardiovascular dynamics performed using point-process nonlinear models based on Laguerre expansion of the linear and nonlinear Wiener-Volterra kernels. As quantifiers, instantaneous measures such as high order spectral features and Lyapunov exponents can be estimated from a quadratic and cubic autoregressive formulation of the model first order moment, respectively. Here, these measures are evaluated on heartbeat series coming from 16 healthy subjects and 14 patients with Congestive Hearth Failure (CHF). Data were gathered from the on-line repository PhysioBank, which has been taken as landmark for testing nonlinear indices. Results show that the proposed nonlinear Laguerre-Volterra point-process methods are able to track the nonlinear and complex cardiovascular dynamics, distinguishing significantly between CHF and healthy heartbeat series.

Stochastic modeling and control system designs of the NASA/MSFC Ground Facility for large space structures: The maximum entropy/optimal projection approach

NASA Technical Reports Server (NTRS)

Hsia, Wei-Shen

1986-01-01

In the Control Systems Division of the Systems Dynamics Laboratory of the NASA/MSFC, a Ground Facility (GF), in which the dynamics and control system concepts being considered for Large Space Structures (LSS) applications can be verified, was designed and built. One of the important aspects of the GF is to design an analytical model which will be as close to experimental data as possible so that a feasible control law can be generated. Using Hyland's Maximum Entropy/Optimal Projection Approach, a procedure was developed in which the maximum entropy principle is used for stochastic modeling and the optimal projection technique is used for a reduced-order dynamic compensator design for a high-order plant.

Modelling and simulation of a heat exchanger

NASA Technical Reports Server (NTRS)

Xia, Lei; Deabreu-Garcia, J. Alex; Hartley, Tom T.

1991-01-01

Two models for two different control systems are developed for a parallel heat exchanger. First by spatially lumping a heat exchanger model, a good approximate model which has a high system order is produced. Model reduction techniques are applied to these to obtain low order models that are suitable for dynamic analysis and control design. The simulation method is discussed to ensure a valid simulation result.

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.

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.

A role for low-order system dynamics models in urban health policy making.

PubMed

Newell, Barry; Siri, José

2016-10-01

Cities are complex adaptive systems whose responses to policy initiatives emerge from feedback interactions between their parts. Urban policy makers must routinely deal with both detail and dynamic complexity, coupled with high levels of diversity, uncertainty and contingency. In such circumstances, it is difficult to generate reliable predictions of health-policy outcomes. In this paper we explore the potential for low-order system dynamics (LOSD) models to make a contribution towards meeting this challenge. By definition, LOSD models have few state variables (≤5), illustrate the non-linear effects caused by feedback and accumulation, and focus on endogenous dynamics generated within well-defined boundaries. We suggest that experience with LOSD models can help practitioners to develop an understanding of basic principles of system dynamics, giving them the ability to 'see with new eyes'. Because efforts to build a set of LOSD models can help a transdisciplinary group to develop a shared, coherent view of the problems that they seek to tackle, such models can also become the foundations of 'powerful ideas'. Powerful ideas are conceptual metaphors that provide the members of a policy-making group with the a priori shared context required for effective communication, the co-production of knowledge, and the collaborative development of effective public health policies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validation of Potential Models for Li2O in Classical Molecular Dynamics Simulation

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

Oda, Takuji; Oya, Yasuhisa; Tanaka, Satoru

2007-08-01

Four Buckingham-type pairwise potential models for Li2O were assessed by molecular static and dynamics simulations. In the static simulation, all models afforded acceptable agreement with experimental values and ab initio calculation results for the crystalline properties. Moreover, the superionic phase transition was realized in the dynamics simulation. However, the Li diffusivity and the lattice expansion were not adequately reproduced at the same time by any model. When using these models in future radiation simulation, these features should be taken into account, in order to reduce the model dependency of the results.

Nonlinear identification of the total baroreflex arc.

PubMed

Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru; Mukkamala, Ramakrishna

2015-12-15

The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This "Uryson" model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. Copyright © 2015 the American Physiological Society.

Nonlinear identification of the total baroreflex arc

PubMed Central

Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru

2015-01-01

The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This “Uryson” model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. PMID:26354845

Generation of localized patterns in anharmonic lattices with cubic-quintic nonlinearities and fourth-order dispersion via a variational approach

NASA Astrophysics Data System (ADS)

Wamba, Etienne; Tchakoutio Nguetcho, Aurélien S.

2018-05-01

We use the time-dependent variational method to examine the formation of localized patterns in dynamically unstable anharmonic lattices with cubic-quintic nonlinearities and fourth-order dispersion. The governing equation is an extended nonlinear Schrödinger equation known for modified Frankel-Kontorova models of atomic lattices and here derived from an extended Bose-Hubbard model of bosonic lattices with local three-body interactions. In presence of modulated waves, we derive and investigate the ordinary differential equations for the time evolution of the amplitude and phase of dynamical perturbation. Through an effective potential, we find the modulationally unstable domains of the lattice and discuss the effect of the fourth-order dispersion in the dynamics. Direct numerical simulations are performed to support our analytical results, and a good agreement is found. Various types of localized patterns, including breathers and solitonic chirped-like pulses, form in the system as a result of interplay between the cubic-quintic nonlinearities and the second- and fourth-order dispersions.

Development of collision dynamics models to estimate the results of full-scale rail vehicle impact tests : Tufts University Master's Thesis

DOT National Transportation Integrated Search

2000-11-01

In an effort to study occupant survivability in train collisions, analyses and tests were conducted to understand and improve the crashworthiness of rail vehicles. A collision dynamics model was developed in order to estimate the rigid body motion of...

Non-equilibrium many-body influence on mode-locked Vertical External-cavity Surface-emitting Lasers

NASA Astrophysics Data System (ADS)

Kilen, Isak Ragnvald

Vertical external-cavity surface-emitting lasers are ideal testbeds for studying the influence of the non-equilibrium many-body dynamics on mode locking. As we will show in this thesis, ultra short pulse generation involves a marked departure from Fermi carrier distributions assumed in prior theoretical studies. A quantitative model of the mode locking dynamics is presented, where the semiconductor Bloch equations with Maxwell's equation are coupled, in order to study the influences of quantum well carrier scattering on mode locking dynamics. This is the first work where the full model is solved without adiabatically eliminating the microscopic polarizations. In many instances we find that higher order correlation contributions (e.g. polarization dephasing, carrier scattering, and screening) can be represented by rate models, with the effective rates extracted at the level of second Born-Markov approximations. In other circumstances, such as continuous wave multi-wavelength lasing, we are forced to fully include these higher correlation terms. In this thesis we identify the key contributors that control mode locking dynamics, the stability of single pulse mode-locking, and the influence of higher order correlation in sustaining multi-wavelength continuous wave operation.

Non-Gaussian lineshapes and dynamics of time-resolved linear and nonlinear (correlation) spectra.

PubMed

Dinpajooh, Mohammadhasan; Matyushov, Dmitry V

2014-07-17

Signatures of nonlinear and non-Gaussian dynamics in time-resolved linear and nonlinear (correlation) 2D spectra are analyzed in a model considering a linear plus quadratic dependence of the spectroscopic transition frequency on a Gaussian nuclear coordinate of the thermal bath (quadratic coupling). This new model is contrasted to the commonly assumed linear dependence of the transition frequency on the medium nuclear coordinates (linear coupling). The linear coupling model predicts equality between the Stokes shift and equilibrium correlation functions of the transition frequency and time-independent spectral width. Both predictions are often violated, and we are asking here the question of whether a nonlinear solvent response and/or non-Gaussian dynamics are required to explain these observations. We find that correlation functions of spectroscopic observables calculated in the quadratic coupling model depend on the chromophore's electronic state and the spectral width gains time dependence, all in violation of the predictions of the linear coupling models. Lineshape functions of 2D spectra are derived assuming Ornstein-Uhlenbeck dynamics of the bath nuclear modes. The model predicts asymmetry of 2D correlation plots and bending of the center line. The latter is often used to extract two-point correlation functions from 2D spectra. The dynamics of the transition frequency are non-Gaussian. However, the effect of non-Gaussian dynamics is limited to the third-order (skewness) time correlation function, without affecting the time correlation functions of higher order. The theory is tested against molecular dynamics simulations of a model polar-polarizable chromophore dissolved in a force field water.

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.

Inverse Dynamics Model for the Ankle Joint with Applications in Tibia Malleolus Fracture

NASA Astrophysics Data System (ADS)

Budescu, E.; Merticaru, E.; Chirazi, M.

The paper presents a biomechanical model of the ankle joint, in order to determine the force and the torque of reaction into the articulation, through inverse dynamic analysis, in various stages of the gait. Thus, knowing the acceleration of the foot and the reaction force between foot and ground during the gait, determined by experimental measurement, there was calculated, for five different positions of the foot, the joint reaction forces, on the basis of dynamic balance equations. The values numerically determined were compared with the admissible forces appearing in the technical systems of osteosynthesis of tibia malleolus fracture, in order to emphasize the motion restrictions during bone healing.

Aircraft Pitch Control With Fixed Order LQ Compensators

NASA Technical Reports Server (NTRS)

Green, James; Ashokkumar, C. R.; Homaifar, Abdollah

1997-01-01

This paper considers a given set of fixed order compensators for aircraft pitch control problem. By augmenting compensator variables to the original state equations of the aircraft, a new dynamic model is considered to seek a LQ controller. While the fixed order compensators can achieve a set of desired poles in a specified region, LQ formulation provides the inherent robustness properties. The time response for ride quality is significantly improved with a set of dynamic compensators.

Aircraft Pitch Control with Fixed Order LQ Compensators

NASA Technical Reports Server (NTRS)

Green, James; Ashokkumar, Cr.; Homaifar, A.

1997-01-01

This paper considers a given set of fixed order compensators for aircraft pitch control problem. By augmenting compensator variables to the original state equations of the aircraft, a new dynamic model is considered to seek a LQ controller. While the fixed order compensators can achieve a set of desired poles in a specified region, LQ formulation provides the inherent robustness properties. The time response for ride quality is significantly improved with a set of dynamic compensators.

X-56A MUTT: Aeroservoelastic Modeling

NASA Technical Reports Server (NTRS)

Ouellette, Jeffrey A.

2015-01-01

For the NASA X-56a Program, Armstrong Flight Research Center has been developing a set of linear states space models that integrate the flight dynamics and structural dynamics. These high order models are needed for the control design, control evaluation, and test input design. The current focus has been on developing stiff wing models to validate the current modeling approach. The extension of the modeling approach to the flexible wings requires only a change in the structural model. Individual subsystems models (actuators, inertial properties, etc.) have been validated by component level ground tests. Closed loop simulation of maneuvers designed to validate the flight dynamics of these models correlates very well flight test data. The open loop structural dynamics are also shown to correlate well to the flight test data.

A non-linear mathematical model for dynamic analysis of spur gears including shaft and bearing dynamics

NASA Technical Reports Server (NTRS)

Ozguven, H. Nevzat

1991-01-01

A six-degree-of-freedom nonlinear semi-definite model with time varying mesh stiffness has been developed for the dynamic analysis of spur gears. The model includes a spur gear pair, two shafts, two inertias representing load and prime mover, and bearings. As the shaft and bearing dynamics have also been considered in the model, the effect of lateral-torsional vibration coupling on the dynamics of gears can be studied. In the nonlinear model developed several factors such as time varying mesh stiffness and damping, separation of teeth, backlash, single- and double-sided impacts, various gear errors and profile modifications have been considered. The dynamic response to internal excitation has been calculated by using the 'static transmission error method' developed. The software prepared (DYTEM) employs the digital simulation technique for the solution, and is capable of calculating dynamic tooth and mesh forces, dynamic factors for pinion and gear, dynamic transmission error, dynamic bearing forces and torsions of shafts. Numerical examples are given in order to demonstrate the effect of shaft and bearing dynamics on gear dynamics.

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

2016-11-01

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.

Jacobian projection reduced-order models for dynamic systems with contact nonlinearities

NASA Astrophysics Data System (ADS)

Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.

2018-02-01

In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.

A robust computational technique for model order reduction of two-time-scale discrete systems via genetic algorithms.

PubMed

Alsmadi, Othman M K; Abo-Hammour, Zaer S

2015-01-01

A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA) with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

Communication: Accurate higher-order van der Waals coefficients between molecules from a model dynamic multipole polarizability

DOE PAGES

Tao, Jianmin; Rappe, Andrew M.

2016-01-20

Due to the absence of the long-range van der Waals (vdW) interaction, conventional density functional theory (DFT) often fails in the description of molecular complexes and solids. In recent years, considerable progress has been made in the development of the vdW correction. However, the vdW correction based on the leading-order coefficient C 6 alone can only achieve limited accuracy, while accurate modeling of higher-order coefficients remains a formidable task, due to the strong non-additivity effect. Here, we apply a model dynamic multipole polarizability within a modified single-frequency approximation to calculate C 8 and C 10 between small molecules. We findmore » that the higher-order vdW coefficients from this model can achieve remarkable accuracy, with mean absolute relative deviations of 5% for C 8 and 7% for C 10. As a result, inclusion of accurate higher-order contributions in the vdW correction will effectively enhance the predictive power of DFT in condensed matter physics and quantum chemistry.« less

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.

Lagrangian-Hamiltonian unified formalism for autonomous higher order dynamical systems

NASA Astrophysics Data System (ADS)

Prieto-Martínez, Pedro Daniel; Román-Roy, Narciso

2011-09-01

The Lagrangian-Hamiltonian unified formalism of Skinner and Rusk was originally stated for autonomous dynamical systems in classical mechanics. It has been generalized for non-autonomous first-order mechanical systems, as well as for first-order and higher order field theories. However, a complete generalization to higher order mechanical systems is yet to be described. In this work, after reviewing the natural geometrical setting and the Lagrangian and Hamiltonian formalisms for higher order autonomous mechanical systems, we develop a complete generalization of the Lagrangian-Hamiltonian unified formalism for these kinds of systems, and we use it to analyze some physical models from this new point of view.

a Numerical Comparison of Langrange and Kane's Methods of AN Arm Segment

NASA Astrophysics Data System (ADS)

Rambely, Azmin Sham; Halim, Norhafiza Ab.; Ahmad, Rokiah Rozita

A 2-D model of a two-link kinematic chain is developed using two dynamics equations of motion, namely Kane's and Lagrange Methods. The dynamics equations are reduced to first order differential equation and solved using modified Euler and fourth order Runge Kutta to approximate the shoulder and elbow joint angles during a smash performance in badminton. Results showed that Runge-Kutta produced a better and exact approximation than that of modified Euler and both dynamic equations produced better absolute errors.

A simple running model with rolling contact and its role as a template for dynamic locomotion on a hexapod robot.

PubMed

Huang, Ke-Jung; Huang, Chun-Kai; Lin, Pei-Chun

2014-10-07

We report on the development of a robot's dynamic locomotion based on a template which fits the robot's natural dynamics. The developed template is a low degree-of-freedom planar model for running with rolling contact, which we call rolling spring loaded inverted pendulum (R-SLIP). Originating from a reduced-order model of the RHex-style robot with compliant circular legs, the R-SLIP model also acts as the template for general dynamic running. The model has a torsional spring and a large circular arc as the distributed foot, so during locomotion it rolls on the ground with varied equivalent linear stiffness. This differs from the well-known spring loaded inverted pendulum (SLIP) model with fixed stiffness and ground contact points. Through dimensionless steps-to-fall and return map analysis, within a wide range of parameter spaces, the R-SLIP model is revealed to have self-stable gaits and a larger stability region than that of the SLIP model. The R-SLIP model is then embedded as the reduced-order 'template' in a more complex 'anchor', the RHex-style robot, via various mapping definitions between the template and the anchor. Experimental validation confirms that by merely deploying the stable running gaits of the R-SLIP model on the empirical robot with simple open-loop control strategy, the robot can easily initiate its dynamic running behaviors with a flight phase and can move with similar body state profiles to those of the model, in all five testing speeds. The robot, embedded with the SLIP model but performing walking locomotion, further confirms the importance of finding an adequate template of the robot for dynamic locomotion.

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.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

DTIC Science & Technology

2012-09-30

characterization of extratropical storms and extremes and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson...simulating and predicting a wide range of climate phenomena including ENSO, tropical Atlantic sea surface temperatures (SSTs), storm track variability...into empirical prediction models. Use observations to improve low-order dynamical MJO models. Adam Sobel, Daehyun Kim. Extratropical variability

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.

Study of atmospheric dynamics

NASA Technical Reports Server (NTRS)

Mcnider, Richard T.; Christy, John R.; Cox, Gregory N.

1993-01-01

In order to better understand the dynamics of the global atmosphere, a data set of precision temperature measurements was developed using the NASA built Microwave Sounding Unit. Modeling research was carried out to validate global model outputs using various satellite data. Idealized flows in a rotating annulus were studied and applied to the general circulation of the atmosphere. Dynamic stratospheric ozone fluctuations were investigated. An extensive bibliography and several reprints are appended.

Recent literature on structural modeling, identification, and analysis

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1990-01-01

The literature on the mathematical modeling of large space structures is first reviewed, with attention given to continuum models, model order reduction, substructuring, and computational techniques. System identification and mode verification are then discussed with reference to the verification of mathematical models of large space structures. In connection with analysis, the paper surveys recent research on eigensolvers and dynamic response solvers for large-order finite-element-based models.

Evolution of a beam dynamics model for the transport line in a proton therapy facility

NASA Astrophysics Data System (ADS)

Rizzoglio, V.; Adelmann, A.; Baumgarten, C.; Frey, M.; Gerbershagen, A.; Meer, D.; Schippers, J. M.

2017-12-01

During the conceptual design of an accelerator or beamline, first-order beam dynamics models are essential for studying beam properties. However, they can only produce approximate results. During commissioning, these approximate results are compared to measurements, which will rarely coincide if the model does not include the relevant physics. It is therefore essential that this linear model is extended to include higher-order effects. In this paper, the effects of particle-matter interaction have been included in the model of the transport lines in the proton therapy facility at the Paul Scherrer Institut (PSI) in Switzerland. The first-order models of these beamlines provide an approximated estimation of beam size, energy loss and transmission. To improve the performance of the facility, a more precise model was required and has been developed with opal (Object Oriented Parallel Accelerator Library), a multiparticle open source beam dynamics code. In opal, the Monte Carlo simulations of Coulomb scattering and energy loss are performed seamless with the particle tracking. Beside the linear optics, the influence of the passive elements (e.g., degrader, collimators, scattering foils, and air gaps) on the beam emittance and energy spread can be analyzed in the new model. This allows for a significantly improved precision in the prediction of beam transmission and beam properties. The accuracy of the opal model has been confirmed by numerous measurements.

A steady state pressure drop model for screen channel liquid acquisition devices

NASA Astrophysics Data System (ADS)

Hartwig, J. W.; Darr, S. R.; McQuillen, J. B.; Rame, E.; Chato, D. J.

2014-11-01

This paper presents the derivation of a simplified one dimensional (1D) steady state pressure drop model for flow through a porous liquid acquisition device (LAD) inside a cryogenic propellant tank. Experimental data is also presented from cryogenic LAD tests in liquid hydrogen (LH2) and liquid oxygen (LOX) to compare against the simplified model and to validate the model at cryogenic temperatures. The purpose of the experiments was to identify the various pressure drop contributions in the analytical model which govern LAD channel behavior during dynamic, steady state outflow. LH2 pipe flow of LAD screen samples measured the second order flow-through-screen (FTS) pressure drop, horizontal LOX LAD outflow tests determined the relative magnitude of the third order frictional and dynamic losses within the channel, while LH2 inverted vertical outflow tests determined the magnitude of the first order hydrostatic pressure loss and validity of the full 1D model. When compared to room temperature predictions, the FTS pressure drop is shown to be temperature dependent, with a significant increase in flow resistance at LH2 temperatures. Model predictions of frictional and dynamic losses down the channel compare qualitatively with LOX LADs data. Meanwhile, the 1D model predicted breakdown points track the trends in the LH2 inverted outflow experimental results, with discrepancies being due to a non-uniform injection velocity across the LAD screen not accounted for in the model.

Design an optimum safety policy for personnel safety management - A system dynamic approach

NASA Astrophysics Data System (ADS)

Balaji, P.

2014-10-01

Personnel safety management (PSM) ensures that employee's work conditions are healthy and safe by various proactive and reactive approaches. Nowadays it is a complex phenomenon because of increasing dynamic nature of organisations which results in an increase of accidents. An important part of accident prevention is to understand the existing system properly and make safety strategies for that system. System dynamics modelling appears to be an appropriate methodology to explore and make strategy for PSM. Many system dynamics models of industrial systems have been built entirely for specific host firms. This thesis illustrates an alternative approach. The generic system dynamics model of Personnel safety management was developed and tested in a host firm. The model was undergone various structural, behavioural and policy tests. The utility and effectiveness of model was further explored through modelling a safety scenario. In order to create effective safety policy under resource constraint, DOE (Design of experiment) was used. DOE uses classic designs, namely, fractional factorials and central composite designs. It used to make second order regression equation which serve as an objective function. That function was optimized under budget constraint and optimum value used for safety policy which shown greatest improvement in overall PSM. The outcome of this research indicates that personnel safety management model has the capability for acting as instruction tool to improve understanding of safety management and also as an aid to policy making.

Modeling Personnel Turnover in the Parametric Organization

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1991-01-01

A primary issue in organizing a new parametric cost analysis function is to determine the skill mix and number of personnel required. The skill mix can be obtained by a functional decomposition of the tasks required within the organization and a matrixed correlation with educational or experience backgrounds. The number of personnel is a function of the skills required to cover all tasks, personnel skill background and cross training, the intensity of the workload for each task, migration through various tasks by personnel along a career path, personnel hiring limitations imposed by management and the applicant marketplace, personnel training limitations imposed by management and personnel capability, and the rate at which personnel leave the organization for whatever reason. Faced with the task of relating all of these organizational facets in order to grow a parametric cost analysis (PCA) organization from scratch, it was decided that a dynamic model was required in order to account for the obvious dynamics of the forming organization. The challenge was to create such a simple model which would be credible during all phases of organizational development. The model development process was broken down into the activities of determining the tasks required for PCA, determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the dynamic model, implementing the dynamic model, and testing the dynamic model.

Exploring the Lyapunov instability properties of high-dimensional atmospheric and climate models

NASA Astrophysics Data System (ADS)

De Cruz, Lesley; Schubert, Sebastian; Demaeyer, Jonathan; Lucarini, Valerio; Vannitsem, Stéphane

2018-05-01

The stability properties of intermediate-order climate models are investigated by computing their Lyapunov exponents (LEs). The two models considered are PUMA (Portable University Model of the Atmosphere), a primitive-equation simple general circulation model, and MAOOAM (Modular Arbitrary-Order Ocean-Atmosphere Model), a quasi-geostrophic coupled ocean-atmosphere model on a β-plane. We wish to investigate the effect of the different levels of filtering on the instabilities and dynamics of the atmospheric flows. Moreover, we assess the impact of the oceanic coupling, the dissipation scheme, and the resolution on the spectra of LEs. The PUMA Lyapunov spectrum is computed for two different values of the meridional temperature gradient defining the Newtonian forcing to the temperature field. The increase in the gradient gives rise to a higher baroclinicity and stronger instabilities, corresponding to a larger dimension of the unstable manifold and a larger first LE. The Kaplan-Yorke dimension of the attractor increases as well. The convergence rate of the rate function for the large deviation law of the finite-time Lyapunov exponents (FTLEs) is fast for all exponents, which can be interpreted as resulting from the absence of a clear-cut atmospheric timescale separation in such a model. The MAOOAM spectra show that the dominant atmospheric instability is correctly represented even at low resolutions. However, the dynamics of the central manifold, which is mostly associated with the ocean dynamics, is not fully resolved because of its associated long timescales, even at intermediate orders. As expected, increasing the mechanical atmosphere-ocean coupling coefficient or introducing a turbulent diffusion parametrisation reduces the Kaplan-Yorke dimension and Kolmogorov-Sinai entropy. In all considered configurations, we are not yet in the regime in which one can robustly define large deviation laws describing the statistics of the FTLEs. This paper highlights the need to investigate the natural variability of the atmosphere-ocean coupled dynamics by associating rate of growth and decay of perturbations with the physical modes described using the formalism of the covariant Lyapunov vectors and considering long integrations in order to disentangle the dynamical processes occurring at all timescales.

Non-linear dynamic analysis of geared systems. Final Report Ph.D. Thesis

NASA Technical Reports Server (NTRS)

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

1990-01-01

Under driving conditions, a typical geared system may be subjected to large dynamic loads. Also, the vibration level of the geared system is directly related to the noise radiated from the gear box. The steady state dynamic behavior of the system is examined in order to design reliable and quiet transmissions. The scope is limited to a system containing a spur gear pair with backlash and periodically time varying mesh stiffness, and rolling element bearings with clearance type nonlinearities. The internal static transmission error at the gear mesh, which is of importance from high frequency noise and vibration control view point, is considered in the formulation in sinusoidal or periodic form. 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 forced vibration characteristics are investigated. Several reduced order LTI models are developed and validated by comparing their eigen solutions with the finite element model results. Using the reduced order formulations, a three degree of freedom dynamic model is developed which includes nonlinearities associated with radical clearances in the radial rolling element bearings, backlash between a spur gear pair and periodically varying gear mesh stiffness. As a limiting case, a single degree of freedom model of the spur gear pair with backlash is considered and mathematical conditions for tooth separation and back collision are defined. Both digital simulation technique and analytical models such as method of harmonic balance and the method of multiple scales were used to develop the steady state frequency response characteristics for various nonlinear and/or time varying cases.

Dynamical arrest with zero complexity: The unusual behavior of the spherical Blume-Emery-Griffiths disordered model

NASA Astrophysics Data System (ADS)

Rainone, Corrado; Ferrari, Ulisse; Paoluzzi, Matteo; Leuzzi, Luca

2015-12-01

The short- and long-time dynamics of model systems undergoing a glass transition with apparent inversion of Kauzmann and dynamical arrest glass transition lines is investigated. These models belong to the class of the spherical mean-field approximation of a spin-1 model with p -body quenched disordered interaction, with p >2 , termed spherical Blume-Emery-Griffiths models. Depending on temperature and chemical potential the system is found in a paramagnetic or in a glassy phase and the transition between these phases can be of a different nature. In specific regions of the phase diagram coexistence of low-density and high-density paramagnets can occur, as well as the coexistence of spin-glass and paramagnetic phases. The exact static solution for the glassy phase is known to be obtained by the one-step replica symmetry breaking ansatz. Different scenarios arise for both the dynamic and the thermodynamic transitions. These include: (i) the usual random first-order transition (Kauzmann-like) for mean-field glasses preceded by a dynamic transition, (ii) a thermodynamic first-order transition with phase coexistence and latent heat, and (iii) a regime of apparent inversion of static transition line and dynamic transition lines, the latter defined as a nonzero complexity line. The latter inversion, though, turns out to be preceded by a dynamical arrest line at higher temperature. Crossover between different regimes is analyzed by solving mode-coupling-theory equations near the boundaries of paramagnetic solutions and the relationship with the underlying statics is discussed.

Relating dynamics of model unentangled, crystallizable polymeric liquids to their local structure

NASA Astrophysics Data System (ADS)

Nguyen, Hong T.; Hoy, Robert S.

We study the liquid-state dynamics of a recently developed, crystallizable bead-spring polymer model. The model possesses a single ground state (NCP, wherein monomers close-pack and chains are nematically aligned) for all finite bending stiffnesses kb, but the solid morphologies formed under cooling vary strongly with kb, varying from NCP to amorphous. We find that systems with kb producing amorphous order are good glass-formers exhibiting the classic Vogel-Fulcher slowdown with decreasing temperature T. In contrast, systems with kb producing crystalline solids exhibit a simpler dynamics when kb is small. Larger kb produce more complex dynamics, but these are associated with the existence of an intermediate nematic liquid rather than glassy slowdown. We relate these differences to local, cluster-level structure measured via TCC analyses. Formation propensities and lifetimes of various clusters (associated with amorphous or crystalline order) vary strongly with kb and T. We relate these differences to those measured by the self-intermediate scattering function and other macroscopic measures of dynamics. Our results should aid in understanding the competition between crystallization and glass-formation in synthetic polymers.

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.

Impact analyses for negative flexural responses (hogging) in railway prestressed concrete sleepers

NASA Astrophysics Data System (ADS)

Kaewunruen, S.; Ishida, T.; Remennikov, AM

2016-09-01

By nature, ballast interacts with railway concrete sleepers in order to provide bearing support to track system. Most train-track dynamic models do not consider the degradation of ballast over time. In fact, the ballast degradation causes differential settlement and impact forces acting on partial and unsupported tracks. Furthermore, localised ballast breakages underneath railseat increase the likelihood of centrebound cracks in concrete sleepers due to the unbalanced support under sleepers. This paper presents a dynamic finite element model of a standard-gauge concrete sleeper in a track system, taking into account the tensionless nature of ballast support. The finite element model was calibrated using static and dynamic responses in the past. In this paper, the effects of centre-bound ballast support on the impact behaviours of sleepers are highlighted. In addition, it is the first to demonstrate the dynamic effects of sleeper length on the dynamic design deficiency in concrete sleepers. The outcome of this study will benefit the rail maintenance criteria of track resurfacing in order to restore ballast profile and appropriate sleeper/ballast interaction.

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

Closed-Loop System Identification Experience for Flight Control Law and Flying Qualities Evaluation of a High Performance Fighter Aircraft

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.

1996-01-01

This paper highlights some of the results and issues associated with estimating models to evaluate control law design methods and design criteria for advanced high performance aircraft. Experimental fighter aircraft such as the NASA-High Alpha Research Vehicle (HARV) have the capability to maneuver at very high angles of attack where nonlinear aerodynamics often predominate. HARV is an experimental F/A-18, configured with thrust vectoring and conformal actuated nose strakes. Identifying closed-loop models for this type of aircraft can be made difficult by nonlinearities and high order characteristics of the system. In this paper, only lateral-directional axes are considered since the lateral-directional control law was specifically designed to produce classical airplane responses normally expected with low-order, rigid-body systems. Evaluation of the control design methodology was made using low-order equivalent systems determined from flight and simulation. This allowed comparison of the closed-loop rigid-body dynamics achieved in flight with that designed in simulation. In flight, the On Board Excitation System was used to apply optimal inputs to lateral stick and pedals at five angles at attack : 5, 20, 30, 45, and 60 degrees. Data analysis and closed-loop model identification were done using frequency domain maximum likelihood. The structure of identified models was a linear state-space model reflecting classical 4th-order airplane dynamics. Input time delays associated with the high-order controller and aircraft system were accounted for in data preprocessing. A comparison of flight estimated models with small perturbation linear design models highlighted nonlinearities in the system and indicated that the closed-loop rigid-body dynamics were sensitive to input amplitudes at 20 and 30 degrees angle of attack.

Closed-Loop System Identification Experience for Flight Control Law and Flying Qualities Evaluation of a High Performance Fighter Aircraft

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.

1999-01-01

This paper highlights some of the results and issues associated with estimating models to evaluate control law design methods and design criteria for advanced high performance aircraft. Experimental fighter aircraft such as the NASA High Alpha Research Vehicle (HARV) have the capability to maneuver at very high angles of attack where nonlinear aerodynamics often predominate. HARV is an experimental F/A-18, configured with thrust vectoring and conformal actuated nose strakes. Identifying closed-loop models for this type of aircraft can be made difficult by nonlinearities and high-order characteristics of the system. In this paper only lateral-directional axes are considered since the lateral-directional control law was specifically designed to produce classical airplane responses normally expected with low-order, rigid-body systems. Evaluation of the control design methodology was made using low-order equivalent systems determined from flight and simulation. This allowed comparison of the closed-loop rigid-body dynamics achieved in flight with that designed in simulation. In flight, the On Board Excitation System was used to apply optimal inputs to lateral stick and pedals at five angles of attack: 5, 20, 30, 45, and 60 degrees. Data analysis and closed-loop model identification were done using frequency domain maximum likelihood. The structure of the identified models was a linear state-space model reflecting classical 4th-order airplane dynamics. Input time delays associated with the high-order controller and aircraft system were accounted for in data preprocessing. A comparison of flight estimated models with small perturbation linear design models highlighted nonlinearities in the system and indicated that the estimated closed-loop rigid-body dynamics were sensitive to input amplitudes at 20 and 30 degrees angle of attack.

Unsymmetric Lanczos model reduction and linear state function observer for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1991-01-01

This report summarizes part of the research work accomplished during the second year of a two-year grant. The research, entitled 'Application of Lanczos Vectors to Control Design of Flexible Structures' concerns various ways to use Lanczos vectors and Krylov vectors to obtain reduced-order mathematical models for use in the dynamic response analyses and in control design studies. This report presents a one-sided, unsymmetric block Lanczos algorithm for model reduction of structural dynamics systems with unsymmetric damping matrix, and a control design procedure based on the theory of linear state function observers to design low-order controllers for flexible structures.

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Spin dynamics of counterrotating Kitaev spirals via duality

NASA Astrophysics Data System (ADS)

Kimchi, Itamar; Coldea, Radu

2016-11-01

Incommensurate spiral order is a common occurrence in frustrated magnetic insulators. Typically, all magnetic moments rotate uniformly, through the same wavevector. However the honeycomb iridates family Li2IrO3 shows an incommensurate order where spirals on neighboring sublattices are counterrotating, giving each moment a different local environment. Theoretically describing its spin dynamics has remained a challenge: The Kitaev interactions proposed to stabilize this state, which arise from strong spin-orbit effects, induce magnon umklapp scattering processes in spin-wave theory. Here we propose an approach via a (Klein) duality transformation into a conventional spiral of a frustrated Heisenberg model, allowing a direct derivation of the dynamical structure factor. We analyze both Kitaev and Dzyaloshinskii-Moriya based models, both of which can stabilize counterrotating spirals, but with different spin dynamics, and we propose experimental tests to identify the origin of counterrotation.

A hierarchy for modeling high speed propulsion systems

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Deabreu, Alex

1991-01-01

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery such as inlets, ramjets, and scramjets. The discussion is separated into four sections: (1) computational fluid dynamics model for the entire nonlinear system or high order nonlinear models; (2) high order linearized model derived from fundamental physics; (3) low order linear models obtained from other high order models; and (4) low order nonlinear models. Included are special considerations on any relevant control system designs. The methods discussed are for the quasi-one dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, moving normal shocks, hammershocks, subsonic combustion via heat addition, temperature dependent gases, detonation, and thermal choking.

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.

Dynamic characteristics of hydrocarbon fuel within the channel at supercritical and pyrolysis condition

NASA Astrophysics Data System (ADS)

Yu, Bin; Zhou, Weixing; Qin, Jiang; Bao, Wen

2017-12-01

Regenerative cooling with fuel as the coolant is used in the scramjet engine. In order to grasp the dynamic characteristics of engine fuel supply processes, this article studies the dynamic characteristics of hydrocarbon fuel within the channel. A one-dimensional dynamic model was proved, the thermal energy storage effect, fuel volume effect and chemical dynamic effect have been considered in the model, the ordinary differential equations were solved using a 4th order Runge-Kutta method. The precision of the model was validated by three groups of experimental data. The effects of input signal, working condition, tube size on the dynamic characteristics of pressure, flow rate, temperature have been simulated. It is found that cracking reaction increased the compressibility of the fuel pyrolysis mixture and lead to longer responding time of outlet flow. The responding time of outlet flow can reach 3s when tube is 5m long which will greatly influence the control performance of the engine thrust system. Meanwhile, when the inlet flow rate appears the step change, the inlet pressure leads to overshoot, the overshoot can reach as much as 100%, such highly transient impulse will result in detrimental effect on fuel pump.

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes

NASA Astrophysics Data System (ADS)

Debnath, M.; Santoni, C.; Leonardi, S.; Iungo, G. V.

2017-03-01

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator. This article is part of the themed issue 'Wind energy in complex terrains'.

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

Dynamic analysis of spiral bevel and hypoid gears with high-order transmission errors

NASA Astrophysics Data System (ADS)

Yang, J. J.; Shi, Z. H.; Zhang, H.; Li, T. X.; Nie, S. W.; Wei, B. Y.

2018-03-01

A new gear surface modification methodology based on curvature synthesis is proposed in this study to improve the transmission performance. The generated high-order transmission error (TE) for spiral bevel and hypoid gears is proved to reduce the vibration of geared-rotor system. The method is comprised of the following steps: Firstly, the fully conjugate gear surfaces with pinion flank modified according to the predesigned relative transmission movement are established based on curvature correction. Secondly, a 14-DOF geared-rotor system model considering backlash nonlinearity is used to evaluate the effect of different orders of TE on the dynamic performance a hypoid gear transmission system. For case study, numerical simulation is performed to illustrate the dynamic response of hypoid gear pair with parabolic, fourth-order and sixth-order transmission error derived. The results show that the parabolic TE curve has higher peak to peak amplitude compared to the other two types of TE. Thus, the excited dynamic response also shows larger amplitude at response peaks. Dynamic responses excited by fourth and sixth order TE also demonstrate distinct response components due to their different TE period which is expected to generate different sound quality or other acoustic characteristics.

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

Competition-Colonization Trade-Offs, Competitive Uncertainty, and the Evolutionary Assembly of Species

PubMed Central

Pillai, Pradeep; Guichard, Frédéric

2012-01-01

We utilize a standard competition-colonization metapopulation model in order to study the evolutionary assembly of species. Based on earlier work showing how models assuming strict competitive hierarchies will likely lead to runaway evolution and self-extinction for all species, we adopt a continuous competition function that allows for levels of uncertainty in the outcome of competition. We then, by extending the standard patch-dynamic metapopulation model in order to include evolutionary dynamics, allow for the coevolution of species into stable communities composed of species with distinct limiting similarities. Runaway evolution towards stochastic extinction then becomes a limiting case controlled by the level of competitive uncertainty. We demonstrate how intermediate competitive uncertainty maximizes the equilibrium species richness as well as maximizes the adaptive radiation and self-assembly of species under adaptive dynamics with mutations of non-negligible size. By reconciling competition-colonization tradeoff theory with co-evolutionary dynamics, our results reveal the importance of intermediate levels of competitive uncertainty for the evolutionary assembly of species. PMID:22448253

Mathematical modelling and linear stability analysis of laser fusion cutting

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

Hermanns, Torsten; Schulz, Wolfgang; Vossen, Georg

A model for laser fusion cutting is presented and investigated by linear stability analysis in order to study the tendency for dynamic behavior and subsequent ripple formation. The result is a so called stability function that describes the correlation of the setting values of the process and the process’ amount of dynamic behavior.

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.

Using gamma distribution to determine half-life of rotenone, applied in freshwater.

PubMed

Rohan, Maheswaran; Fairweather, Alastair; Grainger, Natasha

2015-09-15

Following the use of rotenone to eradicate invasive pest fish, a dynamic first-order kinetic model is usually used to determine the half-life and rate at which rotenone dissipated from the treated waterbody. In this study, we investigate the use of a stochastic gamma model for determining the half-life and rate at which rotenone dissipates from waterbodies. The first-order kinetic and gamma models produced similar values for the half-life (4.45 days and 5.33 days respectively) and days to complete dissipation (51.2 days and 52.48 days respectively). However, the gamma model fitted the data better and was more flexible than the first-order kinetic model, allowing us to use covariates and to predict a possible range for the half-life of rotenone. These benefits are particularly important when examining the influence that different environmental factors have on rotenone dissipation and when trying to predict the rate at which rotenone will dissipate during future operations. We therefore recommend that in future the gamma distribution model is used when calculating the half-life of rotenone in preference to the dynamic first-order kinetics model. Copyright © 2015 Elsevier B.V. All rights reserved.

Role of optimization in the human dynamics of task execution

NASA Astrophysics Data System (ADS)

Cajueiro, Daniel O.; Maldonado, Wilfredo L.

2008-03-01

In order to explain the empirical evidence that the dynamics of human activity may not be well modeled by Poisson processes, a model based on queuing processes was built in the literature [A. L. Barabasi, Nature (London) 435, 207 (2005)]. The main assumption behind that model is that people execute their tasks based on a protocol that first executes the high priority item. In this context, the purpose of this paper is to analyze the validity of that hypothesis assuming that people are rational agents that make their decisions in order to minimize the cost of keeping nonexecuted tasks on the list. Therefore, we build and analytically solve a dynamic programming model with two priority types of tasks and show that the validity of this hypothesis depends strongly on the structure of the instantaneous costs that a person has to face if a given task is kept on the list for more than one period. Moreover, one interesting finding is that in one of the situations the protocol used to execute the tasks generates complex one-dimensional dynamics.

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

PubMed Central

Roach, Shane M.; Song, Dong; Berger, Theodore W.

2012-01-01

Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

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.

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.

Ankle Joint Intrinsic Dynamics is More Complex than a Mass-Spring-Damper Model.

PubMed

Sobhani Tehrani, Ehsan; Jalaleddini, Kian; Kearney, Robert E

2017-09-01

This paper describes a new small signal parametric model of ankle joint intrinsic mechanics in normal subjects. We found that intrinsic ankle mechanics is a third-order system and the second-order mass-spring-damper model, referred to as IBK, used by many researchers in the literature cannot adequately represent ankle dynamics at all frequencies in a number of important tasks. This was demonstrated using experimental data from five healthy subjects with no voluntary muscle contraction and at seven ankle positions covering the range of motion. We showed that the difference between the new third-order model and the conventional IBK model increased from dorsi to plantarflexed position. The new model was obtained using a multi-step identification procedure applied to experimental input/output data of the ankle joint. The procedure first identifies a non-parametric model of intrinsic joint stiffness where ankle position is the input and torque is the output. Then, in several steps, the model is converted into a continuous-time transfer function of ankle compliance, which is the inverse of stiffness. Finally, we showed that the third-order model is indeed structurally consistent with agonist-antagonist musculoskeletal structure of human ankle, which is not the case for the IBK model.

Testing higher-order Lagrangian perturbation theory against numerical simulations. 2: Hierarchical models

NASA Technical Reports Server (NTRS)

Melott, A. L.; Buchert, T.; Weib, A. G.

1995-01-01

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of scales. The Lagrangian theory of gravitational instability of Friedmann-Lemaitre cosmogonies is compared with numerical simulations. We study the dynamics of hierarchical models as a second step. In the first step we analyzed the performance of the Lagrangian schemes for pancake models, the difference being that in the latter models the initial power spectrum is truncated. This work probed the quasi-linear and weakly non-linear regimes. We here explore whether the results found for pancake models carry over to hierarchical models which are evolved deeply into the non-linear regime. We smooth the initial data by using a variety of filter types and filter scales in order to determine the optimal performance of the analytical models, as has been done for the 'Zel'dovich-approximation' - hereafter TZA - in previous work. We find that for spectra with negative power-index the second-order scheme performs considerably better than TZA in terms of statistics which probe the dynamics, and slightly better in terms of low-order statistics like the power-spectrum. However, in contrast to the results found for pancake models, where the higher-order schemes get worse than TZA at late non-linear stages and on small scales, we here find that the second-order model is as robust as TZA, retaining the improvement at later stages and on smaller scales. In view of these results we expect that the second-order truncated Lagrangian model is especially useful for the modelling of standard dark matter models such as Hot-, Cold-, and Mixed-Dark-Matter.

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.

A fast recursive algorithm for molecular dynamics simulation

NASA Technical Reports Server (NTRS)

Jain, A.; Vaidehi, N.; Rodriguez, G.

1993-01-01

The present recursive algorithm for solving molecular systems' dynamical equations of motion employs internal variable models that reduce such simulations' computation time by an order of magnitude, relative to Cartesian models. Extensive use is made of spatial operator methods recently developed for analysis and simulation of the dynamics of multibody systems. A factor-of-450 speedup over the conventional O(N-cubed) algorithm is demonstrated for the case of a polypeptide molecule with 400 residues.

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Classification and recognition of dynamical models: the role of phase, independent components, kernels and optimal transport.

PubMed

Bissacco, Alessandro; Chiuso, Alessandro; Soatto, Stefano

2007-11-01

We address the problem of performing decision tasks, and in particular classification and recognition, in the space of dynamical models in order to compare time series of data. Motivated by the application of recognition of human motion in image sequences, we consider a class of models that include linear dynamics, both stable and marginally stable (periodic), both minimum and non-minimum phase, driven by non-Gaussian processes. This requires extending existing learning and system identification algorithms to handle periodic modes and nonminimum phase behavior, while taking into account higher-order statistics of the data. Once a model is identified, we define a kernel-based cord distance between models that includes their dynamics, their initial conditions as well as input distribution. This is made possible by a novel kernel defined between two arbitrary (non-Gaussian) distributions, which is computed by efficiently solving an optimal transport problem. We validate our choice of models, inference algorithm, and distance on the tasks of human motion synthesis (sample paths of the learned models), and recognition (nearest-neighbor classification in the computed distance). However, our work can be applied more broadly where one needs to compare historical data while taking into account periodic trends, non-minimum phase behavior, and non-Gaussian input distributions.

Theoretical studies in interstellar cloud chemistry

NASA Technical Reports Server (NTRS)

Chiu, Y. T.; Prasad, S. S.

1993-01-01

This final report represents the completion of the three tasks under the purchase order no. SCPDE5620,1,2F. Chemical composition of gravitationally contracting, but otherwise quiescent, interstellar clouds and of interstellar clouds traversed by high velocity shocks, were modeled in a comprehensive manner that represents a significant progress in modeling these objects. The evolutionary chemical modeling, done under this NASA contract, represents a notable advance over the 'classical' fixed condition equilibrium models because the evolutionary models consider not only the chemical processes but also the dynamical processes by which the dark interstellar clouds may have assumed their present state. The shock calculations, being reported here, are important because they extend the limited chemical composition derivable from dynamical calculations for the total density and temperature structures behind the shock front. In order to be tractable, the dynamical calculations must severely simplify the chemistry. The present shock calculations take the shock profiles from the dynamical calculations and derive chemical composition in a comprehensive manner. The results of the present modeling study are still to be analyzed with reference to astronomical observational data and other contemporary model predictions. As far as humanly possible, this analysis will be continued with CRE's (Creative Research Enterprises's) IR&D resources, until a sponsor is found.

Dynamics of Aqueous Foam Drops

NASA Technical Reports Server (NTRS)

Akhatov, Iskander; McDaniel, J. Gregory; Holt, R. Glynn

2001-01-01

We develop a model for the nonlinear oscillations of spherical drops composed of aqueous foam. Beginning with a simple mixture law, and utilizing a mass-conserving bubble-in-cell scheme, we obtain a Rayleigh-Plesset-like equation for the dynamics of bubbles in a foam mixture. The dispersion relation for sound waves in a bubbly liquid is then coupled with a normal modes expansion to derive expressions for the frequencies of eigenmodal oscillations. These eigenmodal (breathing plus higher-order shape modes) frequencies are elicited as a function of the void fraction of the foam. A Mathieu-like equation is obtained for the dynamics of the higher-order shape modes and their parametric coupling to the breathing mode. The proposed model is used to explain recently obtained experimental data.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

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

Xavier, MA; Trimboli, MS

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 suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

Accurate Sloshing Modes Modeling: A New Analytical Solution and its Consequences on Control

NASA Astrophysics Data System (ADS)

Gonidou, Luc-Olivier; Desmariaux, Jean

2014-06-01

This study addresses the issue of sloshing modes modeling for GNC analyses purposes. On European launchers, equivalent mechanical systems are commonly used for modeling sloshing effects on launcher dynamics. The representativeness of such a methodology is discussed here. First an exact analytical formulation of the launcher dynamics fitted with sloshing modes is proposed and discrepancies with equivalent mechanical system approach are emphasized. Then preliminary comparative GNC analyses are performed using the different models of dynamics in order to evaluate the impact of the aforementioned discrepancies from GNC standpoint. Special attention is paid to system stability.

Dynamic rupture modeling of the M7.2 2010 El Mayor-Cucapah earthquake: Comparison with a geodetic model

USGS Publications Warehouse

Kyriakopoulos, Christos; Oglesby, David D.; Funning, Gareth J.; Ryan, Kenneth

2017-01-01

The 2010 Mw 7.2 El Mayor-Cucapah earthquake is the largest event recorded in the broader Southern California-Baja California region in the last 18 years. Here we try to analyze primary features of this type of event by using dynamic rupture simulations based on a multifault interface and later compare our results with space geodetic models. Our results show that starting from homogeneous prestress conditions, slip heterogeneity can be achieved as a result of variable dip angle along strike and the modulation imposed by step over segments. We also considered effects from a topographic free surface and find that although this does not produce significant first-order effects for this earthquake, even a low topographic dome such as the Cucapah range can affect the rupture front pattern and fault slip rate. Finally, we inverted available interferometric synthetic aperture radar data, using the same geometry as the dynamic rupture model, and retrieved the space geodetic slip distribution that serves to constrain the dynamic rupture models. The one to one comparison of the final fault slip pattern generated with dynamic rupture models and the space geodetic inversion show good agreement. Our results lead us to the following conclusion: in a possible multifault rupture scenario, and if we have first-order geometry constraints, dynamic rupture models can be very efficient in predicting large-scale slip heterogeneities that are important for the correct assessment of seismic hazard and the magnitude of future events. Our work contributes to understanding the complex nature of multifault systems.

Dynamic stresses in a Francis model turbine at deep part load

NASA Astrophysics Data System (ADS)

Weber, Wilhelm; von Locquenghien, Florian; Conrad, Philipp; Koutnik, Jiri

2017-04-01

A comparison between numerically obtained dynamic stresses in a Francis model turbine at deep part load with experimental ones is presented. Due to the change in the electrical power mix to more content of new renewable energy sources, Francis turbines are forced to operate at deep part load in order to compensate stochastic nature of wind and solar power and to ensure grid stability. For the extension of the operating range towards deep part load improved understanding of the harsh flow conditions and their impact on material fatigue of hydraulic components is required in order to ensure long life time of the power unit. In this paper pressure loads on a model turbine runner from unsteady two-phase computational fluid dynamics simulation at deep part load are used for calculation of mechanical stresses by finite element analysis. Therewith, stress distribution over time is determined. Since only few runner rotations are simulated due to enormous numerical cost, more effort has to be spent to evaluation procedure in order to obtain objective results. By comparing the numerical results with measured strains accuracy of the whole simulation procedure is verified.

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.

Dynamic analysis of Space Shuttle/RMS configuration using continuum approach

NASA Technical Reports Server (NTRS)

Ramakrishnan, Jayant; Taylor, Lawrence W., Jr.

1994-01-01

The initial assembly of Space Station Freedom involves the Space Shuttle, its Remote Manipulation System (RMS) and the evolving Space Station Freedom. The dynamics of this coupled system involves both the structural and the control system dynamics of each of these components. The modeling and analysis of such an assembly is made even more formidable by kinematic and joint nonlinearities. The current practice of modeling such flexible structures is to use finite element modeling in which the mass and interior dynamics is ignored between thousands of nodes, for each major component. The model characteristics of only tens of modes are kept out of thousands which are calculated. The components are then connected by approximating the boundary conditions and inserting the control system dynamics. In this paper continuum models are used instead of finite element models because of the improved accuracy, reduced number of model parameters, the avoidance of model order reduction, and the ability to represent the structural and control system dynamics in the same system of equations. Dynamic analysis of linear versions of the model is performed and compared with finite element model results. Additionally, the transfer matrix to continuum modeling is presented.

A continued fraction resummation form of bath relaxation effect in the spin-boson model

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

Gong, Zhihao; Tang, Zhoufei; Wu, Jianlan, E-mail: jianlanwu@zju.edu.cn

2015-02-28

In the spin-boson model, a continued fraction form is proposed to systematically resum high-order quantum kinetic expansion (QKE) rate kernels, accounting for the bath relaxation effect beyond the second-order perturbation. In particular, the analytical expression of the sixth-order QKE rate kernel is derived for resummation. With higher-order correction terms systematically extracted from higher-order rate kernels, the resummed quantum kinetic expansion approach in the continued fraction form extends the Pade approximation and can fully recover the exact quantum dynamics as the expansion order increases.

An efficient formulation of robot arm dynamics for control and computer simulation

NASA Astrophysics Data System (ADS)

Lee, C. S. G.; Nigam, R.

This paper describes an efficient formulation of the dynamic equations of motion of industrial robots based on the Lagrange formulation of d'Alembert's principle. This formulation, as applied to a PUMA robot arm, results in a set of closed form second order differential equations with cross product terms. They are not as efficient in computation as those formulated by the Newton-Euler method, but provide a better analytical model for control analysis and computer simulation. Computational complexities of this dynamic model together with other models are tabulated for discussion.

Uncertainty Due to Unsteady Fluid/Structure Interaction for the Ares I Vehicle Traversing the Transonic Regime

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2012-01-01

Rapid reduced-order numerical models are being investigated as candidates to simulate the dynamics of a flexible launch vehicle during atmospheric ascent. There has also been the extension of these new approaches to include gust response. These methods are used to perform aeroelastic and gust response analyses at isolated Mach numbers. Such models require a method to time march through a succession of ascent Mach numbers. An approach is presented for interpolating reduced-order models of the unsteady aerodynamics at successive Mach numbers. The transonic Mach number range is considered here since launch vehicles can suffer the highest dynamic loads through this range. Realistic simulations of the flexible vehicle behavior as it traverses this Mach number range are presented. The response of the vehicle due to gusts is computed. Uncertainties in root mean square and maximum bending moment and crew module accelerations are presented due to assumed probability distributions in design parameters, ascent flight conditions, gusts. The primary focus is on the uncertainty introduced by modeling fidelity. It is found that an unsteady reduced order model produces larger excursions in the root mean square loading and accelerations than does a quasi-steady reduced order model.

Model for the orientational ordering of the plant microtubule cortical array

NASA Astrophysics Data System (ADS)

Hawkins, Rhoda J.; Tindemans, Simon H.; Mulder, Bela M.

2010-07-01

The plant microtubule cortical array is a striking feature of all growing plant cells. It consists of a more or less homogeneously distributed array of highly aligned microtubules connected to the inner side of the plasma membrane and oriented transversely to the cell growth axis. Here, we formulate a continuum model to describe the origin of orientational order in such confined arrays of dynamical microtubules. The model is based on recent experimental observations that show that a growing cortical microtubule can interact through angle dependent collisions with pre-existing microtubules that can lead either to co-alignment of the growth, retraction through catastrophe induction or crossing over the encountered microtubule. We identify a single control parameter, which is fully determined by the nucleation rate and intrinsic dynamics of individual microtubules. We solve the model analytically in the stationary isotropic phase, discuss the limits of stability of this isotropic phase, and explicitly solve for the ordered stationary states in a simplified version of the model.

Dynamics of a Flywheel Energy Storage System Supporting a Wind Turbine Generator in a Microgrid

NASA Astrophysics Data System (ADS)

Nair S, Gayathri; Senroy, Nilanjan

2016-02-01

Integration of an induction machine based flywheel energy storage system with a wind energy conversion system is implemented in this paper. The nonlinear and linearized models of the flywheel are studied, compared and a reduced order model of the same simulated to analyze the influence of the flywheel inertia and control in system response during a wind power change. A quantification of the relation between the inertia of the flywheel and the controller gain is obtained which allows the system to be considered as a reduced order model that is more controllable in nature. A microgrid setup comprising of the flywheel energy storage system, a two mass model of a DFIG based wind turbine generator and a reduced order model of a diesel generator is utilized to analyse the microgrid dynamics accurately in the event of frequency variations arising due to wind power change. The response of the microgrid with and without the flywheel is studied.

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

NASA Astrophysics Data System (ADS)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

Model reconstruction using POD method for gray-box fault detection

NASA Technical Reports Server (NTRS)

Park, H. G.; Zak, M.

2003-01-01

This paper describes using Proper Orthogonal Decomposition (POD) method to create low-order dynamical models for the Model Filter component of Beacon-based Exception Analysis for Multi-missions (BEAM).

Simulations of Operation Dynamics of Different Type GaN Particle Sensors

PubMed Central

Gaubas, Eugenijus; Ceponis, Tomas; Kalesinskas, Vidas; Pavlov, Jevgenij; Vysniauskas, Juozas

2015-01-01

The operation dynamics of the capacitor-type and PIN diode type detectors based on GaN have been simulated using the dynamic and drift-diffusion models. The drift-diffusion current simulations have been implemented by employing the software package Synopsys TCAD Sentaurus. The monopolar and bipolar drift regimes have been analyzed by using dynamic models based on the Shockley-Ramo theorem. The carrier multiplication processes determined by impact ionization have been considered in order to compensate carrier lifetime reduction due to introduction of radiation defects into GaN detector material. PMID:25751080

Dynamic output feedback control of a flexible air-breathing hypersonic vehicle via T-S fuzzy approach

NASA Astrophysics Data System (ADS)

Hu, Xiaoxiang; Wu, Ligang; Hu, Changhua; Wang, Zhaoqiang; Gao, Huijun

2014-08-01

By utilising Takagi-Sugeno (T-S) fuzzy set approach, this paper addresses the robust H∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics' enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T-S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T-S fuzzy dynamic output feedback control method is demonstrated by numerical simulations.

An Alternative Optimization Model and Robust Experimental Design for the Assignment Scheduling Capability for Unmanned Aerial Vehicles (ASC-U) Simulation

DTIC Science & Technology

2007-06-01

introduces ASC-U’s approach for solving the dynamic UAV allocation problem. 26 Christopher J...18 Figure 6. Assignments Dynamics Example (after) .........................................................20 Figure 7. ASC-U Dynamic Cueing...decisions in order to respond to the dynamic environment they face. Thus, to succeed, the Army’s transformation cannot rely

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.

Differential renormalization-group generators for static and dynamic critical phenomena

NASA Astrophysics Data System (ADS)

Chang, T. S.; Vvedensky, D. D.; Nicoll, J. F.

1992-09-01

The derivation of differential renormalization-group (DRG) equations for applications to static and dynamic critical phenomena is reviewed. The DRG approach provides a self-contained closed-form representation of the Wilson renormalization group (RG) and should be viewed as complementary to the Callan-Symanzik equations used in field-theoretic approaches to the RG. The various forms of DRG equations are derived to illustrate the general mathematical structure of each approach and to point out the advantages and disadvantages for performing practical calculations. Otherwise, the review focuses upon the one-particle-irreducible DRG equations derived by Nicoll and Chang and by Chang, Nicoll, and Young; no attempt is made to provide a general treatise of critical phenomena. A few specific examples are included to illustrate the utility of the DRG approach: the large- n limit of the classical n-vector model (the spherical model), multi- or higher-order critical phenomena, and crit ical dynamics far from equilibrium. The large- n limit of the n-vector model is used to introduce the application of DRG equations to a well-known example, with exact solution obtained for the nonlinear trajectories, generating functions for nonlinear scaling fields, and the equation of state. Trajectory integrals and nonlinear scaling fields within the framework of ɛ-expansions are then discussed for tricritical crossover, and briefly for certain aspects of multi- or higher-order critical points, including the derivation of the Helmholtz free energy and the equation of state. The discussion then turns to critical dynamics with a development of the path integral formulation for general dynamic processes. This is followed by an application to a model far-from-equilibrium system that undergoes a phase transformation analogous to a second-order critical point, the Schlögl model for a chemical instability.

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.

Phase-field-crystal model for ordered crystals

NASA Astrophysics Data System (ADS)

Alster, Eli; Elder, K. R.; Hoyt, Jeffrey J.; Voorhees, Peter W.

2017-02-01

We describe a general method to model multicomponent ordered crystals using the phase-field-crystal (PFC) formalism. As a test case, a generic B2 compound is investigated. We are able to produce a line of either first-order or second-order order-disorder phase transitions, features that have not been incorporated in existing PFC approaches. Further, it is found that the only elastic constant for B2 that depends on ordering is C11. This B2 model is then used to study antiphase boundaries (APBs). The APBs are shown to reproduce classical mean-field results. Dynamical simulations of ordering across small-angle grain boundaries predict that dislocation cores pin the evolution of APBs.

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.

Optimal community structure for social contagions

NASA Astrophysics Data System (ADS)

Su, Zhen; Wang, Wei; Li, Lixiang; Stanley, H. Eugene; Braunstein, Lidia A.

2018-05-01

Community structure is an important factor in the behavior of real-world networks because it strongly affects the stability and thus the phase transition order of the spreading dynamics. We here propose a reversible social contagion model of community networks that includes the factor of social reinforcement. In our model an individual adopts a social contagion when the number of received units of information exceeds its adoption threshold. We use mean-field approximation to describe our proposed model, and the results agree with numerical simulations. The numerical simulations and theoretical analyses both indicate that there is a first-order phase transition in the spreading dynamics, and that a hysteresis loop emerges in the system when there is a variety of initially adopted seeds. We find an optimal community structure that maximizes spreading dynamics. We also find a rich phase diagram with a triple point that separates the no-diffusion phase from the two diffusion phases.

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical 'cores' of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. The two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical 'simple physics' parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

An Intercomparison of the Dynamical Cores of Global Atmospheric Circulation Models for Mars

NASA Technical Reports Server (NTRS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1998-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Cen- ter and San Jose State University, Department of Meteorology. The focus of this JRI has been to evaluate the dynamical "cores" of two global atmospheric circulation models for Mars that are in operation at the NASA Ames Research Center. ne two global circulation models in use are fundamentally different: one uses spherical harmonics in its horizontal representation of field variables; the other uses finite differences on a uniform longitude-latitude grid. Several simulations have been conducted to assess how the dynamical processors of each of these circulation models perform using identical "simple physics" parameterizations. A variety of climate statistics (e.g., time-mean flows and eddy fields) have been compared for realistic solstitial mean basic states. Results of this research have demonstrated that the two Mars circulation models with completely different spatial representations and discretizations produce rather similar circulation statistics for first-order meteorological fields, suggestive of a tendency for convergence of numerical solutions. Second and higher-order fields can, however, vary significantly between the two models.

Modelling social interaction as perceptual crossing: an investigation into the dynamics of the interaction process

NASA Astrophysics Data System (ADS)

Froese, Tom; Di Paolo, Ezequiel A.

2010-03-01

This paper continues efforts to establish a mutually informative dialogue between psychology and evolutionary robotics in order to investigate the dynamics of social interaction. We replicate a recent simulation model of a minimalist experiment in perceptual crossing and confirm the results with significantly simpler artificial agents. A series of psycho-physical tests of their behaviour informs a hypothetical circuit model of their internal operation. However, a detailed study of the actual internal dynamics reveals this circuit model to be unfounded, thereby offering a tale of caution for those hypothesising about sub-personal processes in terms of behavioural observations. In particular, it is shown that the behaviour of the agents largely emerges out of the interaction process itself rather than being an individual achievement alone. We also extend the original simulation model in two novel directions in order to test further the extent to which perceptual crossing between agents can self-organise in a robust manner. These modelling results suggest new hypotheses that can become the basis for further psychological experiments.

Monolayers of hard rods on planar substrates. II. Growth

NASA Astrophysics Data System (ADS)

Klopotek, M.; Hansen-Goos, H.; Dixit, M.; Schilling, T.; Schreiber, F.; Oettel, M.

2017-02-01

Growth of hard-rod monolayers via deposition is studied in a lattice model using rods with discrete orientations and in a continuum model with hard spherocylinders. The lattice model is treated with kinetic Monte Carlo simulations and dynamic density functional theory while the continuum model is studied by dynamic Monte Carlo simulations equivalent to diffusive dynamics. The evolution of nematic order (excess of upright particles, "standing-up" transition) is an entropic effect and is mainly governed by the equilibrium solution, rendering a continuous transition [Paper I, M. Oettel et al., J. Chem. Phys. 145, 074902 (2016)]. Strong non-equilibrium effects (e.g., a noticeable dependence on the ratio of rates for translational and rotational moves) are found for attractive substrate potentials favoring lying rods. Results from the lattice and the continuum models agree qualitatively if the relevant characteristic times for diffusion, relaxation of nematic order, and deposition are matched properly. Applicability of these monolayer results to multilayer growth is discussed for a continuum-model realization in three dimensions where spherocylinders are deposited continuously onto a substrate via diffusion.

Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

PubMed

Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

2017-01-01

By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

Finite element modeling of hyper-viscoelasticity of peripheral nerve ultrastructures.

PubMed

Chang, Cheng-Tao; Chen, Yu-Hsing; Lin, Chou-Ching K; Ju, Ming-Shaung

2015-07-16

The mechanical characteristics of ultrastructures of rat sciatic nerves were investigated through animal experiments and finite element analyses. A custom-designed dynamic testing apparatus was used to conduct in vitro transverse compression experiments on the nerves. The optical coherence tomography (OCT) was utilized to record the cross-sectional images of nerve during the dynamic testing. Two-dimensional finite element models of the nerves were built based on their OCT images. A hyper-viscoelastic model was employed to describe the elastic and stress relaxation response of each ultrastructure of the nerve, namely the endoneurium, the perineurium and the epineurium. The first-order Ogden model was employed to describe the elasticity of each ultrastructure and a generalized Maxwell model for the relaxation. The inverse finite element analysis was used to estimate the material parameters of the ultrastructures. The results show the instantaneous shear modulus of the ultrastructures in decreasing order is perineurium, endoneurium, and epineurium. The FE model combined with the first-order Ogden model and the second-order Prony series is good enough for describing the compress-and-hold response of the nerve ultrastructures. The integration of OCT and the nonlinear finite element modeling may be applicable to study the viscoelasticity of peripheral nerve down to the ultrastructural level. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamic Modeling and Simulation of a Rotational Inverted Pendulum

NASA Astrophysics Data System (ADS)

Duart, J. L.; Montero, B.; Ospina, P. A.; González, E.

2017-01-01

This paper presents an alternative way to the dynamic modeling of a rotational inverted pendulum using the classic mechanics known as Euler-Lagrange allows to find motion equations that describe our model. It also has a design of the basic model of the system in SolidWorks software, which based on the material and dimensions of the model provides some physical variables necessary for modeling. In order to verify the theoretical results, It was made a contrast between the solutions obtained by simulation SimMechanics-Matlab and the system of equations Euler-Lagrange, solved through ODE23tb method included in Matlab bookstores for solving equations systems of the type and order obtained. This article comprises a pendulum trajectory analysis by a phase space diagram that allows the identification of stable and unstable regions of the system.

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

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

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

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

Reduced size first-order subsonic and supersonic aeroelastic modeling

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1990-01-01

Various aeroelastic, aeroservoelastic, dynamic-response, and sensitivity analyses are based on a time-domain first-order (state-space) formulation of the equations of motion. The formulation of this paper is based on the minimum-state (MS) aerodynamic approximation method, which yields a low number of aerodynamic augmenting states. Modifications of the MS and the physical weighting procedures make the modeling method even more attractive. The flexibility of constraint selection is increased without increasing the approximation problem size; the accuracy of dynamic residualization of high-frequency modes is improved; and the resulting model is less sensitive to parametric changes in subsequent analyses. Applications to subsonic and supersonic cases demonstrate the generality, flexibility, accuracy, and efficiency of the method.

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.

Low-order modelling of a drop on a highly-hydrophobic substrate: statics and dynamics

NASA Astrophysics Data System (ADS)

Wray, Alexander W.; Matar, Omar K.; Davis, Stephen H.

2017-11-01

We analyse the behaviour of droplets resting on highly-hydrophobic substrates. This problem is of practical interest due to its appearance in many physical contexts involving the spreading, wetting, and dewetting of fluids on solid substrates. In mathematical terms, it exhibits an interesting challenge as the interface is multi-valued as a function of the natural Cartesian co-ordinates, presenting a stumbling block to typical low-order modelling techniques. Nonetheless, we show that in the static case, the interfacial shape is governed by the Young-Laplace equation, which may be solved explicitly in terms of elliptic functions. We present simple low-order expressions that faithfully reproduce the shapes. We then consider the dynamic case, showing that the predictions of our low-order model compare favourably with those obtained from direct numerical simulations. We also examine the characteristic flow regimes of interest. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

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.

Switching moving boundary models for two-phase flow evaporators and condensers

NASA Astrophysics Data System (ADS)

Bonilla, Javier; Dormido, Sebastián; Cellier, François E.

2015-03-01

The moving boundary method is an appealing approach for the design, testing and validation of advanced control schemes for evaporators and condensers. When it comes to advanced control strategies, not only accurate but fast dynamic models are required. Moving boundary models are fast low-order dynamic models, and they can describe the dynamic behavior with high accuracy. This paper presents a mathematical formulation based on physical principles for two-phase flow moving boundary evaporator and condenser models which support dynamic switching between all possible flow configurations. The models were implemented in a library using the equation-based object-oriented Modelica language. Several integrity tests in steady-state and transient predictions together with stability tests verified the models. Experimental data from a direct steam generation parabolic-trough solar thermal power plant is used to validate and compare the developed moving boundary models against finite volume models.

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.

A general science-based framework for dynamical spatio-temporal models

USGS Publications Warehouse

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic nonlinearity and demonstrate that it accommodates many different classes of scientific-based parameterizations as special cases. The model is presented in a hierarchical Bayesian framework and is illustrated with examples from ecology and oceanography. ?? 2010 Sociedad de Estad??stica e Investigaci??n Operativa.

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.

Simulating coupled dynamics of a rigid-flexible multibody system and compressible fluid

NASA Astrophysics Data System (ADS)

Hu, Wei; Tian, Qiang; Hu, HaiYan

2018-04-01

As a subsequent work of previous studies of authors, a new parallel computation approach is proposed to simulate the coupled dynamics of a rigid-flexible multibody system and compressible fluid. In this approach, the smoothed particle hydrodynamics (SPH) method is used to model the compressible fluid, the natural coordinate formulation (NCF) and absolute nodal coordinate formulation (ANCF) are used to model the rigid and flexible bodies, respectively. In order to model the compressible fluid properly and efficiently via SPH method, three measures are taken as follows. The first is to use the Riemann solver to cope with the fluid compressibility, the second is to define virtual particles of SPH to model the dynamic interaction between the fluid and the multibody system, and the third is to impose the boundary conditions of periodical inflow and outflow to reduce the number of SPH particles involved in the computation process. Afterwards, a parallel computation strategy is proposed based on the graphics processing unit (GPU) to detect the neighboring SPH particles and to solve the dynamic equations of SPH particles in order to improve the computation efficiency. Meanwhile, the generalized-alpha algorithm is used to solve the dynamic equations of the multibody system. Finally, four case studies are given to validate the proposed parallel computation approach.

Buoyancy-induced mixing during wash and elution steps in expanded bed adsorption.

PubMed

Fee, C J; Liten, A D

2001-01-01

Buoyancy-induced mixing occurs during expanded bed adsorption processes when the feed stream entering the bottom of the system has a lower density than that of the fluid above it. In the absence of a headspace, mixing in the expanded bed can be modeled as a single, well-mixed vessel, with first-order dynamics. In the presence of a headspace, the system exhibits second-order dynamics for the densities typically encountered in protein chromatography, and can be modeled as two well-mixed vessels (the expanded bed and the headspace) arranged in series. In this paper, the mixing dynamics of the expanded bed are described and a mathematical model of the system is presented. Experimental measurements of density changes during the dilution of sucrose and salt solutions in a STREAMLINE 25 column are presented. These show excellent agreement with predictions using the model. A number of strategies for wash and elution in expanded mode, both in the presence and absence of headspace, are discussed.

Network community-based model reduction for vortical flows

NASA Astrophysics Data System (ADS)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya G.; Taira, Kunihiko

2018-06-01

A network community-based reduced-order model is developed to capture key interactions among coherent structures in high-dimensional unsteady vortical flows. The present approach is data-inspired and founded on network-theoretic techniques to identify important vortical communities that are comprised of vortical elements that share similar dynamical behavior. The overall interaction-based physics of the high-dimensional flow field is distilled into the vortical community centroids, considerably reducing the system dimension. Taking advantage of these vortical interactions, the proposed methodology is applied to formulate reduced-order models for the inter-community dynamics of vortical flows, and predict lift and drag forces on bodies in wake flows. We demonstrate the capabilities of these models by accurately capturing the macroscopic dynamics of a collection of discrete point vortices, and the complex unsteady aerodynamic forces on a circular cylinder and an airfoil with a Gurney flap. The present formulation is found to be robust against simulated experimental noise and turbulence due to its integrating nature of the system reduction.

On the Interplay between Order Parameter Dynamics and System Parameter Dynamics in Human Perceptual-Cognitive-Behavioral Systems.

PubMed

Frank, T D

2015-04-01

Previous research has demonstrated that perceiving, thinking, and acting are human activities that correspond to self-organized patterns. The emergence of such patterns can be completely described in terms of the dynamics of the pattern amplitudes, which are referred to as order parameters. The patterns emerge at bifurcations points when certain system parameters internal and external to a human agent exceed critical values. At issue is how one might study the order parameter dynamics for sequences of consecutive, emergent perceptual, cognitive, or behavioral activities. In particular, these activities may in turn impact the system parameters that have led to the emergence of the activities in the first place. This interplay between order parameter dynamics and system parameter dynamics is discussed in general and formulated in mathematical terms. Previous work that has made use of this two-tiered framework of order parameter and system parameter dynamics are briefly addressed. As an application, a model for perception under functional fixedness is presented. Finally, it is argued that the phenomena that emerge in this framework and can be observed when human agents perceive, think, and act are just as likely to occur in pattern formation systems of the inanimate world. Consequently, these phenomena do not necessarily have a neurophysiological basis but should instead be understood from the perspective of the theory of self-organization.

Dynamic intersectoral models with power-law memory

NASA Astrophysics Data System (ADS)

Tarasova, Valentina V.; Tarasov, Vasily E.

2018-01-01

Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.

Ndarts

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2011-01-01

Ndarts software provides algorithms for computing quantities associated with the dynamics of articulated, rigid-link, multibody systems. It is designed as a general-purpose dynamics library that can be used for the modeling of robotic platforms, space vehicles, molecular dynamics, and other such applications. The architecture and algorithms in Ndarts are based on the Spatial Operator Algebra (SOA) theory for computational multibody and robot dynamics developed at JPL. It uses minimal, internal coordinate models. The algorithms are low-order, recursive scatter/ gather algorithms. In comparison with the earlier Darts++ software, this version has a more general and cleaner design needed to support a larger class of computational dynamics needs. It includes a frames infrastructure, allows algorithms to operate on subgraphs of the system, and implements lazy and deferred computation for better efficiency. Dynamics modeling modules such as Ndarts are core building blocks of control and simulation software for space, robotic, mechanism, bio-molecular, and material systems modeling.

The mathematical cell model reconstructed from interference microscopy data

NASA Astrophysics Data System (ADS)

Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

2017-09-01

The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

Documentation of the Fourth Order Band Model

NASA Technical Reports Server (NTRS)

Kalnay-Rivas, E.; Hoitsma, D.

1979-01-01

A general circulation model is presented which uses quadratically conservative, fourth order horizontal space differences on an unstaggered grid and second order vertical space differences with a forward-backward or a smooth leap frog time scheme to solve the primitive equations of motion. The dynamic equations for motion, finite difference equations, a discussion of the structure and flow chart of the program code, a program listing, and three relevent papers are given.

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling.

PubMed

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-09-22

This manuscript presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling

PubMed Central

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-01-01

This paper presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10 mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. PMID:25169658

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.

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.

Flexible aircraft dynamic modeling for dynamic analysis and control synthesis

NASA Technical Reports Server (NTRS)

Schmidt, David K.

1989-01-01

The linearization and simplification of a nonlinear, literal model for flexible aircraft is highlighted. Areas of model fidelity that are critical if the model is to be used for control system synthesis are developed and several simplification techniques that can deliver the necessary model fidelity are discussed. These techniques include both numerical and analytical approaches. An analytical approach, based on first-order sensitivity theory is shown to lead not only to excellent numerical results, but also to closed-form analytical expressions for key system dynamic properties such as the pole/zero factors of the vehicle transfer-function matrix. The analytical results are expressed in terms of vehicle mass properties, vibrational characteristics, and rigid-body and aeroelastic stability derivatives, thus leading to the underlying causes for critical dynamic characteristics.

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.

Anomalous glassy dynamics in simple models of dense biological tissue

NASA Astrophysics Data System (ADS)

Sussman, Daniel M.; Paoluzzi, M.; Marchetti, M. Cristina; Manning, M. Lisa

2018-02-01

In order to understand the mechanisms for glassy dynamics in biological tissues and shed light on those in non-biological materials, we study the low-temperature disordered phase of 2D vertex-like models. Recently it has been noted that vertex models have quite unusual behavior in the zero-temperature limit, with rigidity transitions that are controlled by residual stresses and therefore exhibit very different scaling and phenomenology compared to particulate systems. Here we investigate the finite-temperature phase of two-dimensional Voronoi and Vertex models, and show that they have highly unusual, sub-Arrhenius scaling of dynamics with temperature. We connect the anomalous glassy dynamics to features of the potential energy landscape associated with zero-temperature inherent states.

Reduced order model of a blended wing body aircraft configuration

NASA Astrophysics Data System (ADS)

Stroscher, F.; Sika, Z.; Petersson, O.

2013-12-01

This paper describes the full development process of a numerical simulation model for the ACFA2020 (Active Control for Flexible 2020 Aircraft) blended wing body (BWB) configuration. Its requirements are the prediction of aeroelastic and flight dynamic response in time domain, with relatively small model order. Further, the model had to be parameterized with regard to multiple fuel filling conditions, as well as flight conditions. High efforts have been conducted in high-order aerodynamic analysis, for subsonic and transonic regime, by several project partners. The integration of the unsteady aerodynamic databases was one of the key issues in aeroelastic modeling.

Modelling and control issues of dynamically substructured systems: adaptive forward prediction taken as an example

PubMed Central

Tu, Jia-Ying; Hsiao, Wei-De; Chen, Chih-Ying

2014-01-01

Testing techniques of dynamically substructured systems dissects an entire engineering system into parts. Components can be tested via numerical simulation or physical experiments and run synchronously. Additional actuator systems, which interface numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by the actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. An adaptive forward prediction (AFP) algorithm based on delay compensation concepts has been proposed to deal with substructuring control issues. Although the settling performance and numerical conditions of the AFP controller are improved using new direct-compensation and singular value decomposition methods, the experimental results show that a linear dynamics-based controller still outperforms the AFP controller. Based on experimental observations, the least-squares fitting technique, effectiveness of the AFP compensation and differences between delay and ordinary differential equations are discussed herein, in order to reflect the fundamental issues of actuator modelling in relevant literature and, more specifically, to show that the actuator and numerical substructure are heterogeneous dynamic components and should not be collectively modelled as a homogeneous delay differential equation. PMID:25104902

Modeling the Dynamic Interrelations between Mobility, Utility, and Land Asking Price

NASA Astrophysics Data System (ADS)

Hidayat, E.; Rudiarto, I.; Siegert, F.; Vries, W. D.

2018-02-01

Limited and insufficient information about the dynamic interrelation among mobility, utility, and land price is the main reason to conduct this research. Several studies, with several approaches, and several variables have been conducted so far in order to model the land price. However, most of these models appear to generate primarily static land prices. Thus, a research is required to compare, design, and validate different models which calculate and/or compare the inter-relational changes of mobility, utility, and land price. The applied method is a combination of analysis of literature review, expert interview, and statistical analysis. The result is newly improved mathematical model which have been validated and is suitable for the case study location. This improved model consists of 12 appropriate variables. This model can be implemented in the Salatiga city as the case study location in order to arrange better land use planning to mitigate the uncontrolled urban growth.

A computational framework for simultaneous estimation of muscle and joint contact forces and body motion using optimization and surrogate modeling.

PubMed

Eskinazi, Ilan; Fregly, Benjamin J

2018-04-01

Concurrent estimation of muscle activations, joint contact forces, and joint kinematics by means of gradient-based optimization of musculoskeletal models is hindered by computationally expensive and non-smooth joint contact and muscle wrapping algorithms. We present a framework that simultaneously speeds up computation and removes sources of non-smoothness from muscle force optimizations using a combination of parallelization and surrogate modeling, with special emphasis on a novel method for modeling joint contact as a surrogate model of a static analysis. The approach allows one to efficiently introduce elastic joint contact models within static and dynamic optimizations of human motion. We demonstrate the approach by performing two optimizations, one static and one dynamic, using a pelvis-leg musculoskeletal model undergoing a gait cycle. We observed convergence on the order of seconds for a static optimization time frame and on the order of minutes for an entire dynamic optimization. The presented framework may facilitate model-based efforts to predict how planned surgical or rehabilitation interventions will affect post-treatment joint and muscle function. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes.

PubMed

Debnath, M; Santoni, C; Leonardi, S; Iungo, G V

2017-04-13

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Mixed-order phase transition in a minimal, diffusion-based spin model.

PubMed

Fronczak, Agata; Fronczak, Piotr

2016-07-01

In this paper we exactly solve, within the grand canonical ensemble, a minimal spin model with the hybrid phase transition. We call the model diffusion based because its Hamiltonian can be recovered from a simple dynamic procedure, which can be seen as an equilibrium statistical mechanics representation of a biased random walk. We outline the derivation of the phase diagram of the model, in which the triple point has the hallmarks of the hybrid transition: discontinuity in the average magnetization and algebraically diverging susceptibilities. At this point, two second-order transition curves meet in equilibrium with the first-order curve, resulting in a prototypical mixed-order behavior.

Dynamical regimes due to technological change in a microeconomical model of production

NASA Astrophysics Data System (ADS)

Hamacher, K.

2012-09-01

We develop a microeconomical model to investigate the impact of technological change onto production decisions of suppliers—modeling an effective feedback mechanism of the market. An important property—the time horizon of production planning—is related to the Kolmogorov entropy of the one-dimensional maps describing price dynamics. We simulate this price dynamics in an ensemble representing the whole macroeconomy. We show how this model can be used to support ongoing research in economic growth and incorporate the obtained microeconomic findings into the discussion about appropriate macroeconomic quantities such as the production function—thus effectively underpinning macroeconomics with microeconomical dynamics. From there we can show that the model exhibits different dynamical regimes (suggesting "phase transitions") with respect to an order parameter. The non-linear feedback under technological change was found to be the crucial mechanism. The implications of the obtained regimes are finally discussed.

Dynamical regimes due to technological change in a microeconomical model of production.

PubMed

Hamacher, K

2012-09-01

We develop a microeconomical model to investigate the impact of technological change onto production decisions of suppliers-modeling an effective feedback mechanism of the market. An important property-the time horizon of production planning-is related to the Kolmogorov entropy of the one-dimensional maps describing price dynamics. We simulate this price dynamics in an ensemble representing the whole macroeconomy. We show how this model can be used to support ongoing research in economic growth and incorporate the obtained microeconomic findings into the discussion about appropriate macroeconomic quantities such as the production function-thus effectively underpinning macroeconomics with microeconomical dynamics. From there we can show that the model exhibits different dynamical regimes (suggesting "phase transitions") with respect to an order parameter. The non-linear feedback under technological change was found to be the crucial mechanism. The implications of the obtained regimes are finally discussed.

Nonequilibrium Statistical Mechanics in One Dimension

NASA Astrophysics Data System (ADS)

Privman, Vladimir

2005-08-01

Part I. Reaction-Diffusion Systems and Models of Catalysis; 1. Scaling theories of diffusion-controlled and ballistically-controlled bimolecular reactions S. Redner; 2. The coalescence process, A+A->A, and the method of interparticle distribution functions D. ben-Avraham; 3. Critical phenomena at absorbing states R. Dickman; Part II. Kinetic Ising Models; 4. Kinetic ising models with competing dynamics: mappings, correlations, steady states, and phase transitions Z. Racz; 5. Glauber dynamics of the ising model N. Ito; 6. 1D Kinetic ising models at low temperatures - critical dynamics, domain growth, and freezing S. Cornell; Part III. Ordering, Coagulation, Phase Separation; 7. Phase-ordering dynamics in one dimension A. J. Bray; 8. Phase separation, cluster growth, and reaction kinetics in models with synchronous dynamics V. Privman; 9. Stochastic models of aggregation with injection H. Takayasu and M. Takayasu; Part IV. Random Sequential Adsorption and Relaxation Processes; 10. Random and cooperative sequential adsorption: exactly solvable problems on 1D lattices, continuum limits, and 2D extensions J. W. Evans; 11. Lattice models of irreversible adsorption and diffusion P. Nielaba; 12. Deposition-evaporation dynamics: jamming, conservation laws and dynamical diversity M. Barma; Part V. Fluctuations In Particle and Surface Systems; 13. Microscopic models of macroscopic shocks S. A. Janowsky and J. L. Lebowitz; 14. The asymmetric exclusion model: exact results through a matrix approach B. Derrida and M. R. Evans; 15. Nonequilibrium surface dynamics with volume conservation J. Krug; 16. Directed walks models of polymers and wetting J. Yeomans; Part VI. Diffusion and Transport In One Dimension; 17. Some recent exact solutions of the Fokker-Planck equation H. L. Frisch; 18. Random walks, resonance, and ratchets C. R. Doering and T. C. Elston; 19. One-dimensional random walks in random environment K. Ziegler; Part VII. Experimental Results; 20. Diffusion-limited exciton kinetics in one-dimensional systems R. Kroon and R. Sprik; 21. Experimental investigations of molecular and excitonic elementary reaction kinetics in one-dimensional systems R. Kopelman and A. L. Lin; 22. Luminescence quenching as a probe of particle distribution S. H. Bossmann and L. S. Schulman; Index.

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

Robustness of reduced-order multivariable state-space self-tuning controller

NASA Technical Reports Server (NTRS)

Yuan, Zhuzhi; Chen, Zengqiang

1994-01-01

In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

Speculative behavior and asset price dynamics.

PubMed

Westerhoff, Frank

2003-07-01

This paper deals with speculative trading. Guided by empirical observations, a nonlinear deterministic asset pricing model is developed in which traders repeatedly choose between technical and fundamental analysis to determine their orders. The interaction between the trading rules produces complex dynamics. The model endogenously replicates the stylized facts of excess volatility, high trading volumes, shifts in the level of asset prices, and volatility clustering.

A survey of decentralized control techniques for large space structures

NASA Technical Reports Server (NTRS)

Lindner, D. K.; Reichard, K.

1987-01-01

Preliminary results on the design of decentralized controllers for the COFS I Mast are reported. A nine mode finite element model is used along with second order model of the actuators. It is shown that without actuator dynamics, the system is stable with collocated rate feedback and has acceptable performace. However, when actuator dynamics are included, the system is unstable.

Effects of vibration on inertial wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Buehrle, Ralph D.; Balakrishna, S.; Kilgore, W. Allen

1994-01-01

Results of an experimental study of a wind tunnel model inertial angle-of-attack sensor response to a simulated dynamic environment are presented. The inertial device cannot distinguish between the gravity vector and the centrifugal accelerations associated with wind tunnel model vibration, this situation results in a model attitude measurement bias error. Significant bias error in model attitude measurement was found for the model system tested. The model attitude bias error was found to be vibration mode and amplitude dependent. A first order correction model was developed and used for estimating attitude measurement bias error due to dynamic motion. A method for correcting the output of the model attitude inertial sensor in the presence of model dynamics during on-line wind tunnel operation is proposed.

Dynamic rain fade compensation techniques for the advanced communications technology satellite

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1992-01-01

The dynamic and composite nature of propagation impairments that are incurred on earth-space communications links at frequencies in and above the 30/20 GHz Ka band necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) project by the implementation of optimal processing schemes derived through the use of the ACTS Rain Attenuation Prediction Model and nonlinear Markov filtering theory. The ACTS Rain Attenuation Prediction Model discerns climatological variations on the order of 0.5 deg in latitude and longitude in the continental U.S. The time-dependent portion of the model gives precise availability predictions for the 'spot beam' links of ACTS. However, the structure of the dynamic portion of the model, which yields performance parameters such as fade duration probabilities, is isomorphic to the state-variable approach of stochastic control theory and is amenable to the design of such statistical fade processing schemes which can be made specific to the particular climatological location at which they are employed.

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.

Output feedback regulator design for jet engine control systems

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1977-01-01

A multivariable control design procedure based on the output feedback regulator formulation is described and applied to turbofan engine model. Full order model dynamics, were incorporated in the example design. The effect of actuator dynamics on closed loop performance was investigaged. Also, the importance of turbine inlet temperature as an element of the dynamic feedback was studied. Step responses were given to indicate the improvement in system performance with this control. Calculation times for all experiments are given in CPU seconds for comparison purposes.

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

Transmission dynamics of cholera: Mathematical modeling and control strategies

NASA Astrophysics Data System (ADS)

Sun, Gui-Quan; Xie, Jun-Hui; Huang, Sheng-He; Jin, Zhen; Li, Ming-Tao; Liu, Liqun

2017-04-01

Cholera, as an endemic disease around the world, has generated great threat to human society and caused enormous morbidity and mortality with weak surveillance system. In this paper, we propose a mathematical model to describe the transmission of Cholera. Moreover, basic reproduction number and the global dynamics of the dynamical model are obtained. Then we apply our model to characterize the transmission process of Cholera in China. It was found that, in order to avoid its outbreak in China, it may be better to increase immunization coverage rate and make effort to improve environmental management especially for drinking water. Our results may provide some new insights for elimination of Cholera.

Core reactivity estimation in space reactors using recurrent dynamic networks

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Tsai, Wei K.

1991-01-01

A recurrent multilayer perceptron network topology is used in the identification of nonlinear dynamic systems from only the input/output measurements. The identification is performed in the discrete time domain, with the learning algorithm being a modified form of the back propagation (BP) rule. The recurrent dynamic network (RDN) developed is applied for the total core reactivity prediction of a spacecraft reactor from only neutronic power level measurements. Results indicate that the RDN can reproduce the nonlinear response of the reactor while keeping the number of nodes roughly equal to the relative order of the system. As accuracy requirements are increased, the number of required nodes also increases, however, the order of the RDN necessary to obtain such results is still in the same order of magnitude as the order of the mathematical model of the system. It is believed that use of the recurrent MLP structure with a variety of different learning algorithms may prove useful in utilizing artificial neural networks for recognition, classification, and prediction of dynamic systems.

Numerical study of anomalous dynamic scaling behaviour of (1+1)-dimensional Das Sarma-Tamborenea model

NASA Astrophysics Data System (ADS)

Xun, Zhi-Peng; Tang, Gang; Han, Kui; Hao, Da-Peng; Xia, Hui; Zhou, Wei; Yang, Xi-Quan; Wen, Rong-Ji; Chen, Yu-Ling

2010-07-01

In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the (1+1)-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the (1+1)-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L > 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1+1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.

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

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

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.

Dynamic regulation of heart rate during acute hypotension: new insight into baroreflex function

NASA Technical Reports Server (NTRS)

Zhang, R.; Behbehani, K.; Crandall, C. G.; Zuckerman, J. H.; Levine, B. D.; Blomqvist, C. G. (Principal Investigator)

2001-01-01

To examine the dynamic properties of baroreflex function, we measured beat-to-beat changes in arterial blood pressure (ABP) and heart rate (HR) during acute hypotension induced by thigh cuff deflation in 10 healthy subjects under supine resting conditions and during progressive lower body negative pressure (LBNP). The quantitative, temporal relationship between ABP and HR was fitted by a second-order autoregressive (AR) model. The frequency response was evaluated by transfer function analysis. Results: HR changes during acute hypotension appear to be controlled by an ABP error signal between baseline and induced hypotension. The quantitative relationship between changes in ABP and HR is characterized by a second-order AR model with a pure time delay of 0.75 s containing low-pass filter properties. During LBNP, the change in HR/change in ABP during induced hypotension significantly decreased, as did the numerator coefficients of the AR model and transfer function gain. Conclusions: 1) Beat-to-beat HR responses to dynamic changes in ABP may be controlled by an error signal rather than directional changes in pressure, suggesting a "set point" mechanism in short-term ABP control. 2) The quantitative relationship between dynamic changes in ABP and HR can be described by a second-order AR model with a pure time delay. 3) The ability of the baroreflex to evoke a HR response to transient changes in pressure was reduced during LBNP, which was due primarily to a reduction of the static gain of the baroreflex.

GARCH modelling of covariance in dynamical estimation of inverse solutions

NASA Astrophysics Data System (ADS)

Galka, Andreas; Yamashita, Okito; Ozaki, Tohru

2004-12-01

The problem of estimating unobserved states of spatially extended dynamical systems poses an inverse problem, which can be solved approximately by a recently developed variant of Kalman filtering; in order to provide the model of the dynamics with more flexibility with respect to space and time, we suggest to combine the concept of GARCH modelling of covariance, well known in econometrics, with Kalman filtering. We formulate this algorithm for spatiotemporal systems governed by stochastic diffusion equations and demonstrate its feasibility by presenting a numerical simulation designed to imitate the situation of the generation of electroencephalographic recordings by the human cortex.

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining

PubMed Central

Truccolo, Wilson

2017-01-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics (“order parameters”) inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. PMID:28336305

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining.

PubMed

Truccolo, Wilson

2016-11-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.

Model for dynamic self-assembled magnetic surface structures

NASA Astrophysics Data System (ADS)

Belkin, M.; Glatz, A.; Snezhko, A.; Aranson, I. S.

2010-07-01

We propose a first-principles model for the dynamic self-assembly of magnetic structures at a water-air interface reported in earlier experiments. The model is based on the Navier-Stokes equation for liquids in shallow water approximation coupled to Newton equations for interacting magnetic particles suspended at a water-air interface. The model reproduces most of the observed phenomenology, including spontaneous formation of magnetic snakelike structures, generation of large-scale vortex flows, complex ferromagnetic-antiferromagnetic ordering of the snake, and self-propulsion of bead-snake hybrids.

Trajectory optimization and guidance law development for national aerospace plane applications

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1988-01-01

The work completed to date is comprised of the following: a simple vehicle model representative of the aerospace plane concept in the hypersonic flight regime, fuel-optimal climb profiles for the unconstrained and dynamic pressure constrained cases generated using a reduced order dynamic model, an analytic switching condition for transition to rocket powered flight as orbital velocity is approached, simple feedback guidance laws for both the unconstrained and dynamic pressure constrained cases derived via singular perturbation theory and a nonlinear transformation technique, and numerical simulation results for ascent to orbit in the dynamic pressure constrained case.

Microworlds of the dynamic balanced scorecard for university (DBSC-UNI)

NASA Astrophysics Data System (ADS)

Hawari, Nurul Nazihah; Tahar, Razman Mat

2015-12-01

This research focuses on the development of a Microworlds of the dynamic balanced scorecard for university in order to enhance the university strategic planning process. To develop the model, we integrated both the balanced scorecard method and the system dynamics modelling method. Contrasting the traditional university planning tools, the developed model addresses university management problems holistically and dynamically. It is found that using system dynamics modelling method, the cause-and-effect relationships among variables related to the four conventional balanced scorecard perspectives are better understand. The dynamic processes that give rise to performance differences between targeted and actual performances also could be better understood. So, it is expected that the quality of the decisions taken are improved because of being better informed. The developed Microworlds can be exploited by university management to design policies that can positively influence the future in the direction of desired goals, and will have minimal side effects. This paper integrates balanced scorecard and system dynamics modelling methods in analyzing university performance. Therefore, this paper demonstrates the effectiveness and strength of system dynamics modelling method in solving problem in strategic planning area particularly in higher education sector.

Dynamic Modeling and Simulation of an Underactuated System

NASA Astrophysics Data System (ADS)

Libardo Duarte Madrid, Juan; Ospina Henao, P. A.; González Querubín, E.

2017-06-01

In this paper, is used the Lagrangian classical mechanics for modeling the dynamics of an underactuated system, specifically a rotary inverted pendulum that will have two equations of motion. A basic design of the system is proposed in SOLIDWORKS 3D CAD software, which based on the material and dimensions of the model provides some physical variables necessary for modeling. In order to verify the results obtained, a comparison the CAD model simulated in the environment SimMechanics of MATLAB software with the mathematical model who was consisting of Euler-Lagrange’s equations implemented in Simulink MATLAB, solved with the ODE23tb method, included in the MATLAB libraries for the solution of systems of equations of the type and order obtained. This article also has a topological analysis of pendulum trajectories through a phase space diagram, which allows the identification of stable and unstable regions of the system.

Instability in interacting dark sector: an appropriate holographic Ricci dark energy model

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

Herrera, Ramón; Hipólito-Ricaldi, W.S.; Videla, Nelson, E-mail: ramon.herrera@pucv.cl, E-mail: wiliam.ricaldi@ufes.br, E-mail: nelson.videla@ing.uchile.cl

In this paper we investigate the consequences of phantom crossing considering the perturbative dynamics in models with interaction in their dark sector. By mean of a general study of gauge-invariant variables in comoving gauge, we relate the sources of instabilities in the structure formation process with the phantom crossing. In order to illustrate these relations and its consequences in more detail, we consider a specific case of an holographic dark energy interacting with dark matter. We find that in spite of the model is in excellent agreement with observational data at background level, however it is plagued of instabilities inmore » its perturbative dynamics. We reconstruct the model in order to avoid these undesirable instabilities, and we show that this implies a modification of the concordance model at background. Also we find drastic changes on the parameters space in our model when instabilities are avoided.« less

Dynamic Decision Making under Uncertainty and Partial Information

DTIC Science & Technology

2017-01-30

order to address these problems, we investigated efficient computational methodologies for dynamic decision making under uncertainty and partial...information. In the course of this research, we developed and studied efficient simulation-based methodologies for dynamic decision making under...uncertainty and partial information; (ii) studied the application of these decision making models and methodologies to practical problems, such as those

Masticatory biomechanics in the rabbit: a multi-body dynamics analysis.

PubMed

Watson, Peter J; Gröning, Flora; Curtis, Neil; Fitton, Laura C; Herrel, Anthony; McCormack, Steven W; Fagan, Michael J

2014-10-06

Multi-body dynamics is a powerful engineering tool which is becoming increasingly popular for the simulation and analysis of skull biomechanics. This paper presents the first application of multi-body dynamics to analyse the biomechanics of the rabbit skull. A model has been constructed through the combination of manual dissection and three-dimensional imaging techniques (magnetic resonance imaging and micro-computed tomography). Individual muscles are represented with multiple layers, thus more accurately modelling muscle fibres with complex lines of action. Model validity was sought through comparing experimentally measured maximum incisor bite forces with those predicted by the model. Simulations of molar biting highlighted the ability of the masticatory system to alter recruitment of two muscle groups, in order to generate shearing or crushing movements. Molar shearing is capable of processing a food bolus in all three orthogonal directions, whereas molar crushing and incisor biting are predominately directed vertically. Simulations also show that the masticatory system is adapted to process foods through several cycles with low muscle activations, presumably in order to prevent rapidly fatiguing fast fibres during repeated chewing cycles. Our study demonstrates the usefulness of a validated multi-body dynamics model for investigating feeding biomechanics in the rabbit, and shows the potential for complementing and eventually reducing in vivo experiments.

Masticatory biomechanics in the rabbit: a multi-body dynamics analysis

PubMed Central

Watson, Peter J.; Gröning, Flora; Curtis, Neil; Fitton, Laura C.; Herrel, Anthony; McCormack, Steven W.; Fagan, Michael J.

2014-01-01

Multi-body dynamics is a powerful engineering tool which is becoming increasingly popular for the simulation and analysis of skull biomechanics. This paper presents the first application of multi-body dynamics to analyse the biomechanics of the rabbit skull. A model has been constructed through the combination of manual dissection and three-dimensional imaging techniques (magnetic resonance imaging and micro-computed tomography). Individual muscles are represented with multiple layers, thus more accurately modelling muscle fibres with complex lines of action. Model validity was sought through comparing experimentally measured maximum incisor bite forces with those predicted by the model. Simulations of molar biting highlighted the ability of the masticatory system to alter recruitment of two muscle groups, in order to generate shearing or crushing movements. Molar shearing is capable of processing a food bolus in all three orthogonal directions, whereas molar crushing and incisor biting are predominately directed vertically. Simulations also show that the masticatory system is adapted to process foods through several cycles with low muscle activations, presumably in order to prevent rapidly fatiguing fast fibres during repeated chewing cycles. Our study demonstrates the usefulness of a validated multi-body dynamics model for investigating feeding biomechanics in the rabbit, and shows the potential for complementing and eventually reducing in vivo experiments. PMID:25121650

Long-term dynamic modeling of tethered spacecraft using nodal position finite element method and symplectic integration

NASA Astrophysics Data System (ADS)

Li, G. Q.; Zhu, Z. H.

2015-12-01

Dynamic modeling of tethered spacecraft with the consideration of elasticity of tether is prone to the numerical instability and error accumulation over long-term numerical integration. This paper addresses the challenges by proposing a globally stable numerical approach with the nodal position finite element method (NPFEM) and the implicit, symplectic, 2-stage and 4th order Gaussian-Legendre Runge-Kutta time integration. The NPFEM eliminates the numerical error accumulation by using the position instead of displacement of tether as the state variable, while the symplectic integration enforces the energy and momentum conservation of the discretized finite element model to ensure the global stability of numerical solution. The effectiveness and robustness of the proposed approach is assessed by an elastic pendulum problem, whose dynamic response resembles that of tethered spacecraft, in comparison with the commonly used time integrators such as the classical 4th order Runge-Kutta schemes and other families of non-symplectic Runge-Kutta schemes. Numerical results show that the proposed approach is accurate and the energy of the corresponding numerical model is conservative over the long-term numerical integration. Finally, the proposed approach is applied to the dynamic modeling of deorbiting process of tethered spacecraft over a long period.

Theoretical study and control optimization of an integrated pest management predator-prey model with power growth rate.

PubMed

Sun, Kaibiao; Zhang, Tonghua; Tian, Yuan

2016-09-01

This work presents a pest control predator-prey model, where rate of change in prey density follows a scaling law with exponent less than one and the control is by an integrated management strategy. The aim is to investigate the change in system dynamics and determine a pest control level with minimum control price. First, the dynamics of the proposed model without control is investigated by taking the exponent as an index parameter. And then, to determine the frequency of spraying chemical pesticide and yield releases of the predator, the existence of the order-1 periodic orbit of the control system is discussed in cases. Furthermore, to ensure a certain robustness of the adopted control, i.e., for an inaccurately detected species density or a deviation, the control system could be stabilized at the order-1 periodic orbit, the stability of the order-1 periodic orbit is verified by an stability criterion for a general semi-continuous dynamical system. In addition, to minimize the total cost input in pest control, an optimization problem is formulated and the optimum pest control level is obtained. At last, the numerical simulations with a specific model are carried out to complement the theoretical results. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

A numerical solution for a variable-order reaction-diffusion model by using fractional derivatives with non-local and non-singular kernel

NASA Astrophysics Data System (ADS)

Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Torres, L.; Escobar-Jiménez, R. F.

2018-02-01

A reaction-diffusion system can be represented by the Gray-Scott model. The reaction-diffusion dynamic is described by a pair of time and space dependent Partial Differential Equations (PDEs). In this paper, a generalization of the Gray-Scott model by using variable-order fractional differential equations is proposed. The variable-orders were set as smooth functions bounded in (0 , 1 ] and, specifically, the Liouville-Caputo and the Atangana-Baleanu-Caputo fractional derivatives were used to express the time differentiation. In order to find a numerical solution of the proposed model, the finite difference method together with the Adams method were applied. The simulations results showed the chaotic behavior of the proposed model when different variable-orders are applied.

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks

PubMed Central

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

Models of networks of Leaky Integrate-and-Fire (LIF) neurons are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single neuron and neural population dynamics of conductance-based networks (COBNs) and current-based networks (CUBNs) of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity). However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-modulated in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, the network activity of COBN showed stronger synchronization in the gamma band, and spectral information about the input higher and spread over a broader range of frequencies. These results suggest that the second order statistics of network dynamics depend strongly on the choice of synaptic model. PMID:24634645

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks.

PubMed

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

Models of networks of Leaky Integrate-and-Fire (LIF) neurons are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single neuron and neural population dynamics of conductance-based networks (COBNs) and current-based networks (CUBNs) of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity). However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-modulated in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, the network activity of COBN showed stronger synchronization in the gamma band, and spectral information about the input higher and spread over a broader range of frequencies. These results suggest that the second order statistics of network dynamics depend strongly on the choice of synaptic model.

Dynamical analysis of the avian-human influenza epidemic model using the semi-analytical method

NASA Astrophysics Data System (ADS)

Jabbari, Azizeh; Kheiri, Hossein; Bekir, Ahmet

2015-03-01

In this work, we present a dynamic behavior of the avian-human influenza epidemic model by using efficient computational algorithm, namely the multistage differential transform method(MsDTM). The MsDTM is used here as an algorithm for approximating the solutions of the avian-human influenza epidemic model in a sequence of time intervals. In order to show the efficiency of the method, the obtained numerical results are compared with the fourth-order Runge-Kutta method (RK4M) and differential transform method(DTM) solutions. It is shown that the MsDTM has the advantage of giving an analytical form of the solution within each time interval which is not possible in purely numerical techniques like RK4M.

Numerical tests of local scale invariance in ageing q-state Potts models

NASA Astrophysics Data System (ADS)

Lorenz, E.; Janke, W.

2007-01-01

Much effort has been spent over the last years to achieve a coherent theoretical description of ageing as a non-linear dynamics process. Long supposed to be a consequence of the slow dynamics of glassy systems only, ageing phenomena could also be identified in the phase-ordering kinetics of simple ferromagnets. As a phenomenological approach Henkel et al. developed a group of local scale transformations under which two-time autocorrelation and response functions should transform covariantly. This work is to extend previous numerical tests of the predicted scaling functions for the Ising model by Monte Carlo simulations of two-dimensional q-state Potts models with q=3 and 8, which, in equilibrium, undergo temperature-driven phase transitions of second and first order, respectively.

White noise analysis of Phycomyces light growth response system. I. Normal intensity range.

PubMed Central

Lipson, E D

1975-01-01

The Wiener-Lee-Schetzen method for the identification of a nonlinear system through white gaussian noise stimulation was applied to the transient light growth response of the sporangiophore of Phycomyces. In order to cover a moderate dynamic range of light intensity I, the imput variable was defined to be log I. The experiments were performed in the normal range of light intensity, centered about I0 = 10(-6) W/cm2. The kernels of the Wierner functionals were computed up to second order. Within the range of a few decades the system is reasonably linear with log I. The main nonlinear feature of the second-order kernel corresponds to the property of rectification. Power spectral analysis reveals that the slow dynamics of the system are of at least fifth order. The system can be represented approximately by a linear transfer function, including a first-order high-pass (adaptation) filter with a 4 min time constant and an underdamped fourth-order low-pass filter. Accordingly a linear electronic circuit was constructed to simulate the small scale response characteristics. In terms of the adaptation model of Delbrück and Reichardt (1956, in Cellular Mechanisms in Differentiation and Growth, Princeton University Press), kernels were deduced for the dynamic dependence of the growth velocity (output) on the "subjective intensity", a presumed internal variable. Finally the linear electronic simulator above was generalized to accommodate the large scale nonlinearity of the adaptation model and to serve as a tool for deeper test of the model. PMID:1203444

Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

PubMed

Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

2017-01-01

Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

Linear and non-linear dynamic models of a geared rotor-bearing system

NASA Technical Reports Server (NTRS)

Kahraman, Ahmet; Singh, Rajendra

1990-01-01

A three degree of freedom non-linear model of a geared rotor-bearing system with gear backlash and radial clearances in rolling element bearings is proposed here. This reduced order model can be used to describe the transverse-torsional motion of the system. It is justified by comparing the eigen solutions yielded by corresponding linear model with the finite element method results. Nature of nonlinearities in bearings is examined and two approximate nonlinear stiffness functions are proposed. These approximate bearing models are verified by comparing their frequency responses with the results given by the exact form of nonlinearity. The proposed nonlinear dynamic model of the geared rotor-bearing system can be used to investigate the dynamic behavior and chaos.

Emergence of Collective Motion in a Model of Interacting Brownian Particles.

PubMed

Dossetti, Victor; Sevilla, Francisco J

2015-07-31

By studying a system of Brownian particles that interact among themselves only through a local velocity-alignment force that does not affect their speed, we show that self-propulsion is not a necessary feature for the flocking transition to take place as long as underdamped particle dynamics can be guaranteed. Moreover, the system transits from stationary phases close to thermal equilibrium, with no net flux of particles, to far-from-equilibrium ones exhibiting collective motion, phase coexistence, long-range order, and giant number fluctuations, features typically associated with ordered phases of models where self-propelled particles with overdamped dynamics are considered.

A physical model for earthquakes. I - Fluctuations and interactions. II - Application to southern California

NASA Technical Reports Server (NTRS)

Rundle, John B.

1988-01-01

The idea that earthquakes represent a fluctuation about the long-term motion of plates is expressed mathematically through the fluctuation hypothesis, under which all physical quantities which pertain to the occurance of earthquakes are required to depend on the difference between the present state of slip on the fault and its long-term average. It is shown that under certain circumstances the model fault dynamics undergo a sudden transition from a spatially ordered, temporally disordered state to a spatially disordered, temporally ordered state, and that the latter stages are stable for long intervals of time. For long enough faults, the dynamics are evidently chaotic. The methods developed are then used to construct a detailed model for earthquake dynamics in southern California. The result is a set of slip-time histories for all the major faults, which are similar to data obtained by geological trenching studies. Although there is an element of periodicity to the events, the patterns shift, change and evolve with time. Time scales for pattern evolution seem to be of the order of a thousand years for average recurring intervals of about a hundred years.

Validation of a RANS transition model using a high-order weighted compact nonlinear scheme

NASA Astrophysics Data System (ADS)

Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang

2013-04-01

A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.

Exponential quantum spreading in a class of kicked rotor systems near high-order resonances

NASA Astrophysics Data System (ADS)

Wang, Hailong; Wang, Jiao; Guarneri, Italo; Casati, Giulio; Gong, Jiangbin

2013-11-01

Long-lasting exponential quantum spreading was recently found in a simple but very rich dynamical model, namely, an on-resonance double-kicked rotor model [J. Wang, I. Guarneri, G. Casati, and J. B. Gong, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.234104 107, 234104 (2011)]. The underlying mechanism, unrelated to the chaotic motion in the classical limit but resting on quasi-integrable motion in a pseudoclassical limit, is identified for one special case. By presenting a detailed study of the same model, this work offers a framework to explain long-lasting exponential quantum spreading under much more general conditions. In particular, we adopt the so-called “spinor” representation to treat the kicked-rotor dynamics under high-order resonance conditions and then exploit the Born-Oppenheimer approximation to understand the dynamical evolution. It is found that the existence of a flat band (or an effectively flat band) is one important feature behind why and how the exponential dynamics emerges. It is also found that a quantitative prediction of the exponential spreading rate based on an interesting and simple pseudoclassical map may be inaccurate. In addition to general interests regarding the question of how exponential behavior in quantum systems may persist for a long time scale, our results should motivate further studies toward a better understanding of high-order resonance behavior in δ-kicked quantum systems.

Study on longitudinal force simulation of heavy-haul train

NASA Astrophysics Data System (ADS)

Chang, Chongyi; Guo, Gang; Wang, Junbiao; Ma, Yingming

2017-04-01

The longitudinal dynamics model of heavy-haul trains and air brake model used in the longitudinal train dynamics (LTDs) are established. The dry friction damping hysteretic characteristic of steel friction draft gears is simulated by the equation which describes the suspension forces in truck leaf springs. The model of draft gears introduces dynamic loading force, viscous friction of steel friction and the damping force. Consequently, the numerical model of the draft gears is brought forward. The equation of LTDs is strongly non-linear. In order to solve the response of the strongly non-linear system, the high-precision and equilibrium iteration method based on the Newmark-β method is presented and numerical analysis is made. Longitudinal dynamic forces of the 20,000 tonnes heavy-haul train are tested, and models and solution method provided are verified by the test results.

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

Persistence of Soil Organic Carbon can be Explained as an Emergent Property of Microbial Ecology and Population Dynamics

NASA Astrophysics Data System (ADS)

Woolf, D.; Lehmann, J.

2016-12-01

The exchange of carbon between soils and the atmosphere represents an important uncertainty in climate predictions. Current Earth system models apply soil organic matter (SOM) models based on independent carbon pools with 1st order decomposition dynamics. It has been widely argued over the last decade that such models do not accurately describe soil processes and mechanisms. For example, the long term persistence of soil organic carbon (SOC) is only adequately described by such models by the post hoc assumption of passive or inert carbon pools. Further, such 1st order models also fail to account for microbially-mediated dynamics such as priming interactions. These shortcomings may limit their applicability to long term predictions under conditions of global environmental change. In addition to incorporating recent conceptual advances in the mechanisms of SOM decomposition and protection, next-generation SOM models intended for use in Earth system models need to meet further quality criteria. Namely, that they should (a) accurately describe historical data from long term trials and the current global distribution of soil organic carbon, (b) be computationally efficient for large number of iterations involved in climate modeling, and (c) have sufficiently simple parameterization that they can be run on spatially-explicit data available at global scale under varying conditions of global change over long time scales. Here we show that linking fundamental ecological principles and microbial population dynamics to SOC turnover rates results in a dynamic model that meets all of these quality criteria. This approach simultaneously eliminates the need to postulate biogeochemically-implausible passive or inert pools, instead showing how SOM persistence emerges from ecological principles, while also reproducing observed priming interactions.

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.

A Lagrangian dynamic subgrid-scale model turbulence

NASA Technical Reports Server (NTRS)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

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.

Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Mathematical model of the loan portfolio dynamics in the form of Markov chain considering the process of new customers attraction

NASA Astrophysics Data System (ADS)

Bozhalkina, Yana

2017-12-01

Mathematical model of the loan portfolio structure change in the form of Markov chain is explored. This model considers in one scheme both the process of customers attraction, their selection based on the credit score, and loans repayment. The model describes the structure and volume of the loan portfolio dynamics, which allows to make medium-term forecasts of profitability and risk. Within the model corrective actions of bank management in order to increase lending volumes or to reduce the risk are formalized.

Approaches and possible improvements in the area of multibody dynamics modeling

NASA Technical Reports Server (NTRS)

Lips, K. W.; Singh, R.

1987-01-01

A wide ranging look is taken at issues involved in the dynamic modeling of complex, multibodied orbiting space systems. Capabilities and limitations of two major codes (DISCOS, TREETOPS) are assessed and possible extensions to the CONTOPS software are outlined. In addition, recommendations are made concerning the direction future development should take in order to achieve higher fidelity, more computationally efficient multibody software solutions.

Understanding bicycling in cities using system dynamics modelling.

PubMed

Macmillan, Alexandra; Woodcock, James

2017-12-01

Increasing urban bicycling has established net benefits for human and environmental health. Questions remain about which policies are needed and in what order, to achieve an increase in cycling while avoiding negative consequences. Novel ways of considering cycling policy are needed, bringing together expertise across policy, community and research to develop a shared understanding of the dynamically complex cycling system. In this paper we use a collaborative learning process to develop a dynamic causal model of urban cycling to develop consensus about the nature and order of policies needed in different cycling contexts to optimise outcomes. We used participatory system dynamics modelling to develop causal loop diagrams (CLDs) of cycling in three contrasting contexts: Auckland, London and Nijmegen. We combined qualitative interviews and workshops to develop the CLDs. We used the three CLDs to compare and contrast influences on cycling at different points on a "cycling trajectory" and drew out policy insights. The three CLDs consisted of feedback loops dynamically influencing cycling, with significant overlap between the three diagrams. Common reinforcing patterns emerged: growing numbers of people cycling lifts political will to improve the environment; cycling safety in numbers drives further growth; and more cycling can lead to normalisation across the population. By contrast, limits to growth varied as cycling increases. In Auckland and London, real and perceived danger was considered the main limit, with added barriers to normalisation in London. Cycling congestion and "market saturation" were important in the Netherlands. A generalisable, dynamic causal theory for urban cycling enables a more ordered set of policy recommendations for different cities on a cycling trajectory. Participation meant the collective knowledge of cycling stakeholders was represented and triangulated with research evidence. Extending this research to further cities, especially in low-middle income countries, would enhance generalizability of the CLDs.

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.

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

A Model Comparison for Characterizing Protein Motions from Structure

NASA Astrophysics Data System (ADS)

David, Charles; Jacobs, Donald

2011-10-01

A comparative study is made using three computational models that characterize native state dynamics starting from known protein structures taken from four distinct SCOP classifications. A geometrical simulation is performed, and the results are compared to the elastic network model and molecular dynamics. The essential dynamics is quantified by a direct analysis of a mode subspace constructed from ANM and a principal component analysis on both the FRODA and MD trajectories using root mean square inner product and principal angles. Relative subspace sizes and overlaps are visualized using the projection of displacement vectors on the model modes. Additionally, a mode subspace is constructed from PCA on an exemplar set of X-ray crystal structures in order to determine similarly with respect to the generated ensembles. Quantitative analysis reveals there is significant overlap across the three model subspaces and the model independent subspace. These results indicate that structure is the key determinant for native state dynamics.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

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.

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.

QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin

PubMed Central

Savol, Andrej J.; Burger, Virginia M.; Agarwal, Pratul K.; Ramanathan, Arvind; Chennubhotla, Chakra S.

2011-01-01

Motivation: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. Results: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 μs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. Contact: ramanathana@ornl.gov; chakracs@pitt.edu PMID:21685101

VHDL-AMS modelling and simulation of a planar electrostatic micromotor

NASA Astrophysics Data System (ADS)

Endemaño, A.; Fourniols, J. Y.; Camon, H.; Marchese, A.; Muratet, S.; Bony, F.; Dunnigan, M.; Desmulliez, M. P. Y.; Overton, G.

2003-09-01

System level simulation results of a planar electrostatic micromotor, based on analytical models of the static and dynamic torque behaviours, are presented. A planar variable capacitance (VC) electrostatic micromotor designed, fabricated and tested at LAAS (Toulouse) in 1995 is simulated using the high level language VHDL-AMS (VHSIC (very high speed integrated circuits) hardware description language-analog mixed signal). The analytical torque model is obtained by first calculating the overlaps and capacitances between different electrodes based on a conformal mapping transformation. Capacitance values in the order of 10-16 F and torque values in the order of 10-11 N m have been calculated in agreement with previous measurements and simulations from this type of motor. A dynamic model has been developed for the motor by calculating the inertia coefficient and estimating the friction-coefficient-based values calculated previously for other similar devices. Starting voltage results obtained from experimental measurement are in good agreement with our proposed simulation model. Simulation results of starting voltage values, step response, switching response and continuous operation of the micromotor, based on the dynamic model of the torque, are also presented. Four VHDL-AMS blocks were created, validated and simulated for power supply, excitation control, micromotor torque creation and micromotor dynamics. These blocks can be considered as the initial phase towards the creation of intellectual property (IP) blocks for microsystems in general and electrostatic micromotors in particular.

From Glass Formation to Icosahedral Ordering by Curving Three-Dimensional Space.

PubMed

Turci, Francesco; Tarjus, Gilles; Royall, C Patrick

2017-05-26

Geometric frustration describes the inability of a local molecular arrangement, such as icosahedra found in metallic glasses and in model atomic glass formers, to tile space. Local icosahedral order, however, is strongly frustrated in Euclidean space, which obscures any causal relationship with the observed dynamical slowdown. Here we relieve frustration in a model glass-forming liquid by curving three-dimensional space onto the surface of a 4-dimensional hypersphere. For sufficient curvature, frustration vanishes and the liquid "freezes" in a fully icosahedral structure via a sharp "transition." Frustration increases upon reducing the curvature, and the transition to the icosahedral state smoothens while glassy dynamics emerge. Decreasing the curvature leads to decoupling between dynamical and structural length scales and the decrease of kinetic fragility. This sheds light on the observed glass-forming behavior in Euclidean space.

Order parameter analysis of synchronization transitions on star networks

NASA Astrophysics Data System (ADS)

Chen, Hong-Bin; Sun, Yu-Ting; Gao, Jian; Xu, Can; Zheng, Zhi-Gang

2017-12-01

The collective behaviors of populations of coupled oscillators have attracted significant attention in recent years. In this paper, an order parameter approach is proposed to study the low-dimensional dynamical mechanism of collective synchronizations, by adopting the star-topology of coupled oscillators as a prototype system. The order parameter equation of star-linked phase oscillators can be obtained in terms of the Watanabe-Strogatz transformation, Ott-Antonsen ansatz, and the ensemble order parameter approach. Different solutions of the order parameter equation correspond to the diverse collective states, and different bifurcations reveal various transitions among these collective states. The properties of various transitions in the star-network model are revealed by using tools of nonlinear dynamics such as time reversibility analysis and linear stability analysis.

SCISEAL: A CFD code for analysis of fluid dynamic forces in seals

NASA Technical Reports Server (NTRS)

Athavale, Mahesh; Przekwas, Andrzej

1994-01-01

A viewgraph presentation is made of the objectives, capabilities, and test results of the computer code SCISEAL. Currently, the seal code has: a finite volume, pressure-based integration scheme; colocated variables with strong conservation approach; high-order spatial differencing, up to third-order; up to second-order temporal differencing; a comprehensive set of boundary conditions; a variety of turbulence models and surface roughness treatment; moving grid formulation for arbitrary rotor whirl; rotor dynamic coefficients calculated by the circular whirl and numerical shaker methods; and small perturbation capabilities to handle centered and eccentric seals.

Study on dynamic characteristics of hydraulic pumping unit on offshore platform

NASA Astrophysics Data System (ADS)

Chang, Zong-yu; Yu, Yan-qun; Qi, Yao-guang

2017-12-01

A new technology of offshore oil rod pumping production is developed for offshore heavy oil recovery. A new type of miniature hydraulic pumping unit with long-stroke, low pumping speed and compact structure is designed based on the spatial characteristics of offshore platforms. By combining the strengths of sinusoidal velocity curve and trapezoidal velocity curve, a kinematical model of the acceleration, the velocity and displacement of the pumping unit's hanging point is established. The results show that the pumping unit has good kinematic characteristics of smooth motion and small dynamic load. The multi-degree-of-freedom dynamic model of the single-well pumping unit is established. The first and second order natural frequencies of the sucker rod string subsystem and the pumping unit subsystem are studied. The results show that the first and the second order natural frequencies among the pumping rod string, pumping unit-platform subsystem and the dynamic excitation have differences over 5 times from each other, indicating that resonance phenomenon will not appear during the operation and the dynamic requirements for field use are met in the system.

Optimal sensor placement for control of a supersonic mixed-compression inlet with variable geometry

NASA Astrophysics Data System (ADS)

Moore, Kenneth Thomas

A method of using fluid dynamics models for the generation of models that are useable for control design and analysis is investigated. The problem considered is the control of the normal shock location in the VDC inlet, which is a mixed-compression, supersonic, variable-geometry inlet of a jet engine. A quasi-one-dimensional set of fluid equations incorporating bleed and moving walls is developed. An object-oriented environment is developed for simulation of flow systems under closed-loop control. A public interface between the controller and fluid classes is defined. A linear model representing the dynamics of the VDC inlet is developed from the finite difference equations, and its eigenstructure is analyzed. The order of this model is reduced using the square root balanced model reduction method to produce a reduced-order linear model that is suitable for control design and analysis tasks. A modification to this method that improves the accuracy of the reduced-order linear model for the purpose of sensor placement is presented and analyzed. The reduced-order linear model is used to develop a sensor placement method that quantifies as a function of the sensor location the ability of a sensor to provide information on the variable of interest for control. This method is used to develop a sensor placement metric for the VDC inlet. The reduced-order linear model is also used to design a closed loop control system to control the shock position in the VDC inlet. The object-oriented simulation code is used to simulate the nonlinear fluid equations under closed-loop control.

Optimization of an intracavity Q-switched solid-state second order Raman laser

NASA Astrophysics Data System (ADS)

Chen, Zhiqiong; Fu, Xihong; Peng, Hangyu; Zhang, Jun; Qin, Li; Ning, Yongqiang

2017-01-01

In this paper, the model of an intracavity Q-switched second order Raman laser is established, the characteristics of the output 2nd Stokes are simulated. The dynamic balance mechanism among intracavity conversion rates of stimulated emission, first order Raman and second order Raman is obtained. Finally, optimization solutions for increasing output 2nd Stokes pulse energy are proposed.

A Petascale Non-Hydrostatic Atmospheric Dynamical Core in the HOMME Framework

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

Tufo, Henry

The High-Order Method Modeling Environment (HOMME) is a framework for building scalable, conserva- tive atmospheric models for climate simulation and general atmospheric-modeling applications. Its spatial discretizations are based on Spectral-Element (SE) and Discontinuous Galerkin (DG) methods. These are local methods employing high-order accurate spectral basis-functions that have been shown to perform well on massively parallel supercomputers at any resolution and scale particularly well at high resolutions. HOMME provides the framework upon which the CAM-SE community atmosphere model dynamical-core is constructed. In its current incarnation, CAM-SE employs the hydrostatic primitive-equations (PE) of motion, which limits its resolution to simulations coarser thanmore » 0.1 per grid cell. The primary objective of this project is to remove this resolution limitation by providing HOMME with the capabilities needed to build nonhydrostatic models that solve the compressible Euler/Navier-Stokes equations.« less

Distributed containment control of heterogeneous fractional-order multi-agent systems with communication delays

NASA Astrophysics Data System (ADS)

Yang, Hongyong; Han, Fujun; Zhao, Mei; Zhang, Shuning; Yue, Jun

2017-08-01

Because many networked systems can only be characterized with fractional-order dynamics in complex environments, fractional-order calculus has been studied deeply recently. When diverse individual features are shown in different agents of networked systems, heterogeneous fractional-order dynamics will be used to describe the complex systems. Based on the distinguishing properties of agents, heterogeneous fractional-order multi-agent systems (FOMAS) are presented. With the supposition of multiple leader agents in FOMAS, distributed containment control of FOMAS is studied in directed weighted topologies. By applying Laplace transformation and frequency domain theory of the fractional-order operator, an upper bound of delays is obtained to ensure containment consensus of delayed heterogenous FOMAS. Consensus results of delayed FOMAS in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.

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.

Quasi One-Dimensional Unsteady Modeling of External Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Kratz, Jonathan

2012-01-01

The AeroServoElasticity task under the NASA Supersonics Project is developing dynamic models of the propulsion system and the vehicle in order to conduct research for integrated vehicle dynamic performance. As part of this effort, a nonlinear quasi 1-dimensional model of an axisymmetric external compression supersonic inlet is being developed. The model utilizes compressible flow computational fluid dynamics to model the internal inlet segment as well as the external inlet portion between the cowl lip and normal shock, and compressible flow relations with flow propagation delay to model the oblique shocks upstream of the normal shock. The external compression portion between the cowl-lip and the normal shock is also modeled with leaking fluxes crossing the sonic boundary, with a moving CFD domain at the normal shock boundary. This model has been verified in steady state against tunnel inlet test data and it s a first attempt towards developing a more comprehensive model for inlet dynamics.

Proper Orthogonal Decomposition in Optimal Control of Fluids

NASA Technical Reports Server (NTRS)

Ravindran, S. S.

1999-01-01

In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.

Modeling and characterization of an electromagnetic system for the estimation of Frequency Response Function of spindle

NASA Astrophysics Data System (ADS)

Tlalolini, David; Ritou, Mathieu; Rabréau, Clément; Le Loch, Sébastien; Furet, Benoit

2018-05-01

The paper presents an electromagnetic system that has been developed to measure the quasi-static and dynamic behavior of machine-tool spindle, at different spindle speeds. This system consists in four Pulse Width Modulation amplifiers and four electromagnets to produce magnetic forces of ± 190 N for the static mode and ± 80 N for the dynamic mode up to 5 kHz. In order to measure the Frequency Response Function (FRF) of spindle, the applied force is required, which is a key issue. A dynamic force model is proposed in order to obtain the load from the measured current in the amplifiers. The model depends on the exciting frequency and on the magnetic characteristics of the system. The predicted force at high speed is validated with a specific experiment and the performance limits of the experimental device are investigated. The FRF obtained with the electromagnetic system is compared to a classical tap test measurement.

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

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

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.

Influence of credit scoring on the dynamics of Markov chain

NASA Astrophysics Data System (ADS)

Galina, Timofeeva

2015-11-01

Markov processes are widely used to model the dynamics of a credit portfolio and forecast the portfolio risk and profitability. In the Markov chain model the loan portfolio is divided into several groups with different quality, which determined by presence of indebtedness and its terms. It is proposed that dynamics of portfolio shares is described by a multistage controlled system. The article outlines mathematical formalization of controls which reflect the actions of the bank's management in order to improve the loan portfolio quality. The most important control is the organization of approval procedure of loan applications. The credit scoring is studied as a control affecting to the dynamic system. Different formalizations of "good" and "bad" consumers are proposed in connection with the Markov chain model.

Cycle-averaged dynamics of a periodically driven, closed-loop circulation model

NASA Technical Reports Server (NTRS)

Heldt, T.; Chang, J. L.; Chen, J. J. S.; Verghese, G. C.; Mark, R. G.

2005-01-01

Time-varying elastance models have been used extensively in the past to simulate the pulsatile nature of cardiovascular waveforms. Frequently, however, one is interested in dynamics that occur over longer time scales, in which case a detailed simulation of each cardiac contraction becomes computationally burdensome. In this paper, we apply circuit-averaging techniques to a periodically driven, closed-loop, three-compartment recirculation model. The resultant cycle-averaged model is linear and time invariant, and greatly reduces the computational burden. It is also amenable to systematic order reduction methods that lead to further efficiencies. Despite its simplicity, the averaged model captures the dynamics relevant to the representation of a range of cardiovascular reflex mechanisms. c2004 Elsevier Ltd. All rights reserved.

Entropy production in a Glauber–Ising irreversible model with dynamical competition

NASA Astrophysics Data System (ADS)

Barbosa, Oscar A.; Tomé, Tânia

2018-06-01

An out of equilibrium Glauber–Ising model, evolving in accordance with an irreversible and stochastic Markovian dynamics, is analyzed in order to improve our comprehension concerning critical behavior and phase transitions in nonequilibrium systems. Therefore, a lattice model ruled by the competition between two Glauber dynamics acting on interlaced square lattices is proposed. Previous results have shown how the entropy production provides information about irreversibility and criticality. Mean-field approximations and Monte Carlo simulations were used in the analysis. The results obtained here show a continuous phase transition, reflected in the entropy production as a logarithmic divergence of its derivative, which suggests a shared universality class with the irreversible models invariant under the symmetry operations of the Ising model.

Earthquake models using rate and state friction and fast multipoles

NASA Astrophysics Data System (ADS)

Tullis, T.

2003-04-01

The most realistic current earthquake models employ laboratory-derived non-linear constitutive laws. These are the rate and state friction laws having both a non-linear viscous or direct effect and an evolution effect in which frictional resistance depends on time of stationary contact and has a memory of past slip velocity that fades with slip. The frictional resistance depends on the log of the slip velocity as well as the log of stationary hold time, and the fading memory involves an approximately exponential decay with slip. Due to the nonlinearly of these laws, analytical earthquake models are not attainable and numerical models are needed. The situation is even more difficult if true dynamic models are sought that deal with inertial forces and slip velocities on the order of 1 m/s as are observed during dynamic earthquake slip. Additional difficulties that exist if the dynamic slip phase of earthquakes is modeled arise from two sources. First, many physical processes might operate during dynamic slip, but they are only poorly understood, the relative importance of the processes is unknown, and the processes are even more nonlinear than those described by the current rate and state laws. Constitutive laws describing such behaviors are still being developed. Second, treatment of inertial forces and the influence that dynamic stresses from elastic waves may have on slip on the fault requires keeping track of the history of slip on remote parts of the fault as far into the past as it takes waves to travel from there. This places even more stringent requirements on computer time. Challenges for numerical modeling of complete earthquake cycles are that both time steps and mesh sizes must be small. Time steps must be milliseconds during dynamic slip, and yet models must represent earthquake cycles 100 years or more in length; methods using adaptive step sizes are essential. Element dimensions need to be on the order of meters, both to approximate continuum behavior adequately and to model microseismicity as well as large earthquakes. In order to model significant sized earthquakes this requires millions of elements. Modeling methods like the boundary element method that involve Green's functions normally require computation times that increase with the number N of elements squared, so using large N becomes impossible. We have adapted the Fast Multipole method to this problem in which the influence of sufficiently remote elements are grouped together and the elements are indexed such that the computations more efficient when run on parallel computers. Compute time varies with N log N rather than N squared. Computer programs are available that use this approach (http://www.servogrid.org/slide/GEM/PARK). Whether the multipole approach can be adapted to dynamic modeling is unclear.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Reduced-Order Modeling: Cooperative Research and Development at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Beran, Philip S.; Cesnik, Carlos E. S.; Guendel, Randal E.; Kurdila, Andrew; Prazenica, Richard J.; Librescu, Liviu; Marzocca, Piergiovanni; Raveh, Daniella E.

2001-01-01

Cooperative research and development activities at the NASA Langley Research Center (LaRC) involving reduced-order modeling (ROM) techniques are presented. Emphasis is given to reduced-order methods and analyses based on Volterra series representations, although some recent results using Proper Orthogonal Deco in position (POD) are discussed as well. Results are reported for a variety of computational and experimental nonlinear systems to provide clear examples of the use of reduced-order models, particularly within the field of computational aeroelasticity. The need for and the relative performance (speed, accuracy, and robustness) of reduced-order modeling strategies is documented. The development of unsteady aerodynamic state-space models directly from computational fluid dynamics analyses is presented in addition to analytical and experimental identifications of Volterra kernels. Finally, future directions for this research activity are summarized.

Fixing the fixed-point system—Applying Dynamic Renormalization Group to systems with long-range interactions

NASA Astrophysics Data System (ADS)

Katzav, Eytan

2013-04-01

In this paper, a mode of using the Dynamic Renormalization Group (DRG) method is suggested in order to cope with inconsistent results obtained when applying it to a continuous family of one-dimensional nonlocal models. The key observation is that the correct fixed-point dynamical system has to be identified during the analysis in order to account for all the relevant terms that are generated under renormalization. This is well established for static problems, however poorly implemented in dynamical ones. An application of this approach to a nonlocal extension of the Kardar-Parisi-Zhang equation resolves certain problems in one-dimension. Namely, obviously problematic predictions are eliminated and the existing exact analytic results are recovered.

Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

NASA Astrophysics Data System (ADS)

Li, Lesheng; Giokas, Paul G.; Kanai, Yosuke; Moran, Andrew M.

2014-06-01

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO2 using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.

First dynamic model of dissolved organic carbon derived directly from high-frequency observations through contiguous storms.

PubMed

Jones, Timothy D; Chappell, Nick A; Tych, Wlodek

2014-11-18

The first dynamic model of dissolved organic carbon (DOC) export in streams derived directly from high frequency (subhourly) observations sampled at a regular interval through contiguous storms is presented. The optimal model, identified using the recently developed RIVC algorithm, captured the rapid dynamics of DOC load from 15 min monitored rainfall with high simulation efficiencies and constrained uncertainty with a second-order (two-pathway) structure. Most of the DOC export in the four headwater basins studied was associated with the faster hydrometric pathway (also modeled in parallel), and was soon exhausted in the slower pathway. A delay in the DOC mobilization became apparent as the ambient temperatures increased. These features of the component pathways were quantified in the dynamic response characteristics (DRCs) identified by RIVC. The model and associated DRCs are intended as a foundation for a better understanding of storm-related DOC dynamics and predictability, given the increasing availability of subhourly DOC concentration data.

Self-sustaining turbulence in a restricted nonlinear model of plane Couette flow

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

Thomas, Vaughan L.; Gayme, Dennice F.; Lieu, Binh K.

2014-10-15

This paper demonstrates the maintenance of self-sustaining turbulence in a restricted nonlinear (RNL) model of plane Couette flow. The RNL system is derived directly from the Navier-Stokes equations and permits higher resolution studies of the dynamical system associated with the stochastic structural stability theory (S3T) model, which is a second order approximation of the statistical state dynamics of the flow. The RNL model shares the dynamical restrictions of the S3T model but can be easily implemented by reducing a DNS code so that it retains only the RNL dynamics. Comparisons of turbulence arising from DNS and RNL simulations demonstrate thatmore » the RNL system supports self-sustaining turbulence with a mean flow as well as structural and dynamical features that are consistent with DNS. These results demonstrate that the simplified RNL system captures fundamental aspects of fully developed turbulence in wall-bounded shear flows and motivate use of the RNL/S3T framework for further study of wall-turbulence.« less

PDEMOD: Software for control/structures optimization

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr.; Zimmerman, David

1991-01-01

Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.

Dynamic emulation modelling for the optimal operation of water systems: an overview

NASA Astrophysics Data System (ADS)

Castelletti, A.; Galelli, S.; Giuliani, M.

2014-12-01

Despite sustained increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems. As a result, increasing attention is now being devoted to emulation modelling (or model reduction) as a way of overcoming these limitations. An emulation model, or emulator, is a low-order approximation of the process-based model that can be substituted for it in order to solve high resource-demanding problems. In this talk, an overview of emulation modelling within the context of the optimal operation of water systems will be provided. Particular emphasis will be given to Dynamic Emulation Modelling (DEMo), a special type of model complexity reduction in which the dynamic nature of the original process-based model is preserved, with consequent advantages in a wide range of problems, particularly feedback control problems. This will be contrasted with traditional non-dynamic emulators (e.g. response surface and surrogate models) that have been studied extensively in recent years and are mainly used for planning purposes. A number of real world numerical experiences will be used to support the discussion ranging from multi-outlet water quality control in water reservoir through erosion/sedimentation rebalancing in the operation of run-off-river power plants to salinity control in lake and reservoirs.

Global dynamics and diffusion in triaxial galactic models

NASA Astrophysics Data System (ADS)

Papaphilippou, Y.

We apply the Frequency Map Analysis method to the 3--dimensional logarithmic galactic potential in order to clarify the dynamical behaviour of triaxial power--law galactic models. All the fine dynamical details are displayed in the complete frequency map, a direct representation of the system's Arnol'd web. The influence of resonant lines and the extent of the chaotic zones are directly associated with the physical space of the system. Some new results related with the diffusion of galactic orbits are also discussed. This approach reveals many unknown dynamical features of triaxial galactic potentials and provides strong indications that chaos should be an innate characteristic of triaxial configurations.

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

Barbante, Paolo; Frezzotti, Aldo; Gibelli, Livio

The unsteady evaporation of a thin planar liquid film is studied by molecular dynamics simulations of Lennard-Jones fluid. The obtained results are compared with the predictions of a diffuse interface model in which capillary Korteweg contributions are added to hydrodynamic equations, in order to obtain a unified description of the liquid bulk, liquid-vapor interface and vapor region. Particular care has been taken in constructing a diffuse interface model matching the thermodynamic and transport properties of the Lennard-Jones fluid. The comparison of diffuse interface model and molecular dynamics results shows that, although good agreement is obtained in equilibrium conditions, remarkable deviationsmore » of diffuse interface model predictions from the reference molecular dynamics results are observed in the simulation of liquid film evaporation. It is also observed that molecular dynamics results are in good agreement with preliminary results obtained from a composite model which describes the liquid film by a standard hydrodynamic model and the vapor by the Boltzmann equation. The two mathematical model models are connected by kinetic boundary conditions assuming unit evaporation coefficient.« less

Weighted fractional permutation entropy and fractional sample entropy for nonlinear Potts financial dynamics

NASA Astrophysics Data System (ADS)

Xu, Kaixuan; Wang, Jun

2017-02-01

In this paper, recently introduced permutation entropy and sample entropy are further developed to the fractional cases, weighted fractional permutation entropy (WFPE) and fractional sample entropy (FSE). The fractional order generalization of information entropy is utilized in the above two complexity approaches, to detect the statistical characteristics of fractional order information in complex systems. The effectiveness analysis of proposed methods on the synthetic data and the real-world data reveals that tuning the fractional order allows a high sensitivity and more accurate characterization to the signal evolution, which is useful in describing the dynamics of complex systems. Moreover, the numerical research on nonlinear complexity behaviors is compared between the returns series of Potts financial model and the actual stock markets. And the empirical results confirm the feasibility of the proposed model.

Design an optimum safety policy for personnel safety management - A system dynamic approach

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

Balaji, P.

2014-10-06

Personnel safety management (PSM) ensures that employee's work conditions are healthy and safe by various proactive and reactive approaches. Nowadays it is a complex phenomenon because of increasing dynamic nature of organisations which results in an increase of accidents. An important part of accident prevention is to understand the existing system properly and make safety strategies for that system. System dynamics modelling appears to be an appropriate methodology to explore and make strategy for PSM. Many system dynamics models of industrial systems have been built entirely for specific host firms. This thesis illustrates an alternative approach. The generic system dynamicsmore » model of Personnel safety management was developed and tested in a host firm. The model was undergone various structural, behavioural and policy tests. The utility and effectiveness of model was further explored through modelling a safety scenario. In order to create effective safety policy under resource constraint, DOE (Design of experiment) was used. DOE uses classic designs, namely, fractional factorials and central composite designs. It used to make second order regression equation which serve as an objective function. That function was optimized under budget constraint and optimum value used for safety policy which shown greatest improvement in overall PSM. The outcome of this research indicates that personnel safety management model has the capability for acting as instruction tool to improve understanding of safety management and also as an aid to policy making.« less

Massively Parallel Simulations of Diffusion in Dense Polymeric Structures

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

Faulon, Jean-Loup, Wilcox, R.T.

1997-11-01

An original computational technique to generate close-to-equilibrium dense polymeric structures is proposed. Diffusion of small gases are studied on the equilibrated structures using massively parallel molecular dynamics simulations running on the Intel Teraflops (9216 Pentium Pro processors) and Intel Paragon(1840 processors). Compared to the current state-of-the-art equilibration methods this new technique appears to be faster by some orders of magnitude.The main advantage of the technique is that one can circumvent the bottlenecks in configuration space that inhibit relaxation in molecular dynamics simulations. The technique is based on the fact that tetravalent atoms (such as carbon and silicon) fit in themore » center of a regular tetrahedron and that regular tetrahedrons can be used to mesh the three-dimensional space. Thus, the problem of polymer equilibration described by continuous equations in molecular dynamics is reduced to a discrete problem where solutions are approximated by simple algorithms. Practical modeling applications include the constructing of butyl rubber and ethylene-propylene-dimer-monomer (EPDM) models for oxygen and water diffusion calculations. Butyl and EPDM are used in O-ring systems and serve as sealing joints in many manufactured objects. Diffusion coefficients of small gases have been measured experimentally on both polymeric systems, and in general the diffusion coefficients in EPDM are an order of magnitude larger than in butyl. In order to better understand the diffusion phenomena, 10, 000 atoms models were generated and equilibrated for butyl and EPDM. The models were submitted to a massively parallel molecular dynamics simulation to monitor the trajectories of the diffusing species.« less

A multilayer approach for price dynamics in financial markets

NASA Astrophysics Data System (ADS)

Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

2017-02-01

We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dynamics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.

On DSS Implementation in the Dynamic Model of the Digital Oil field

NASA Astrophysics Data System (ADS)

Korovin, Iakov S.; Khisamutdinov, Maksim V.; Kalyaev, Anatoly I.

2018-02-01

Decision support systems (DSS), especially based on the artificial intelligence (AI) techniques are been widely applied in different domains nowadays. In the paper we depict an approach of implementing DSS in to Digital Oil Field (DOF) dynamic model structure in order to reduce the human factor influence, considering the automation of all production processes to be the DOF model clue element. As the basic tool of data handling we propose the hybrid application on artificial neural networks and evolutional algorithms.

Analysing and controlling the tax evasion dynamics via majority-vote model

NASA Astrophysics Data System (ADS)

Lima, F. W. S.

2010-09-01

Within the context of agent-based Monte-Carlo simulations, we study the well-known majority-vote model (MVM) with noise applied to tax evasion on simple square lattices, Voronoi-Delaunay random lattices, Barabasi-Albert networks, and Erdös-Rényi random graphs. In the order to analyse and to control the fluctuations for tax evasion in the economics model proposed by Zaklan, MVM is applied in the neighborhod of the noise critical qc to evolve the Zaklan model. The Zaklan model had been studied recently using the equilibrium Ising model. Here we show that the Zaklan model is robust because this can be studied using equilibrium dynamics of Ising model also through the nonequilibrium MVM and on various topologies cited above giving the same behavior regardless of dynamic or topology used here.

Toward Simplification of Dynamic Subgrid-Scale Models

NASA Technical Reports Server (NTRS)

Pruett, C. David

1997-01-01

We examine the relationship between the filter and the subgrid-scale (SGS) model for large-eddy simulations, in general, and for those with dynamic SGS models, in particular. From a review of the literature, it would appear that many practitioners of LES consider the link between the filter and the model more or less as a formality of little practical effect. In contrast, we will show that the filter and the model are intimately linked, that the Smagorinsky SGS model is appropriate only for filters of first- or second-order, and that the Smagorinsky model is inconsistent with spectral filters. Moreover, the Germano identity is shown to be both problematic and unnecessary for the development of dynamic SGS models. Its use obscures the following fundamental realization: For a suitably chosen filter, the computible resolved turbulent stresses, property scaled, closely approximate the SGS stresses.

A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives.

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2014-01-01

In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding a good "reshaping" function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion.

A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2014-01-01

In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a “reshaping” function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal “reshaping” functions). In this article, we use this architecture with the actor-critic algorithms for finding a good “reshaping” function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion. PMID:25324773

Dynamics of 3D Timoshenko gyroelastic beams with large attitude changes for the gyros

NASA Astrophysics Data System (ADS)

Hassanpour, Soroosh; Heppler, G. R.

2016-01-01

This work is concerned with the theoretical development of dynamic equations for undamped gyroelastic beams which are dynamic systems with continuous inertia, elasticity, and gyricity. Assuming unrestricted or large attitude changes for the axes of the gyros and utilizing generalized Hooke's law, Duleau torsion theory, and Timoshenko bending theory, the energy expressions and equations of motion for the gyroelastic beams in three-dimensional space are derived. The so-obtained comprehensive gyroelastic beam model is compared against earlier gyroelastic beam models developed using Euler-Bernoulli beam models and is used to study the dynamics of gyroelastic beams through numerical examples. It is shown that there are significant differences between the developed unrestricted Timoshenko gyroelastic beam model and the previously derived zero-order restricted Euler-Bernoulli gyroelastic beam models. These differences are more pronounced in the short beam and transverse gyricity cases.

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Zia, Omar

1989-01-01

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

The Artificial Hamiltonian, First Integrals, and Closed-Form Solutions of Dynamical Systems for Epidemics

NASA Astrophysics Data System (ADS)

Naz, Rehana; Naeem, Imran

2018-03-01

The non-standard Hamiltonian system, also referred to as a partial Hamiltonian system in the literature, of the form {\\dot q^i} = {partial H}/{partial {p_i}},\\dot p^i = - {partial H}/{partial {q_i}} + {Γ ^i}(t,{q^i},{p_i}) appears widely in economics, physics, mechanics, and other fields. The non-standard (partial) Hamiltonian systems arise from physical Hamiltonian structures as well as from artificial Hamiltonian structures. We introduce the term `artificial Hamiltonian' for the Hamiltonian of a model having no physical structure. We provide here explicitly the notion of an artificial Hamiltonian for dynamical systems of ordinary differential equations (ODEs). Also, we show that every system of second-order ODEs can be expressed as a non-standard (partial) Hamiltonian system of first-order ODEs by introducing an artificial Hamiltonian. This notion of an artificial Hamiltonian gives a new way to solve dynamical systems of first-order ODEs and systems of second-order ODEs that can be expressed as a non-standard (partial) Hamiltonian system by using the known techniques applicable to the non-standard Hamiltonian systems. We employ the proposed notion to solve dynamical systems of first-order ODEs arising in epidemics.

Low energy excitations and Drude-Smith carrier dynamics in Sm0.5Sr0.5MnO3

NASA Astrophysics Data System (ADS)

Kumar, K. Santhosh; Das, Sarmistha; Prajapati, G. L.; Philip, Sharon S.; Rana, D. S.

2017-05-01

We have performed terahertz time-domain spectroscopic measurements on half-doped charge-ordered manganite Sm0.5Sr0.5MnO3 in the temperature range of 5-300 K to explore the possibilities of the charge density wave (CDW) ground state and understand the low energy charge carrier dynamics. While a resonance absorption peak at 0.275 meV suggests formation of a CDW condensate, the increase in background conductivity due to uncondensed carriers obey the Drude-Smith model of carrier dynamics. This study confirms that CDW is a generic feature of charge-ordered manganites.

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Effect of Dust Coagulation Dynamics on the Geometry of Aggregates

NASA Technical Reports Server (NTRS)

Nakamura, R.

1996-01-01

Master equation gives a more fundamental description of stochastic coagulation processes rather than popular Smoluchowski's equation. In order to examine the effect of the dynamics on the geometry of resulting aggregates, we study Master equation with a rigorous Monte Carlo algorithm. It is found that Cluster-Cluster aggregation model is a good approximation of orderly growth and the aggregates have fluffy structures with a fractal dimension approx. 2. A scaling analysis of Smoluchowski's equation also supports this conclusion.

Prediction of muscle activation for an eye movement with finite element modeling.

PubMed

Karami, Abbas; Eghtesad, Mohammad; Haghpanah, Seyyed Arash

2017-10-01

In this paper, a 3D finite element (FE) modeling is employed in order to predict extraocular muscles' activation and investigate force coordination in various motions of the eye orbit. A continuum constitutive hyperelastic model is employed for material description in dynamic modeling of the extraocular muscles (EOMs). Two significant features of this model are accurate mass modeling with FE method and stimulating EOMs for motion through muscle activation parameter. In order to validate the eye model, a forward dynamics simulation of the eye motion is carried out by variation of the muscle activation. Furthermore, to realize muscle activation prediction in various eye motions, two different tracking-based inverse controllers are proposed. The performance of these two inverse controllers is investigated according to their resulted muscle force magnitude and muscle force coordination. The simulation results are compared with the available experimental data and the well-known existing neurological laws. The comparison authenticates both the validation and the prediction results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling Dynamic Regulatory Processes in Stroke.

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

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

2012-10-11

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less

Dynamic modeling of hybrid renewable energy systems for off-grid applications

NASA Astrophysics Data System (ADS)

Hasemeyer, Mark David

The volatile prices of fossil fuels and their contribution to global warming have caused many people to turn to renewable energy systems. Many developing communities are forced to use these systems as they are too far from electrical distribution. As a result, numerous software models have been developed to simulate hybrid renewable energy systems. However almost, if not all, implementations are static in design. A static design limits the ability of the model to account for changes over time. Dynamic modeling can be used to fill the gaps where other modeling techniques fall short. This modeling practice allows the user to account for the effects of technological and economic factors over time. These factors can include changes in energy demand, energy production, and income level. Dynamic modeling can be particularly useful for developing communities who are off-grid and developing at rapid rates. In this study, a dynamic model was used to evaluate a real world system. A non-governmental organization interested in improving their current infrastructure was selected. Five different scenarios were analyzed and compared in order to discover which factors the model is most sensitive to. In four of the scenarios, a new energy system was purchased in order to account for the opening of a restaurant that would be used as a source of local income generation. These scenarios were then compared to a base case in which a new system was not purchased, and the restaurant was not opened. Finally, the results were used to determine which variables had the greatest impact on the various outputs of the simulation.

Reduced quantum dynamics with arbitrary bath spectral densities: hierarchical equations of motion based on several different bath decomposition schemes.

PubMed

Liu, Hao; Zhu, Lili; Bai, Shuming; Shi, Qiang

2014-04-07

We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly in the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.

Reduced quantum dynamics with arbitrary bath spectral densities: Hierarchical equations of motion based on several different bath decomposition schemes

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

Liu, Hao; Zhu, Lili; Bai, Shuming

2014-04-07

We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly inmore » the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.« less

Dynamic modelling and simulation of linear Fresnel solar field model based on molten salt heat transfer fluid

NASA Astrophysics Data System (ADS)

Hakkarainen, Elina; Tähtinen, Matti

2016-05-01

Demonstrations of direct steam generation (DSG) in linear Fresnel collectors (LFC) have given promising results related to higher steam parameters compared to the current state-of-the-art parabolic trough collector (PTC) technology using oil as heat transfer fluid (HTF). However, DSG technology lacks feasible solution for long-term thermal energy storage (TES) system. This option is important for CSP technology in order to offer dispatchable power. Recently, molten salts have been proposed to be used as HTF and directly as storage medium in both line-focusing solar fields, offering storage capacity of several hours. This direct molten salt (DMS) storage concept has already gained operational experience in solar tower power plant, and it is under demonstration phase both in the case of LFC and PTC systems. Dynamic simulation programs offer a valuable effort for design and optimization of solar power plants. In this work, APROS dynamic simulation program is used to model a DMS linear Fresnel solar field with two-tank TES system, and example simulation results are presented in order to verify the functionality of the model and capability of APROS for CSP modelling and simulation.

Implementation of Kalman filter algorithm on models reduced using singular pertubation approximation method and its application to measurement of water level

NASA Astrophysics Data System (ADS)

Rachmawati, Vimala; Khusnul Arif, Didik; Adzkiya, Dieky

2018-03-01

The systems contained in the universe often have a large order. Thus, the mathematical model has many state variables that affect the computation time. In addition, generally not all variables are known, so estimations are needed to measure the magnitude of the system that cannot be measured directly. In this paper, we discuss the model reduction and estimation of state variables in the river system to measure the water level. The model reduction of a system is an approximation method of a system with a lower order without significant errors but has a dynamic behaviour that is similar to the original system. The Singular Perturbation Approximation method is one of the model reduction methods where all state variables of the equilibrium system are partitioned into fast and slow modes. Then, The Kalman filter algorithm is used to estimate state variables of stochastic dynamic systems where estimations are computed by predicting state variables based on system dynamics and measurement data. Kalman filters are used to estimate state variables in the original system and reduced system. Then, we compare the estimation results of the state and computational time between the original and reduced system.

A Spalart-Allmaras local correlation-based transition model for Thermo-fuid dynamics

NASA Astrophysics Data System (ADS)

D'Alessandro, V.; Garbuglia, F.; Montelpare, S.; Zoppi, A.

2017-11-01

The study of innovative energy systems often involves complex fluid flows problems and the Computational Fluid-Dynamics (CFD) is one of the main tools of analysis. It is important to put in evidence that in several energy systems the flow field experiences the laminar-to-turbulent transition. Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) are able to predict the flow transition but they are still inapplicable to the study of real problems due to the significant computational resources requirements. Differently standard Reynolds Averaged Navier Stokes (RANS) approaches are not always reliable since they assume a fully turbulent regime. In order to overcome this drawback in the recent years some locally formulated transition RANS models have been developed. In this work, we present a local correlation-based transition approach adding two equations that control the laminar-toturbulent transition process -γ and \\[\\overset{}{\\mathop{{{\\operatorname{Re}}θ, \\text{t}}}} \\] - to the well-known Spalart-Allmaras (SA) turbulence model. The new model was implemented within OpenFOAM code. The energy equation is also implemented in order to evaluate the model performance in thermal-fluid dynamics applications. In all the considered cases a very good agreement between numerical and experimental data was observed.

Simulation and optimization of pressure swing adsorption systmes using reduced-order modeling

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

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

2009-01-01

Over the past three decades, pressure swing adsorption (PSA) processes have been widely used as energyefficient gas separation techniques, especially for high purity hydrogen purification from refinery gases. Models for PSA processes are 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 fronts moving with time. As a result, the optimization of such systems represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approachmore » to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. This study develops a reducedorder model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization and making the optimization problem computationally efficient. The method has been applied to the dynamic coupled PDE-based model of a twobed 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 reduced-order model has been successfully used to maximize hydrogen recovery by manipulating operating pressures, step times and feed and regeneration velocities, while meeting product purity and tight bounds on these parameters. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes.« less

Short-Range Order and Collective Dynamics of DMPC Bilayers: A Comparison between Molecular Dynamics Simulations, X-Ray, and Neutron Scattering Experiments

PubMed Central

Hub, Jochen S.; Salditt, Tim; Rheinstädter, Maikel C.; de Groot, Bert L.

2007-01-01

We present an extensive comparison of short-range order and short wavelength dynamics of a hydrated phospholipid bilayer derived by molecular dynamics simulations, elastic x-ray, and inelastic neutron scattering experiments. The quantities that are compared between simulation and experiment include static and dynamic structure factors, reciprocal space mappings, and electron density profiles. We show that the simultaneous use of molecular dynamics and diffraction data can help to extract real space properties like the area per lipid and the lipid chain ordering from experimental data. In addition, we assert that the interchain distance can be computed to high accuracy from the interchain correlation peak of the structure factor. Moreover, it is found that the position of the interchain correlation peak is not affected by the area per lipid, while its correlation length decreases linearly with the area per lipid. This finding allows us to relate a property of the structure factor quantitatively to the area per lipid. Finally, the short wavelength dynamics obtained from the simulations and from inelastic neutron scattering are analyzed and compared. The conventional interpretation in terms of the three-effective-eigenmode model is found to be only partly suitable to describe the complex fluid dynamics of lipid chains. PMID:17631531

Probing α -RuCl3 Beyond Magnetic Order: Effects of Temperature and Magnetic Field

NASA Astrophysics Data System (ADS)

Winter, Stephen M.; Riedl, Kira; Kaib, David; Coldea, Radu; Valentí, Roser

2018-02-01

Recent studies have brought α -RuCl3 to the forefront of experimental searches for materials realizing Kitaev spin-liquid physics. This material exhibits strongly anisotropic exchange interactions afforded by the spin-orbit coupling of the 4 d Ru centers. We investigate the dynamical response at finite temperature and magnetic field for a realistic model of the magnetic interactions in α -RuCl3 . These regimes are thought to host unconventional paramagnetic states that emerge from the suppression of magnetic order. Using exact diagonalization calculations of the quantum model complemented by semiclassical analysis, we find a very rich evolution of the spin dynamics as the applied field suppresses the zigzag order and stabilizes a quantum paramagnetic state that is adiabatically connected to the fully polarized state at high fields. At finite temperature, we observe large redistributions of spectral weight that can be attributed to the anisotropic frustration of the model. These results are compared to recent experiments and provide a road map for further studies of these regimes.

An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems

NASA Astrophysics Data System (ADS)

Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.

2016-04-01

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).

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.

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.

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

NASA Astrophysics Data System (ADS)

Ockenden, Mary C.; Tych, Wlodek; Beven, Keith J.; Collins, Adrian L.; Evans, Robert; Falloon, Peter D.; Forber, Kirsty J.; Hiscock, Kevin M.; Hollaway, Michael J.; Kahana, Ron; Macleod, Christopher J. A.; Villamizar, Martha L.; Wearing, Catherine; Withers, Paul J. A.; Zhou, Jian G.; Benskin, Clare McW. H.; Burke, Sean; Cooper, Richard J.; Freer, Jim E.; Haygarth, Philip M.

2017-12-01

Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with non-linear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10-50 km2). The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

Technology Integration (Task 20) Aeroservoelastic Modeling and Design Studies. Part A; Evaluation of Aeroservoelastic Effects on Flutter and Dynamic Gust Response

NASA Technical Reports Server (NTRS)

Nagaraja, K. S.; Kraft, R. H.

1999-01-01

The HSCT Flight Controls Group has developed longitudinal control laws, utilizing PTC aeroelastic flexible models to minimize aeroservoelastic interaction effects, for a number of flight conditions. The control law design process resulted in a higher order controller and utilized a large number of sensors distributed along the body for minimizing the flexibility effects. Processes were developed to implement these higher order control laws for performing the dynamic gust loads and flutter analyses. The processes and its validation were documented in Reference 2, for selected flight condition. The analytical results for additional flight conditions are presented in this document for further validation.

Langevin Equation for DNA Dynamics

NASA Astrophysics Data System (ADS)

Grych, David; Copperman, Jeremy; Guenza, Marina

Under physiological conditions, DNA oligomers can contain well-ordered helical regions and also flexible single-stranded regions. We describe the site-specific motion of DNA with a modified Rouse-Zimm Langevin equation formalism that describes DNA as a coarse-grained polymeric chain with global structure and local flexibility. The approach has successfully described the protein dynamics in solution and has been extended to nucleic acids. Our approach provides diffusive mode analytical solutions for the dynamics of global rotational diffusion and internal motion. The internal DNA dynamics present a rich energy landscape that accounts for an interior where hydrogen bonds and base-stacking determine structure and experience limited solvent exposure. We have implemented several models incorporating different coarse-grained sites with anisotropic rotation, energy barrier crossing, and local friction coefficients that include a unique internal viscosity and our models reproduce dynamics predicted by atomistic simulations. The models reproduce bond autocorrelation along the sequence as compared to that directly calculated from atomistic molecular dynamics simulations. The Langevin equation approach captures the essence of DNA dynamics without a cumbersome atomistic representation.

A methodology for the efficient integration of transient constraints in the design of aircraft dynamic systems

NASA Astrophysics Data System (ADS)

Phan, Leon L.

The motivation behind this thesis mainly stems from previous work performed at Hispano-Suiza (Safran Group) in the context of the European research project "Power Optimised Aircraft". Extensive testing on the COPPER Bird RTM, a test rig designed to characterize aircraft electrical networks, demonstrated the relevance of transient regimes in the design and development of dynamic systems. Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. For example, the switching on of a high electrical load might cause a network voltage drop inducing a loss of power available to critical aircraft systems. These transient behaviors are thus often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated, building on a nonlinear system identification technique using wavelet neural networks (or wavenets), which allow the multiscale nature of transient signals to be captured. However, training multivariate wavenets can become computationally prohibitive as the number of design variables increases. Therefore, an alternate approach is formulated, in which dynamic surrogate models using sigmoid-based neural networks are used to emulate the transient behavior of the envelopes of the time-domain response. Thus, in order to train the neural network, the envelopes are extracted by first separating the scales of the dynamic response, using a multiresolution analysis (MRA) based on the discrete wavelet transform. The MRA separates the dynamic response into a trend and a noise signal (ripple). The envelope of the noise is then computed with a windowing method, and recombined with the trend in order to reconstruct the global envelope of the dynamic response. The run-time efficiency of the resulting dynamic surrogate models enable the implementation of a data farming approach, in which a Monte-Carlo simulation generates time-domain behaviors of transient responses for a vast set of design and operation scenarios spanning the design and operation space. An interactive visualization environment, enabling what-if analyses, will be developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, are tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.

Structure of the first- and second-neighbor shells of simulated water: Quantitative relation to translational and orientational order

NASA Astrophysics Data System (ADS)

Yan, Zhenyu; Buldyrev, Sergey V.; Kumar, Pradeep; Giovambattista, Nicolas; Debenedetti, Pablo G.; Stanley, H. Eugene

2007-11-01

We perform molecular dynamics simulations of water using the five-site transferable interaction potential (TIP5P) model to quantify structural order in both the first shell (defined by four nearest neighbors) and second shell (defined by twelve next-nearest neighbors) of a central water molecule. We find that the anomalous decrease of orientational order upon compression occurs in both shells, but the anomalous decrease of translational order upon compression occurs mainly in the second shell. The decreases of translational order and orientational order upon compression (called the “structural anomaly”) are thus correlated only in the second shell. Our findings quantitatively confirm the qualitative idea that the thermodynamic, structural, and hence dynamic anomalies of water are related to changes upon compression in the second shell.

Classical Dynamics of Fullerenes

NASA Astrophysics Data System (ADS)

Sławianowski, Jan J.; Kotowski, Romuald K.

2017-06-01

The classical mechanics of large molecules and fullerenes is studied. The approach is based on the model of collective motion of these objects. The mixed Lagrangian (material) and Eulerian (space) description of motion is used. In particular, the Green and Cauchy deformation tensors are geometrically defined. The important issue is the group-theoretical approach to describing the affine deformations of the body. The Hamiltonian description of motion based on the Poisson brackets methodology is used. The Lagrange and Hamilton approaches allow us to formulate the mechanics in the canonical form. The method of discretization in analytical continuum theory and in classical dynamics of large molecules and fullerenes enable us to formulate their dynamics in terms of the polynomial expansions of configurations. Another approach is based on the theory of analytical functions and on their approximations by finite-order polynomials. We concentrate on the extremely simplified model of affine deformations or on their higher-order polynomial perturbations.

A Coupled Approach for Structural Damage Detection with Incomplete Measurements

NASA Technical Reports Server (NTRS)

James, George; Cao, Timothy; Kaouk, Mo; Zimmerman, David

2013-01-01

This historical work couples model order reduction, damage detection, dynamic residual/mode shape expansion, and damage extent estimation to overcome the incomplete measurements problem by using an appropriate undamaged structural model. A contribution of this work is the development of a process to estimate the full dynamic residuals using the columns of a spring connectivity matrix obtained by disassembling the structural stiffness matrix. Another contribution is the extension of an eigenvector filtering procedure to produce full-order mode shapes that more closely match the measured active partition of the mode shapes using a set of modified Ritz vectors. The full dynamic residuals and full mode shapes are used as inputs to the minimum rank perturbation theory to provide an estimate of damage location and extent. The issues associated with this process are also discussed as drivers of near-term development activities to understand and improve this approach.

Combined analysis of field and model data: A case study of the phosphate dynamics in the German Bight in summer 1994

NASA Astrophysics Data System (ADS)

Pohlmann, Th.; Raabe, Th.; Doerffer, R.; Beddig, S.; Brockmann, U.; Dick, S.; Engel, M.; Hesse, K.-J.; König, P.; Mayer, B.; Moll, A.; Murphy, D.; Puls, W.; Rick, H.-J.; Schmidt-Nia, R.; Schönfeld, W.; Sündermann, J.

1999-09-01

The intention of this paper is to analyse a specific phenomenon observed during the KUSTOS campaigns in order to demonstrate the general capability of the KUSTOS and TRANSWATT approach, i.e. the combination of field and modelling activities in an interdisciplinary framework. The selected phenomenon is the increase in phosphate concentrations off the peninsula of Eiderstedt on the North Frisian coast sampled during four subsequent station grids of the KUSTOS summer campaign in 1994. First of all, a characterisation of the observed summer situation is given. The phosphate increase is described in detail in relation to the dynamics of other nutrients. In a second step, a first-order estimate of the dispersion of phosphate is discussed. The estimate is based on the box model approach and will focus on the effects of the river Elbe and Wadden Sea inputs on phosphate dynamics. Thirdly, a fully three-dimensional model system is presented, which was implemented in order to analyse the phosphate development. The model system is discussed briefly, with emphasis on phosphorus-related processes. The reliability of one of the model components, i.e. the hydrodynamical model, is demonstrated by means of a comparison of model results with observed current data. Thereafter, results of the German Bight seston model are employed to interpret the observed phosphate increase. From this combined analysis, it was possible to conclude that the phosphate increase during the first three surveys was due to internal transformation processes within the phosphorus cycle. On the other hand, the higher phosphate concentrations measured in the last station grid survey were caused by a horizontal transport of phosphate being remobilised in the Wadden Sea.

Effect of motor dynamics on nonlinear feedback robot arm control

NASA Technical Reports Server (NTRS)

Tarn, Tzyh-Jong; Li, Zuofeng; Bejczy, Antal K.; Yun, Xiaoping

1991-01-01

A nonlinear feedback robot controller that incorporates the robot manipulator dynamics and the robot joint motor dynamics is proposed. The manipulator dynamics and the motor dynamics are coupled to obtain a third-order-dynamic model, and differential geometric control theory is applied to produce a linearized and decoupled robot controller. The derived robot controller operates in the robot task space, thus eliminating the need for decomposition of motion commands into robot joint space commands. Computer simulations are performed to verify the feasibility of the proposed robot controller. The controller is further experimentally evaluated on the PUMA 560 robot arm. The experiments show that the proposed controller produces good trajectory tracking performances and is robust in the presence of model inaccuracies. Compared with a nonlinear feedback robot controller based on the manipulator dynamics only, the proposed robot controller yields conspicuously improved performance.

Intermittency and dynamical Lee-Yang zeros of open quantum systems.

PubMed

Hickey, James M; Flindt, Christian; Garrahan, Juan P

2014-12-01

We use high-order cumulants to investigate the Lee-Yang zeros of generating functions of dynamical observables in open quantum systems. At long times the generating functions take on a large-deviation form with singularities of the associated cumulant generating functions-or dynamical free energies-signifying phase transitions in the ensemble of dynamical trajectories. We consider a driven three-level system as well as the dissipative Ising model. Both systems exhibit dynamical intermittency in the statistics of quantum jumps. From the short-time behavior of the dynamical Lee-Yang zeros, we identify critical values of the counting field which we attribute to the observed intermittency and dynamical phase coexistence. Furthermore, for the dissipative Ising model we construct a trajectory phase diagram and estimate the value of the transverse field where the stationary state changes from being ferromagnetic (inactive) to paramagnetic (active).

Epidemic outbreaks and its control using a fractional order model with seasonality and stochastic infection

NASA Astrophysics Data System (ADS)

He, Shaobo; Banerjee, Santo

2018-07-01

A fractional-order SIR epidemic model is proposed under the influence of both parametric seasonality and the external noise. The integer order SIR epidemic model originally is stable. By introducing seasonality and noise force to the model, behaviors of the system is changed. It is shown that the system has rich dynamical behaviors with different system parameters, fractional derivative order and the degree of seasonality and noise. Complexity of the stochastic model is investigated by using multi-scale fuzzy entropy. Finally, hard limiter controlled system is designed and simulation results show the ratio of infected individuals can converge to a small enough target ρ, which means the epidemic outbreak can be under control by the implementation of some effective medical and health measures.

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.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

The new car following model considering vehicle dynamics influence and numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Dihua; Liu, Hui; Zhang, Geng; Zhao, Min

2015-12-01

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

Model and controller reduction of large-scale structures based on projection methods

NASA Astrophysics Data System (ADS)

Gildin, Eduardo

The design of low-order controllers for high-order plants is a challenging problem theoretically as well as from a computational point of view. Frequently, robust controller design techniques result in high-order controllers. It is then interesting to achieve reduced-order models and controllers while maintaining robustness properties. Controller designed for large structures based on models obtained by finite element techniques yield large state-space dimensions. In this case, problems related to storage, accuracy and computational speed may arise. Thus, model reduction methods capable of addressing controller reduction problems are of primary importance to allow the practical applicability of advanced controller design methods for high-order systems. A challenging large-scale control problem that has emerged recently is the protection of civil structures, such as high-rise buildings and long-span bridges, from dynamic loadings such as earthquakes, high wind, heavy traffic, and deliberate attacks. Even though significant effort has been spent in the application of control theory to the design of civil structures in order increase their safety and reliability, several challenging issues are open problems for real-time implementation. This dissertation addresses with the development of methodologies for controller reduction for real-time implementation in seismic protection of civil structures using projection methods. Three classes of schemes are analyzed for model and controller reduction: nodal truncation, singular value decomposition methods and Krylov-based methods. A family of benchmark problems for structural control are used as a framework for a comparative study of model and controller reduction techniques. It is shown that classical model and controller reduction techniques, such as balanced truncation, modal truncation and moment matching by Krylov techniques, yield reduced-order controllers that do not guarantee stability of the closed-loop system, that is, the reduced-order controller implemented with the full-order plant. A controller reduction approach is proposed such that to guarantee closed-loop stability. It is based on the concept of dissipativity (or positivity) of linear dynamical systems. Utilizing passivity preserving model reduction together with dissipative-LQG controllers, effective low-order optimal controllers are obtained. Results are shown through 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.

Replication of Cancellation Orders Using First-Passage Time Theory in Foreign Currency Market

NASA Astrophysics Data System (ADS)

Boilard, Jean-François; Kanazawa, Kiyoshi; Takayasu, Hideki; Takayasu, Misako

Our research focuses on the annihilation dynamics of limit orders in a spot foreign currency market for various currency pairs. We analyze the cancellation order distribution conditioned on the normalized distance from the mid-price; where the normalized distance is defined as the final distance divided by the initial distance. To reproduce real data, we introduce two simple models that assume the market price moves randomly and cancellation occurs either after fixed time t or following the Poisson process. Results of our model qualitatively reproduce basic statistical properties of cancellation orders of the data when limit orders are cancelled according to the Poisson process. We briefly discuss implication of our findings in the construction of more detailed microscopic models.

Data Driven Model Development for the SuperSonic SemiSpan Transport (S(sup 4)T)

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2011-01-01

In this report, we will investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models, and a data-driven system identification procedure. It is shown via analysis of experimental SuperSonic SemiSpan Transport (S4T) wind-tunnel data that by using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.

Dawn Orbit Determination Team: Trajectory Modeling and Reconstruction Processes at Vesta

NASA Technical Reports Server (NTRS)

Abrahamson, Matthew J.; Ardito, Alessandro; Han, Dongsuk; Haw, Robert; Kennedy, Brian; Mastrodemos, Nick; Nandi, Sumita; Park, Ryan; Rush, Brian; Vaughan, Andrew

2013-01-01

The Dawn spacecraft spent over a year in orbit around Vesta from July 2011 through August 2012. In order to maintain the designated science reference orbits and enable the transfers between those orbits, precise and timely orbit determination was required. Challenges included low-thrust ion propulsion modeling, estimation of relatively unknown Vesta gravity and rotation models, track-ing data limitations, incorporation of real-time telemetry into dynamics model updates, and rapid maneuver design cycles during transfers. This paper discusses the dynamics models, filter configuration, and data processing implemented to deliver a rapid orbit determination capability to the Dawn project.

Overeducation Dynamics and Personality

ERIC Educational Resources Information Center

Blazquez, Maite; Budria, Santiago

2012-01-01

In this paper, we use the 2000-2008 waves of the German Socioeconomic Panel to examine overeducation transitions. The results are based on a first-order Markov model that allows us to account for both the initial conditions problem and potential endogeneity in attrition. We found that overeducation dynamics, especially the probability of entering…

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.

Multiple Quantum Coherences (MQ) NMR and Entanglement Dynamics in the Mixed-Three-Spin XXX Heisenberg Model with Single-Ion Anisotropy

NASA Astrophysics Data System (ADS)

Hamid, Arian Zad

2016-12-01

We analytically investigate Multiple Quantum (MQ) NMR dynamics in a mixed-three-spin (1/2,1,1/2) system with XXX Heisenberg model at the front of an external homogeneous magnetic field B. A single-ion anisotropy property ζ is considered for the spin-1. The intensities dependence of MQ NMR coherences on their orders (zeroth and second orders) for two pairs of spins (1,1/2) and (1/2,1/2) of the favorite tripartite system are obtained. It is also investigated dynamics of the pairwise quantum entanglement for the bipartite (sub)systems (1,1/2) and (1/2,1/2) permanently coupled by, respectively, coupling constants J}1 and J}2, by means of concurrence and fidelity. Then, some straightforward comparisons are done between these quantities and the intensities of MQ NMR coherences and ultimately some interesting results are reported. We also show that the time evolution of MQ coherences based on the reduced density matrix of the pair spins (1,1/2) is closely connected with the dynamics of the pairwise entanglement. Finally, we prove that one can introduce MQ coherence of the zeroth order corresponds to the pair spins (1,1/2) as an entanglement witness at some special time intervals.

The Borexino Thermal Monitoring & Management System and simulations of the fluid-dynamics of the Borexino detector under asymmetrical, changing boundary conditions

NASA Astrophysics Data System (ADS)

Bravo-Berguño, D.; Mereu, R.; Cavalcante, P.; Carlini, M.; Ianni, A.; Goretti, A.; Gabriele, F.; Wright, T.; Yokley, Z.; Vogelaar, R. B.; Calaprice, F.; Inzoli, F.

2018-03-01

A comprehensive monitoring system for the thermal environment inside the Borexino neutrino detector was developed and installed in order to reduce uncertainties in determining temperatures throughout the detector. A complementary thermal management system limits undesirable thermal couplings between the environment and Borexino's active sections. This strategy is bringing improved radioactive background conditions to the region of interest for the physics signal thanks to reduced fluid mixing induced in the liquid scintillator. Although fluid-dynamical equilibrium has not yet been fully reached, and thermal fine-tuning is possible, the system has proven extremely effective at stabilizing the detector's thermal conditions while offering precise insights into its mechanisms of internal thermal transport. Furthermore, a Computational Fluid-Dynamics analysis has been performed, based on the empirical measurements provided by the thermal monitoring system, and providing information into present and future thermal trends. A two-dimensional modeling approach was implemented in order to achieve a proper understanding of the thermal and fluid-dynamics in Borexino. It was optimized for different regions and periods of interest, focusing on the most critical effects that were identified as influencing background concentrations. Literature experimental case studies were reproduced to benchmark the method and settings, and a Borexino-specific benchmark was implemented in order to validate the modeling approach for thermal transport. Finally, fully-convective models were applied to understand general and specific fluid motions impacting the detector's Active Volume.

A High Precision Prediction Model Using Hybrid Grey Dynamic Model

ERIC Educational Resources Information Center

Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro

2008-01-01

In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…

Reduced-order model based active disturbance rejection control of hydraulic servo system with singular value perturbation theory.

PubMed

Wang, Chengwen; Quan, Long; Zhang, Shijie; Meng, Hongjun; Lan, Yuan

2017-03-01

Hydraulic servomechanism is the typical mechanical/hydraulic double-dynamics coupling system with the high stiffness control and mismatched uncertainties input problems, which hinder direct applications of many advanced control approaches in the hydraulic servo fields. In this paper, by introducing the singular value perturbation theory, the original double-dynamics coupling model of the hydraulic servomechanism was reduced to a integral chain system. So that, the popular ADRC (active disturbance rejection control) technology could be directly applied to the reduced system. In addition, the high stiffness control and mismatched uncertainties input problems are avoided. The validity of the simplified model is analyzed and proven theoretically. The standard linear ADRC algorithm is then developed based on the obtained reduced-order model. Extensive comparative co-simulations and experiments are carried out to illustrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A Reduced Order Model for Whole-Chip Thermal Analysis of Microfluidic Lab-on-a-Chip Systems

PubMed Central

Wang, Yi; Song, Hongjun; Pant, Kapil

2013-01-01

This paper presents a Krylov subspace projection-based Reduced Order Model (ROM) for whole microfluidic chip thermal analysis, including conjugate heat transfer. Two key steps in the reduced order modeling procedure are described in detail, including (1) the acquisition of a 3D full-scale computational model in the state-space form to capture the dynamic thermal behavior of the entire microfluidic chip; and (2) the model order reduction using the Block Arnoldi algorithm to markedly lower the dimension of the full-scale model. Case studies using practically relevant thermal microfluidic chip are undertaken to establish the capability and to evaluate the computational performance of the reduced order modeling technique. The ROM is compared against the full-scale model and exhibits good agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) and over three orders-of-magnitude acceleration in computational speed. The salient model reusability and real-time simulation capability renders it amenable for operational optimization and in-line thermal control and management of microfluidic systems and devices. PMID:24443647

A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience.

PubMed

Corradi, Luca; Porro, Ivan; Schenone, Andrea; Momeni, Parastoo; Ferrari, Raffaele; Nobili, Flavio; Ferrara, Michela; Arnulfo, Gabriele; Fato, Marco M

2012-10-08

Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of "meta" data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach. Finally, data integration aspects have been addressed by providing the repository application with an efficient dynamic interface designed to enable the user to both easily query the data depending on defined datatypes and view all the data of every patient in an integrated and simple way. The results of our work have been twofold. First, a dynamically extensible data model has been implemented and tested based on a "meta" data-model enabling users to define their own data types independently from the application context. This data model has allowed users to dynamically include additional data types without the need of rebuilding the underlying database. Then a complex process-event data structure has been built, based on this data model, describing patient-centered diagnostic processes and merging information from data and metadata. Second, a repository implementing such a data structure has been deployed on a distributed Data Grid in order to provide scalability both in terms of data input and data storage and to exploit distributed data and computational approaches in order to share resources more efficiently. Moreover, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications. Based on such repository, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications.

A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience

PubMed Central

2012-01-01

Background Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. Methods A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of “meta” data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach. Finally, data integration aspects have been addressed by providing the repository application with an efficient dynamic interface designed to enable the user to both easily query the data depending on defined datatypes and view all the data of every patient in an integrated and simple way. Results The results of our work have been twofold. First, a dynamically extensible data model has been implemented and tested based on a “meta” data-model enabling users to define their own data types independently from the application context. This data model has allowed users to dynamically include additional data types without the need of rebuilding the underlying database. Then a complex process-event data structure has been built, based on this data model, describing patient-centered diagnostic processes and merging information from data and metadata. Second, a repository implementing such a data structure has been deployed on a distributed Data Grid in order to provide scalability both in terms of data input and data storage and to exploit distributed data and computational approaches in order to share resources more efficiently. Moreover, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications. Conclusions Based on such repository, data managing has been made possible through a friendly web interface. The driving principle of not being forced to preconfigured data types has been satisfied. It is up to users to dynamically configure the data model for the given experiment or data acquisition program, thus making it potentially suitable for customized applications. PMID:23043673

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

Transient carrier dynamics in a Mott insulator with antiferromagnetic order

NASA Astrophysics Data System (ADS)

Iyoda, Eiki; Ishihara, Sumio

2014-03-01

We study transient dynamics of hole carriers injected into a Mott insulator with antiferromagnetic long-range order. This "dynamical hole doping" contrasts with chemical hole doping. The theoretical framework for the transient carrier dynamics is presented based on the two-dimensional t-J model. The time dependencies of the optical conductivity spectra, as well as the one-particle excitation spectra, are calculated based on the Keldysh Green's function formalism at zero temperature combined with the self-consistent Born approximation. In the early stage after dynamical hole doping, the Drude component appears, and then incoherent components originating from hole-magnon scattering start to grow. Fast oscillatory behavior owing to coherent magnon and slow relaxation dynamics are confirmed in the spectra. The time profiles are interpreted as doped bare holes being dressed by magnon clouds and relaxed into spin polaron quasiparticle states. The characteristic relaxation times for Drude and incoherent peaks strongly depend on the momentum of the dynamically doped hole and the exchange constant. Implications for recent pump-probe experiments are discussed.

A generative spike train model with time-structured higher order correlations.

PubMed

Trousdale, James; Hu, Yu; Shea-Brown, Eric; Josić, Krešimir

2013-01-01

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.

Numerical prediction of pollutant dispersion and transport in an atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Zeoli, Stéphanie; Bricteux, Laurent; Mech. Eng. Dpt. Team

2014-11-01

The ability to accurately predict concentration levels of air pollutant released from point sources is required in order to determine their environmental impact. A wall modeled large-eddy simulation (WMLES) of the ABL is performed using the OpenFoam based solver SOWFA (Churchfield and Lee, NREL). It uses Boussinesq approximation for buoyancy effects and takes into account Coriolis forces. A synthetic eddy method is proposed to properly model turbulence inlet velocity boundary conditions. This method will be compared with the standard pressure gradient forcing. WMLES are usually performed using a standard Smagorinsky model or its dynamic version. It is proposed here to investigate a subgrid scale (SGS) model with a better spectral behavior. To this end, a regularized variational multiscale (RVMs) model (Jeanmart and Winckelmans, 2007) is implemented together with standard wall function in order to preserve the dynamics of the large scales within the Ekman layer. The influence of the improved SGS model on the wind simulation and scalar transport will be discussed based on turbulence diagnostics.

Spreading out Muscle Mass within a Hill-Type Model: A Computer Simulation Study

PubMed Central

Günther, Michael; Röhrle, Oliver; Haeufle, Daniel F. B.; Schmitt, Syn

2012-01-01

It is state of the art that muscle contraction dynamics is adequately described by a hyperbolic relation between muscle force and contraction velocity (Hill relation), thereby neglecting muscle internal mass inertia (first-order dynamics). Accordingly, the vast majority of modelling approaches also neglect muscle internal inertia. Assuming that such first-order contraction dynamics yet interacts with muscle internal mass distribution, this study investigates two questions: (i) what is the time scale on which the muscle responds to a force step? (ii) How does this response scale with muscle design parameters? Thereto, we simulated accelerated contractions of alternating sequences of Hill-type contractile elements and point masses. We found that in a typical small muscle the force levels off after about 0.2 ms, contraction velocity after about 0.5 ms. In an upscaled version representing bigger mammals' muscles, the force levels off after about 20 ms, and the theoretically expected maximum contraction velocity is not reached. We conclude (i) that it may be indispensable to introduce second-order contributions into muscle models to understand high-frequency muscle responses, particularly in bigger muscles. Additionally, (ii) constructing more elaborate measuring devices seems to be worthwhile to distinguish viscoelastic and inertia properties in rapid contractile responses of muscles. PMID:23227110

Molecular dynamics simulations of stratum corneum lipid models: fatty acids and cholesterol.

PubMed

Höltje, M; Förster, T; Brandt, B; Engels, T; von Rybinski, W; Höltje, H D

2001-03-09

We report the results of an investigation on stratum corneum lipids, which present the main barrier of the skin. Molecular dynamics simulations, thermal analysis and FTIR measurements were applied. The primary objective of this work was to study the effect of cholesterol on skin structure and dynamics. Two molecular models were constructed, a free fatty acid bilayer (stearic acid, palmitic acid) and a fatty acid/cholesterol mixture at a 1:1 molar ratio. Our simulations were performed at constant pressure and temperature on a nanosecond time scale. The resulting model structures were characterized by calculating surface areas per headgroup, conformational properties, atom densities and order parameters of the fatty acids. Analysis of the simulations indicates that the free fatty acid fraction of stratum corneum lipids stays in a highly ordered crystalline state at skin temperatures. The phase behavior is strongly influenced when cholesterol is added. Cholesterol smoothes the rigid phases of the fatty acids: the order of the hydrocarbon tails (mainly of the last eight bonds) is reduced, the area per molecule becomes larger, the fraction of trans dihedrals is lower and the hydrophobic thickness is reduced. The simulation results are in good agreement with our experimental data from FTIR analysis and NIR-FT Raman spectroscopy.

Finite-Size Scaling of a First-Order Dynamical Phase Transition: Adaptive Population Dynamics and an Effective Model

NASA Astrophysics Data System (ADS)

Nemoto, Takahiro; Jack, Robert L.; Lecomte, Vivien

2017-03-01

We analyze large deviations of the time-averaged activity in the one-dimensional Fredrickson-Andersen model, both numerically and analytically. The model exhibits a dynamical phase transition, which appears as a singularity in the large deviation function. We analyze the finite-size scaling of this phase transition numerically, by generalizing an existing cloning algorithm to include a multicanonical feedback control: this significantly improves the computational efficiency. Motivated by these numerical results, we formulate an effective theory for the model in the vicinity of the phase transition, which accounts quantitatively for the observed behavior. We discuss potential applications of the numerical method and the effective theory in a range of more general contexts.

Effects of Gas Rarefaction on Dynamic Characteristics of Micro Spiral-Grooved Thrust Bearing.

PubMed

Liu, Ren; Wang, Xiao-Li; Zhang, Xiao-Qing

2012-04-01

The effects of gas-rarefaction on dynamic characteristics of micro spiral-grooved-thrust-bearing are studied. The Reynolds equation is modified by the first order slip model, and the corresponding perturbation equations are then obtained on the basis of the linear small perturbation method. In the converted spiral-curve-coordinates system, the finite-volume-method (FVM) is employed to discrete the surface domain of micro bearing. The results show, compared with the continuum-flow model, that under the slip-flow regime, the decrease in the pressure and stiffness become obvious with the increasing of the compressibility number. Moreover, with the decrease of the relative gas-film-thickness, the deviations of dynamic coefficients between slip-flow-model and continuum-flow-model are increasing.

Dynamics and forecast in a simple model of sustainable development for rural populations.

PubMed

Angulo, David; Angulo, Fabiola; Olivar, Gerard

2015-02-01

Society is becoming more conscious on the need to preserve the environment. Sustainable development schemes have grown rapidly as a tool for managing, predicting and improving the growth path in different regions and economy sectors. We introduce a novel and simple mathematical model of ordinary differential equations (ODEs) in order to obtain a dynamical description for each one of the sustainability components (economy, social development and environment conservation), together with their dependence with demographic dynamics. The main part in the modeling task is inspired by the works by Cobb, Douglas, Brander and Taylor. This is completed through some new insights by the authors. A model application is presented for three specific geographical rural regions in Caldas (Colombia).

Development of an improved MATLAB GUI for the prediction of coefficients of restitution, and integration into LMS.

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

Baca, Renee Nicole; Congdon, Michael L.; Brake, Matthew Robert

In 2012, a Matlab GUI for the prediction of the coefficient of restitution was developed in order to enable the formulation of more accurate Finite Element Analysis (FEA) models of components. This report details the development of a new Rebound Dynamics GUI, and how it differs from the previously developed program. The new GUI includes several new features, such as source and citation documentation for the material database, as well as a multiple materials impact modeler for use with LMS Virtual.Lab Motion (LMS VLM), and a rigid body dynamics modeling software. The Rebound Dynamics GUI has been designed to workmore » with LMS VLM to enable straightforward incorporation of velocity-dependent coefficients of restitution in rigid body dynamics simulations.« less

Time-varying nonlinear dynamics of a deploying piezoelectric laminated composite plate under aerodynamic force

NASA Astrophysics Data System (ADS)

Lu, S. F.; Zhang, W.; Song, X. J.

2017-09-01

Using Reddy's high-order shear theory for laminated plates and Hamilton's principle, a nonlinear partial differential equation for the dynamics of a deploying cantilevered piezoelectric laminated composite plate, under the combined action of aerodynamic load and piezoelectric excitation, is introduced. Two-degree of freedom (DOF) nonlinear dynamic models for the time-varying coefficients describing the transverse vibration of the deploying laminate under the combined actions of a first-order aerodynamic force and piezoelectric excitation were obtained by selecting a suitable time-dependent modal function satisfying the displacement boundary conditions and applying second-order discretization using the Galerkin method. Using a numerical method, the time history curves of the deploying laminate were obtained, and its nonlinear dynamic characteristics, including extension speed and different piezoelectric excitations, were studied. The results suggest that the piezoelectric excitation has a clear effect on the change of the nonlinear dynamic characteristics of such piezoelectric laminated composite plates. The nonlinear vibration of the deploying cantilevered laminate can be effectively suppressed by choosing a suitable voltage and polarity.

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

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.

Experimental Validation of a Coupled Fluid-Multibody Dynamics Model for Tanker Trucks

DTIC Science & Technology

2007-11-08

order to accurately predict the dynamic response of tanker trucks, the model must accurately account for the following effects : • Incompressible...computational code which uses a time- accurate explicit solution procedure is used to solve both the solid and fluid equations of motion. Many commercial...position vector, τ is the deviatoric stress tensor, D is the rate of deformation tensor, f r is the body force vector, r is the artificial

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.

Direct and indirect effects of birth order on personality and identity: support for the null hypothesis.

PubMed

Dunkel, Curtis S; Harbke, Colin R; Papini, Dennis R

2009-06-01

The authors proposed that birth order affects psychosocial outcomes through differential investment from parent to child and differences in the degree of identification from child to parent. The authors conducted this study to test these 2 models. Despite the use of statistical and methodological procedures to increase sensitivity and reduce error, the authors did not find support for the models. They discuss results in the context of the mixed-research findings regarding birth order and suggest further research on the proposed developmental dynamics that may produce birth-order effects.

Evaluation of Geometrically Nonlinear Reduced Order Models with Nonlinear Normal Modes

DOE PAGES

Kuether, Robert J.; Deaner, Brandon J.; Hollkamp, Joseph J.; ...

2015-09-15

Several reduced-order modeling strategies have been developed to create low-order models of geometrically nonlinear structures from detailed finite element models, allowing one to compute the dynamic response of the structure at a dramatically reduced cost. But, the parameters of these reduced-order models are estimated by applying a series of static loads to the finite element model, and the quality of the reduced-order model can be highly sensitive to the amplitudes of the static load cases used and to the type/number of modes used in the basis. Our paper proposes to combine reduced-order modeling and numerical continuation to estimate the nonlinearmore » normal modes of geometrically nonlinear finite element models. Not only does this make it possible to compute the nonlinear normal modes far more quickly than existing approaches, but the nonlinear normal modes are also shown to be an excellent metric by which the quality of the reduced-order model can be assessed. Hence, the second contribution of this work is to demonstrate how nonlinear normal modes can be used as a metric by which nonlinear reduced-order models can be compared. Moreover, various reduced-order models with hardening nonlinearities are compared for two different structures to demonstrate these concepts: a clamped–clamped beam model, and a more complicated finite element model of an exhaust panel cover.« less

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.

Chaos Suppression in Fractional order Permanent Magnet Synchronous Generator in Wind Turbine Systems

NASA Astrophysics Data System (ADS)

Rajagopal, Karthikeyan; Karthikeyan, Anitha; Duraisamy, Prakash

2017-06-01

In this paper we investigate the control of three-dimensional non-autonomous fractional-order uncertain model of a permanent magnet synchronous generator (PMSG) via a adaptive control technique. We derive a dimensionless fractional order model of the PMSM from the integer order presented in the literatures. Various dynamic properties of the fractional order model like eigen values, Lyapunov exponents, bifurcation and bicoherence are investigated. The system chaotic behavior for various orders of fractional calculus are presented. An adaptive controller is derived to suppress the chaotic oscillations of the fractional order model. As the direct Lyapunov stability analysis of the robust controller is difficult for a fractional order first derivative, we have derived a new lemma to analyze the stability of the system. Numerical simulations of the proposed chaos suppression methodology are given to prove the analytical results derived through which we show that for the derived adaptive controller and the parameter update law, the origin of the system for any bounded initial conditions is asymptotically stable.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

C. botulinum inactivation kinetics implemented in a computational model of a high-pressure sterilization process.

PubMed

Juliano, Pablo; Knoerzer, Kai; Fryer, Peter J; Versteeg, Cornelis

2009-01-01

High-pressure, high-temperature (HPHT) processing is effective for microbial spore inactivation using mild preheating, followed by rapid volumetric compression heating and cooling on pressure release, enabling much shorter processing times than conventional thermal processing for many food products. A computational thermal fluid dynamic (CTFD) model has been developed to model all processing steps, including the vertical pressure vessel, an internal polymeric carrier, and food packages in an axis-symmetric geometry. Heat transfer and fluid dynamic equations were coupled to four selected kinetic models for the inactivation of C. botulinum; the traditional first-order kinetic model, the Weibull model, an nth-order model, and a combined discrete log-linear nth-order model. The models were solved to compare the resulting microbial inactivation distributions. The initial temperature of the system was set to 90 degrees C and pressure was selected at 600 MPa, holding for 220 s, with a target temperature of 121 degrees C. A representation of the extent of microbial inactivation throughout all processing steps was obtained for each microbial model. Comparison of the models showed that the conventional thermal processing kinetics (not accounting for pressure) required shorter holding times to achieve a 12D reduction of C. botulinum spores than the other models. The temperature distribution inside the vessel resulted in a more uniform inactivation distribution when using a Weibull or an nth-order kinetics model than when using log-linear kinetics. The CTFD platform could illustrate the inactivation extent and uniformity provided by the microbial models. The platform is expected to be useful to evaluate models fitted into new C. botulinum inactivation data at varying conditions of pressure and temperature, as an aid for regulatory filing of the technology as well as in process and equipment design.

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

Bubbly vertex dynamics: A dynamical and geometrical model for epithelial tissues with curved cell shapes

NASA Astrophysics Data System (ADS)

Ishimoto, Yukitaka; Morishita, Yoshihiro

2014-11-01

In order to describe two-dimensionally packed cells in epithelial tissues both mathematically and physically, there have been developed several sorts of geometrical models, such as the vertex model, the finite element model, the cell-centered model, and the cellular Potts model. So far, in any case, pressures have not neatly been dealt with and the curvatures of the cell boundaries have been even omitted through their approximations. We focus on these quantities and formulate them in the vertex model. Thus, a model with the curvatures is constructed, and its algorithm for simulation is provided. The possible extensions and applications of this model are also discussed.

Understanding viral video dynamics through an epidemic modelling approach

NASA Astrophysics Data System (ADS)

Sachak-Patwa, Rahil; Fadai, Nabil T.; Van Gorder, Robert A.

2018-07-01

Motivated by the hypothesis that the spread of viral videos is analogous to the spread of a disease epidemic, we formulate a novel susceptible-exposed-infected-recovered-susceptible (SEIRS) delay differential equation epidemic model to describe the popularity evolution of viral videos. Our models incorporate time-delay, in order to accurately describe the virtual contact process between individuals and the temporary immunity of individuals to videos after they have grown tired of watching them. We validate our models by fitting model parameters to viewing data from YouTube music videos, in order to demonstrate that the model solutions accurately reproduce real behaviour seen in this data. We use an SEIR model to describe the initial growth and decline of daily views, and an SEIRS model to describe the long term behaviour of the popularity of music videos. We also analyse the decay rates in the daily views of videos, determining whether they follow a power law or exponential distribution. Although we focus on viral videos, the modelling approach may be used to understand dynamics emergent from other areas of science which aim to describe consumer behaviour.

Development of a simulation model for dynamic derailment analysis of high-speed trains

NASA Astrophysics Data System (ADS)

Ling, Liang; Xiao, Xin-Biao; Jin, Xue-Song

2014-12-01

The running safety of high-speed trains has become a major concern of the current railway research with the rapid development of high-speed railways around the world. The basic safety requirement is to prevent the derailment. The root causes of the dynamic derailment of high-speed trains operating in severe environments are not easy to identify using the field tests or laboratory experiments. Numerical simulation using an advanced train-track interaction model is a highly efficient and low-cost approach to investigate the dynamic derailment behavior and mechanism of high-speed trains. This paper presents a three-dimensional dynamic model of a high-speed train coupled with a ballast track for dynamic derailment analysis. The model considers a train composed of multiple vehicles and the nonlinear inter-vehicle connections. The ballast track model consists of rails, fastenings, sleepers, ballasts, and roadbed, which are modeled by Euler beams, nonlinear spring-damper elements, equivalent ballast bodies, and continuous viscoelastic elements, in which the modal superposition method was used to reduce the order of the partial differential equations of Euler beams. The commonly used derailment safety assessment criteria around the world are embedded in the simulation model. The train-track model was then used to investigate the dynamic derailment responses of a high-speed train passing over a buckled track, in which the derailment mechanism and train running posture during the dynamic derailment process were analyzed in detail. The effects of train and track modelling on dynamic derailment analysis were also discussed. The numerical results indicate that the train and track modelling options have a significant effect on the dynamic derailment analysis. The inter-vehicle impacts and the track flexibility and nonlinearity should be considered in the dynamic derailment simulations.

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.

A novel method for predicting the power outputs of wave energy converters

NASA Astrophysics Data System (ADS)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

NASA Astrophysics Data System (ADS)

Kim, Byung Soo; Lee, Woon-Seek; Koh, Shiegheun

2012-07-01

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

A consensus-based dynamics for market volumes

NASA Astrophysics Data System (ADS)

Sabatelli, Lorenzo; Richmond, Peter

2004-12-01

We develop a model of trading orders based on opinion dynamics. The agents may be thought as the share holders of a major mutual fund rather than as direct traders. The balance between their buy and sell orders determines the size of the fund order (volume) and has an impact on prices and indexes. We assume agents interact simultaneously to each other through a Sznajd-like interaction. Their degree of connection is determined by the probability of changing opinion independently of what their neighbours are doing. We assume that such a probability may change randomly, after each transaction, of an amount proportional to the relative difference between the volatility then measured and a benchmark that we assume to be an exponential moving average of the past volume values. We show how this simple model is compatible with some of the main statistical features observed for the asset volumes in financial markets.

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.

A Method for Generating Reduced Order Linear Models of Supersonic Inlets

NASA Technical Reports Server (NTRS)

Chicatelli, Amy; Hartley, Tom T.

1997-01-01

For the modeling of high speed propulsion systems, there are at least two major categories of models. One is based on computational fluid dynamics (CFD), and the other is based on design and analysis of control systems. CFD is accurate and gives a complete view of the internal flow field, but it typically has many states and runs much slower dm real-time. Models based on control design typically run near real-time but do not always capture the fundamental dynamics. To provide improved control models, methods are needed that are based on CFD techniques but yield models that are small enough for control analysis and design.

Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

Modelling stock order flows with non-homogeneous intensities from high-frequency data

NASA Astrophysics Data System (ADS)

Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.

2013-10-01

A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).

Modeling and Simulation of Metallurgical Process Based on Hybrid Petri Net

NASA Astrophysics Data System (ADS)

Ren, Yujuan; Bao, Hong

2016-11-01

In order to achieve the goals of energy saving and emission reduction of iron and steel enterprises, an increasing number of modeling and simulation technologies are used to research and analyse metallurgical production process. In this paper, the basic principle of Hybrid Petri net is used to model and analyse the Metallurgical Process. Firstly, the definition of Hybrid Petri Net System of Metallurgical Process (MPHPNS) and its modeling theory are proposed. Secondly, the model of MPHPNS based on material flow is constructed. The dynamic flow of materials and the real-time change of each technological state in metallurgical process are simulated vividly by using this model. The simulation process can implement interaction between the continuous event dynamic system and the discrete event dynamic system at the same level, and play a positive role in the production decision.

Design of an Adaptive Power Regulation Mechanism and a Nozzle for a Hydroelectric Power Plant Turbine Test Rig

NASA Astrophysics Data System (ADS)

Mert, Burak; Aytac, Zeynep; Tascioglu, Yigit; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

2014-11-01

This study deals with the design of a power regulation mechanism for a Hydroelectric Power Plant (HEPP) model turbine test system which is designed to test Francis type hydroturbines up to 2 MW power with varying head and flow(discharge) values. Unlike the tailor made regulation mechanisms of full-sized, functional HEPPs; the design for the test system must be easily adapted to various turbines that are to be tested. In order to achieve this adaptability, a dynamic simulation model is constructed in MATLAB/Simulink SimMechanics. This model acquires geometric data and hydraulic loading data of the regulation system from Autodesk Inventor CAD models and Computational Fluid Dynamics (CFD) analysis respectively. The dynamic model is explained and case studies of two different HEPPs are performed for validation. CFD aided design of the turbine guide vanes, which is used as input for the dynamic model, is also presented. This research is financially supported by Turkish Ministry of Development.

Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2017-09-01

In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.

The dynamic and steady state behavior of a PEM fuel cell as an electric energy source

NASA Astrophysics Data System (ADS)

Costa, R. A.; Camacho, J. R.

The main objective of this work is to extract information on the internal behavior of three small polymer electrolyte membrane fuel cells under static and dynamic load conditions. A computational model was developed using Scilab [SCILAB 4, Scilab-a free scientific software package, http://www.scilab.org/, INRIA, France, December, 2005] to simulate the static and dynamic performance [J.M. Correa, A.F. Farret, L.N. Canha, An analysis of the dynamic performance of proton exchange membrane fuel cells using an electrochemical model, in: 27th Annual Conference of IEEE Industrial Electronics Society, 2001, pp. 141-146] of this particular type of fuel cell. This dynamic model is based on electrochemical equations and takes into consideration most of the chemical and physical characteristics of the device in order to generate electric power. The model takes into consideration the operating, design parameters and physical material properties. The results show the internal losses and concentration effects behavior, which are of interest for power engineers and researchers.

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 .

Dynamic fuzzy modeling of storm water infiltration in urban fractured aquifers

USGS Publications Warehouse

Hong, Y.-S.; Rosen, Michael R.; Reeves, R.R.

2002-01-01

In an urban fractured-rock aquifer in the Mt. Eden area of Auckland, New Zealand, disposal of storm water is via "soakholes" drilled directly into the top of the fractured basalt rock. The dynamic response of the groundwater level due to the storm water infiltration shows characteristics of a strongly time-varying system. A dynamic fuzzy modeling approach, which is based on multiple local models that are weighted using fuzzy membership functions, has been developed to identify and predict groundwater level fluctuations caused by storm water infiltration. The dynamic fuzzy model is initialized by the fuzzy clustering algorithm and optimized by the gradient-descent algorithm in order to effectively derive the multiple local models-each of which is associated with a locally valid model that represents the groundwater level state as a response to different intensities of rainfall events. The results have shown that even if the number of fuzzy local models derived is small, the fuzzy modeling approach developed provides good prediction results despite the highly time-varying nature of this urban fractured-rock aquifer system. Further, it allows interpretable representations of the dynamic behavior of the groundwater system due to storm water infiltration.

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

Gas dynamics in strong centrifugal fields

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

Bogovalov, S.V.; Kislov, V.A.; Tronin, I.V.

2015-03-10

Dynamics of waves generated by scopes in gas centrifuges (GC) for isotope separation is considered. The centrifugal acceleration in the GC reaches values of the order of 106g. The centrifugal and Coriolis forces modify essentially the conventional sound waves. Three families of the waves with different polarisation and dispersion exist in these conditions. Dynamics of the flow in the model GC Iguasu is investigated numerically. Comparison of the results of the numerical modelling of the wave dynamics with the analytical predictions is performed. New phenomena of the resonances in the GC is found. The resonances occur for the waves polarizedmore » along the rotational axis having the smallest dumping due to the viscosity.« less

Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

PubMed

Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

2014-03-01

In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamic Testing of a Subscale Sunshield for the Next Generation Space Telescope (NGST)

NASA Technical Reports Server (NTRS)

Lienard, Sebastien; Johnston, John D.; Ross, Brian; Smith, James; Brodeur, Steve (Technical Monitor)

2001-01-01

The NGST sunshield is a lightweight, flexible structure consisting of multiple layers of pretensioned, thin-film membranes supported by deployable booms. The structural dynamic behavior of the sunshield must be well understood in order to predict its influence on observatory performance. Ground tests were carried out in a vacuum environment to characterize the structural dynamic behavior of a one-tenth scale model of the sunshield. Results from the tests will be used to validate analytical modeling techniques that can be used in conjunction with scaling laws to predict the performance of the full-sized structure. This paper summarizes the ground tests and presents representative results for the dynamic behavior of the sunshield.

Research a Novel Integrated and Dynamic Multi-object Trade-Off Mechanism in Software Project

NASA Astrophysics Data System (ADS)

Jiang, Weijin; Xu, Yuhui

Aiming at practical requirements of present software project management and control, the paper presented to construct integrated multi-object trade-off model based on software project process management, so as to actualize integrated and dynamic trade-oil of the multi-object system of project. Based on analyzing basic principle of dynamic controlling and integrated multi-object trade-off system process, the paper integrated method of cybernetics and network technology, through monitoring on some critical reference points according to the control objects, emphatically discussed the integrated and dynamic multi- object trade-off model and corresponding rules and mechanism in order to realize integration of process management and trade-off of multi-object system.

Dynamics of Sequential Decision Making

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin

2006-11-01

We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.

Application of finite-element methods to dynamic analysis of flexible spatial and co-planar linkage systems, part 2

NASA Technical Reports Server (NTRS)

Dubowsky, Steven

1989-01-01

An approach is described to modeling the flexibility effects in spatial mechanisms and manipulator systems. The method is based on finite element representations of the individual links in the system. However, it should be noted that conventional finite element methods and software packages will not handle the highly nonlinear dynamic behavior of these systems which results form their changing geometry. In order to design high-performance lightweight systems and their control systems, good models of their dynamic behavior which include the effects of flexibility are required.

Dynamics in a nonlinear Keynesian good market model

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

Naimzada, Ahmad, E-mail: ahmad.naimzada@unimib.it; Pireddu, Marina, E-mail: marina.pireddu@unimib.it

2014-03-15

In this paper, we show how a rich variety of dynamical behaviors can emerge in the standard Keynesian income-expenditure model when a nonlinearity is introduced, both in the cases with and without endogenous government spending. A specific sigmoidal functional form is used for the adjustment mechanism of income with respect to the excess demand, in order to bound the income variation. With the aid of analytical and numerical tools, we investigate the stability conditions, bifurcations, as well as periodic and chaotic dynamics. Globally, we study multistability phenomena, i.e., the coexistence of different kinds of attractors.

Modeling the system dynamics for nutrient removal in an innovative septic tank media filter.

PubMed

Xuan, Zhemin; Chang, Ni-Bin; Wanielista, Martin

2012-05-01

A next generation septic tank media filter to replace or enhance the current on-site wastewater treatment drainfields was proposed in this study. Unit operation with known treatment efficiencies, flow pattern identification, and system dynamics modeling was cohesively concatenated in order to prove the concept of a newly developed media filter. A multicompartmental model addressing system dynamics and feedbacks based on our assumed microbiological processes accounting for aerobic, anoxic, and anaerobic conditions in the media filter was constructed and calibrated with the aid of in situ measurements and the understanding of the flow patterns. Such a calibrated system dynamics model was then applied for a sensitivity analysis under changing inflow conditions based on the rates of nitrification and denitrification characterized through the field-scale testing. This advancement may contribute to design such a drainfield media filter in household septic tank systems in the future.

Study on dynamic performance of SOFC

NASA Astrophysics Data System (ADS)

Zhan, Haiyang; Liang, Qianchao; Wen, Qiang; Zhu, Runkai

2017-05-01

In order to solve the problem of real-time matching of load and fuel cell power, it is urgent to study the dynamic response process of SOFC in the case of load mutation. The mathematical model of SOFC is constructed, and its performance is simulated. The model consider the influence factors such as polarization effect, ohmic loss. It also takes the diffusion effect, thermal effect, energy exchange, mass conservation, momentum conservation. One dimensional dynamic mathematical model of SOFC is constructed by using distributed lumped parameter method. The simulation results show that the I-V characteristic curves are in good agreement with the experimental data, and the accuracy of the model is verified. The voltage response curve, power response curve and the efficiency curve are obtained by this way. It lays a solid foundation for the research of dynamic performance and optimal control in power generation system of high power fuel cell stack.

Improved Boron for Enhanced Combustion

DTIC Science & Technology

1990-06-01

elements scanned. - 11 - C. Particle Dynamics Ultrafine particles on the order of 0.01 to 0.1 micron diameter are known to exhibit dynamic behavior...very short relaxation times after perturbations [7]. Of the four major regimes of particle dynamic behavior, these ultrafine particles are classified in...modeling. Ultrafine particles up to approximately 0.1 micron in diameter tend to have unequilibrated surface energy [7,8,9,101. This is particularly

Nonlinear dynamics of global atmospheric and Earth-system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel

1990-01-01

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

Proceedings of the International Workshop on Dynamics and Aeroelastic Modeling of Rotorcraft (7th) held in St. Louis, Missouri on 14-16 October, 1997

DTIC Science & Technology

1997-10-14

Metrics + Modeling and Results + Conclusions ------------------- ------------------- Introduction Floquet Theory * Primary mathematical tool for...addition, a higher order plate theory is incorporated into the plate segment constitutive equations. The shear strain correction influences the torsion...behavior while the higher order plate theory influences the transverse shear behavior. The theory is validated against 3-D finite element results

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

Modal Substructuring of Geometrically Nonlinear Finite Element Models with Interface Reduction

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

Kuether, Robert J.; Allen, Matthew S.; Hollkamp, Joseph J.

Substructuring methods have been widely used in structural dynamics to divide large, complicated finite element models into smaller substructures. For linear systems, many methods have been developed to reduce the subcomponents down to a low order set of equations using a special set of component modes, and these are then assembled to approximate the dynamics of a large scale model. In this paper, a substructuring approach is developed for coupling geometrically nonlinear structures, where each subcomponent is drastically reduced to a low order set of nonlinear equations using a truncated set of fixedinterface and characteristic constraint modes. The method usedmore » to extract the coefficients of the nonlinear reduced order model (NLROM) is non-intrusive in that it does not require any modification to the commercial FEA code, but computes the NLROM from the results of several nonlinear static analyses. The NLROMs are then assembled to approximate the nonlinear differential equations of the global assembly. The method is demonstrated on the coupling of two geometrically nonlinear plates with simple supports at all edges. The plates are joined at a continuous interface through the rotational degrees-of-freedom (DOF), and the nonlinear normal modes (NNMs) of the assembled equations are computed to validate the models. The proposed substructuring approach reduces a 12,861 DOF nonlinear finite element model down to only 23 DOF, while still accurately reproducing the first three NNMs of the full order model.« less

Modal Substructuring of Geometrically Nonlinear Finite Element Models with Interface Reduction

DOE PAGES

Kuether, Robert J.; Allen, Matthew S.; Hollkamp, Joseph J.

2017-03-29

Substructuring methods have been widely used in structural dynamics to divide large, complicated finite element models into smaller substructures. For linear systems, many methods have been developed to reduce the subcomponents down to a low order set of equations using a special set of component modes, and these are then assembled to approximate the dynamics of a large scale model. In this paper, a substructuring approach is developed for coupling geometrically nonlinear structures, where each subcomponent is drastically reduced to a low order set of nonlinear equations using a truncated set of fixedinterface and characteristic constraint modes. The method usedmore » to extract the coefficients of the nonlinear reduced order model (NLROM) is non-intrusive in that it does not require any modification to the commercial FEA code, but computes the NLROM from the results of several nonlinear static analyses. The NLROMs are then assembled to approximate the nonlinear differential equations of the global assembly. The method is demonstrated on the coupling of two geometrically nonlinear plates with simple supports at all edges. The plates are joined at a continuous interface through the rotational degrees-of-freedom (DOF), and the nonlinear normal modes (NNMs) of the assembled equations are computed to validate the models. The proposed substructuring approach reduces a 12,861 DOF nonlinear finite element model down to only 23 DOF, while still accurately reproducing the first three NNMs of the full order model.« less

Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization.

PubMed

Samaan, Michael A; Weinhandl, Joshua T; Bawab, Sebastian Y; Ringleb, Stacie I

2016-12-01

Musculoskeletal modeling allows for the determination of various parameters during dynamic maneuvers by using in vivo kinematic and ground reaction force (GRF) data as inputs. Differences between experimental and model marker data and inconsistencies in the GRFs applied to these musculoskeletal models may not produce accurate simulations. Therefore, residual forces and moments are applied to these models in order to reduce these differences. Numerical optimization techniques can be used to determine optimal tracking weights of each degree of freedom of a musculoskeletal model in order to reduce differences between the experimental and model marker data as well as residual forces and moments. In this study, the particle swarm optimization (PSO) and simplex simulated annealing (SIMPSA) algorithms were used to determine optimal tracking weights for the simulation of a sidestep cut. The PSO and SIMPSA algorithms were able to produce model kinematics that were within 1.4° of experimental kinematics with residual forces and moments of less than 10 N and 18 Nm, respectively. The PSO algorithm was able to replicate the experimental kinematic data more closely and produce more dynamically consistent kinematic data for a sidestep cut compared to the SIMPSA algorithm. Future studies should use external optimization routines to determine dynamically consistent kinematic data and report the differences between experimental and model data for these musculoskeletal simulations.

Dynamics and Control of Constrained Multibody Systems modeled with Maggi's equation: Application to Differential Mobile Robots Part I

NASA Astrophysics Data System (ADS)

Amengonu, Yawo H.; Kakad, Yogendra P.

2014-07-01

Quasivelocity techniques such as Maggi's and Boltzmann-Hamel's equations eliminate Lagrange multipliers from the beginning as opposed to the Euler-Lagrange method where one has to solve for the n configuration variables and the multipliers as functions of time when there are m nonholonomic constraints. Maggi's equation produces n second-order differential equations of which (n-m) are derived using (n-m) independent quasivelocities and the time derivative of the m kinematic constraints which add the remaining m second order differential equations. This technique is applied to derive the dynamics of a differential mobile robot and a controller which takes into account these dynamics is developed.

Adding dynamic rules to self-organizing fuzzy systems

NASA Technical Reports Server (NTRS)

Buhusi, Catalin V.

1992-01-01

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Stability enhancement of high Prandtl number chaotic convection in an anisotropic porous layer with feedback control

NASA Astrophysics Data System (ADS)

Mahmud, M. N.

2018-04-01

The chaotic dynamical behaviour of thermal convection in an anisotropic porous layer subject to gravity, heated from below and cooled from above, is studied based on theory of dynamical system in the presence of feedback control. The extended Darcy model, which includes the time derivative has been employed in the momentum equation to derive a low dimensional Lorenz-like equation by using Galerkin-truncated approximation. The classical fourth-order Runge-Kutta method is used to obtain the numerical solution in order to exemplify the dynamics of the nonlinear autonomous system. The results show that stability enhancement of chaotic convection is feasible via feedback control.

Climate effects and feedback structure determining weed population dynamics in a long-term experiment.

PubMed

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements.

Climate Effects and Feedback Structure Determining Weed Population Dynamics in a Long-Term Experiment

PubMed Central

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements. PMID:22272362

Rotational Brownian Dynamics simulations of clathrin cage formation

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

Ilie, Ioana M.; Briels, Wim J.; MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede

2014-08-14

The self-assembly of nearly rigid proteins into ordered aggregates is well suited for modeling by the patchy particle approach. Patchy particles are traditionally simulated using Monte Carlo methods, to study the phase diagram, while Brownian Dynamics simulations would reveal insights into the assembly dynamics. However, Brownian Dynamics of rotating anisotropic particles gives rise to a number of complications not encountered in translational Brownian Dynamics. We thoroughly test the Rotational Brownian Dynamics scheme proposed by Naess and Elsgaeter [Macromol. Theory Simul. 13, 419 (2004); Naess and Elsgaeter Macromol. Theory Simul. 14, 300 (2005)], confirming its validity. We then apply the algorithmmore » to simulate a patchy particle model of clathrin, a three-legged protein involved in vesicle production from lipid membranes during endocytosis. Using this algorithm we recover time scales for cage assembly comparable to those from experiments. We also briefly discuss the undulatory dynamics of the polyhedral cage.« less

Multiscale crystal defect dynamics: A coarse-grained lattice defect model based on crystal microstructure

NASA Astrophysics Data System (ADS)

Lyu, Dandan; Li, Shaofan

2017-10-01

Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.