Event heap: a coordination infrastructure for dynamic heterogeneous application interactions in ubiquitous computing environments

DOEpatents

Johanson, Bradley E.; Fox, Armando; Winograd, Terry A.; Hanrahan, Patrick M.

2010-04-20

An efficient and adaptive middleware infrastructure called the Event Heap system dynamically coordinates application interactions and communications in a ubiquitous computing environment, e.g., an interactive workspace, having heterogeneous software applications running on various machines and devices across different platforms. Applications exchange events via the Event Heap. Each event is characterized by a set of unordered, named fields. Events are routed by matching certain attributes in the fields. The source and target versions of each field are automatically set when an event is posted or used as a template. The Event Heap system implements a unique combination of features, both intrinsic to tuplespaces and specific to the Event Heap, including content based addressing, support for routing patterns, standard routing fields, limited data persistence, query persistence/registration, transparent communication, self-description, flexible typing, logical/physical centralization, portable client API, at most once per source first-in-first-out ordering, and modular restartability.

Analysis methods for wind turbine control and electrical system dynamics

NASA Technical Reports Server (NTRS)

Hinrichsen, E. N.

1995-01-01

The integration of new energy technologies into electric power systems requires methods which recognize the full range of dynamic events in both the new generating unit and the power system. Since new energy technologies are initially perceived as small contributors to large systems, little attention is generally paid to system integration, i.e. dynamic events in the power system are ignored. As a result, most new energy sources are only capable of base-load operation, i.e. they have no load following or cycling capability. Wind turbines are no exception. Greater awareness of this implicit (and often unnecessary) limitation is needed. Analysis methods are recommended which include very low penetration (infinite bus) as well as very high penetration (stand-alone) scenarios.

X-ray transmission movies of spontaneous dynamic events

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

Smilowitz, L.; Henson, B. F.; Holmes, M.

2014-11-15

We describe a new x-ray radiographic imaging system which allows for continuous x-ray transmission imaging of spontaneous dynamic events. We demonstrate this method on thermal explosions in three plastic bonded formulations of the energetic material octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine. We describe the x-ray imaging system and triggering developed to enable the continuous imaging of a thermal explosion.

Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-01-01

This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

Space Launch System Scale Model Acoustic Test Ignition Overpressure Testing

NASA Technical Reports Server (NTRS)

Nance, Donald K.; Liever, Peter A.

2015-01-01

The overpressure phenomenon is a transient fluid dynamic event occurring during rocket propulsion system ignition. This phenomenon results from fluid compression of the accelerating plume gas, subsequent rarefaction, and subsequent propagation from the exhaust trench and duct holes. The high-amplitude unsteady fluid-dynamic perturbations can adversely affect the vehicle and surrounding structure. Commonly known as ignition overpressure (IOP), this is an important design-to environment for the Space Launch System (SLS) that NASA is currently developing. Subscale testing is useful in validating and verifying the IOP environment. This was one of the objectives of the Scale Model Acoustic Test (SMAT), conducted at Marshall Space Flight Center (MSFC). The test data quantifies the effectiveness of the SLS IOP suppression system and improves the analytical models used to predict the SLS IOP environments. The reduction and analysis of the data gathered during the SMAT IOP test series requires identification and characterization of multiple dynamic events and scaling of the event waveforms to provide the most accurate comparisons to determine the effectiveness of the IOP suppression systems. The identification and characterization of the overpressure events, the waveform scaling, the computation of the IOP suppression system knockdown factors, and preliminary comparisons to the analytical models are discussed.

Space Launch System Scale Model Acoustic Test Ignition Overpressure Testing

NASA Technical Reports Server (NTRS)

Nance, Donald; Liever, Peter; Nielsen, Tanner

2015-01-01

The overpressure phenomenon is a transient fluid dynamic event occurring during rocket propulsion system ignition. This phenomenon results from fluid compression of the accelerating plume gas, subsequent rarefaction, and subsequent propagation from the exhaust trench and duct holes. The high-amplitude unsteady fluid-dynamic perturbations can adversely affect the vehicle and surrounding structure. Commonly known as ignition overpressure (IOP), this is an important design-to environment for the Space Launch System (SLS) that NASA is currently developing. Subscale testing is useful in validating and verifying the IOP environment. This was one of the objectives of the Scale Model Acoustic Test, conducted at Marshall Space Flight Center. The test data quantifies the effectiveness of the SLS IOP suppression system and improves the analytical models used to predict the SLS IOP environments. The reduction and analysis of the data gathered during the SMAT IOP test series requires identification and characterization of multiple dynamic events and scaling of the event waveforms to provide the most accurate comparisons to determine the effectiveness of the IOP suppression systems. The identification and characterization of the overpressure events, the waveform scaling, the computation of the IOP suppression system knockdown factors, and preliminary comparisons to the analytical models are discussed.

Analytically Solvable Model of Spreading Dynamics with Non-Poissonian Processes

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

2014-01-01

Non-Poissonian bursty processes are ubiquitous in natural and social phenomena, yet little is known about their effects on the large-scale spreading dynamics. In order to characterize these effects, we devise an analytically solvable model of susceptible-infected spreading dynamics in infinite systems for arbitrary inter-event time distributions and for the whole time range. Our model is stationary from the beginning, and the role of the lower bound of inter-event times is explicitly considered. The exact solution shows that for early and intermediate times, the burstiness accelerates the spreading as compared to a Poisson-like process with the same mean and same lower bound of inter-event times. Such behavior is opposite for late-time dynamics in finite systems, where the power-law distribution of inter-event times results in a slower and algebraic convergence to a fully infected state in contrast to the exponential decay of the Poisson-like process. We also provide an intuitive argument for the exponent characterizing algebraic convergence.

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

Hauer, John F.; Mittelstadt, William; Martin, Kenneth E.

During 2005 and 2006 the Western Electricity Coordinating Council (WECC) performed three major tests of western system dynamics. These tests used a Wide Area Measurement System (WAMS) based primarily on Phasor Measurement Units (PMUs) to determine response to events including the insertion of the 1400-MW Chief Joseph braking resistor, probing signals, and ambient events. Test security was reinforced through real-time analysis of wide area effects, and high-quality data provided dynamic profiles for interarea modes across the entire western interconnection. The tests established that low-level optimized pseudo-random ±20-MW probing with the Pacific DC Intertie (PDCI) roughly doubles the apparent noise thatmore » is natural to the power system, providing sharp dynamic information with negligible interference to system operations. Such probing is an effective alternative to use of the 1400-MW Chief Joseph dynamic brake, and it is under consideration as a standard means for assessing dynamic security.« less

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

PubMed

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

2014-04-01

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

Collapse of Experimental Colloidal Aging using Record Dynamics

NASA Astrophysics Data System (ADS)

Robe, Dominic; Boettcher, Stefan; Sibani, Paolo; Yunker, Peter

The theoretical framework of record dynamics (RD) posits that aging behavior in jammed systems is controlled by short, rare events involving activation of only a few degrees of freedom. RD predicts dynamics in an aging system to progress with the logarithm of t /tw . This prediction has been verified through new analysis of experimental data on an aging 2D colloidal system. MSD and persistence curves spanning three orders of magnitude in waiting time are collapsed. These predictions have also been found consistent with a number of experiments and simulations, but verification of the specific assumptions that RD makes about the underlying statistics of these rare events has been elusive. Here the observation of individual particles allows for the first time the direct verification of the assumptions about event rates and sizes. This work is suppoted by NSF Grant DMR-1207431.

Introduction to State Estimation of High-Rate System Dynamics.

PubMed

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Event Processing and Variable Part of Sample Period Determining in Combined Systems Using GA

NASA Astrophysics Data System (ADS)

Strémy, Maximilián; Závacký, Pavol; Jedlička, Martin

2011-01-01

This article deals with combined dynamic systems and usage of modern techniques in dealing with these systems, focusing particularly on sampling period design, cyclic processing tasks and related processing algorithms in the combined event management systems using genetic algorithms.

Drop dynamics

NASA Technical Reports Server (NTRS)

Elleman, D. D.

1981-01-01

The drop dynamics module is a Spacelab-compatible acoustic positioning and control system for conducting drop dynamics experiments in space. It consists basically of a chamber, a drop injector system, an acoustic positioning system, and a data collection system. The principal means of collecting data is by a cinegraphic camera. The drop is positioned in the center of the chamber by forces created by standing acoustic waves generated in the nearly cubical chamber (about 12 cm on a side). The drop can be spun or oscillated up to fission by varying the phse and amplitude of the acoustic waves. The system is designed to perform its experiments unattended, except for start-up and shutdown events and other unique events that require the attention of the Spacelab payload specialist.

An Empirical Study of Combining Communicating Processes in a Parallel Discrete Event Simulation

DTIC Science & Technology

1990-12-01

dynamics of the cost/performance criteria which typically made up computer resource acquisition decisions . offering a broad range of tradeoffs in the way... prcesses has a significant impact on simulation performance. It is the hypothesis of this 3-4 SYSTEM DECOMPOSITION PHYSICAL SYSTEM 1: N PHYSICAL PROCESS 1...EMPTY)) next-event = pop(next-event-queue); lp-clock = next-event - time; Simulate next event departure- consume event-enqueue new event end while; If no

Understanding wheel dynamics.

PubMed

Proffitt, D R; Kaiser, M K; Whelan, S M

1990-07-01

In five experiments, assessments were made of people's understandings about the dynamics of wheels. It was found that undergraduates make highly erroneous dynamical judgments about the motions of this commonplace event, both in explicit problem-solving contexts and when viewing ongoing events. These problems were also presented to bicycle racers and high-school physics teachers; both groups were found to exhibit misunderstandings similar to those of naive undergraduates. Findings were related to our account of dynamical event complexity. The essence of this account is that people encounter difficulties when evaluating the dynamics of any mechanical system that has more than one dynamically relevant object parameter. A rotating wheel is multidimensional in this respect: in addition to the motion of its center of mass, its mass distribution is also of dynamical relevance. People do not spontaneously form the essential multidimensional quantities required to adequately evaluate wheel dynamics.

Geostationary Coastal Ecosystem Dynamics Imager (GEO CEDI) for the GEO Coastal and Air Pollution Events (GEO CAPE) Mission. Concept Presentation

NASA Technical Reports Server (NTRS)

Janz, Scott; Smith, James C.; Mannino, Antonio

2010-01-01

This slide presentation reviews the concepts of the Geostationary Coastal Ecosystem Dynamics Imager (GEO CEDI) which will be used on the GEO Coastal and Air Pollution Events (GEO CAPE) Mission. The primary science requirements require scans of the U.S. Coastal waters 3 times per day during the daylight hours. Included in the overview are presentations about the systems, the optics, the detectors, the mechanical systems, the electromechanical systems, the electrical design, the flight software, the thermal systems, and the contamination prevention requirements.

76 FR 66057 - North American Electric Reliability Corporation; Order Approving Regional Reliability Standard

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

... system conditions when the system experiences dynamic events such as low frequency oscillations, or... R8 requires that dynamic disturbance recorders function continuously. To capture system disturbance... recording capability necessary to monitor the response of the Bulk-Power System to system disturbances...

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network.

PubMed

Zhao, Bo; Ding, Ruoxi; Chen, Shoushun; Linares-Barranco, Bernabe; Tang, Huajin

2015-09-01

This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.

Dynamic Event Tree advancements and control logic improvements

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

Alfonsi, Andrea; Rabiti, Cristian; Mandelli, Diego

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN is currently equipped with three different sampling categories: Forward samplers (Monte Carlo, Latin Hyper Cube, Stratified, Grid Sampler, Factorials, etc.), Adaptive Samplers (Limit Surface search, Adaptive Polynomial Chaos, etc.) and Dynamic Event Tree (DET) samplers (Deterministic and Adaptive Dynamic Event Trees). The main subject of this document is to report the activities that have been donemore » in order to: start the migration of the RAVEN/RELAP-7 control logic system into MOOSE, and develop advanced dynamic sampling capabilities based on the Dynamic Event Tree approach. In order to provide to all MOOSE-based applications a control logic capability, in this Fiscal Year an initial migration activity has been initiated, moving the control logic system, designed for RELAP-7 by the RAVEN team, into the MOOSE framework. In this document, a brief explanation of what has been done is going to be reported. The second and most important subject of this report is about the development of a Dynamic Event Tree (DET) sampler named “Hybrid Dynamic Event Tree” (HDET) and its Adaptive variant “Adaptive Hybrid Dynamic Event Tree” (AHDET). As other authors have already reported, among the different types of uncertainties, it is possible to discern two principle types: aleatory and epistemic uncertainties. The classical Dynamic Event Tree is in charge of treating the first class (aleatory) uncertainties; the dependence of the probabilistic risk assessment and analysis on the epistemic uncertainties are treated by an initial Monte Carlo sampling (MCDET). From each Monte Carlo sample, a DET analysis is run (in total, N trees). The Monte Carlo employs a pre-sampling of the input space characterized by epistemic uncertainties. The consequent Dynamic Event Tree performs the exploration of the aleatory space. In the RAVEN code, a more general approach has been developed, not limiting the exploration of the epistemic space through a Monte Carlo method but using all the forward sampling strategies RAVEN currently employs. The user can combine a Latin Hyper Cube, Grid, Stratified and Monte Carlo sampling in order to explore the epistemic space, without any limitation. From this pre-sampling, the Dynamic Event Tree sampler starts its aleatory space exploration. As reported by the authors, the Dynamic Event Tree is a good fit to develop a goal-oriented sampling strategy. The DET is used to drive a Limit Surface search. The methodology that has been developed by the authors last year, performs a Limit Surface search in the aleatory space only. This report documents how this approach has been extended in order to consider the epistemic space interacting with the Hybrid Dynamic Event Tree methodology.« less

Introduction to State Estimation of High-Rate System Dynamics

PubMed Central

Dodson, Jacob; Joyce, Bryan

2018-01-01

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events.

PubMed

Lacour, C; Joannis, C; Gromaire, M-C; Chebbo, G

2009-01-01

Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious hectare and both the mean and maximum hydraulic flow for each event, was also studied. Moreover, the dynamics of flow and turbidity signals were compared at the event scale. No simple relation between turbidity responses, hydraulic flow dynamics and the chosen parameters was derived from this effort. Knowledge of turbidity dynamics could therefore potentially improve wet weather management, especially when using pollution-based real-time control (P-RTC) since turbidity contains information not included in hydraulic flow dynamics and not readily predictable from such dynamics.

Reaction Event Counting Statistics of Biopolymer Reaction Systems with Dynamic Heterogeneity.

PubMed

Lim, Yu Rim; Park, Seong Jun; Park, Bo Jung; Cao, Jianshu; Silbey, Robert J; Sung, Jaeyoung

2012-04-10

We investigate the reaction event counting statistics (RECS) of an elementary biopolymer reaction in which the rate coefficient is dependent on states of the biopolymer and the surrounding environment and discover a universal kinetic phase transition in the RECS of the reaction system with dynamic heterogeneity. From an exact analysis for a general model of elementary biopolymer reactions, we find that the variance in the number of reaction events is dependent on the square of the mean number of the reaction events when the size of measurement time is small on the relaxation time scale of rate coefficient fluctuations, which does not conform to renewal statistics. On the other hand, when the size of the measurement time interval is much greater than the relaxation time of rate coefficient fluctuations, the variance becomes linearly proportional to the mean reaction number in accordance with renewal statistics. Gillespie's stochastic simulation method is generalized for the reaction system with a rate coefficient fluctuation. The simulation results confirm the correctness of the analytic results for the time dependent mean and variance of the reaction event number distribution. On the basis of the obtained results, we propose a method of quantitative analysis for the reaction event counting statistics of reaction systems with rate coefficient fluctuations, which enables one to extract information about the magnitude and the relaxation times of the fluctuating reaction rate coefficient, without a bias that can be introduced by assuming a particular kinetic model of conformational dynamics and the conformation dependent reactivity. An exact relationship is established between a higher moment of the reaction event number distribution and the multitime correlation of the reaction rate for the reaction system with a nonequilibrium initial state distribution as well as for the system with the equilibrium initial state distribution.

Dynamically triggered slip leading to sustained fault gouge weakening under laboratory shear conditions

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

Johnson, Paul Allan

We investigate dynamic wave-triggered slip under laboratory shear conditions. The experiment is composed of a three-block system containing two gouge layers composed of glass beads and held in place by a fixed load in a biaxial configuration. When the system is sheared under steady state conditions at a normal load of 4 MPa, we find that shear failure may be instantaneously triggered by a dynamic wave, corresponding to material weakening and softening if the system is in a critical shear stress state (near failure). Following triggering, the gouge material remains in a perturbed state over multiple slip cycles as evidencedmore » by the recovery of the material strength, shear modulus, and slip recurrence time. This work suggests that faults must be critically stressed to trigger under dynamic conditions and that the recovery process following a dynamically triggered event differs from the recovery following a spontaneous event.« less

Dynamically triggered slip leading to sustained fault gouge weakening under laboratory shear conditions

DOE PAGES

Johnson, Paul Allan

2016-02-28

We investigate dynamic wave-triggered slip under laboratory shear conditions. The experiment is composed of a three-block system containing two gouge layers composed of glass beads and held in place by a fixed load in a biaxial configuration. When the system is sheared under steady state conditions at a normal load of 4 MPa, we find that shear failure may be instantaneously triggered by a dynamic wave, corresponding to material weakening and softening if the system is in a critical shear stress state (near failure). Following triggering, the gouge material remains in a perturbed state over multiple slip cycles as evidencedmore » by the recovery of the material strength, shear modulus, and slip recurrence time. This work suggests that faults must be critically stressed to trigger under dynamic conditions and that the recovery process following a dynamically triggered event differs from the recovery following a spontaneous event.« less

Towards a unified study of extreme events using universality concepts and transdisciplinary analysis methods

NASA Astrophysics Data System (ADS)

Balasis, George; Donner, Reik V.; Donges, Jonathan F.; Radebach, Alexander; Eftaxias, Konstantinos; Kurths, Jürgen

2013-04-01

The dynamics of many complex systems is characterized by the same universal principles. In particular, systems which are otherwise quite different in nature show striking similarities in their behavior near tipping points (bifurcations, phase transitions, sudden regime shifts) and associated extreme events. Such critical phenomena are frequently found in diverse fields such as climate, seismology, or financial markets. Notably, the observed similarities include a high degree of organization, persistent behavior, and accelerated energy release, which are common to (among others) phenomena related to geomagnetic variability of the terrestrial magnetosphere (intense magnetic storms), seismic activity (electromagnetic emissions prior to earthquakes), solar-terrestrial physics (solar flares), neurophysiology (epileptic seizures), and socioeconomic systems (stock market crashes). It is an open question whether the spatial and temporal complexity associated with extreme events arises from the system's structural organization (geometry) or from the chaotic behavior inherent to the nonlinear equations governing the dynamics of these phenomena. On the one hand, the presence of scaling laws associated with earthquakes and geomagnetic disturbances suggests understanding these events as generalized phase transitions similar to nucleation and critical phenomena in thermal and magnetic systems. On the other hand, because of the structural organization of the systems (e.g., as complex networks) the associated spatial geometry and/or topology of interactions plays a fundamental role in the emergence of extreme events. Here, a few aspects of the interplay between geometry and dynamics (critical phase transitions) that could result in the emergence of extreme events, which is an open problem, will be discussed.

Event-driven management algorithm of an Engineering documents circulation system

NASA Astrophysics Data System (ADS)

Kuzenkov, V.; Zebzeev, A.; Gromakov, E.

2015-04-01

Development methodology of an engineering documents circulation system in the design company is reviewed. Discrete event-driven automatic models using description algorithms of project management is offered. Petri net use for dynamic design of projects is offered.

Synoptic thermodynamic and dynamic patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil)

NASA Astrophysics Data System (ADS)

da Silva, Fabricio Polifke; Justi da Silva, Maria Gertrudes Alvarez; Rotunno Filho, Otto Corrêa; Pires, Gisele Dornelles; Sampaio, Rafael João; de Araújo, Afonso Augusto Magalhães

2018-05-01

Natural disasters are the result of extreme or intense natural phenomena that cause severe impacts on society. These impacts can be mitigated through preventive measures that can be aided by better knowledge of extreme phenomena and monitoring of forecasting and alert systems. The city of Petropolis (in a mountainous region of the state of Rio de Janeiro, Brazil) is prone to heavy rain events, often leading to River overflows, landslides, and loss of life. In that context, this work endeavored to characterize the thermodynamic and dynamic synoptic patterns that trigger heavy rainfall episodes and the corresponding flooding of Quitandinha River. More specifically, we reviewed events from the time period between January 2013 and December 2014 using reanalysis data. We expect that the overall description obtained of synoptic patterns should provide adequate qualitative aid to the decision-making processes involved in operational forecasting procedures. We noticed that flooding events were related to the presence of the South Atlantic Convergence Zone (SACZ), frontal systems (FS), and convective storms (CS). These systems showed a similar behavior on high-frequency wind components, notably with respect to northwest winds before precipitation and to a strong southwest wind component during rainfall events. Clustering analyses indicated that the main component for precipitation formation with regard to CS systems comes from daytime heating, with the dynamic component presenting greater efficiency for the FS configurations. The SACZ events were influenced by moisture availability along the vertical column of the atmosphere and also due to dynamic components of precipitation efficiency and daytime heating, the latter related to the continuous transport of moisture from the Amazon region and South Atlantic Ocean towards Rio de Janeiro state.

Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

PubMed

Zhang, Qichao; Zhao, Dongbin; Wang, Ding

2018-01-01

In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

Fractional dynamics of globally slow transcription and its impact on deterministic genetic oscillation.

PubMed

Wei, Kun; Gao, Shilong; Zhong, Suchuan; Ma, Hong

2012-01-01

In dynamical systems theory, a system which can be described by differential equations is called a continuous dynamical system. In studies on genetic oscillation, most deterministic models at early stage are usually built on ordinary differential equations (ODE). Therefore, gene transcription which is a vital part in genetic oscillation is presupposed to be a continuous dynamical system by default. However, recent studies argued that discontinuous transcription might be more common than continuous transcription. In this paper, by appending the inserted silent interval lying between two neighboring transcriptional events to the end of the preceding event, we established that the running time for an intact transcriptional event increases and gene transcription thus shows slow dynamics. By globally replacing the original time increment for each state increment by a larger one, we introduced fractional differential equations (FDE) to describe such globally slow transcription. The impact of fractionization on genetic oscillation was then studied in two early stage models--the Goodwin oscillator and the Rössler oscillator. By constructing a "dual memory" oscillator--the fractional delay Goodwin oscillator, we suggested that four general requirements for generating genetic oscillation should be revised to be negative feedback, sufficient nonlinearity, sufficient memory and proper balancing of timescale. The numerical study of the fractional Rössler oscillator implied that the globally slow transcription tends to lower the chance of a coupled or more complex nonlinear genetic oscillatory system behaving chaotically.

An extension of the OpenModelica compiler for using Modelica models in a discrete event simulation

DOE PAGES

Nutaro, James

2014-11-03

In this article, a new back-end and run-time system is described for the OpenModelica compiler. This new back-end transforms a Modelica model into a module for the adevs discrete event simulation package, thereby extending adevs to encompass complex, hybrid dynamical systems. The new run-time system that has been built within the adevs simulation package supports models with state-events and time-events and that comprise differential-algebraic systems with high index. Finally, although the procedure for effecting this transformation is based on adevs and the Discrete Event System Specification, it can be adapted to any discrete event simulation package.

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

NASA Technical Reports Server (NTRS)

Mizell, Carolyn Barrett; Malone, Linda

2007-01-01

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Spatiotemporal stick-slip phenomena in a coupled continuum-granular system

NASA Astrophysics Data System (ADS)

Ecke, Robert

In sheared granular media, stick-slip behavior is ubiquitous, especially at very small shear rates and weak drive coupling. The resulting slips are characteristic of natural phenomena such as earthquakes and well as being a delicate probe of the collective dynamics of the granular system. In that spirit, we developed a laboratory experiment consisting of sheared elastic plates separated by a narrow gap filled with quasi-two-dimensional granular material (bi-dispersed nylon rods) . We directly determine the spatial and temporal distributions of strain displacements of the elastic continuum over 200 spatial points located adjacent to the gap. Slip events can be divided into large system-spanning events and spatially distributed smaller events. The small events have a probability distribution of event moment consistent with an M - 3 / 2 power law scaling and a Poisson distributed recurrence time distribution. Large events have a broad, log-normal moment distribution and a mean repetition time. As the applied normal force increases, there are fractionally more (less) large (small) events, and the large-event moment distribution broadens. The magnitude of the slip motion of the plates is well correlated with the root-mean-square displacements of the granular matter. Our results are consistent with mean field descriptions of statistical models of earthquakes and avalanches. We further explore the high-speed dynamics of system events and also discuss the effective granular friction of the sheared layer. We find that large events result from stored elastic energy in the plates in this coupled granular-continuum system.

Behavior dynamics: One perspective

PubMed Central

Marr, M. Jackson

1992-01-01

Behavior dynamics is a field devoted to analytic descriptions of behavior change. A principal source of both models and methods for these descriptions is found in physics. This approach is an extension of a long conceptual association between behavior analysis and physics. A theme common to both is the role of molar versus molecular events in description and prediction. Similarities and differences in how these events are treated are discussed. Two examples are presented that illustrate possible correspondence between mechanical and behavioral systems. The first demonstrates the use of a mechanical model to describe the molar properties of behavior under changing reinforcement conditions. The second, dealing with some features of concurrent schedules, focuses on the possible utility of nonlinear dynamical systems to the description of both molar and molecular behavioral events as the outcome of a deterministic, but chaotic, process. PMID:16812655

Hierarchy of temporal responses of multivariate self-excited epidemic processes

NASA Astrophysics Data System (ADS)

Saichev, Alexander; Maillart, Thomas; Sornette, Didier

2013-04-01

Many natural and social systems are characterized by bursty dynamics, for which past events trigger future activity. These systems can be modelled by so-called self-excited Hawkes conditional Poisson processes. It is generally assumed that all events have similar triggering abilities. However, some systems exhibit heterogeneity and clusters with possibly different intra- and inter-triggering, which can be accounted for by generalization into the "multivariate" self-excited Hawkes conditional Poisson processes. We develop the general formalism of the multivariate moment generating function for the cumulative number of first-generation and of all generation events triggered by a given mother event (the "shock") as a function of the current time t. This corresponds to studying the response function of the process. A variety of different systems have been analyzed. In particular, for systems in which triggering between events of different types proceeds through a one-dimension directed or symmetric chain of influence in type space, we report a novel hierarchy of intermediate asymptotic power law decays ˜ 1/ t 1-( m+1) θ of the rate of triggered events as a function of the distance m of the events to the initial shock in the type space, where 0 < θ < 1 for the relevant long-memory processes characterizing many natural and social systems. The richness of the generated time dynamics comes from the cascades of intermediate events of possibly different kinds, unfolding via random changes of types genealogy.

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

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

Jankovsky, Zachary Kyle; Denman, Matthew R.

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

Controlling extreme events on complex networks

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

2014-08-01

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

Rare event computation in deterministic chaotic systems using genealogical particle analysis

NASA Astrophysics Data System (ADS)

Wouters, J.; Bouchet, F.

2016-09-01

In this paper we address the use of rare event computation techniques to estimate small over-threshold probabilities of observables in deterministic dynamical systems. We demonstrate that genealogical particle analysis algorithms can be successfully applied to a toy model of atmospheric dynamics, the Lorenz ’96 model. We furthermore use the Ornstein-Uhlenbeck system to illustrate a number of implementation issues. We also show how a time-dependent objective function based on the fluctuation path to a high threshold can greatly improve the performance of the estimator compared to a fixed-in-time objective function.

Reproducing the scaling laws for Slow and Fast ruptures

NASA Astrophysics Data System (ADS)

Romanet, Pierre; Bhat, Harsha; Madariaga, Raúl

2017-04-01

Modelling long term behaviour of large, natural fault systems, that are geometrically complex, is a challenging problem. This is why most of the research so far has concentrated on modelling the long term response of single planar fault system. To overcome this limitation, we appeal to a novel algorithm called the Fast Multipole Method which was developed in the context of modelling gravitational N-body problems. This method allows us to decrease the computational complexity of the calculation from O(N2) to O(N log N), N being the number of discretised elements on the fault. We then adapted this method to model the long term quasi-dynamic response of two faults, with step-over like geometry, that are governed by rate and state friction laws. We assume the faults have spatially uniform rate weakening friction. The results show that when stress interaction between faults is accounted, a complex spectrum of slip (including slow-slip events, dynamic ruptures and partial ruptures) emerges naturally. The simulated slow-slip and dynamic events follow the scaling law inferred by Ide et al. 2007 i. e. M ∝ T for slow-slip events and M ∝ T2 (in 2D) for dynamic events.

HLH Drive System

DTIC Science & Technology

1977-09-01

Material Comparison ....... .. 359 D-16 Comparison Chart - Rotor Brake Designs, Boeing Vertol, HLH ........... 360 D-17 Conventional Steel Disk Dynamic ...engines off. 0 In the event of a rotor brake caliper or disc failure, the system shall preclude damage to critical dynamic components. * The rotor brake... Dynamic System Test Rig (DSTR) shown in Figure. .8 provided a means for integrating and testing the aft and conbiner trans- missions, the aft rotor , thr’ee

Phase-Space Detection of Cyber Events

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

Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J

Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The datamore » analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.« less

Dynamic decision modeling for inland waterway disruptions : August 1, 2014 - December 31, 2016 : final research report.

DOT National Transportation Integrated Search

2017-01-31

Inland waterway system is an essential part of the U.S. transportation system, which provides efficient and economic freight transportation through 12,000 miles of navigable waterway. An unexpected event (such as a natural event or unscheduled mainte...

A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

PubMed

Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

2018-02-01

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

Simulating Coronal Loop Implosion and Compressible Wave Modes in a Flare Hit Active Region

NASA Astrophysics Data System (ADS)

Sarkar, Aveek; Vaidya, Bhargav; Hazra, Soumitra; Bhattacharyya, Jishnu

2017-12-01

There is considerable observational evidence of implosion of magnetic loop systems inside solar coronal active regions following high-energy events like solar flares. In this work, we propose that such collapse can be modeled in three dimensions quite accurately within the framework of ideal magnetohydrodynamics. We furthermore argue that the dynamics of loop implosion is only sensitive to the transmitted disturbance of one or more of the system variables, e.g., velocity generated at the event site. This indicates that to understand loop implosion, it is sensible to leave the event site out of the simulated active region. Toward our goal, a velocity pulse is introduced to model the transmitted disturbance generated at the event site. Magnetic field lines inside our simulated active region are traced in real time, and it is demonstrated that the subsequent dynamics of the simulated loops closely resemble observed imploding loops. Our work highlights the role of plasma β in regards to the rigidity of the loop systems and how that might affect the imploding loops’ dynamics. Compressible magnetohydrodynamic modes such as kink and sausage are also shown to be generated during such processes, in accordance with observations.

Patient Litter System Response in a Full-Scale CH-46 Crash Test.

PubMed

Weisenbach, Charles A; Rooks, Tyler; Bowman, Troy; Fralish, Vince; McEntire, B Joseph

2017-03-01

U.S. Military aeromedical patient litter systems are currently required to meet minimal static strength performance requirements at the component level. Operationally, these components must function as a system and are subjected to the dynamics of turbulent flight and potentially crash events. The first of two full-scale CH-46 crash tests was conducted at NASA's Langley Research Center and included an experiment to assess patient and litter system response during a severe but survivable crash event. A three-tiered strap and pole litter system was mounted into the airframe and occupied by three anthropomorphic test devices (ATDs). During the crash event, the litter system failed to maintain structural integrity and collapsed. Component structural failures were recorded from the litter support system and the litters. The upper ATD was displaced laterally into the cabin, while the middle ATD was displaced longitudinally into the cabin. Acceleration, force, and bending moment data from the instrumented middle ATD were analyzed using available injury criteria. Results indicated that a patient might sustain a neck injury. The current test illustrates that a litter system, with components designed and tested to static requirements only, experiences multiple component structural failures during a dynamic crash event and does not maintain restraint control of its patients. It is unknown if a modern litter system, with components tested to the same static criteria, would perform differently. A systems level dynamic performance requirement needs to be developed so that patients can be provided with protection levels equivalent to that provided to seated aircraft occupants. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.

Autonomous Multi-sensor Coordination: The Science Goal Monitor

NASA Technical Reports Server (NTRS)

Koratkar, Anuradha; Jung, John; Geiger, Jenny; Grosvenor, Sandy

2004-01-01

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

NASA Technical Reports Server (NTRS)

Koratkar, Anuradha; Grosvenor, Sandy; Jung, John; Hess, Melissa; Jones, Jeremy

2004-01-01

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Application of importance sampling to the computation of large deviations in nonequilibrium processes.

PubMed

Kundu, Anupam; Sabhapandit, Sanjib; Dhar, Abhishek

2011-03-01

We present an algorithm for finding the probabilities of rare events in nonequilibrium processes. The algorithm consists of evolving the system with a modified dynamics for which the required event occurs more frequently. By keeping track of the relative weight of phase-space trajectories generated by the modified and the original dynamics one can obtain the required probabilities. The algorithm is tested on two model systems of steady-state particle and heat transport where we find a huge improvement from direct simulation methods.

Real-time monitoring of Lévy flights in a single quantum system

NASA Astrophysics Data System (ADS)

Issler, M.; Höller, J.; Imamoǧlu, A.

2016-02-01

Lévy flights are random walks where the dynamics is dominated by rare events. Even though they have been studied in vastly different physical systems, their observation in a single quantum system has remained elusive. Here we analyze a periodically driven open central spin system and demonstrate theoretically that the dynamics of the spin environment exhibits Lévy flights. For the particular realization in a single-electron charged quantum dot driven by periodic resonant laser pulses, we use Monte Carlo simulations to confirm that the long waiting times between successive nuclear spin-flip events are governed by a power-law distribution; the corresponding exponent η =-3 /2 can be directly measured in real time by observing the waiting time distribution of successive photon emission events. Remarkably, the dominant intrinsic limitation of the scheme arising from nuclear quadrupole coupling can be minimized by adjusting the magnetic field or by implementing spin echo.

LCP method for a planar passive dynamic walker based on an event-driven scheme

NASA Astrophysics Data System (ADS)

Zheng, Xu-Dong; Wang, Qi

2018-06-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

LCP method for a planar passive dynamic walker based on an event-driven scheme

NASA Astrophysics Data System (ADS)

Zheng, Xu-Dong; Wang, Qi

2018-02-01

The main purpose of this paper is to present a linear complementarity problem (LCP) method for a planar passive dynamic walker with round feet based on an event-driven scheme. The passive dynamic walker is treated as a planar multi-rigid-body system. The dynamic equations of the passive dynamic walker are obtained by using Lagrange's equations of the second kind. The normal forces and frictional forces acting on the feet of the passive walker are described based on a modified Hertz contact model and Coulomb's law of dry friction. The state transition problem of stick-slip between feet and floor is formulated as an LCP, which is solved with an event-driven scheme. Finally, to validate the methodology, four gaits of the walker are simulated: the stance leg neither slips nor bounces; the stance leg slips without bouncing; the stance leg bounces without slipping; the walker stands after walking several steps.

Facilitating preemptive hardware system design using partial reconfiguration techniques.

PubMed

Dondo Gazzano, Julio; Rincon, Fernando; Vaderrama, Carlos; Villanueva, Felix; Caba, Julian; Lopez, Juan Carlos

2014-01-01

In FPGA-based control system design, partial reconfiguration is especially well suited to implement preemptive systems. In real-time systems, the deadline for critical task can compel the preemption of noncritical one. Besides, an asynchronous event can demand immediate attention and, then, force launching a reconfiguration process for high-priority task implementation. If the asynchronous event is previously scheduled, an explicit activation of the reconfiguration process is performed. If the event cannot be previously programmed, such as in dynamically scheduled systems, an implicit activation to the reconfiguration process is demanded. This paper provides a hardware-based approach to explicit and implicit activation of the partial reconfiguration process in dynamically reconfigurable SoCs and includes all the necessary tasks to cope with this issue. Furthermore, the reconfiguration service introduced in this work allows remote invocation of the reconfiguration process and then the remote integration of off-chip components. A model that offers component location transparency is also presented to enhance and facilitate system integration.

Facilitating Preemptive Hardware System Design Using Partial Reconfiguration Techniques

PubMed Central

Rincon, Fernando; Vaderrama, Carlos; Villanueva, Felix; Caba, Julian; Lopez, Juan Carlos

2014-01-01

In FPGA-based control system design, partial reconfiguration is especially well suited to implement preemptive systems. In real-time systems, the deadline for critical task can compel the preemption of noncritical one. Besides, an asynchronous event can demand immediate attention and, then, force launching a reconfiguration process for high-priority task implementation. If the asynchronous event is previously scheduled, an explicit activation of the reconfiguration process is performed. If the event cannot be previously programmed, such as in dynamically scheduled systems, an implicit activation to the reconfiguration process is demanded. This paper provides a hardware-based approach to explicit and implicit activation of the partial reconfiguration process in dynamically reconfigurable SoCs and includes all the necessary tasks to cope with this issue. Furthermore, the reconfiguration service introduced in this work allows remote invocation of the reconfiguration process and then the remote integration of off-chip components. A model that offers component location transparency is also presented to enhance and facilitate system integration. PMID:24672292

A Risk Assessment System with Automatic Extraction of Event Types

NASA Astrophysics Data System (ADS)

Capet, Philippe; Delavallade, Thomas; Nakamura, Takuya; Sandor, Agnes; Tarsitano, Cedric; Voyatzi, Stavroula

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Magnetic storms and solar flares: can be analysed within similar mathematical framework with other extreme events?

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Potirakis, Stelios M.; Papadimitriou, Constantinos; Zitis, Pavlos I.; Eftaxias, Konstantinos

2015-04-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to different extreme events, in order to support the suggestion that a dynamical analogy characterizes the generation of a single magnetic storm, solar flare, earthquake (in terms of pre-seismic electromagnetic signals) , epileptic seizure, and economic crisis. The analysis reveals that all the above mentioned different extreme events can be analyzed within similar mathematical framework. More precisely, we show that the populations of magnitudes of fluctuations included in all the above mentioned pulse-like-type time series follow the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar nonextensive q-parameter values. Moreover, based on a multidisciplinary statistical analysis we show that the extreme events are characterized by crucial common symptoms, namely: (i) high organization, high compressibility, low complexity, high information content; (ii) strong persistency; and (iii) existence of clear preferred direction of emerged activities. These symptoms clearly discriminate the appearance of the extreme events under study from the corresponding background noise.

Adaptive Sampling using Support Vector Machines

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

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Ultrafast table-top dynamic radiography of spontaneous or stimulated events

DOEpatents

Smilowitz, Laura; Henson, Bryan

2018-01-16

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography. For example, certain embodiments concern X-ray radiography of spontaneous events. Particular embodiments of the disclosed technology provide continuous high-speed x-ray imaging of spontaneous dynamic events, such as explosions, reaction-front propagation, and even material failure. Further, in certain embodiments, x-ray activation and data collection activation are triggered by the object itself that is under observation (e.g., triggered by a change of state detected by one or more sensors monitoring the object itself).

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

Modelling machine ensembles with discrete event dynamical system theory

NASA Technical Reports Server (NTRS)

Hunter, Dan

1990-01-01

Discrete Event Dynamical System (DEDS) theory can be utilized as a control strategy for future complex machine ensembles that will be required for in-space construction. The control strategy involves orchestrating a set of interactive submachines to perform a set of tasks for a given set of constraints such as minimum time, minimum energy, or maximum machine utilization. Machine ensembles can be hierarchically modeled as a global model that combines the operations of the individual submachines. These submachines are represented in the global model as local models. Local models, from the perspective of DEDS theory , are described by the following: a set of system and transition states, an event alphabet that portrays actions that takes a submachine from one state to another, an initial system state, a partial function that maps the current state and event alphabet to the next state, and the time required for the event to occur. Each submachine in the machine ensemble is presented by a unique local model. The global model combines the local models such that the local models can operate in parallel under the additional logistic and physical constraints due to submachine interactions. The global model is constructed from the states, events, event functions, and timing requirements of the local models. Supervisory control can be implemented in the global model by various methods such as task scheduling (open-loop control) or implementing a feedback DEDS controller (closed-loop control).

Linking Crystal Populations to Dynamic States: Crystal Dissolution and Growth During an Open-System Event

NASA Astrophysics Data System (ADS)

Bergantz, G. W.; Schleicher, J.; Burgisser, A.

2016-12-01

The identification of shared characteristics in zoned crystals has motivated the definition of crystal populations. These populations reflect the simultaneous transport of crystals, heat and composition during open-system events. An obstacle to interpreting the emergence of a population is the absence of a way to correlate specific dynamic conditions with the characteristic attributes of a population. By combining a boundary-layer diffusion controlled model for crystal growth/dissolution with discrete-element magma dynamics simulations of crystal-bearing magmas, the creation of populations can be simulated. We have implemented a method that decomposes the chemical potential into the thermal and compositional contributions to crystal dissolution/growth. This allows for the explicit treatment of thermal inertia and thermal-compositional decoupling as fluid circulation stirs the system during an open-system event. We have identified three distinct dynamic states producing crystal populations. They are based on the volume fraction of crystals. In a mushy system, thermal and compositional states are tightly linked as the volume involved in the mixing is constrained by the so-called mixing bowl (Bergantz et al., 2015). The mixing bowl volume is a function of the visco-plastic response of the mush and the intrusion width, not by the progressive entrainment of the new intrusion as commonly assumed. Crystal dissolution is the dominate response to input of more primitive magma. At the other endmember, under very dilute conditions, thermal and compositional conditions can become decoupled, and the in-coming magma forms a double-diffusive low-Re jet. This can allow for both dissolution and growth as crystals circulate widely into an increasingly stratified system. A middle range of crystal concentration produces a very complex feedback, as sedimenting crystals form fingers and chains that interact with the incoming magma, break-up the entrainment with chaotic stirring and add a second length scale to the mixing. It simultaneously forms a small mixing bowl in the pile of crystals sedimenting at the base. This can produce very complex populations even in a simple open-system event. Bergantz et al., 2015, Open-system dynamics and mixing in magma mushes, Nature Geosci., DOI: 10.1038/NGEO2534

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.

A Discrete Events Delay Differential System Model for Transmission of Vancomycin-Resistant Enterococcus (VRE) in Hospitals

DTIC Science & Technology

2010-09-19

estimated directly form the surveillance data Infection control measures were implemented in the form of health care worker hand - hygiene before and after...hospital infections , is used to motivate possibilities of modeling nosocomial infec- tion dynamics. This is done in the context of hospital monitoring and...model development. Key Words: Delay equations, discrete events, nosocomial infection dynamics, surveil- lance data, inverse problems, parameter

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

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

Dodge, D. A.; Harris, D. B.

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE PAGES

Dodge, D. A.; Harris, D. B.

2016-03-15

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Sensorimotor event: an approach to the dynamic, embodied, and embedded nature of sensorimotor cognition

PubMed Central

Vilarroya, Oscar

2014-01-01

In this paper, I explore the notion of sensorimotor event as the building block of sensorimotor cognition. A sensorimotor event is presented here as a neurally controlled event that recruits those processes and elements that are necessary to address the demands of the situation in which the individual is involved. The notion of sensorimotor event is intended to subsume the dynamic, embodied, and embedded nature of sensorimotor cognition, in agreement with the satisficing and bricoleur approach to sensorimotor cognition presented elsewhere (Vilarroya, 2012). In particular, the notion of sensorimotor event encompasses those relevant neural processes, but also those bodily and environmental elements, that are necessary to deal with the situation in which the individual is involved. This continuum of neural processes as well as bodily and environmental elements can be characterized, and this characterization is considered the basis for the identification of the particular sensorimotor event. Among other consequences, the notion of sensorimotor event suggests a different approach to the classical account of sensory-input mapping onto a motor output. Instead of characterizing how a neural system responds to an external input, the idea defended here is to characterize how system-in-an-environment responds to its antecedent situation. PMID:24427133

Event coincidence analysis for quantifying statistical interrelationships between event time series. On the role of flood events as triggers of epidemic outbreaks

NASA Astrophysics Data System (ADS)

Donges, J. F.; Schleussner, C.-F.; Siegmund, J. F.; Donner, R. V.

2016-05-01

Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.

Persistence border collisions in a vibrating system excited by an unbalanced motor with a relay control

NASA Astrophysics Data System (ADS)

Zhusubaliyev, Zhanybai T.; Avrutin, Viktor; Rubanov, Vasily G.; Bushuev, Dmitry A.; Titov, Dmitry V.; Yanochkina, Olga O.

2018-05-01

The paper describes a new scenario for the transition to complex dynamics in a vibrating system with an unbalanced rotor and a relay feedback control. We show that the transition from a regular dynamics without switching events in the relay element to an irregular dynamics which takes place completely in the hysteresis region occurs via a cascade of persistence border collisions.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

Increasing the power of accelerated molecular dynamics methods and plans to exploit the coming exascale

NASA Astrophysics Data System (ADS)

Voter, Arthur

Many important materials processes take place on time scales that far exceed the roughly one microsecond accessible to molecular dynamics simulation. Typically, this long-time evolution is characterized by a succession of thermally activated infrequent events involving defects in the material. In the accelerated molecular dynamics (AMD) methodology, known characteristics of infrequent-event systems are exploited to make reactive events take place more frequently, in a dynamically correct way. For certain processes, this approach has been remarkably successful, offering a view of complex dynamical evolution on time scales of microseconds, milliseconds, and sometimes beyond. We have recently made advances in all three of the basic AMD methods (hyperdynamics, parallel replica dynamics, and temperature accelerated dynamics (TAD)), exploiting both algorithmic advances and novel parallelization approaches. I will describe these advances, present some examples of our latest results, and discuss what should be possible when exascale computing arrives in roughly five years. Funded by the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, and by the Los Alamos Laboratory Directed Research and Development program.

A fuzzy Petri-net-based mode identification algorithm for fault diagnosis of complex systems

NASA Astrophysics Data System (ADS)

Propes, Nicholas C.; Vachtsevanos, George

2003-08-01

Complex dynamical systems such as aircraft, manufacturing systems, chillers, motor vehicles, submarines, etc. exhibit continuous and event-driven dynamics. These systems undergo several discrete operating modes from startup to shutdown. For example, a certain shipboard system may be operating at half load or full load or may be at start-up or shutdown. Of particular interest are extreme or "shock" operating conditions, which tend to severely impact fault diagnosis or the progression of a fault leading to a failure. Fault conditions are strongly dependent on the operating mode. Therefore, it is essential that in any diagnostic/prognostic architecture, the operating mode be identified as accurately as possible so that such functions as feature extraction, diagnostics, prognostics, etc. can be correlated with the predominant operating conditions. This paper introduces a mode identification methodology that incorporates both time- and event-driven information about the process. A fuzzy Petri net is used to represent the possible successive mode transitions and to detect events from processed sensor signals signifying a mode change. The operating mode is initialized and verified by analysis of the time-driven dynamics through a fuzzy logic classifier. An evidence combiner module is used to combine the results from both the fuzzy Petri net and the fuzzy logic classifier to determine the mode. Unlike most event-driven mode identifiers, this architecture will provide automatic mode initialization through the fuzzy logic classifier and robustness through the combining of evidence of the two algorithms. The mode identification methodology is applied to an AC Plant typically found as a component of a shipboard system.

ADAPT

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

Reynolds, John; Jankovsky, Zachary; Metzroth, Kyle G

2018-04-04

The purpose of the ADAPT code is to generate Dynamic Event Trees (DET) using a user specified set of simulators. ADAPT can utilize any simulation tool which meets a minimal set of requirements. ADAPT is based on the concept of DET which uses explicit modeling of the deterministic dynamic processes that take place during a nuclear reactor plant system (or other complex system) evolution along with stochastic modeling. When DET are used to model various aspects of Probabilistic Risk Assessment (PRA), all accident progression scenarios starting from an initiating event are considered simultaneously. The DET branching occurs at user specifiedmore » times and/or when an action is required by the system and/or the operator. These outcomes then decide how the dynamic system variables will evolve in time for each DET branch. Since two different outcomes at a DET branching may lead to completely different paths for system evolution, the next branching for these paths may occur not only at separate times, but can be based on different branching criteria. The computational infrastructure allows for flexibility in ADAPT to link with different system simulation codes, parallel processing of the scenarios under consideration, on-line scenario management (initiation as well as termination), analysis of results, and user friendly graphical capabilities. The ADAPT system is designed for a distributed computing environment; the scheduler can track multiple concurrent branches simultaneously. The scheduler is modularized so that the DET branching strategy can be modified (e.g. biasing towards the worst-case scenario/event). Independent database systems store data from the simulation tasks and the DET structure so that the event tree can be constructed and analyzed later. ADAPT is provided with a user-friendly client which can easily sort through and display the results of an experiment, precluding the need for the user to manually inspect individual simulator runs.« less

Extreme climatic events change the dynamics and invasibility of semi-arid annual plant communities.

PubMed

Jiménez, Milagros A; Jaksic, Fabian M; Armesto, Juan J; Gaxiola, Aurora; Meserve, Peter L; Kelt, Douglas A; Gutiérrez, Julio R

2011-12-01

Extreme climatic events represent disturbances that change the availability of resources. We studied their effects on annual plant assemblages in a semi-arid ecosystem in north-central Chile. We analysed 130 years of precipitation data using generalised extreme-value distribution to determine extreme events, and multivariate techniques to analyse 20 years of plant cover data of 34 native and 11 exotic species. Extreme drought resets the dynamics of the system and renders it susceptible to invasion. On the other hand, by favouring native annuals, moderately wet events change species composition and allow the community to be resilient to extreme drought. The probability of extreme drought has doubled over the last 50 years. Therefore, investigations on the interaction of climate change and biological invasions are relevant to determine the potential for future effects on the dynamics of semi-arid annual plant communities. 2011 Blackwell Publishing Ltd/CNRS.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

PubMed

Besmer, Michael D; Epting, Jannis; Page, Rebecca M; Sigrist, Jürg A; Huggenberger, Peter; Hammes, Frederik

2016-12-07

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL -1 . The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

PubMed Central

Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jürg A.; Huggenberger, Peter; Hammes, Frederik

2016-01-01

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL−1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems. PMID:27924920

Dynamic event tree analysis with the SAS4A/SASSYS-1 safety analysis code

DOE PAGES

Jankovsky, Zachary K.; Denman, Matthew R.; Aldemir, Tunc

2018-02-02

The consequences of a transient in an advanced sodium-cooled fast reactor are difficult to capture with the traditional approach to probabilistic risk assessment (PRA). Numerous safety-relevant systems are passive and may have operational states that cannot be represented by binary success or failure. In addition, the specific order and timing of events may be crucial which necessitates the use of dynamic PRA tools such as ADAPT. The modifications to the SAS4A/SASSYS-1 sodium-cooled fast reactor safety analysis code for linking it to ADAPT to perform a dynamic PRA are described. A test case is used to demonstrate the linking process andmore » to illustrate the type of insights that may be gained with this process. Finally, newly-developed dynamic importance measures are used to assess the significance of reactor parameters/constituents on calculated consequences of initiating events.« less

Dynamic event tree analysis with the SAS4A/SASSYS-1 safety analysis code

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

Jankovsky, Zachary K.; Denman, Matthew R.; Aldemir, Tunc

The consequences of a transient in an advanced sodium-cooled fast reactor are difficult to capture with the traditional approach to probabilistic risk assessment (PRA). Numerous safety-relevant systems are passive and may have operational states that cannot be represented by binary success or failure. In addition, the specific order and timing of events may be crucial which necessitates the use of dynamic PRA tools such as ADAPT. The modifications to the SAS4A/SASSYS-1 sodium-cooled fast reactor safety analysis code for linking it to ADAPT to perform a dynamic PRA are described. A test case is used to demonstrate the linking process andmore » to illustrate the type of insights that may be gained with this process. Finally, newly-developed dynamic importance measures are used to assess the significance of reactor parameters/constituents on calculated consequences of initiating events.« less

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

NASA Technical Reports Server (NTRS)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Characterization of high-intensity, long-duration continuous auroral activity (HILDCAA) events using recurrence quantification analysis

NASA Astrophysics Data System (ADS)

Mendes, Odim; Oliveira Domingues, Margarete; Echer, Ezequiel; Hajra, Rajkumar; Everton Menconi, Varlei

2017-08-01

Considering the magnetic reconnection and the viscous interaction as the fundamental mechanisms for transfer particles and energy into the magnetosphere, we study the dynamical characteristics of auroral electrojet (AE) index during high-intensity, long-duration continuous auroral activity (HILDCAA) events, using a long-term geomagnetic database (1975-2012), and other distinct interplanetary conditions (geomagnetically quiet intervals, co-rotating interaction regions (CIRs)/high-speed streams (HSSs) not followed by HILDCAAs, and events of AE comprised in global intense geomagnetic disturbances). It is worth noting that we also study active but non-HILDCAA intervals. Examining the geomagnetic AE index, we apply a dynamics analysis composed of the phase space, the recurrence plot (RP), and the recurrence quantification analysis (RQA) methods. As a result, the quantification finds two distinct clusterings of the dynamical behaviours occurring in the interplanetary medium: one regarding a geomagnetically quiet condition regime and the other regarding an interplanetary activity regime. Furthermore, the HILDCAAs seem unique events regarding a visible, intense manifestations of interplanetary Alfvénic waves; however, they are similar to the other kinds of conditions regarding a dynamical signature (based on RQA), because it is involved in the same complex mechanism of generating geomagnetic disturbances. Also, by characterizing the proper conditions of transitions from quiescent conditions to weaker geomagnetic disturbances inside the magnetosphere and ionosphere system, the RQA method indicates clearly the two fundamental dynamics (geomagnetically quiet intervals and HILDCAA events) to be evaluated with magneto-hydrodynamics simulations to understand better the critical processes related to energy and particle transfer into the magnetosphere-ionosphere system. Finally, with this work, we have also reinforced the potential applicability of the RQA method for characterizing nonlinear geomagnetic processes related to the magnetic reconnection and the viscous interaction affecting the magnetosphere.

Impact of unexpected events, shocking news, and rumors on foreign exchange market dynamics

NASA Astrophysics Data System (ADS)

McDonald, Mark; Suleman, Omer; Williams, Stacy; Howison, Sam; Johnson, Neil F.

2008-04-01

The dynamical response of a population of interconnected objects, when exposed to external perturbations, is of great interest to physicists working on complex systems. Here we focus on human systems, by analyzing the dynamical response of the world’s financial community to various types of unexpected events—including the 9/11 terrorist attacks as they unfolded on a minute-by-minute basis. For the unfolding events of 9/11, our results show that there was a gradual collective understanding of what was happening, rather than an immediate realization. More generally, we find that for news items which are not simple economic statements—and hence whose implications for the market are not immediately obvious—there are periods of collective discovery during which opinions seem to vary in a remarkably synchronized way.

Archetypes for Organisational Safety

NASA Technical Reports Server (NTRS)

Marais, Karen; Leveson, Nancy G.

2003-01-01

We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.

Variable input observer for state estimation of high-rate dynamics

NASA Astrophysics Data System (ADS)

Hong, Jonathan; Cao, Liang; Laflamme, Simon; Dodson, Jacob

2017-04-01

High-rate systems operating in the 10 μs to 10 ms timescale are likely to experience damaging effects due to rapid environmental changes (e.g., turbulence, ballistic impact). Some of these systems could benefit from real-time state estimation to enable their full potential. Examples of such systems include blast mitigation strategies, automotive airbag technologies, and hypersonic vehicles. Particular challenges in high-rate state estimation include: 1) complex time varying nonlinearities of system (e.g. noise, uncertainty, and disturbance); 2) rapid environmental changes; 3) requirement of high convergence rate. Here, we propose using a Variable Input Observer (VIO) concept to vary the input space as the event unfolds. When systems experience high-rate dynamics, rapid changes in the system occur. To investigate the VIO's potential, a VIO-based neuro-observer is constructed and studied using experimental data collected from a laboratory impact test. Results demonstrate that the input space is unique to different impact conditions, and that adjusting the input space throughout the dynamic event produces better estimations than using a traditional fixed input space strategy.

A diagnosis system using object-oriented fault tree models

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

SPACE PROPULSION SYSTEM PHASED-MISSION PROBABILITY ANALYSIS USING CONVENTIONAL PRA METHODS

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

Curtis Smith; James Knudsen

As part of a series of papers on the topic of advance probabilistic methods, a benchmark phased-mission problem has been suggested. This problem consists of modeling a space mission using an ion propulsion system, where the mission consists of seven mission phases. The mission requires that the propulsion operate for several phases, where the configuration changes as a function of phase. The ion propulsion system itself consists of five thruster assemblies and a single propellant supply, where each thruster assembly has one propulsion power unit and two ion engines. In this paper, we evaluate the probability of mission failure usingmore » the conventional methodology of event tree/fault tree analysis. The event tree and fault trees are developed and analyzed using Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE). While the benchmark problem is nominally a "dynamic" problem, in our analysis the mission phases are modeled in a single event tree to show the progression from one phase to the next. The propulsion system is modeled in fault trees to account for the operation; or in this case, the failure of the system. Specifically, the propulsion system is decomposed into each of the five thruster assemblies and fed into the appropriate N-out-of-M gate to evaluate mission failure. A separate fault tree for the propulsion system is developed to account for the different success criteria of each mission phase. Common-cause failure modeling is treated using traditional (i.e., parametrically) methods. As part of this paper, we discuss the overall results in addition to the positive and negative aspects of modeling dynamic situations with non-dynamic modeling techniques. One insight from the use of this conventional method for analyzing the benchmark problem is that it requires significant manual manipulation to the fault trees and how they are linked into the event tree. The conventional method also requires editing the resultant cut sets to obtain the correct results. While conventional methods may be used to evaluate a dynamic system like that in the benchmark, the level of effort required may preclude its use on real-world problems.« less

Advances in the continuous monitoring of erosion and deposition dynamics: Developments and applications of the new PEEP-3T system

NASA Astrophysics Data System (ADS)

Lawler, D. M.

2008-01-01

In most episodic erosion and deposition systems, knowledge of the timing of geomorphological change, in relation to fluctuations in the driving forces, is crucial to strong erosion process inference, and model building, validation and development. A challenge for geomorphology, however, is that few studies have focused on geomorphological event structure (timing, magnitude, frequency and duration of individual erosion and deposition events), in relation to applied stresses, because of the absence of key monitoring methodologies. This paper therefore (a) presents full details of a new erosion and deposition measurement system — PEEP-3T — developed from the Photo-Electronic Erosion Pin sensor in five key areas, including the addition of nocturnal monitoring through the integration of the Thermal Consonance Timing (TCT) concept, to produce a continuous sensing system; (b) presents novel high-resolution datasets from the redesigned PEEP-3T system for river bank system of the Rivers Nidd and Wharfe, northern England, UK; and (c) comments on their potential for wider application throughout geomorphology to address these key measurement challenges. Relative to manual methods of erosion and deposition quantification, continuous PEEP-3T methodologies increase the temporal resolution of erosion/deposition event detection by more than three orders of magnitude (better than 1-second resolution if required), and this facility can significantly enhance process inference. Results show that river banks are highly dynamic thermally and respond quickly to radiation inputs. Data on bank retreat timing, fixed with PEEP-3T TCT evidence, confirmed that they were significantly delayed up to 55 h after flood peaks. One event occurred 13 h after emergence from the flow. This suggests that mass failure processes rather than fluid entrainment dominated the system. It is also shown how, by integrating turbidity instrumentation with TCT ideas, linkages between sediment supply and sediment flux can be forged at event timescales, and a lack of sediment exhaustion was evident here. Five challenges for wider geomorphological process investigation are discussed. This event-based dynamics approach, based on continuous monitoring methodologies, appears to have considerable wider potential for stronger process inference and model testing and validation in many areas of geomorphology.

[Design of medical devices management system supporting full life-cycle process management].

PubMed

Su, Peng; Zhong, Jianping

2014-03-01

Based on the analysis of the present status of medical devices management, this paper optimized management process, developed a medical devices management system with Web technologies. With information technology to dynamic master the use of state of the entire life-cycle of medical devices. Through the closed-loop management with pre-event budget, mid-event control and after-event analysis, improved the delicacy management level of medical devices, optimized asset allocation, promoted positive operation of devices.

Response of the coupled M-I-T system to the March 17, 2015 solar wind dynamic pressure enhancement event

NASA Astrophysics Data System (ADS)

Ozturk, D. S.; Zou, S.; Slavin, J. A.; Ridley, A. J.

2017-12-01

When the solar wind dynamic pressure is enhanced, it could perturb the global magnetosphere-ionosphere-thermosphere (M-I-T) system. The most notable indicators of such disruptions are changes in Field-Aligned Currents (FACs), ionospheric convection patterns and magnetic perturbations observed by ground magnetometers. The link between dynamic pressure enhancements and FACs has been well established, but studies on how these FACs affect the ionosphere-thermosphere system are very limited. In order to understand the large-scale dynamic processes in the M-I-T system due to the solar wind dynamic pressure enhancement, we study the 17 March 2015 event in detail. This is one of the most geoeffective events of the solar cycle 24 with Dst minimum of -222 nT. The Wind spacecraft recorded a two-step increment in the solar wind dynamic pressure, from 2 nPa to 12 nPa within 3 minutes, while the IMF Bz stayed northward. We used the University of Michigan Block Adaptive Tree Solarwind Roe Upwind Scheme (BATS'R'US), global MHD code to study the generation and propagation of perturbations associated with the compression of the magnetosphere. To effectively represent the coupled magnetosphere-ionosphere system, we included the Global Magnetosphere (GM), Inner Magnetosphere (IM) and Ionospheric electrodynamic (IE) modules. 600 uniformly distributed virtual magnetometers are included in the simulation to identify the magnetic perturbations associated with the FAC pairs as well as their temporal and spatial variations. In addition, we used the IE module output to drive the University of Michigan Global Ionosphere Thermosphere Model (GITM) to study how the I-T system responds to dynamic pressure enhancement. We show that as a result of the solar wind dynamic pressure enhancement, two pair of perturbation FACs develop in addition to the NBZ current system. These FACs significantly alter the ionospheric convection profile and create elongated vortices that propagate from dayside to nightside. The ion temperature at the location of these vortices is significantly and immediately enhanced. We analyzed the altitude profiles of plasma temperature, electron density and joule heating to quantitatively understand energy deposition during this process, and compare them with observations from ground-based incoherent scatter radar.

Method and system for dynamic probabilistic risk assessment

NASA Technical Reports Server (NTRS)

Dugan, Joanne Bechta (Inventor); Xu, Hong (Inventor)

2013-01-01

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Conceptual modelling to predict unobserved system states - the case of groundwater flooding in the UK Chalk

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Ireson, A. M.

2017-12-01

Chalk aquifers represent an important source of drinking water in the UK. Due to its fractured-porous structure, Chalk aquifers are characterized by highly dynamic groundwater fluctuations that enhance the risk of groundwater flooding. The risk of groundwater flooding can be assessed by physically-based groundwater models. But for reliable results, a-priori information about the distribution of hydraulic conductivities and porosities is necessary, which is often not available. For that reason, conceptual simulation models are often used to predict groundwater behaviour. They commonly require calibration by historic groundwater observations. Consequently, their prediction performance may reduce significantly, when it comes to system states that did not occur within the calibration time series. In this study, we calibrate a conceptual model to the observed groundwater level observations at several locations within a Chalk system in Southern England. During the calibration period, no groundwater flooding occurred. We then apply our model to predict the groundwater dynamics of the system at a time that includes a groundwater flooding event. We show that the calibrated model provides reasonable predictions before and after the flooding event but it over-estimates groundwater levels during the event. After modifying the model structure to include topographic information, the model is capable of prediction the groundwater flooding event even though groundwater flooding never occurred in the calibration period. Although straight forward, our approach shows how conceptual process-based models can be applied to predict system states and dynamics that did not occur in the calibration period. We believe such an approach can be transferred to similar cases, especially to regions where rainfall intensities are expected to trigger processes and system states that may have not yet been observed.

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Jaworske, D. A.; Myers, J. G.; Goodenow, D.; Young, M.; Arellano, J. D.

2016-01-01

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

A fractal approach to dynamic inference and distribution analysis

PubMed Central

van Rooij, Marieke M. J. W.; Nash, Bertha A.; Rajaraman, Srinivasan; Holden, John G.

2013-01-01

Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods. PMID:23372552

Solar and interplanetary dynamics; Proceedings of the Symposium, Harvard University, Cambridge, Mass., August 27-31, 1979

NASA Technical Reports Server (NTRS)

Dryer, M. (Editor); Tandberg-Hanssen, E.

1980-01-01

The symposium focuses on solar phenomena as the source of transient events propagating through the solar system, and theoretical and observational assessments of the dynamic processes involved in these events. The topics discussed include the life history of coronal structures and fields, coronal and interplanetary responses to long time scale phenomena, solar transient phenomena affecting the corona and interplanetary medium, coronal and interplanetary responses to short time scale phenomena, and future directions.

Distributed Learning and Information Dynamics In Networked Autonomous Systems

DTIC Science & Technology

2015-11-20

2009 to June 30, 2015 4. TITLE AND SUBTITLE DISTRIBUTED LEARNING AND INFORMATION DYNAMICS IN NETWORKED AUTONOMOUS SYSTEMS 5a. CONTRACT NUMBER 5b...AUTONOMOUS SYSTEMS AFOSR Grant #FA9550–09–1–0538 PI: Eric Feron (current) Jeff S. Shamma (former) Georgia Institute of Technology Atlanta, GA 30332 1...Control. Design of event-based optimal remote estimation systems : We have proposed two new for- mulations to study the design of optimal remote

On the dynamics of synoptic scale cyclones associated with flood events in Crete

NASA Astrophysics Data System (ADS)

Flocas, Helena; Katavoutas, George; Tsanis, Ioannis; Iordanidou, Vasiliki

2015-04-01

Flood events in the Mediterranean are frequently linked to synoptic scale cyclones, although topographical or anthropogenic factors can play important role. The knowledge of the vertical profile and dynamics of these cyclones can serve as a reliable early flood warning system that can further help in hazard mitigation and risk management planning. Crete is the second largest island in the eastern Mediterranean region, being characterized by high precipitation amounts during winter, frequently causing flood events. The objective of this study is to examine the dynamic and thermodynamic mechanisms at the upper and lower levels responsible for the generation of these events, according to their origin domain. The flooding events were recorded for a period of almost 20 years. The surface cyclones are identified with the aid of MS scheme that was appropriately modified and extensively employed in the Mediterranean region in previous studies. Then, the software VTS, specially developed for the Mediterranean cyclones, was employed to investigate the vertical extension, slope and dynamic/kinematic characteristics of the surface cyclones. Composite maps of dynamic/thermodynamic parameters, such as potential vorticity, temperature advection, divergence, surface fluxes were then constructed before and during the time of the flood. The dataset includes 6-hourly surface and isobaric analyses on a 0.5° x 0.5° regular latitude-longitude grid, as derived from the ERA-INTERIM Reanalysis of the ECMWF. It was found that cyclones associated with flood events in Crete mainly generate over northern Africa or southern eastern Mediterranean region and experience their minimum pressure over Crete or southwestern Greece. About 84% of the cyclones extend up to 500hPa, demonstrating that they are well vertically well-organized systems. The vast majority (almost 84%) of the surface cyclones attains their minimum pressure when their 500 hpa counterparts are located in the NW or SW, confirming that baroclinicity is one of the most important driving mechanisms for the cyclonic deepening over the examined region. The upper level dynamics acting well before the event and the low level diabatic processes over the Aegean or the Levantine sea contribute to the large amounts of precipitation. The research reported in this paper was fully supported by the "ARISTEIA II" Action ("REINFORCE" program) of the "Operational Education and Life Long Learning programme" and is co-funded by the European Social Fund (ESF) and National Resources.

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms.

PubMed

Andersson, Richard; Larsson, Linnea; Holmqvist, Kenneth; Stridh, Martin; Nyström, Marcus

2017-04-01

Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

River Sensitivity and Catchment Connectivity: Key Controls on Geomorphic Response and Effectiveness

NASA Astrophysics Data System (ADS)

Lisenby, P.; Fryirs, K.; Croke, J.

2016-12-01

The sensitivity of river channels to adjustment and the dynamics of sediment connectivity along a channel network are key controls on the capacity (ability) for a river system to adjust, i.e. the severity, distribution, and type of geomorphic response to disturbance events. In turn, the cumulative impact of geomorphic responses compared with event magnitude will determine the geomorphic effectiveness of a single disturbance event. River sensitivity and sediment connectivity can change significantly over space and time, and vary with changes in internal factors such as channel type and geomorphic landform and external factors such as event sequencing and lithological controls. Correspondingly, the capacity for a geomorphic system to respond to disturbance events will also vary, so that geomorphic effectiveness is not definitively characterized by a static relationship between event magnitude and geomorphic response, but rather is a dynamic comparison between geomorphic response and an actively changing capacity for geomorphic adjustment. Herein, we use the Lockyer Valley, Queensland as a case study to illustrate the variability of river sensitivity and sediment connectivity. We relate this variability to the potential and capacity for geomorphic channel response. We find that the sensitivity to and capacity for geomorphic adjustment varies significantly with channel morphometry and valley position. Additionally, the nature of bedload sediment connectivity changes with the distribution of geomorphic landforms and channel weirs that can impede sediment transference through the system. This variability of river sensitivity and sediment connectivity will control the nature of geomorphic response to disturbance events within the Lockyer Valley. Ultimately, determinations of geomorphic effectiveness for disturbance events will depend on comparisons of their geomorphic impacts with the capacity of the Lockyer geomorphic system to respond.

Implementation and Test of the Automatic Flight Dynamics Operations for Geostationary Satellite Mission

NASA Astrophysics Data System (ADS)

Park, Sangwook; Lee, Young-Ran; Hwang, Yoola; Javier Santiago Noguero Galilea

2009-12-01

This paper describes the Flight Dynamics Automation (FDA) system for COMS Flight Dynamics System (FDS) and its test result in terms of the performance of the automation jobs. FDA controls the flight dynamics functions such as orbit determination, orbit prediction, event prediction, and fuel accounting. The designed FDA is independent from the specific characteristics which are defined by spacecraft manufacturer or specific satellite missions. Therefore, FDA could easily links its autonomous job control functions to any satellite mission control system with some interface modification. By adding autonomous system along with flight dynamics system, it decreases the operator’s tedious and repeated jobs but increase the usability and reliability of the system. Therefore, FDA is used to improve the completeness of whole mission control system’s quality. The FDA is applied to the real flight dynamics system of a geostationary satellite, COMS and the experimental test is performed. The experimental result shows the stability and reliability of the mission control operations through the automatic job control.

Nonlinear dynamic failure process of tunnel-fault system in response to strong seismic event

NASA Astrophysics Data System (ADS)

Yang, Zhihua; Lan, Hengxing; Zhang, Yongshuang; Gao, Xing; Li, Langping

2013-03-01

Strong earthquakes and faults have significant effect on the stability capability of underground tunnel structures. This study used a 3-Dimensional Discrete Element model and the real records of ground motion in the Wenchuan earthquake to investigate the dynamic response of tunnel-fault system. The typical tunnel-fault system was composed of one planned railway tunnel and one seismically active fault. The discrete numerical model was prudentially calibrated by means of the comparison between the field survey and numerical results of ground motion. It was then used to examine the detailed quantitative information on the dynamic response characteristics of tunnel-fault system, including stress distribution, strain, vibration velocity and tunnel failure process. The intensive tunnel-fault interaction during seismic loading induces the dramatic stress redistribution and stress concentration in the intersection of tunnel and fault. The tunnel-fault system behavior is characterized by the complicated nonlinear dynamic failure process in response to a real strong seismic event. It can be qualitatively divided into 5 main stages in terms of its stress, strain and rupturing behaviors: (1) strain localization, (2) rupture initiation, (3) rupture acceleration, (4) spontaneous rupture growth and (5) stabilization. This study provides the insight into the further stability estimation of underground tunnel structures under the combined effect of strong earthquakes and faults.

Long-time atomistic dynamics through a new self-adaptive accelerated molecular dynamics method

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

Gao, N.; Yang, L.; Gao, F.

2017-02-27

A self-adaptive accelerated molecular dynamics method is developed to model infrequent atomic- scale events, especially those events that occur on a rugged free-energy surface. Key in the new development is the use of the total displacement of the system at a given temperature to construct a boost-potential, which is slowly increased to accelerate the dynamics. The temperature is slowly increased to accelerate the dynamics. By allowing the system to evolve from one steady-state con guration to another by overcoming the transition state, this self-evolving approach makes it possible to explore the coupled motion of species that migrate on vastly differentmore » time scales. The migrations of single vacancy (V) and small He-V clusters, and the growth of nano-sized He-V clusters in Fe for times in the order of seconds are studied by this new method. An interstitial- assisted mechanism is rst explored for the migration of a helium-rich He-V cluster, while a new two-component Ostwald ripening mechanism is suggested for He-V cluster growth.« less

Towards a method to characterize temporary groundwater dynamics during droughts

NASA Astrophysics Data System (ADS)

Heudorfer, Benedikt; Stahl, Kerstin

2016-04-01

In order to improve our understanding of the complex mechanisms involved in the development, propagation and termination of drought events, a major challenge is to grasp the role of groundwater systems. Research on how groundwater responds to meteorological drought events (i.e. short-term climate anomalies) is still limited. Part of the problem is that there is as yet no generic method to characterize the response of different groundwater systems to extreme climate anomalies. In order to explore possibilities for such a methodology, we evaluate two statistical approaches to characterize groundwater dynamics on short time scales by applying them on observed groundwater head data from different pre- and peri-mountainous groundwater systems in humid central Europe (Germany). The first method is based on the coefficient of variation in moving windows of various lengths, the second method is based on streamflow recession characteristics applied on groundwater data. With these methods, the gauges behavior during low head events and its response to precipitation was explored. Findings regarding the behavior of the gauges make it possible to distinguish between gauges with a dominance of cyclic patterns, and gauges with a dominance of patterns on seasonal or event scale (commonly referred to as slow/fast responding gauges, respectively). While some clues on what factors that might control these patterns are present, the specific controls are general unclear for the gauges in this study. However as the key conclusion stands the question if the variety of manifestations of groundwater dynamics, as they occur in real systems, is subsumable with one unique method. Further studies on the topic are in progress.

Nonlinear waves of a nonlocal modified KdV equation in the atmospheric and oceanic dynamical system

NASA Astrophysics Data System (ADS)

Tang, Xiao-yan; Liang, Zu-feng; Hao, Xia-zhi

2018-07-01

A new general nonlocal modified KdV equation is derived from the nonlinear inviscid dissipative and equivalent barotropic vorticity equation in a β-plane. The nonlocal property is manifested in the shifted parity and delayed time reversal symmetries. Exact solutions of the nonlocal modified KdV equation are obtained including periodic waves, kink waves, solitary waves, kink- and/or anti-kink-cnoidal periodic wave interaction solutions, which can be utilized to describe various two-place and time-delayed correlated events. As an illustration, a special approximate solution is applied to theoretically capture the salient features of two correlated dipole blocking events in atmospheric dynamical systems.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Sublattice parallel replica dynamics.

PubMed

Martínez, Enrique; Uberuaga, Blas P; Voter, Arthur F

2014-06-01

Exascale computing presents a challenge for the scientific community as new algorithms must be developed to take full advantage of the new computing paradigm. Atomistic simulation methods that offer full fidelity to the underlying potential, i.e., molecular dynamics (MD) and parallel replica dynamics, fail to use the whole machine speedup, leaving a region in time and sample size space that is unattainable with current algorithms. In this paper, we present an extension of the parallel replica dynamics algorithm [A. F. Voter, Phys. Rev. B 57, R13985 (1998)] by combining it with the synchronous sublattice approach of Shim and Amar [ and , Phys. Rev. B 71, 125432 (2005)], thereby exploiting event locality to improve the algorithm scalability. This algorithm is based on a domain decomposition in which events happen independently in different regions in the sample. We develop an analytical expression for the speedup given by this sublattice parallel replica dynamics algorithm and compare it with parallel MD and traditional parallel replica dynamics. We demonstrate how this algorithm, which introduces a slight additional approximation of event locality, enables the study of physical systems unreachable with traditional methodologies and promises to better utilize the resources of current high performance and future exascale computers.

A Study of Primary Collision Dynamics in Inverse-Kinematics Reaction of 78Kr on 40Ca at a Bombarding Energy of 10 MeV per Nucleon

NASA Astrophysics Data System (ADS)

Henry, Eric M.

The CHIMERA multi-detector array at LNS Catania has been used to study the inverse-kinematics reaction of 78Kr + 40Ca at a bombarding energy of 10 A MeV. The multi-detector is capable of detecting individual products of the collision essential for the reconstruction of the collision dynamics. This is the first time CHIMERA has been used at low-energy, which offered a unique challenge for the calibration and interpretation of experimental data. Initial interrogation of the calibrated data revealed a class of selected events characterized by two coincident heavy fragments (atomic number Z>3) that together account for the majority of the total mass of the colliding system. These events are consistent with the complete fusion and subsequent binary split (fission) of a composite nucleus. The observed fission fragments are characterized by a broad A, Z distribution and are centered about symmetric fission while exhibiting relative velocities significantly higher than given by Viola systematics. Additional analysis of the kinematic relationship between the fission fragments was performed. Of note, is that the center-of-mass angular distribution (dsigma/dtheta) of the fission fragments exhibits an unexpected anisotropy inconsistent with a compound-nucleus reaction. This anisotropy is indicative of a dynamic fusion/fission-like process. The observed angular distribution features a forward-backward anisotropy most prevalent for mass-asymmetric events. Furthermore, the more massive fragment of mass-asymmetric events appears to emerge preferentially in the forward direction, along the beam axis. Analysis of the angular distribution of alpha particles emitted from these fission fragments suggests the events are associated mostly with central collisions. The observations associated with this subset of events are similar to those reported for dynamic fragmentation of projectile-like fragments, but have not before been observed for a fusion/fission-like process. Comparisons to dynamic and statistical reaction model predictions are inconsistent with known phenomena, but suggest a peculiar dynamics-driven scenario. A plausible explanation of the experimental results is the existence of a phenomenon similar to a "fusion window", or a range of impact parameters in which complete fusion cannot be achieved. In this scenario, the system must absorb all the relative motion and convert it to vibrational energy or heat. As the energy increases the system may not be able to accommodate this conversion of energy without breaking apart.

Event-triggered consensus tracking of multi-agent systems with Lur'e nonlinear dynamics

NASA Astrophysics Data System (ADS)

Huang, Na; Duan, Zhisheng; Wen, Guanghui; Zhao, Yu

2016-05-01

In this paper, distributed consensus tracking problem for networked Lur'e systems is investigated based on event-triggered information interactions. An event-triggered control algorithm is designed with the advantages of reducing controller update frequency and sensor energy consumption. By using tools of ?-procedure and Lyapunov functional method, some sufficient conditions are derived to guarantee that consensus tracking is achieved under a directed communication topology. Meanwhile, it is shown that Zeno behaviour of triggering time sequences is excluded for the proposed event-triggered rule. Finally, some numerical simulations on coupled Chua's circuits are performed to illustrate the effectiveness of the theoretical algorithms.

Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling

PubMed Central

Zhao, Liang; Chen, Feng; Dai, Jing; Hua, Ting; Lu, Chang-Tien; Ramakrishnan, Naren

2014-01-01

Twitter has become a popular data source as a surrogate for monitoring and detecting events. Targeted domains such as crime, election, and social unrest require the creation of algorithms capable of detecting events pertinent to these domains. Due to the unstructured language, short-length messages, dynamics, and heterogeneity typical of Twitter data streams, it is technically difficult and labor-intensive to develop and maintain supervised learning systems. We present a novel unsupervised approach for detecting spatial events in targeted domains and illustrate this approach using one specific domain, viz. civil unrest modeling. Given a targeted domain, we propose a dynamic query expansion algorithm to iteratively expand domain-related terms, and generate a tweet homogeneous graph. An anomaly identification method is utilized to detect spatial events over this graph by jointly maximizing local modularity and spatial scan statistics. Extensive experiments conducted in 10 Latin American countries demonstrate the effectiveness of the proposed approach. PMID:25350136

Methodology for Collision Risk Assessment of an Airspace Flow Corridor Concept

NASA Astrophysics Data System (ADS)

Zhang, Yimin

This dissertation presents a methodology to estimate the collision risk associated with a future air-transportation concept called the flow corridor. The flow corridor is a Next Generation Air Transportation System (NextGen) concept to reduce congestion and increase throughput in en-route airspace. The flow corridor has the potential to increase throughput by reducing the controller workload required to manage aircraft outside the corridor and by reducing separation of aircraft within corridor. The analysis in this dissertation is a starting point for the safety analysis required by the Federal Aviation Administration (FAA) to eventually approve and implement the corridor concept. This dissertation develops a hybrid risk analysis methodology that combines Monte Carlo simulation with dynamic event tree analysis. The analysis captures the unique characteristics of the flow corridor concept, including self-separation within the corridor, lane change maneuvers, speed adjustments, and the automated separation assurance system. Monte Carlo simulation is used to model the movement of aircraft in the flow corridor and to identify precursor events that might lead to a collision. Since these precursor events are not rare, standard Monte Carlo simulation can be used to estimate these occurrence rates. Dynamic event trees are then used to model the subsequent series of events that may lead to collision. When two aircraft are on course for a near-mid-air collision (NMAC), the on-board automated separation assurance system provides a series of safety layers to prevent the impending NNAC or collision. Dynamic event trees are used to evaluate the potential failures of these layers in order to estimate the rare-event collision probabilities. The results show that the throughput can be increased by reducing separation to 2 nautical miles while maintaining the current level of safety. A sensitivity analysis shows that the most critical parameters in the model related to the overall collision probability are the minimum separation, the probability that both flights fail to respond to traffic collision avoidance system, the probability that an NMAC results in a collision, the failure probability of the automatic dependent surveillance broadcast in receiver, and the conflict detection probability.

Filament dynamics in confined chemical gardens and in filiform corrosion.

PubMed

Brau, Fabian; Haudin, Florence; Thouvenel-Romans, Stephanie; De Wit, Anne; Steinbock, Oliver; Cardoso, Silvana S S; Cartwright, Julyan H E

2018-01-03

Two reaction systems that are at first sight very different produce similar macroscopic filamentary product trails. The systems are chemical gardens confined to a Hele-Shaw cell and corroding metal plates that undergo filiform corrosion. We show that the two systems are in fact very much alike. Our experiments and analysis show that filament dynamics obey similar scaling laws in both instances: filament motion is nearly ballistic and fully self-avoiding, which creates self-trapping events.

Evolution and Extinction Dynamics in Rugged Fitness Landscapes

NASA Astrophysics Data System (ADS)

Sibani, Paolo; Brandt, Michael; Alstrøm, Preben

After an introductory section summarizing the paleontological data and some of their theoretical descriptions, we describe the "reset" model and its (in part analytically soluble) mean field version, which have been briefly introduced in Letters.1,2 Macroevolution is considered as a problem of stochastic dynamics in a system with many competing agents. Evolutionary events (speciations and extinctions) are triggered by fitness records found by random exploration of the agents' fitness landscapes. As a consequence, the average fitness in the system increases logarithmically with time, while the rate of extinction steadily decreases. This non-stationary dynamics is studied by numerical simulations and, in a simpler mean field version, analytically. We also consider the effect of externally added "mass" extinctions. The predictions for various quantities of paleontological interest (life-time distribution, distribution of event sizes and behavior of the rate of extinction) are robust and in good agreement with available data.

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons: Event-Specific 1-D Modeling

DOE PAGES

Schiller, Q.; Tu, W.; Ali, A. F.; ...

2017-03-11

The most significant unknown regarding relativistic electrons in Earth’s outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in-situ measurementsmore » during the 13-14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and THEMIS observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss timescale show deviation from the event specific model of nearly two orders of magnitude within 72 hours of the enhancement event. However, models using alternative loss timescales closely resemble the event specific model.« less

Simultaneous event-specific estimates of transport, loss, and source rates for relativistic outer radiation belt electrons: Event-Specific 1-D Modeling

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

Schiller, Q.; Tu, W.; Ali, A. F.

The most significant unknown regarding relativistic electrons in Earth’s outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in-situ measurementsmore » during the 13-14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and THEMIS observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss timescale show deviation from the event specific model of nearly two orders of magnitude within 72 hours of the enhancement event. However, models using alternative loss timescales closely resemble the event specific model.« less

Differential equation models for sharp threshold dynamics.

PubMed

Schramm, Harrison C; Dimitrov, Nedialko B

2014-01-01

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

Characterizing Middle Atmospheric Dynamical Variability and its Impact on the Thermosphere/Ionosphere System During Recent Stratospheric Sudden Warmings

NASA Astrophysics Data System (ADS)

McCormack, J. P.; Sassi, F.; Hoppel, K.; Ma, J.; Eckermann, S. D.

2015-12-01

We investigate the evolution of neutral atmospheric dynamics in the 10-100 km altitude range before, during, and after recent stratospheric sudden warmings (SSWs) using a prototype high-altitude version of the Navy Global Environmental Model (NAVGEM), which combines a 4-dimensional variational (4DVAR) data assimilation system with a 3-time-level semi-Lagrangian semi-implicit global forecast model. In addition to assimilating conventional meteorological observations, NAVGEM also assimilates middle atmospheric temperature and constituent observations from both operational and research satellite platforms to provide global synoptic meteorological analyses of winds, temperatures, ozone, and water vapor from the surface to ~90 km. In this study, NAVGEM analyses are used to diagnose the spatial and temporal evolution of the main dynamical drivers in the mesosphere and lower thermosphere (MLT) before, during, and after specific SSW events during the 2009-2013 period when large disturbances were observed in the thermosphere/ionosphere (TI) region. Preliminary findings show strong modulation of the semidiurnal tide in the MLT during the onset of an SSW. To assess the impact of the neutral atmosphere dynamical variability on the TI system, NAVGEM analyses are used to constrain simulations of select SSW events using the specified dynamics (SD) configuration of the extended Whole Atmosphere Community Climate Model (WACCM-X).

Distributed video data fusion and mining

NASA Astrophysics Data System (ADS)

Chang, Edward Y.; Wang, Yuan-Fang; Rodoplu, Volkan

2004-09-01

This paper presents an event sensing paradigm for intelligent event-analysis in a wireless, ad hoc, multi-camera, video surveillance system. In particilar, we present statistical methods that we have developed to support three aspects of event sensing: 1) energy-efficient, resource-conserving, and robust sensor data fusion and analysis, 2) intelligent event modeling and recognition, and 3) rapid deployment, dynamic configuration, and continuous operation of the camera networks. We outline our preliminary results, and discuss future directions that research might take.

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

PubMed

Zhang, J W; Rangan, A V

2015-04-01

In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.

Advanced Simulation of Coupled Earthquake and Tsunami Events

NASA Astrophysics Data System (ADS)

Behrens, Joern

2013-04-01

Tsunami-Earthquakes represent natural catastrophes threatening lives and well-being of societies in a solitary and unexpected extreme event as tragically demonstrated in Sumatra (2004), Samoa (2009), Chile (2010), or Japan (2011). Both phenomena are consequences of the complex system of interactions of tectonic stress, fracture mechanics, rock friction, rupture dynamics, fault geometry, ocean bathymetry, and coastline geometry. The ASCETE project forms an interdisciplinary research consortium that couples the most advanced simulation technologies for earthquake rupture dynamics and tsunami propagation to understand the fundamental conditions of tsunami generation. We report on the latest research results in physics-based dynamic rupture and tsunami wave propagation simulation, using unstructured and adaptive meshes with continuous and discontinuous Galerkin discretization approaches. Coupling both simulation tools - the physics-based dynamic rupture simulation and the hydrodynamic tsunami wave propagation - will give us the possibility to conduct highly realistic studies of the interaction of rupture dynamics and tsunami impact characteristics.

An Event-Based Approach to Distributed Diagnosis of Continuous Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

2010-01-01

Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

NASA/Army Rotorcraft Technology. Volume 1: Aerodynamics, and Dynamics and Aeroelasticity

NASA Technical Reports Server (NTRS)

1988-01-01

The Conference Proceedings is a compilation of over 30 technical papers presented at this milestone event which reported on the advances in rotorcraft technical knowledge resulting from NASA, Army, and industry rotorcraft research programs over the last 5 to 10 years. The Conference brought together over 230 government, industry, and allied nation conferees to exchange technical information and hear invited technical papers by prominent NASA, Army, and industry researchers covering technology topics which included: aerodynamics, dynamics and elasticity, propulsion and drive systems, flight dynamics and control, acoustics, systems integration, and research aircraft.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-09-01

This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor-critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP.

Low-cost digital dynamic visualization system

NASA Astrophysics Data System (ADS)

Asundi, Anand K.; Sajan, M. R.

1995-05-01

High speed photographic systems like the image rotation camera, the Cranz Schardin camera and the drum camera are typically used for recording and visualization of dynamic events in stress analysis, fluid mechanics, etc. All these systems are fairly expensive and generally not simple to use. Furthermore they are all based on photographic film recording systems requiring time consuming and tedious wet processing of the films. Currently digital cameras are replacing to certain extent the conventional cameras for static experiments. Recently, there is lot of interest in developing and modifying CCD architectures and recording arrangements for dynamic scene analysis. Herein we report the use of a CCD camera operating in the Time Delay and Integration (TDI) mode for digitally recording dynamic scenes. Applications in solid as well as fluid impact problems are presented.

LIDT-DD: A new hybrid model to understand debris discs observations - The case of massive collisions.

NASA Astrophysics Data System (ADS)

Kral, Q.; Thébault, P.; Augereau, J.-C.; Boccaletti, A.; Charnoz, S.

2014-12-01

LIDT-DD is a new hybrid model coupling the collisional and dynamical evolution in debris discs in a self-consistent way. It has been developed in a way that allows to treat a large number of different astrophysical cases where collisions and dynamics have an important role. This interplay was often totally neglected in previous studies whereas, even for the simplest configurations, the real physics of debris discs imposes strong constraints and interactions between dynamics and collisions. After presenting the LIDT-DD model, we will describe the evolution of violent stochastic collisional events with this model. These massive impacts have been invoked as a possible explanation for some debris discs displaying pronounced azimuthal asymmetries or having a luminosity excess exceeding that expected for systems at collisional steady-state. So far, no thorough modelling of the consequences of such stochastic events has been carried out, mainly because of the extreme numerical challenge of coupling the dynamical and collisional evolution of the released dust. We follow the collisional and dynamical evolution of dust released after the breakup of a Ceres-sized body at 6 AU from its central star. We investigate the duration, magnitude and spatial structure of the signature left by such a violent event, as well as its observational detectability. We use the GRaTer package to estimate the system's luminosity at different wavelengths and derive synthetic images for the SPHERE/VLT and MIRI/JWST instruments.

Fine grained event processing on HPCs with the ATLAS Yoda system

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; Van Gemmeren, Peter; Wenaus, Torre

2015-12-01

High performance computing facilities present unique challenges and opportunities for HEP event processing. The massive scale of many HPC systems means that fractionally small utilization can yield large returns in processing throughput. Parallel applications which can dynamically and efficiently fill any scheduling opportunities the resource presents benefit both the facility (maximal utilization) and the (compute-limited) science. The ATLAS Yoda system provides this capability to HEP-like event processing applications by implementing event-level processing in an MPI-based master-client model that integrates seamlessly with the more broadly scoped ATLAS Event Service. Fine grained, event level work assignments are intelligently dispatched to parallel workers to sustain full utilization on all cores, with outputs streamed off to destination object stores in near real time with similarly fine granularity, such that processing can proceed until termination with full utilization. The system offers the efficiency and scheduling flexibility of preemption without requiring the application actually support or employ check-pointing. We will present the new Yoda system, its motivations, architecture, implementation, and applications in ATLAS data processing at several US HPC centers.

A tool for exploring the dynamics of innovative interventions for public health: the critical event card.

PubMed

Figueiro, Ana Claudia; de Araújo Oliveira, Sydia Rosana; Hartz, Zulmira; Couturier, Yves; Bernier, Jocelyne; do Socorro Machado Freire, Maria; Samico, Isabella; Medina, Maria Guadalupe; de Sa, Ronice Franco; Potvin, Louise

2017-03-01

Public health interventions are increasingly represented as complex systems. Research tools for capturing the dynamic of interventions processes, however, are practically non-existent. This paper describes the development and proof of concept process of an analytical tool, the critical event card (CEC), which supports the representation and analysis of complex interventions' evolution, based on critical events. Drawing on the actor-network theory (ANT), we developed and field-tested the tool using three innovative health interventions in northeastern Brazil. Interventions were aimed to promote health equity through intersectoral approaches; were engaged in participatory evaluation and linked to professional training programs. The CEC developing involve practitioners and researchers from projects. Proof of concept was based on document analysis, face-to-face interviews and focus groups. Analytical categories from CEC allow identifying and describing critical events as milestones in the evolution of complex interventions. Categories are (1) event description; (2) actants (human and non-human) involved; (3) interactions between actants; (4) mediations performed; (5) actions performed; (6) inscriptions produced; and (7) consequences for interventions. The CEC provides a tool to analyze and represent intersectoral internvetions' complex and dynamic evolution.

Vibration signature analysis of multistage gear transmission

NASA Technical Reports Server (NTRS)

Choy, F. K.; Tu, Y. K.; Savage, M.; Townsend, D. P.

1989-01-01

An analysis is presented for multistage multimesh gear transmission systems. The analysis predicts the overall system dynamics and the transmissibility to the gear box or the enclosed structure. The modal synthesis approach of the analysis treats the uncoupled lateral/torsional model characteristics of each stage or component independently. The vibration signature analysis evaluates the global dynamics coupling in the system. The method synthesizes the interaction of each modal component or stage with the nonlinear gear mesh dynamics and the modal support geometry characteristics. The analysis simulates transient and steady state vibration events to determine the resulting torque variations, speeds, changes, rotor imbalances, and support gear box motion excitations. A vibration signature analysis examines the overall dynamic characteristics of the system, and the individual model component responses. The gear box vibration analysis also examines the spectral characteristics of the support system.

Accretion dynamics in pre-main sequence binaries

NASA Astrophysics Data System (ADS)

Tofflemire, B.; Mathieu, R.; Herczeg, G.; Ardila, D.; Akeson, R.; Ciardi, D.; Johns-Krull, C.

Binary stars are a common outcome of star formation. Orbital resonances, especially in short-period systems, are capable of reshaping the distribution and flows of circumstellar material. Simulations of the binary-disk interaction predict a dynamically cleared gap around the central binary, accompanied by periodic ``pulsed'' accretion events that are driven by orbital motion. To place observational constraints on the binary-disk interaction, we have conducted a long-term monitoring program tracing the time-variable accretion behavior of 9 short-period binaries. In this proceeding we present two results from our campaign: 1) the detection of periodic pulsed accretion events in DQ Tau and TWA 3A, and 2) evidence that the TWA 3A primary is the dominant accretor in the system.

Using experimental data to test an n -body dynamical model coupled with an energy-based clusterization algorithm at low incident energies

NASA Astrophysics Data System (ADS)

Kumar, Rohit; Puri, Rajeev K.

2018-03-01

Employing the quantum molecular dynamics (QMD) approach for nucleus-nucleus collisions, we test the predictive power of the energy-based clusterization algorithm, i.e., the simulating annealing clusterization algorithm (SACA), to describe the experimental data of charge distribution and various event-by-event correlations among fragments. The calculations are constrained into the Fermi-energy domain and/or mildly excited nuclear matter. Our detailed study spans over different system masses, and system-mass asymmetries of colliding partners show the importance of the energy-based clusterization algorithm for understanding multifragmentation. The present calculations are also compared with the other available calculations, which use one-body models, statistical models, and/or hybrid models.

Butterflies, Black swans and Dragon kings: How to use the Dynamical Systems Theory to build a "zoology" of mid-latitude circulation atmospheric extremes?

NASA Astrophysics Data System (ADS)

Faranda, D.; Yiou, P.; Alvarez-Castro, M. C. M.

2015-12-01

A combination of dynamical systems and statistical techniques allows for a robust assessment of the dynamical properties of the mid-latitude atmospheric circulation. Extremes at different spatial and time scales are not only associated to exceptionally intense weather structures (e.g. extra-tropical cyclones) but also to rapid changes of circulation regimes (thunderstorms, supercells) or the extreme persistence of weather structure (heat waves, cold spells). We will show how the dynamical systems theory of recurrence combined to the extreme value theory can take into account the spatial and temporal dependence structure of the mid-latitude circulation structures and provide information on the statistics of extreme events.

Effects of electronic excitation on cascade dynamics in nickel–iron and nickel–palladium systems

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

Zarkadoula, Eva; Samolyuk, German; Weber, William J.

Using molecular dynamics simulations and the two-temperature model, we provide in this paper a comparison of the surviving damage from single ion irradiation events in nickel-based alloys, for cascades with and without taking into account the effects of the electronic excitations. We find that including the electronic effects impacts the amount of the resulting damage and the production of isolated defects. Finally, irradiation of nickel–palladium systems results in larger numbers of defects compared to nickel–iron systems, with similar numbers of isolated defects. We additionally investigate the mass effect on the two-temperature model in molecular dynamics simulations of cascades.

Effects of electronic excitation on cascade dynamics in nickel–iron and nickel–palladium systems

DOE PAGES

Zarkadoula, Eva; Samolyuk, German; Weber, William J.

2017-06-10

Using molecular dynamics simulations and the two-temperature model, we provide in this paper a comparison of the surviving damage from single ion irradiation events in nickel-based alloys, for cascades with and without taking into account the effects of the electronic excitations. We find that including the electronic effects impacts the amount of the resulting damage and the production of isolated defects. Finally, irradiation of nickel–palladium systems results in larger numbers of defects compared to nickel–iron systems, with similar numbers of isolated defects. We additionally investigate the mass effect on the two-temperature model in molecular dynamics simulations of cascades.

Reaching extended length-scales with temperature-accelerated dynamics

NASA Astrophysics Data System (ADS)

Amar, Jacques G.; Shim, Yunsic

2013-03-01

In temperature-accelerated dynamics (TAD) a high-temperature molecular dynamics (MD) simulation is used to accelerate the search for the next low-temperature activated event. While TAD has been quite successful in extending the time-scales of simulations of non-equilibrium processes, due to the fact that the computational work scales approximately as the cube of the number of atoms, until recently only simulations of relatively small systems have been carried out. Recently, we have shown that by combining spatial decomposition with our synchronous sublattice algorithm, significantly improved scaling is possible. However, in this approach the size of activated events is limited by the processor size while the dynamics is not exact. Here we discuss progress in developing an alternate approach in which high-temperature parallel MD along with localized saddle-point (LSAD) calculations, are used to carry out TAD simulations without restricting the size of activated events while keeping the dynamics ``exact'' within the context of harmonic transition-state theory. In tests of our LSAD method applied to Ag/Ag(100) annealing and Cu/Cu(100) growth simulations we find significantly improved scaling of TAD, while maintaining a negligibly small error in the energy barriers. Supported by NSF DMR-0907399.

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances.

PubMed

Melcher, Anthony A; Horsburgh, Jeffery S

2017-06-01

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.

Effect of the alien invasive bivalve Corbicula fluminea on the nutrient dynamics under climate change scenarios

NASA Astrophysics Data System (ADS)

Coelho, J. P.; Lillebø, A. I.; Crespo, D.; Leston, S.; Dolbeth, M.

2018-05-01

The main aim of this study was to evaluate the impact of the alien invasive bivalve Corbicula fluminea (Müller, 1774) in the nutrient dynamics of temperate estuarine systems (oligohaline areas) under climate change scenarios. The scenarios simulated shifts in climatic conditions, following salinity (0 or 5) and temperature (24 or 30 °C) changes, usual during drought and heat wave events. The effect of the individual size/age (different size classes with fixed biomass) and density (various densities of <1 cm clams) on the bioturbation-associated nutrient dynamics were also evaluated under an 18-day laboratory experimental setup. Results highlight the significant effect of C. fluminea on the ecosystem nutrient dynamics, enhancing the efflux of both phosphate and dissolved inorganic nitrogen (DIN) from the sediments to the water column. Both drought and heat wave events will have an impact on the DIN dynamics within C. fluminea colonized systems, favouring a higher NH4-N efflux. The population structure of C. fluminea will have a decisive role on the impact of the species, with stronger nutrient effluxes associated with a predominantly juvenile population structure.

Adaptive target binarization method based on a dual-camera system

NASA Astrophysics Data System (ADS)

Lei, Jing; Zhang, Ping; Xu, Jiangtao; Gao, Zhiyuan; Gao, Jing

2018-01-01

An adaptive target binarization method based on a dual-camera system that contains two dynamic vision sensors was proposed. First, a preprocessing procedure of denoising is introduced to remove the noise events generated by the sensors. Then, the complete edge of the target is retrieved and represented by events based on an event mosaicking method. Third, the region of the target is confirmed by an event-to-event method. Finally, a postprocessing procedure of image open and close operations of morphology methods is adopted to remove the artifacts caused by event-to-event mismatching. The proposed binarization method has been extensively tested on numerous degraded images with nonuniform illumination, low contrast, noise, or light spots and successfully compared with other well-known binarization methods. The experimental results, which are based on visual and misclassification error criteria, show that the proposed method performs well and has better robustness on the binarization of degraded images.

Statistical Modeling of Extreme Values and Evidence of Presence of Dragon King (DK) in Solar Wind

NASA Astrophysics Data System (ADS)

Gomes, T.; Ramos, F.; Rempel, E. L.; Silva, S.; C-L Chian, A.

2017-12-01

The solar wind constitutes a nonlinear dynamical system, presenting intermittent turbulence, multifractality and chaotic dynamics. One characteristic shared by many such complex systems is the presence of extreme events, that play an important role in several Geophysical phenomena and their statistical characterization is a problem of great practical relevance. This work investigates the presence of extreme events in time series of the modulus of the interplanetary magnetic field measured by Cluster spacecraft on February 2, 2002. One of the main results is that the solar wind near the Earth's bow shock can be modeled by the Generalized Pareto (GP) and Generalized Extreme Values (GEV) distributions. Both models present a statistically significant positive shape parameter which implyies a heavy tail in the probability distribution functions and an unbounded growth in return values as return periods become too long. There is evidence that current sheets are the main responsible for positive values of the shape parameter. It is also shown that magnetic reconnection at the interface between two interplanetary magnetic flux ropes in the solar wind can be considered as Dragon Kings (DK), a class of extreme events whose formation mechanisms are fundamentally different from others. As long as magnetic reconnection can be classified as a Dragon King, there is the possibility of its identification and even its prediction. Dragon kings had previously been identified in time series of financial crashes, nuclear power generation accidents, stock market and so on. It is believed that they are associated with the occurrence of extreme events in dynamical systems at phase transition, bifurcation, crises or tipping points.

Dynamic modeling and vibration characteristics analysis of the aero-engine dual-rotor system with Fan blade out

NASA Astrophysics Data System (ADS)

Yu, Pingchao; Zhang, Dayi; Ma, Yanhong; Hong, Jie

2018-06-01

Fan Blade Out (FBO) from a running rotor of the turbofan engine will not only introduce the sudden unbalance and inertia asymmetry into the rotor, but also apply large impact load and induce rotor-to-stator rubbing on the rotor, which makes the mass, gyroscopic and stiffness matrixes of the dynamic equation become time-varying and highly nonlinear, consequently leads to the system's complicated vibration. The dynamic analysis of the aero-engine rotor system is one essential requirement of the authorities and is vital to the aero-engine's safety. The paper aims at studying the dynamic responses of the complicated dual-rotor systems at instantaneous and windmilling statuses when FBO event occurs. The physical process and mechanical characteristics of the FBO event are described qualitatively, based on which the dynamic modeling for an aero-engine dual-rotor system is carried out considering several excitations caused by FBO. Meanwhile the transient response during the instantaneous status and steady-state response at the windmilling status are obtained. The results reveal that the sudden unbalance can induce impact load to the rotor, and lead to the sharp increase of the vibration amplitude and reaction force. The rub-impact will apply constraint effects on the rotor and restrict the transient vibration amplitude, while the inertia asymmetry has little influence on the transient response. When the rotor with huge unbalance operates at windmilling status, the rub-impact turns to be the main factor determining the rotor's dynamic behavior, and several potential motion states, such as instable dry whip, intermittent rubbing and synchronous full annular rubbing would happen on certain conditions.

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

PubMed Central

Lange, Stefan; Donges, Jonathan F.; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation. Building on a recent study by Feldhoff et al. [1] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system. Three types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed. PMID:25856374

Local difference measures between complex networks for dynamical system model evaluation.

PubMed

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed.

Rare events modeling with support vector machine: Application to forecasting large-amplitude geomagnetic substorms and extreme events in financial markets.

NASA Astrophysics Data System (ADS)

Gavrishchaka, V. V.; Ganguli, S. B.

2001-12-01

Reliable forecasting of rare events in a complex dynamical system is a challenging problem that is important for many practical applications. Due to the nature of rare events, data set available for construction of the statistical and/or machine learning model is often very limited and incomplete. Therefore many widely used approaches including such robust algorithms as neural networks can easily become inadequate for rare events prediction. Moreover in many practical cases models with high-dimensional inputs are required. This limits applications of the existing rare event modeling techniques (e.g., extreme value theory) that focus on univariate cases. These approaches are not easily extended to multivariate cases. Support vector machine (SVM) is a machine learning system that can provide an optimal generalization using very limited and incomplete training data sets and can efficiently handle high-dimensional data. These features may allow to use SVM to model rare events in some applications. We have applied SVM-based system to the problem of large-amplitude substorm prediction and extreme event forecasting in stock and currency exchange markets. Encouraging preliminary results will be presented and other possible applications of the system will be discussed.

Spatial scale effect on sediment dynamics in basin-wide floods within a typical agro-watershed: A case study in the hilly loess region of the Chinese Loess Plateau.

PubMed

Zhang, Le-Tao; Li, Zhan-Bin; Wang, Shan-Shan

2016-12-01

Scale issues, which have been extensively studied in the domain of soil erosion, are considerably significant in geomorphologic processes and hydrologic modelling. However, relatively scarce efforts have been made to quantify the spatial scale effect on event-based sediment dynamics in basin-wide floods. To address this issue, sediment-runoff yield data of 44 basin-wide flood events were collected from gauging stations at the Chabagou river basin, a typical agro-basin (unmanaged) in the hilly loess region of the Chinese Loess Plateau. Thus, the spatial scale effect on event-based sediment dynamics was investigated in the basin system across three different spatial scales from sublateral to basin outlet. Results showed that the event-based suspended sediment concentration, as well as the intra- and inter-scale flow-sediment relationships remained spatially constant. Hence, almost all the sediment-laden flows can reach at the detachment-limited maximum concentration across scales, specifically for hyperconcentrated flows. Consequently, limited influence was exerted by upstream sediment-laden flow on downstream sediment output, particularly for major sediment-producing events. However, flood peak discharge instead of total flood runoff amount can better interpret the dynamics of sediment yield across scales. As a composite parameter, the proposed stream energy factor combines flood runoff depth and flood peak discharge, thereby showing more advantages to describe the event-based inter-scale flow-sediment relationship than other flow-related variables. Overall, this study demonstrates the process-specific characteristics of soil erosion by water flows in the basin system. Therefore, event-based sediment control should be oriented by the process to cut off the connectivity of hyperconcentrated flows and redistribute the erosive energy of flowing water in terms of temporality and spatiality. Furthermore, evaluation of soil conservation benefits should be based on the process of runoff regulation to comprehensively assess the efficiency of anti-erosion strategies in sediment control at the basin scale. Copyright © 2016. Published by Elsevier B.V.

To react or not to react? Intrinsic stochasticity of human control in virtual stick balancing

PubMed Central

Zgonnikov, Arkady; Lubashevsky, Ihor; Kanemoto, Shigeru; Miyazawa, Toru; Suzuki, Takashi

2014-01-01

Understanding how humans control unstable systems is central to many research problems, with applications ranging from quiet standing to aircraft landing. Increasingly, much evidence appears in favour of event-driven control hypothesis: human operators only start actively controlling the system when the discrepancy between the current and desired system states becomes large enough. The event-driven models based on the concept of threshold can explain many features of the experimentally observed dynamics. However, much still remains unclear about the dynamics of human-controlled systems, which likely indicates that humans use more intricate control mechanisms. This paper argues that control activation in humans may be not threshold-driven, but instead intrinsically stochastic, noise-driven. Specifically, we suggest that control activation stems from stochastic interplay between the operator's need to keep the controlled system near the goal state, on the one hand, and the tendency to postpone interrupting the system dynamics, on the other hand. We propose a model capturing this interplay and show that it matches the experimental data on human balancing of virtual overdamped stick. Our results illuminate that the noise-driven activation mechanism plays a crucial role at least in the considered task, and, hypothetically, in a broad range of human-controlled processes. PMID:25056217

Transient analysis techniques in performing impact and crash dynamic studies

NASA Technical Reports Server (NTRS)

Pifko, A. B.; Winter, R.

1989-01-01

Because of the emphasis being placed on crashworthiness as a design requirement, increasing demands are being made by various organizations to analyze a wide range of complex structures that must perform safely when subjected to severe impact loads, such as those generated in a crash event. The ultimate goal of crashworthiness design and analysis is to produce vehicles with the ability to reduce the dynamic forces experienced by the occupants to specified levels, while maintaining a survivable envelope around them during a specified crash event. DYCAST is a nonlinear structural dynamic finite element computer code that started from the plans systems of a finite element program for static nonlinear structural analysis. The essential features of DYCAST are outlined.

ADESSA: A Real-Time Decision Support Service for Delivery of Semantically Coded Adverse Drug Event Data

PubMed Central

Duke, Jon D.; Friedlin, Jeff

2010-01-01

Evaluating medications for potential adverse events is a time-consuming process, typically involving manual lookup of information by physicians. This process can be expedited by CDS systems that support dynamic retrieval and filtering of adverse drug events (ADE’s), but such systems require a source of semantically-coded ADE data. We created a two-component system that addresses this need. First we created a natural language processing application which extracts adverse events from Structured Product Labels and generates a standardized ADE knowledge base. We then built a decision support service that consumes a Continuity of Care Document and returns a list of patient-specific ADE’s. Our database currently contains 534,125 ADE’s from 5602 product labels. An NLP evaluation of 9529 ADE’s showed recall of 93% and precision of 95%. On a trial set of 30 CCD’s, the system provided adverse event data for 88% of drugs and returned these results in an average of 620ms. PMID:21346964

Development and application of the dynamic system doctor to nuclear reactor probabilistic risk assessments.

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

Kunsman, David Marvin; Aldemir, Tunc; Rutt, Benjamin

2008-05-01

This LDRD project has produced a tool that makes probabilistic risk assessments (PRAs) of nuclear reactors - analyses which are very resource intensive - more efficient. PRAs of nuclear reactors are being increasingly relied on by the United States Nuclear Regulatory Commission (U.S.N.R.C.) for licensing decisions for current and advanced reactors. Yet, PRAs are produced much as they were 20 years ago. The work here applied a modern systems analysis technique to the accident progression analysis portion of the PRA; the technique was a system-independent multi-task computer driver routine. Initially, the objective of the work was to fuse the accidentmore » progression event tree (APET) portion of a PRA to the dynamic system doctor (DSD) created by Ohio State University. Instead, during the initial efforts, it was found that the DSD could be linked directly to a detailed accident progression phenomenological simulation code - the type on which APET construction and analysis relies, albeit indirectly - and thereby directly create and analyze the APET. The expanded DSD computational architecture and infrastructure that was created during this effort is called ADAPT (Analysis of Dynamic Accident Progression Trees). ADAPT is a system software infrastructure that supports execution and analysis of multiple dynamic event-tree simulations on distributed environments. A simulator abstraction layer was developed, and a generic driver was implemented for executing simulators on a distributed environment. As a demonstration of the use of the methodological tool, ADAPT was applied to quantify the likelihood of competing accident progression pathways occurring for a particular accident scenario in a particular reactor type using MELCOR, an integrated severe accident analysis code developed at Sandia. (ADAPT was intentionally created with flexibility, however, and is not limited to interacting with only one code. With minor coding changes to input files, ADAPT can be linked to other such codes.) The results of this demonstration indicate that the approach can significantly reduce the resources required for Level 2 PRAs. From the phenomenological viewpoint, ADAPT can also treat the associated epistemic and aleatory uncertainties. This methodology can also be used for analyses of other complex systems. Any complex system can be analyzed using ADAPT if the workings of that system can be displayed as an event tree, there is a computer code that simulates how those events could progress, and that simulator code has switches to turn on and off system events, phenomena, etc. Using and applying ADAPT to particular problems is not human independent. While the human resources for the creation and analysis of the accident progression are significantly decreased, knowledgeable analysts are still necessary for a given project to apply ADAPT successfully. This research and development effort has met its original goals and then exceeded them.« less

Parallel Stochastic discrete event simulation of calcium dynamics in neuron.

PubMed

Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W

2017-09-26

The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.

Understanding the Role of Air-Sea Interaction on Extreme Rainfall in Aquaplanet and Earth-like CESM2

NASA Astrophysics Data System (ADS)

Benedict, J. J.; Clement, A. C.; Medeiros, B.

2017-12-01

Extreme precipitation events are associated with anomalous, latitudinally dependent dynamical and convective weather systems. For example, plumes of excessive poleward water vapor transport and topographical effects drive extreme precipitation events in the midlatitudes, while intense tropical precipitation is associated with organized convective systems. In both cases, air-sea fluxes have the potential to contribute significantly to the moisture budget of these storms, but the roles of surface fluxes and upper-ocean processes and their impact on precipitation extremes have yet to be explored in sufficient detail. To examine such mechanisms, we implement a climate model hierarchy that encompasses a spectrum of ocean models, from prescribed-SST to fully dynamic, as well as both aquaplanet and Earth-like lower boundary types within version 2 of the Community Earth System Model (CESM2). Using the CESM2 hierarchy and comparing to observations, we identify key moisture processes and related air-sea interactions that drive extreme precipitation events across different latitudes in Earth-like models and then generalize the analyses in aquaplanet configurations to highlight the most salient features. The analyses are applied to both present-day and global warming conditions to investigate how these fundamental mechanisms might change extreme precipitation events in the future climate.

Event-Triggered Adaptive Dynamic Programming for Continuous-Time Systems With Control Constraints.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2016-08-31

In this paper, an event-triggered near optimal control structure is developed for nonlinear continuous-time systems with control constraints. Due to the saturating actuators, a nonquadratic cost function is introduced and the Hamilton-Jacobi-Bellman (HJB) equation for constrained nonlinear continuous-time systems is formulated. In order to solve the HJB equation, an actor-critic framework is presented. The critic network is used to approximate the cost function and the action network is used to estimate the optimal control law. In addition, in the proposed method, the control signal is transmitted in an aperiodic manner to reduce the computational and the transmission cost. Both the networks are only updated at the trigger instants decided by the event-triggered condition. Detailed Lyapunov analysis is provided to guarantee that the closed-loop event-triggered system is ultimately bounded. Three case studies are used to demonstrate the effectiveness of the proposed method.

Windstorm Impact Reduction Implementation Plan

DTIC Science & Technology

2007-01-01

wind events, including hurricanes, tornadoes and straight line winds from thunderstorms. This information is repeated in brief during severe weather...event documentation and damage analyses. Better understanding of atmospheric dynamics of straight - line winds Wind observing systems and...Developed techniques for improved extreme wind speed maps Investigation of straight - line winds Wind speed and direction analysis for input to

Elastic body dynamics

NASA Technical Reports Server (NTRS)

Holder, B. W.

1981-01-01

Most of the structural dynamics resources allocated to the Space Shuttle are concentrated on the flight events which result in critical structural loads and/or minimum control stability margins. Since these events are primarily sub-orbital, the data base of interest to those involved in orbital experimentation is somewhat limited. A brief discussion of available data is given. Although estimates of peak acceleration levels and the associated frequency spectrum in the payload bay due to thrusting of the various control system thrusters were made, the actual levels and time histories must be based on updated structural math models and a detailed knowledge of the input forcing functions.

Mechanical stress and network structure drive protein dynamics during cytokinesis.

PubMed

Srivastava, Vasudha; Robinson, Douglas N

2015-03-02

Cell-shape changes associated with processes like cytokinesis and motility proceed on several-second timescales but are derived from molecular events, including protein-protein interactions, filament assembly, and force generation by molecular motors, all of which occur much faster [1-4]. Therefore, defining the dynamics of such molecular machinery is critical for understanding cell-shape regulation. In addition to signaling pathways, mechanical stresses also direct cytoskeletal protein accumulation [5-7]. A myosin-II-based mechanosensory system controls cellular contractility and shape during cytokinesis and under applied stress [6, 8]. In Dictyostelium, this system tunes myosin II accumulation by feedback through the actin network, particularly through the crosslinker cortexillin I. Cortexillin-binding IQGAPs are major regulators of this system. Here, we defined the short timescale dynamics of key cytoskeletal proteins during cytokinesis and under mechanical stress, using fluorescence recovery after photobleaching and fluorescence correlation spectroscopy, to examine the dynamic interplay between these proteins. Equatorially enriched proteins including cortexillin I, IQGAP2, and myosin II recovered much more slowly than actin and polar crosslinkers. The mobility of equatorial proteins was greatly reduced at the furrow compared to the interphase cortex, suggesting their stabilization during cytokinesis. This mobility shift did not arise from a single biochemical event, but rather from a global inhibition of protein dynamics by mechanical-stress-associated changes in the cytoskeletal structure. Mechanical tuning of contractile protein dynamics provides robustness to the cytoskeletal framework responsible for regulating cell shape and contributes to cytokinesis fidelity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

PubMed

Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

2016-12-08

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

A Systems Thinking approach to post-disaster restoration of maritime transportation systems

USGS Publications Warehouse

Lespier, Lizzette Pérez; Long, Suzanna K.; Shoberg, Thomas G.

2015-01-01

A Systems Thinking approach is used to examine elements of a maritime transportation system that are most likely to be impacted by an extreme event. The majority of the literature uses a high-level view that can fail to capture the damage at the sub-system elements. This work uses a system dynamics simulation for a better view and understanding of the Port of San Juan, Puerto Rico, as a whole system and uses Hurricane Georges (1998), as a representative disruptive event. The model focuses on the impacts of natural disasters at the sub-system level with a final goal of determining the sequence needed to restore an ocean-going port to its pre-event state. This work in progress details model development and outlines steps for using real-world information to assist maritime port manager planning and recommendations for best practices to mitigate disaster damage.

Dynamic photoelasticity by TDI imaging

NASA Astrophysics Data System (ADS)

Asundi, Anand K.; Sajan, M. R.

2001-06-01

High speed photographic system like the image rotation camera, the Cranz Schardin camera and the drum camera are typically used for the recording and visualization of dynamic events in stress analysis, fluid mechanics, etc. All these systems are fairly expensive and generally not simple to use. Furthermore they are all based on photographic film recording system requiring time consuming and tedious wet processing of the films. Digital cameras are replacing the conventional cameras, to certain extent in static experiments. Recently, there is lots of interest in development and modifying CCD architectures and recording arrangements for dynamic scenes analysis. Herein we report the use of a CCD camera operating in the Time Delay and Integration mode for digitally recording dynamic photoelastic stress patterns. Applications in strobe and streak photoelastic pattern recording and system limitations will be explained in the paper.

Nonlinear optics of fibre event horizons.

PubMed

Webb, Karen E; Erkintalo, Miro; Xu, Yiqing; Broderick, Neil G R; Dudley, John M; Genty, Goëry; Murdoch, Stuart G

2014-09-17

The nonlinear interaction of light in an optical fibre can mimic the physics at an event horizon. This analogue arises when a weak probe wave is unable to pass through an intense soliton, despite propagating at a different velocity. To date, these dynamics have been described in the time domain in terms of a soliton-induced refractive index barrier that modifies the velocity of the probe. Here we complete the physical description of fibre-optic event horizons by presenting a full frequency-domain description in terms of cascaded four-wave mixing between discrete single-frequency fields, and experimentally demonstrate signature frequency shifts using continuous wave lasers. Our description is confirmed by the remarkable agreement with experiments performed in the continuum limit, reached using ultrafast lasers. We anticipate that clarifying the description of fibre event horizons will significantly impact on the description of horizon dynamics and soliton interactions in photonics and other systems.

Flapping dynamics of a thin liquid sheet

NASA Astrophysics Data System (ADS)

Vadivukkarasan, M.; Kumaran, Dhivyaraja; Panchagnula, Mahesh; Multi-phase flow physics Group Team

2017-11-01

We attempt to delineate and describe the complete evolution of a thin soap film when air is blown through a nozzle in the normal direction. The sequence of events and its intrinsic dynamics are captured using high speed imaging. By careful observation, it was observed that multiple mechanisms occur in the same system and each event is triggered by an independent mechanism. The events include (a) flapping of a liquid sheet and pinching of the bubble, (b) onset of rupture on the liquid sheet, (c) formation of ligaments and (d) ejection of drops. From this study, it is shown that these events are predominantly governed by Kelvin-Helmholtz instability, Taylor - Culick law, Rayleigh-Taylor instability and capillary instability, respectively. The present experiments can be considered as an extension to the previous studies on soap films as well as thin flapping sheets which has direct relevance to coaxial atomizers used in aircraft applications.

Dynamics of pollutant indicators during flood events in a small river under strong anthropogenic pressures

NASA Astrophysics Data System (ADS)

Brion, Natacha; Carbonnel, Vincent; Elskens, Marc; Claeys, Philippe; Verbanck, Michel A.

2017-04-01

In densely populated regions, human activities profoundly modify natural water circulation as well as water quality, with increased hydrological risks (floods, droughts,…) and chemical hazards (untreated sewage releases, industrial pollution,…) as consequence. In order to assess water and pollutants dynamics and their mass-balance in strongly modified river system, it is important to take into account high flow events as a significant fraction of water and pollutants loads may occur during these short events which are generally underrepresented in classical mass balance studies. A good example of strongly modified river systems is the Zenne river in and around the city of Brussels (Belgium).The Zenne River (Belgium) is a rather small but dynamic rain fed river (about 10 m3/s in average) that is under the influence of strong contrasting anthropogenic pressures along its stretch. While the upstream part of its basin is rather characterized by agricultural land-use, urban and industrial areas dominate the downstream part. In particular, the city of Brussels (1.1M inhabitants) discharges in the Zenne River amounts of wastewater that are large compared to the natural riverine flow. In order to assess water and pollutants dynamics and their mass-balance in the Zenne hydrographic network, we followed water flows and concentrations of several water quality tracers during several flood episodes with an hourly frequency and at different locations along the stretch of the River. These parameters were chosen as indicators of a whole range of pollutions and anthropogenic activities. Knowledge of the high-frequency pollutants dynamics during floods is required for establishing accurate mass-balances of these elements. We thus report here the dynamics of selected parameters during entire flood events, from the baseline to the decreasing phase and at hourly frequency. Dynamics at contrasting locations, in agricultural or urban environments are compared. In particular, the importance of combined sewer overflows are evaluated and discussed. Results from this study were obtained in the framework of the OSIRIS research project (INNOVIRIS Anticipate 2015-2019).

In-situ Fluorometers Reveal High Frequency Dynamics In Dissolved Organic Matter For Urban Rivers

NASA Astrophysics Data System (ADS)

Croghan, D.; Bradley, C.; Khamis, K.; Hannah, D. M.; Sadler, J. P.; Van Loon, A.

2017-12-01

To-date Dissolved Organic Matter (DOM) dynamics have been quantified poorly in urban rivers, despite the substantial water quality issues linked to urbanisation. Research has been hindered by the low temporal resolution of observations and over-reliance on manual sampling which often fail to capture precipitation events and diurnal dynamics. High frequency data are essential to estimate more accurately DOM fluxes/loads and to understand DOM furnishing and transport processes. Recent advances in optical sensor technology, including field deployable in-situ fluorometers, are yielding new high resolution DOM information. However, no consensus regarding the monitoring resolution required for urban systems exists, with no studies monitoring at <15 min time steps. High-frequency monitoring (5 min resolution; 4 week duration) was conducted on a headwater urban stream in Birmingham, UK (N 52.447430 W -1.936715) to determine the optimum temporal resolution for characterization of DOM event dynamics. A through-flow GGNU-30 monitored wavelengths corresponding to tryptophan-like fluorescence (TLF; Peak T1) (Ex 285 nm/ Em 345 nm) and humic-like fluorescence (HLF; Peak C) (Ex 365 nm/Em 490 nm). The results suggest that at base flow TLF and HLF are relatively stable, though episodic DOM inputs can pulse through the system, which may be missed during lower temporal resolution monitoring. High temporal variation occurs during storm events in TLF and HLF intensity: TLF intensity is highest during the rising limb of the hydrograph and can rapidly decline thereafter, indicating the importance of fast flow-path and close proximity sources to TLF dynamics. HLF intensity tracks discharge more closely, but can also quickly decline during high flow events due to dilution effects. Furthermore, the ratio of TLF:HLF when derived at high-frequency provides a useful indication of the presence and type of organic effluents in stream, which aids in the identification of Combined Sewage Overflow releases. Our work highlights the need for future studies to utilise shorter temporal scales than previously used to monitor urban DOM dynamics. The application of higher frequency monitoring enables the identification of finer-scale patterns and subsequently aids in deciphering the sources and pathways controlling urban DOM dynamics.

Dynamics of biocide emissions from buildings in a suburban stormwater catchment - concentrations, mass loads and emission processes.

PubMed

Bollmann, Ulla E; Vollertsen, Jes; Carmeliet, Jan; Bester, Kai

2014-06-01

Biocides such as isothiazolinones, carbamates, triazines, phenylureas, azoles and others are used to protect the surfaces of buildings, e.g. painted or unpainted render or wood. These biocides can be mobilized from the materials if rainwater gets into contact with these buildings. Hence, these biocides will be found in rainwater runoff (stormwater) from buildings that is traditionally managed as "clean water" in stormwater sewer systems and often directly discharged into surface waters without further treatment. By means of a 9 month event-based high resolution sampling campaign the biocide emissions in a small suburban stormwater catchment were analysed and the emission dynamics throughout the single rain events were investigated. Five out of twelve of the rain events (peak events) proved significantly higher concentrations than the rest (average) for at least one compound. Highest median concentrations of 0.045 and 0.052 μg L(-1) were found for terbutryn and carbendazim, while the concentrations for isoproturon, diuron, N-octylisothiazolinone, benzoisothiazolinone, cybutryn, propiconazole, tebuconazole, and mecoprop were one order of magnitude lower. However, during the peak events the concentrations reached up to 1.8 and 0.3 μg L(-1) for terbutryn and carbendazim, respectively. Emissions of an averaged single family house into the stormwater sewer turned out to be 59 and 50 μg event(-1) house(-1) terbutryn and carbendazim, respectively. Emissions for the other biocides ranged from 0.1 to 11 μg event(-1) house(-1). Mass load analysis revealed that peak events contributed in single events as much to the emissions as 11 average events. However, the mass loads were highly dependent on the amounts of rainwater, i.e. the hydraulic flow in the receiving sewer pipe. The analysis of the emission dynamics showed first flush emissions only for single parameters in three events out of twelve. Generally biocides seemed to be introduced into the stormwater system rather continuously during the respective events than in the beginning of them. Mass flows during the events did correlate to driving rain, whereas mass loads neither correlated to the length or the intensity of rainfall nor the length of dry period. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of CCSDS DCT to Support Spacecraft Dynamic Events

NASA Technical Reports Server (NTRS)

Sidhwa, Anahita F

2011-01-01

This report discusses the development of Consultative Committee for Space Data Systems (CCSDS) Design Control Table (DCT) to support spacecraft dynamic events. The Consultative Committee for Space Data Systems (CCSDS) Design Control Table (DCT) is a versatile link calculation tool to analyze different kinds of radio frequency links. It started out as an Excel-based program, and is now being evolved into a Mathematica-based link analysis tool. The Mathematica platform offers a rich set of advanced analysis capabilities, and can be easily extended to a web-based architecture. Last year the CCSDS DCT's for the uplink, downlink, two-way, and ranging models were developed as well as the corresponding input and output interfaces. Another significant accomplishment is the integration of the NAIF SPICE library into the Mathematica computation platform.

Distinguishing signatures of determinism and stochasticity in spiking complex systems

PubMed Central

Aragoneses, Andrés; Rubido, Nicolás; Tiana-Alsina, Jordi; Torrent, M. C.; Masoller, Cristina

2013-01-01

We describe a method to infer signatures of determinism and stochasticity in the sequence of apparently random intensity dropouts emitted by a semiconductor laser with optical feedback. The method uses ordinal time-series analysis to classify experimental data of inter-dropout-intervals (IDIs) in two categories that display statistically significant different features. Despite the apparent randomness of the dropout events, one IDI category is consistent with waiting times in a resting state until noise triggers a dropout, and the other is consistent with dropouts occurring during the return to the resting state, which have a clear deterministic component. The method we describe can be a powerful tool for inferring signatures of determinism in the dynamics of complex systems in noisy environments, at an event-level description of their dynamics.

Spacecraft-to-Earth Communications for Juno and Mars Science Laboratory Critical Events

NASA Technical Reports Server (NTRS)

Soriano, Melissa; Finley, Susan; Jongeling, Andre; Fort, David; Goodhart, Charles; Rogstad, David; Navarro, Robert

2012-01-01

Deep Space communications typically utilize closed loop receivers and Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK). Critical spacecraft events include orbit insertion and entry, descent, and landing.---Low gain antennas--> low signal -to-noise-ratio.---High dynamics such as parachute deployment or spin --> Doppler shift. During critical events, open loop receivers and Multiple Frequency Shift Keying (MFSK) used. Entry, Descent, Landing (EDL) Data Analysis (EDA) system detects tones in real-time.

Simulating Large-Scale Earthquake Dynamic Rupture Scenarios On Natural Fault Zones Using the ADER-DG Method

NASA Astrophysics Data System (ADS)

Gabriel, Alice; Pelties, Christian

2014-05-01

In this presentation we will demonstrate the benefits of using modern numerical methods to support physic-based ground motion modeling and research. For this purpose, we utilize SeisSol an arbitrary high-order derivative Discontinuous Galerkin (ADER-DG) scheme to solve the spontaneous rupture problem with high-order accuracy in space and time using three-dimensional unstructured tetrahedral meshes. We recently verified the method in various advanced test cases of the 'SCEC/USGS Dynamic Earthquake Rupture Code Verification Exercise' benchmark suite, including branching and dipping fault systems, heterogeneous background stresses, bi-material faults and rate-and-state friction constitutive formulations. Now, we study the dynamic rupture process using 3D meshes of fault systems constructed from geological and geophysical constraints, such as high-resolution topography, 3D velocity models and fault geometries. Our starting point is a large scale earthquake dynamic rupture scenario based on the 1994 Northridge blind thrust event in Southern California. Starting from this well documented and extensively studied event, we intend to understand the ground-motion, including the relevant high frequency content, generated from complex fault systems and its variation arising from various physical constraints. For example, our results imply that the Northridge fault geometry favors a pulse-like rupture behavior.

Peptide kinetics from picoseconds to microseconds using boxed molecular dynamics: Power law rate coefficients in cyclisation reactions

NASA Astrophysics Data System (ADS)

Shalashilin, Dmitrii V.; Beddard, Godfrey S.; Paci, Emanuele; Glowacki, David R.

2012-10-01

Molecular dynamics (MD) methods are increasingly widespread, but simulation of rare events in complex molecular systems remains a challenge. We recently introduced the boxed molecular dynamics (BXD) method, which accelerates rare events, and simultaneously provides both kinetic and thermodynamic information. We illustrate how the BXD method may be used to obtain high-resolution kinetic data from explicit MD simulations, spanning picoseconds to microseconds. The method is applied to investigate the loop formation dynamics and kinetics of cyclisation for a range of polypeptides, and recovers a power law dependence of the instantaneous rate coefficient over six orders of magnitude in time, in good agreement with experimental observations. Analysis of our BXD results shows that this power law behaviour arises when there is a broad and nearly uniform spectrum of reaction rate coefficients. For the systems investigated in this work, where the free energy surfaces have relatively small barriers, the kinetics is very sensitive to the initial conditions: strongly non-equilibrium conditions give rise to power law kinetics, while equilibrium initial conditions result in a rate coefficient with only a weak dependence on time. These results suggest that BXD may offer us a powerful and general algorithm for describing kinetics and thermodynamics in chemical and biochemical systems.

The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Griffin, Lisa W.

2012-01-01

The Fluid Dynamics Branch's (ER42) at MSFC mission is to support NASA and other customers with discipline expertise to enable successful accomplishment of program/project goals. The branch is responsible for all aspects of the discipline of fluid dynamics, analysis and testing, applied to propulsion or propulsion-induced loads and environments, which includes the propellant delivery system, combustion devices, coupled systems, and launch and separation events. ER42 supports projects from design through development, and into anomaly and failure investigations. ER42 is committed to continually improving the state-of-its-practice to provide accurate, effective, and timely fluid dynamics assessments and in extending the state-of-the-art of the discipline.

GPS synchronized power system phase angle measurements

NASA Astrophysics Data System (ADS)

Wilson, Robert E.; Sterlina, Patrick S.

1994-09-01

This paper discusses the use of Global Positioning System (GPS) synchronized equipment for the measurement and analysis of key power system quantities. Two GPS synchronized phasor measurement units (PMU) were installed before testing. It was indicated that PMUs recorded the dynamic response of the power system phase angles when the northern California power grid was excited by the artificial short circuits. Power system planning engineers perform detailed computer generated simulations of the dynamic response of the power system to naturally occurring short circuits. The computer simulations use models of transmission lines, transformers, circuit breakers, and other high voltage components. This work will compare computer simulations of the same event with field measurement.

Nonlinear Control and Discrete Event Systems

NASA Technical Reports Server (NTRS)

Meyer, George; Null, Cynthia H. (Technical Monitor)

1995-01-01

As the operation of large systems becomes ever more dependent on extensive automation, the need for an effective solution to the problem of design and validation of the underlying software becomes more critical. Large systems possesses much detailed structure, typically hierarchical, and they are hybrid. Information processing at the top of the hierarchy is by means of formal logic and sentences; on the bottom it is by means of simple scalar differential equations and functions of time; and in the middle it is by an interacting mix of nonlinear multi-axis differential equations and automata, and functions of time and discrete events. The lecture will address the overall problem as it relates to flight vehicle management, describe the middle level, and offer a design approach that is based on Differential Geometry and Discrete Event Dynamic Systems Theory.

Dynamic Monte Carlo description of thermal desorption processes

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1994-07-01

The applicability of the dynamic Monte Carlo method of Fichthorn and Weinberg, in which the time evolution of a system is described in terms of the absolute number of different microscopic possible events and their associated transition rates, is discussed for the case of thermal desorption simulations. It is shown that the definition of the time increment at each successful event leads naturally to the macroscopic differential equation of desorption, in the case of simple first- and second-order processes in which the only possible events are desorption and diffusion. This equivalence is numerically demonstrated for a second-order case. In the sequence, the equivalence of this method with the Monte Carlo method of Sales and Zgrablich for more complex desorption processes, allowing for lateral interactions between adsorbates, is shown, even though the dynamic Monte Carlo method does not bear their limitation of a rapid surface diffusion condition, thus being able to describe a more complex ``kinetics'' of surface reactive processes, and therefore be applied to a wider class of phenomena, such as surface catalysis.

Development and validation of a 48-target analytical method for high-throughput monitoring of genetically modified organisms.

PubMed

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-05

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

Development and Validation of A 48-Target Analytical Method for High-throughput Monitoring of Genetically Modified Organisms

PubMed Central

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-01

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection. PMID:25556930

Structural self-assembly and avalanchelike dynamics in locally adaptive networks

NASA Astrophysics Data System (ADS)

Gräwer, Johannes; Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

2015-07-01

Transport networks play a key role across four realms of eukaryotic life: slime molds, fungi, plants, and animals. In addition to the developmental algorithms that build them, many also employ adaptive strategies to respond to stimuli, damage, and other environmental changes. We model these adapting network architectures using a generic dynamical system on weighted graphs and find in simulation that these networks ultimately develop a hierarchical organization of the final weighted architecture accompanied by the formation of a system-spanning backbone. In addition, we find that the long term equilibration dynamics exhibit behavior reminiscent of glassy systems characterized by long periods of slow changes punctuated by bursts of reorganization events.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Heinrich Events as an integral part of glacial-interglacial climate dynamics

NASA Astrophysics Data System (ADS)

Barker, S.; Knorr, G.; Zhang, X.; Gong, X.; Lohmann, G.; Bazin, L.

2017-12-01

Since their discovery in the 1980s Heinrich Events have provided a playground for climate scientists trying to understand the interactions between ice sheets and the ocean. Subsequently it has become clear that these interactions extend to almost all parts of the global climate system, from temperature, winds and rainfall to deep ocean currents and atmospheric CO2. Furthermore it remains unclear as to whether these dramatic events are a cause or consequence (or both) of regional to global perturbations in a range of parameters, including meridional overturning circulation within the Atlantic. Here we will discuss some of these aspects to highlight ongoing and future research related to Heinrich events and abrupt change more generally. We will discuss some of the possible triggers for H-events, including abrupt versus more gradual forcing mechanisms and conversely the potential influence of such events on the wider climate system, including deglacial climate change.

Generating functions and stability study of multivariate self-excited epidemic processes

NASA Astrophysics Data System (ADS)

Saichev, A. I.; Sornette, D.

2011-09-01

We present a stability study of the class of multivariate self-excited Hawkes point processes, that can model natural and social systems, including earthquakes, epileptic seizures and the dynamics of neuron assemblies, bursts of exchanges in social communities, interactions between Internet bloggers, bank network fragility and cascading of failures, national sovereign default contagion, and so on. We present the general theory of multivariate generating functions to derive the number of events over all generations of various types that are triggered by a mother event of a given type. We obtain the stability domains of various systems, as a function of the topological structure of the mutual excitations across different event types. We find that mutual triggering tends to provide a significant extension of the stability (or subcritical) domain compared with the case where event types are decoupled, that is, when an event of a given type can only trigger events of the same type.

HSC Foundation

MedlinePlus

... and social components. The Foundation works with a dynamic network of partners from across the country who ... Foundation Foundation Programs Publications Foundation Partners About the System Calendar of Events News Social Media Copyright © 2016 ...

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

Trajectory-probed instability and statistics of desynchronization events in coupled chaotic systems

NASA Astrophysics Data System (ADS)

de Oliveira, Gilson F.; Chevrollier, Martine; Passerat de Silans, Thierry; Oriá, Marcos; de Souza Cavalcante, Hugo L. D.

2015-11-01

Complex systems, such as financial markets, earthquakes, and neurological networks, exhibit extreme events whose mechanisms of formation are not still completely understood. These mechanisms may be identified and better studied in simpler systems with dynamical features similar to the ones encountered in the complex system of interest. For instance, sudden and brief departures from the synchronized state observed in coupled chaotic systems were shown to display non-normal statistical distributions similar to events observed in the complex systems cited above. The current hypothesis accepted is that these desynchronization events are influenced by the presence of unstable object(s) in the phase space of the system. Here, we present further evidence that the occurrence of large events is triggered by the visitation of the system's phase-space trajectory to the vicinity of these unstable objects. In the system studied here, this visitation is controlled by a single parameter, and we exploit this feature to observe the effect of the visitation rate in the overall instability of the synchronized state. We find that the probability of escapes from the synchronized state and the size of those desynchronization events are enhanced in attractors whose shapes permit the chaotic trajectories to approach the region of strong instability. This result shows that the occurrence of large events requires not only a large local instability to amplify noise, or to amplify the effect of parameter mismatch between the coupled subsystems, but also that the trajectories of the system wander close to this local instability.

78 FR 64916 - Application(s) for Duty-Free Entry of Scientific Instruments

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-30

...., light to heat), crystallization, melting, phase transformations, fracture, and other dynamic events. The... Sciences University, 1120 15th Street, Augusta, GA 30912. Instrument: Imaging System/Digital Microscope... the instrument include fast wavelength change, a dichromotome system, and two different light sources...

Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfurfural tolerance for ethanologenic yeast.

PubMed

Song, M; Ouyang, Z; Liu, Z L

2009-05-01

Composed of linear difference equations, a discrete dynamical system (DDS) model was designed to reconstruct transcriptional regulations in gene regulatory networks (GRNs) for ethanologenic yeast Saccharomyces cerevisiae in response to 5-hydroxymethylfurfural (HMF), a bioethanol conversion inhibitor. The modelling aims at identification of a system of linear difference equations to represent temporal interactions among significantly expressed genes. Power stability is imposed on a system model under the normal condition in the absence of the inhibitor. Non-uniform sampling, typical in a time-course experimental design, is addressed by a log-time domain interpolation. A statistically significant DDS model of the yeast GRN derived from time-course gene expression measurements by exposure to HMF, revealed several verified transcriptional regulation events. These events implicate Yap1 and Pdr3, transcription factors consistently known for their regulatory roles by other studies or postulated by independent sequence motif analysis, suggesting their involvement in yeast tolerance and detoxification of the inhibitor.

Dynamic Analytics-Driven Assessment of Vulnerabilities and Exploitation

DTIC Science & Technology

2016-07-15

integration with big data technologies such as Hadoop , nor does it natively support exporting of events to external relational databases. OSSIM supports...power of big data analytics to determine correlations and temporal causality among vulnerabilities and cyber events. The vulnerability dependencies...via the SCAPE (formerly known as LLCySA [6]). This is illustrated as a big data cyber analytic system architecture in

Hard Sphere Simulation by Event-Driven Molecular Dynamics: Breakthrough, Numerical Difficulty, and Overcoming the issues

NASA Astrophysics Data System (ADS)

Isobe, Masaharu

Hard sphere/disk systems are among the simplest models and have been used to address numerous fundamental problems in the field of statistical physics. The pioneering numerical works on the solid-fluid phase transition based on Monte Carlo (MC) and molecular dynamics (MD) methods published in 1957 represent historical milestones, which have had a significant influence on the development of computer algorithms and novel tools to obtain physical insights. This chapter addresses the works of Alder's breakthrough regarding hard sphere/disk simulation: (i) event-driven molecular dynamics, (ii) long-time tail, (iii) molasses tail, and (iv) two-dimensional melting/crystallization. From a numerical viewpoint, there are serious issues that must be overcome for further breakthrough. Here, we present a brief review of recent progress in this area.

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

A new type of tri-axial accelerometers with high dynamic range MEMS for earthquake early warning

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Chen, Yang; Chen, Quansheng; Yang, Jiansi; Wang, Hongti; Zhu, Xiaoyi; Xu, Zhiqiang; Zheng, Yu

2017-03-01

Earthquake Early Warning System (EEWS) has shown its efficiency for earthquake damage mitigation. As the progress of low-cost Micro Electro Mechanical System (MEMS), many types of MEMS-based accelerometers have been developed and widely used in deploying large-scale, dense seismic networks for EEWS. However, the noise performance of these commercially available MEMS is still insufficient for weak seismic signals, leading to the large scatter of early-warning parameters estimation. In this study, we developed a new type of tri-axial accelerometer based on high dynamic range MEMS with low noise level using for EEWS. It is a MEMS-integrated data logger with built-in seismological processing. The device is built on a custom-tailored Linux 2.6.27 operating system and the method for automatic detecting seismic events is STA/LTA algorithms. When a seismic event is detected, peak ground parameters of all data components will be calculated at an interval of 1 s, and τc-Pd values will be evaluated using the initial 3 s of P wave. These values will then be organized as a trigger packet actively sent to the processing center for event combining detection. The output data of all three components are calibrated to sensitivity 500 counts/cm/s2. Several tests and a real field test deployment were performed to obtain the performances of this device. The results show that the dynamic range can reach 98 dB for the vertical component and 99 dB for the horizontal components, and majority of bias temperature coefficients are lower than 200 μg/°C. In addition, the results of event detection and real field deployment have shown its capabilities for EEWS and rapid intensity reporting.

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

A Black Swan and Sub-continental Scale Dynamics in Humid, Late-Holocene Broadleaf Forests

NASA Astrophysics Data System (ADS)

Pederson, N.; Dyer, J.; McEwan, R.; Hessl, A. E.; Mock, C. J.; Orwig, D.; Rieder, H. E.; Cook, B. I.

2012-12-01

In humid regions with dense broadleaf-dominated forests where gap-dynamics is the prevailing disturbance regime, paleoecological evidence shows regional-scale changes in forest composition associated with climatic change. To investigate the potential for regional events in late-Holocene forests, we use tree-ring data from 76 populations covering 840,000 km2 and 5.3k tree recruitment dates spanning 1.4 million km2 in the eastern US to investigate the occurrence of simultaneous forest dynamics across a humid region. We compare regional forest dynamics with an independent set of annually-resolved tree ring record of hydroclimate to examine whether climate dynamics might drive forest dynamics in this humid region. In forests where light availability is an important limitation for tree recruitment, we document a pulse of tree recruitment during the mid- to late-1600s across the eastern US. This pulse, which can be inferred as large-scale canopy opening, occurred during an era that multiple proxies indicate as extended drought between two intense pluvial. Principal component analysis of the 76 populations indicates a step-change increase in average ring width during the late-1770s resembling a potential canopy accession event over 42,800 km2 of the southeastern US. Growth-release analysis of populations loading strongly on this eigenvector indicates severe canopy disturbance from 1775-1779 that peaked in 1776. The 1776 event follows a period with extended droughts and severe large-scale frost event. We hypothesize these climatic events lead to elevated tree mortality in the late-1770s and canopy accession for understory trees. Superposed epoch analysis reveals that spikes of elevated canopy disturbance from 1685-1850 CE are significantly associated with drought. Extreme value theory statistics indicates the 1776 event lies beyond the 99.9 quantile and nearly 7 sigmas above the 1685-1850 mean rate of disturbance. The time-series of canopy disturbance from 1685-1850 is so poorly described by a Gaussian distribution that it can be considered 'heavy tailed'. Preliminary results show that disturbance events that affect >3-5% of the trees in our dataset occur approximately every 200 years. The most extreme rates (>5%) occur approximately every 500-1000 years. These statistics indicate that the 1775-1779 heavy-tail event can also be considered a 'Black Swan', the rare event that has the potential to alter a system's trajectory further than common events. Our results challenge traditional views regarding characteristic disturbance regime in humid temperate forests, and speak to the importance of punctuated climatic events in shaping forest structure for centuries. Such an understanding is critical given the potential of more frequent extreme climatic events in the future.

Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

NASA Astrophysics Data System (ADS)

Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

2012-09-01

The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

Dynamic Task Optimization in Remote Diabetes Monitoring Systems.

PubMed

Suh, Myung-Kyung; Woodbridge, Jonathan; Moin, Tannaz; Lan, Mars; Alshurafa, Nabil; Samy, Lauren; Mortazavi, Bobak; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid

2012-09-01

Diabetes is the seventh leading cause of death in the United States, but careful symptom monitoring can prevent adverse events. A real-time patient monitoring and feedback system is one of the solutions to help patients with diabetes and their healthcare professionals monitor health-related measurements and provide dynamic feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the domain of remote health monitoring. This paper presents a wireless health project (WANDA) that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. The WANDA dynamic task management function applies data analytics in real-time to discretize continuous features, applying data clustering and association rule mining techniques to manage a sliding window size dynamically and to prioritize required user tasks. The developed algorithm minimizes the number of daily action items required by patients with diabetes using association rules that satisfy a minimum support, confidence and conditional probability thresholds. Each of these tasks maximizes information gain, thereby improving the overall level of patient adherence and satisfaction. Experimental results from applying EM-based clustering and Apriori algorithms show that the developed algorithm can predict further events with higher confidence levels and reduce the number of user tasks by up to 76.19 %.

Dynamic Task Optimization in Remote Diabetes Monitoring Systems

PubMed Central

Suh, Myung-kyung; Woodbridge, Jonathan; Moin, Tannaz; Lan, Mars; Alshurafa, Nabil; Samy, Lauren; Mortazavi, Bobak; Ghasemzadeh, Hassan; Bui, Alex; Ahmadi, Sheila; Sarrafzadeh, Majid

2016-01-01

Diabetes is the seventh leading cause of death in the United States, but careful symptom monitoring can prevent adverse events. A real-time patient monitoring and feedback system is one of the solutions to help patients with diabetes and their healthcare professionals monitor health-related measurements and provide dynamic feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the domain of remote health monitoring. This paper presents a wireless health project (WANDA) that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. The WANDA dynamic task management function applies data analytics in real-time to discretize continuous features, applying data clustering and association rule mining techniques to manage a sliding window size dynamically and to prioritize required user tasks. The developed algorithm minimizes the number of daily action items required by patients with diabetes using association rules that satisfy a minimum support, confidence and conditional probability thresholds. Each of these tasks maximizes information gain, thereby improving the overall level of patient adherence and satisfaction. Experimental results from applying EM-based clustering and Apriori algorithms show that the developed algorithm can predict further events with higher confidence levels and reduce the number of user tasks by up to 76.19 %. PMID:27617297

Karst aquifer characterization using geophysical remote sensing of dynamic recharge events

NASA Astrophysics Data System (ADS)

Grapenthin, R.; Bilek, S. L.; Luhmann, A. J.

2017-12-01

Geophysical monitoring techniques, long used to make significant advances in a wide range of deeper Earth science disciplines, are now being employed to track surficial processes such as landslide, glacier, and river flow. Karst aquifers are another important hydrologic resource that can benefit from geophysical remote sensing, as this monitoring allows for safe, noninvasive karst conduit measurements. Conduit networks are typically poorly constrained, let alone the processes that occur within them. Geophysical monitoring can also provide a regionally integrated analysis to characterize subsurface architecture and to understand the dynamics of flow and recharge processes in karst aquifers. Geophysical signals are likely produced by several processes during recharge events in karst aquifers. For example, pressure pulses occur when water enters conduits that are full of water, and experiments suggest seismic signals result from this process. Furthermore, increasing water pressure in conduits during recharge events increases the load applied to conduit walls, which deforms the surrounding rock to yield measureable surface displacements. Measureable deformation should also occur with mass loading, with subsidence and rebound signals associated with increases and decreases of water mass stored in the aquifer, respectively. Additionally, geophysical signals will likely arise with turbulent flow and pore pressure change in the rock surrounding conduits. Here we present seismic data collected during a pilot study of controlled and natural recharge events in a karst aquifer system near Bear Spring, near Eyota, MN, USA as well as preliminary model results regarding the processes described above. In addition, we will discuss an upcoming field campaign where we will use seismometers, tiltmeters, and GPS instruments to monitor for recharge-induced responses in a FL, USA karst system with existing cave maps, coupling these geophysical observations with hydrologic and meteorologic data to map and characterize conduits and other features of the larger karst system and to monitor subsurface flow dynamics during recharge events.

A Hardware Platform for Characterizing and Validating 1-Dimensional Optical Systems

DTIC Science & Technology

2014-09-01

principle laboratory experiments, a bread -board sensor and data collection system was created to gather fuze data to postprocess after the event...merely differentiates this bistable memory category from dynamic random access memory [RAM], which must be periodically refreshed to retain data.) A

High-speed atomic force microscopy combined with inverted optical microscopy for studying cellular events

PubMed Central

Suzuki, Yuki; Sakai, Nobuaki; Yoshida, Aiko; Uekusa, Yoshitsugu; Yagi, Akira; Imaoka, Yuka; Ito, Shuichi; Karaki, Koichi; Takeyasu, Kunio

2013-01-01

A hybrid atomic force microscopy (AFM)-optical fluorescence microscopy is a powerful tool for investigating cellular morphologies and events. However, the slow data acquisition rates of the conventional AFM unit of the hybrid system limit the visualization of structural changes during cellular events. Therefore, high-speed AFM units equipped with an optical/fluorescence detection device have been a long-standing wish. Here we describe the implementation of high-speed AFM coupled with an optical fluorescence microscope. This was accomplished by developing a tip-scanning system, instead of a sample-scanning system, which operates on an inverted optical microscope. This novel device enabled the acquisition of high-speed AFM images of morphological changes in individual cells. Using this instrument, we conducted structural studies of living HeLa and 3T3 fibroblast cell surfaces. The improved time resolution allowed us to image dynamic cellular events. PMID:23823461

High-speed atomic force microscopy combined with inverted optical microscopy for studying cellular events.

PubMed

Suzuki, Yuki; Sakai, Nobuaki; Yoshida, Aiko; Uekusa, Yoshitsugu; Yagi, Akira; Imaoka, Yuka; Ito, Shuichi; Karaki, Koichi; Takeyasu, Kunio

2013-01-01

A hybrid atomic force microscopy (AFM)-optical fluorescence microscopy is a powerful tool for investigating cellular morphologies and events. However, the slow data acquisition rates of the conventional AFM unit of the hybrid system limit the visualization of structural changes during cellular events. Therefore, high-speed AFM units equipped with an optical/fluorescence detection device have been a long-standing wish. Here we describe the implementation of high-speed AFM coupled with an optical fluorescence microscope. This was accomplished by developing a tip-scanning system, instead of a sample-scanning system, which operates on an inverted optical microscope. This novel device enabled the acquisition of high-speed AFM images of morphological changes in individual cells. Using this instrument, we conducted structural studies of living HeLa and 3T3 fibroblast cell surfaces. The improved time resolution allowed us to image dynamic cellular events.

Dynamic burstiness of word-occurrence and network modularity in textbook systems

NASA Astrophysics Data System (ADS)

Cui, Xue-Mei; Yoon, Chang No; Youn, Hyejin; Lee, Sang Hoon; Jung, Jean S.; Han, Seung Kee

2017-12-01

We show that the dynamic burstiness of word occurrence in textbook systems is attributed to the modularity of the word association networks. At first, a measure of dynamic burstiness is introduced to quantify burstiness of word occurrence in a textbook. The advantage of this measure is that the dynamic burstiness is decomposable into two contributions: one coming from the inter-event variance and the other from the memory effects. Comparing network structures of physics textbook systems with those of surrogate random textbooks without the memory or variance effects are absent, we show that the network modularity increases systematically with the dynamic burstiness. The intra-connectivity of individual word representing the strength of a tie with which a node is bound to a module accordingly increases with the dynamic burstiness, suggesting individual words with high burstiness are strongly bound to one module. Based on the frequency and dynamic burstiness, physics terminology is classified into four categories: fundamental words, topical words, special words, and common words. In addition, we test the correlation between the dynamic burstiness of word occurrence and network modularity using a two-state model of burst generation.

Oscillators and relaxation phenomena in Pleistocene climate theory

PubMed Central

Crucifix, Michel

2012-01-01

Ice sheets appeared in the northern hemisphere around 3 Ma (million years) ago and glacial–interglacial cycles have paced Earth's climate since then. Superimposed on these long glacial cycles comes an intricate pattern of millennial and sub-millennial variability, including Dansgaard–Oeschger and Heinrich events. There are numerous theories about these oscillations. Here, we review a number of them in order to draw a parallel between climatic concepts and dynamical system concepts, including, in particular, the relaxation oscillator, excitability, slow–fast dynamics and homoclinic orbits. Namely, almost all theories of ice ages reviewed here feature a phenomenon of synchronization between internal climate dynamics and astronomical forcing. However, these theories differ in their bifurcation structure and this has an effect on the way the ice age phenomenon could grow 3 Ma ago. All theories on rapid events reviewed here rely on the concept of a limit cycle excited by changes in the surface freshwater balance of the ocean. The article also reviews basic effects of stochastic fluctuations on these models, including the phenomenon of phase dispersion, shortening of the limit cycle and stochastic resonance. It concludes with a more personal statement about the potential for inference with simple stochastic dynamical systems in palaeoclimate science. PMID:22291227

Use of Synchronized Phasor Measurements for Model Validation in ERCOT

NASA Astrophysics Data System (ADS)

Nuthalapati, Sarma; Chen, Jian; Shrestha, Prakash; Huang, Shun-Hsien; Adams, John; Obadina, Diran; Mortensen, Tim; Blevins, Bill

2013-05-01

This paper discusses experiences in the use of synchronized phasor measurement technology in Electric Reliability Council of Texas (ERCOT) interconnection, USA. Implementation of synchronized phasor measurement technology in the region is a collaborative effort involving ERCOT, ONCOR, AEP, SHARYLAND, EPG, CCET, and UT-Arlington. As several phasor measurement units (PMU) have been installed in ERCOT grid in recent years, phasor data with the resolution of 30 samples per second is being used to monitor power system status and record system events. Post-event analyses using recorded phasor data have successfully verified ERCOT dynamic stability simulation studies. Real time monitoring software "RTDMS"® enables ERCOT to analyze small signal stability conditions by monitoring the phase angles and oscillations. The recorded phasor data enables ERCOT to validate the existing dynamic models of conventional and/or wind generator.

Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Jun; Stanley, H. Eugene

2018-02-01

To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.

Fractal analysis of GPS time series for early detection of disastrous seismic events

NASA Astrophysics Data System (ADS)

Filatov, Denis M.; Lyubushin, Alexey A.

2017-03-01

A new method of fractal analysis of time series for estimating the chaoticity of behaviour of open stochastic dynamical systems is developed. The method is a modification of the conventional detrended fluctuation analysis (DFA) technique. We start from analysing both methods from the physical point of view and demonstrate the difference between them which results in a higher accuracy of the new method compared to the conventional DFA. Then, applying the developed method to estimate the measure of chaoticity of a real dynamical system - the Earth's crust, we reveal that the latter exhibits two distinct mechanisms of transition to a critical state: while the first mechanism has already been known due to numerous studies of other dynamical systems, the second one is new and has not previously been described. Using GPS time series, we demonstrate efficiency of the developed method in identification of critical states of the Earth's crust. Finally we employ the method to solve a practically important task: we show how the developed measure of chaoticity can be used for early detection of disastrous seismic events and provide a detailed discussion of the numerical results, which are shown to be consistent with outcomes of other researches on the topic.

Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

High-speed extended-term time-domain simulation for online cascading analysis of power system

NASA Astrophysics Data System (ADS)

Fu, Chuan

A high-speed extended-term (HSET) time domain simulator (TDS), intended to become a part of an energy management system (EMS), has been newly developed for use in online extended-term dynamic cascading analysis of power systems. HSET-TDS includes the following attributes for providing situational awareness of high-consequence events: (i) online analysis, including n-1 and n-k events, (ii) ability to simulate both fast and slow dynamics for 1-3 hours in advance, (iii) inclusion of rigorous protection-system modeling, (iv) intelligence for corrective action ID, storage, and fast retrieval, and (v) high-speed execution. Very fast on-line computational capability is the most desired attribute of this simulator. Based on the process of solving algebraic differential equations describing the dynamics of power system, HSET-TDS seeks to develop computational efficiency at each of the following hierarchical levels, (i) hardware, (ii) strategies, (iii) integration methods, (iv) nonlinear solvers, and (v) linear solver libraries. This thesis first describes the Hammer-Hollingsworth 4 (HH4) implicit integration method. Like the trapezoidal rule, HH4 is symmetrically A-Stable but it possesses greater high-order precision (h4 ) than the trapezoidal rule. Such precision enables larger integration steps and therefore improves simulation efficiency for variable step size implementations. This thesis provides the underlying theory on which we advocate use of HH4 over other numerical integration methods for power system time-domain simulation. Second, motivated by the need to perform high speed extended-term time domain simulation (HSET-TDS) for on-line purposes, this thesis presents principles for designing numerical solvers of differential algebraic systems associated with power system time-domain simulation, including DAE construction strategies (Direct Solution Method), integration methods(HH4), nonlinear solvers(Very Dishonest Newton), and linear solvers(SuperLU). We have implemented a design appropriate for HSET-TDS, and we compare it to various solvers, including the commercial grade PSSE program, with respect to computational efficiency and accuracy, using as examples the New England 39 bus system, the expanded 8775 bus system, and PJM 13029 buses system. Third, we have explored a stiffness-decoupling method, intended to be part of parallel design of time domain simulation software for super computers. The stiffness-decoupling method is able to combine the advantages of implicit methods (A-stability) and explicit method(less computation). With the new stiffness detection method proposed herein, the stiffness can be captured. The expanded 975 buses system is used to test simulation efficiency. Finally, several parallel strategies for super computer deployment to simulate power system dynamics are proposed and compared. Design A partitions the task via scale with the stiffness decoupling method, waveform relaxation, and parallel linear solver. Design B partitions the task via the time axis using a highly precise integration method, the Kuntzmann-Butcher Method - order 8 (KB8). The strategy of partitioning events is designed to partition the whole simulation via the time axis through a simulated sequence of cascading events. For all strategies proposed, a strategy of partitioning cascading events is recommended, since the sub-tasks for each processor are totally independent, and therefore minimum communication time is needed.

Hybrid Cascading Outage Analysis of Extreme Events with Optimized Corrective Actions

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

Vallem, Mallikarjuna R.; Vyakaranam, Bharat GNVSR; Holzer, Jesse T.

2017-10-19

Power system are vulnerable to extreme contingencies (like an outage of a major generating substation) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Some cascading outages are seen within minutes following a major contingency, which may not be captured exclusively using the dynamic simulation of the power system. The utilities plan for contingencies either based on dynamic or steady state analysis separately which may not accurately capture the impact of one process on the other. We address this gap in cascading outage analysis bymore » developing Dynamic Contingency Analysis Tool (DCAT) that can analyze hybrid dynamic and steady state behavior of the power system, including protection system models in dynamic simulations, and simulating corrective actions in post-transient steady state conditions. One of the important implemented steady state processes is to mimic operator corrective actions to mitigate aggravated states caused by dynamic cascading. This paper presents an Optimal Power Flow (OPF) based formulation for selecting corrective actions that utility operators can take during major contingency and thus automate the hybrid dynamic-steady state cascading outage process. The improved DCAT framework with OPF based corrective actions is demonstrated on IEEE 300 bus test system.« less

On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\\infty}$ Control.

PubMed

Wang, Ding; Mu, Chaoxu; Liu, Derong; Ma, Hongwen

2018-04-01

In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

Predictability of rogue events.

PubMed

Birkholz, Simon; Brée, Carsten; Demircan, Ayhan; Steinmeyer, Günter

2015-05-29

Using experimental data from three different rogue wave supporting systems, determinism, and predictability of the underlying dynamics are evaluated with methods of nonlinear time series analysis. We included original records from the Draupner platform in the North Sea as well as time series from two optical systems in our analysis. One of the latter was measured in the infrared tail of optical fiber supercontinua, the other in the fluence profiles of multifilaments. All three data sets exhibit extreme-value statistics and exceed the significant wave height in the respective system by a factor larger than 2. Nonlinear time series analysis indicates a different degree of determinism in the systems. The optical fiber scenario is found to be driven by quantum noise whereas rogue waves emerge as a consequence of turbulence in the others. With the large number of rogue events observed in the multifilament system, we can systematically explore the predictability of such events in a turbulent system. We observe that rogue events do not necessarily appear without a warning, but are often preceded by a short phase of relative order. This surprising finding sheds some new light on the fascinating phenomenon of rogue waves.

The excitation and characteristic frequency of the long-period volcanic event: An approach based on an inhomogeneous autoregressive model of a linear dynamic system

USGS Publications Warehouse

Nakano, M.; Kumagai, H.; Kumazawa, M.; Yamaoka, K.; Chouet, B.A.

1998-01-01

We present a method to quantify the source excitation function and characteristic frequencies of long-period volcanic events. The method is based on an inhomogeneous autoregressive (AR) model of a linear dynamic system, in which the excitation is assumed to be a time-localized function applied at the beginning of the event. The tail of an exponentially decaying harmonic waveform is used to determine the characteristic complex frequencies of the event by the Sompi method. The excitation function is then derived by operating an AR filter constructed from the characteristic frequencies to the entire seismogram of the event, including the inhomogeneous part of the signal. We apply this method to three long-period events at Kusatsu-Shirane Volcano, central Japan, whose waveforms display simple decaying monochromatic oscillations except for the beginning of the events. We recover time-localized excitation functions lasting roughly 1 s at the start of each event and find that the estimated functions are very similar to each other at all the stations of the seismic network for each event. The phases of the characteristic oscillations referred to the estimated excitation function fall within a narrow range for almost all the stations. These results strongly suggest that the excitation and mode of oscillation are both dominated by volumetric change components. Each excitation function starts with a pronounced dilatation consistent with a sudden deflation of the volumetric source which may be interpreted in terms of a choked-flow transport mechanism. The frequency and Q of the characteristic oscillation both display a temporal evolution from event to event. Assuming a crack filled with bubbly water as seismic source for these events, we apply the Van Wijngaarden-Papanicolaou model to estimate the acoustic properties of the bubbly liquid and find that the observed changes in the frequencies and Q are consistently explained by a temporal change in the radii of the bubbles characterizing the bubbly water in the crack.

Selective attention in multi-chip address-event systems.

PubMed

Bartolozzi, Chiara; Indiveri, Giacomo

2009-01-01

Selective attention is the strategy used by biological systems to cope with the inherent limits in their available computational resources, in order to efficiently process sensory information. The same strategy can be used in artificial systems that have to process vast amounts of sensory data with limited resources. In this paper we present a neuromorphic VLSI device, the "Selective Attention Chip" (SAC), which can be used to implement these models in multi-chip address-event systems. We also describe a real-time sensory-motor system, which integrates the SAC with a dynamic vision sensor and a robotic actuator. We present experimental results from each component in the system, and demonstrate how the complete system implements a real-time stimulus-driven selective attention model.

VLSI Implementation of a 2.8 Gevent/s Packet-Based AER Interface with Routing and Event Sorting Functionality

PubMed Central

Scholze, Stefan; Schiefer, Stefan; Partzsch, Johannes; Hartmann, Stephan; Mayr, Christian Georg; Höppner, Sebastian; Eisenreich, Holger; Henker, Stephan; Vogginger, Bernhard; Schüffny, Rene

2011-01-01

State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike-based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behavior of neuromorphic benchmarks. The specialized, dedicated address-event-representation communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA) delivers a factor 25–50 more event transmission rate than other current neuromorphic communication infrastructures. PMID:22016720

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

PubMed Central

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control.

PubMed

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

"Going solid": a model of system dynamics and consequences for patient safety

PubMed Central

Cook, R; Rasmussen, J

2005-01-01



 Rather than being a static property of hospitals and other healthcare facilities, safety is dynamic and often on short time scales. In the past most healthcare delivery systems were loosely coupled—that is, activities and conditions in one part of the system had only limited effect on those elsewhere. Loose coupling allowed the system to buffer many conditions such as short term surges in demand. Modern management techniques and information systems have allowed facilities to reduce inefficiencies in operation. One side effect is the loss of buffers that previously accommodated demand surges. As a result, situations occur in which activities in one area of the hospital become critically dependent on seemingly insignificant events in seemingly distant areas. This tight coupling condition is called "going solid". Rasmussen's dynamic model of risk and safety can be used to formulate a model of patient safety dynamics that includes "going solid" and its consequences. Because the model addresses the dynamic aspects of safety, it is particularly suited to understanding current conditions in modern healthcare delivery and the way these conditions may lead to accidents. PMID:15805459

Study of an External Neutron Source for an Accelerator-Driven System using the PHITS Code

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

Sugawara, Takanori; Iwasaki, Tomohiko; Chiba, Takashi

A code system for the Accelerator Driven System (ADS) has been under development for analyzing dynamic behaviors of a subcritical core coupled with an accelerator. This code system named DSE (Dynamics calculation code system for a Subcritical system with an External neutron source) consists of an accelerator part and a reactor part. The accelerator part employs a database, which is calculated by using PHITS, for investigating the effect related to the accelerator such as the changes of beam energy, beam diameter, void generation, and target level. This analysis method using the database may introduce some errors into dynamics calculations sincemore » the neutron source data derived from the database has some errors in fitting or interpolating procedures. In this study, the effects of various events are investigated to confirm that the method based on the database is appropriate.« less

Direct generation of event-timing equations for generalized flow shop systems

NASA Astrophysics Data System (ADS)

Doustmohammadi, Ali; Kamen, Edward W.

1995-11-01

Flow shop production lines are very common in manufacturing systems such as car assemblies, manufacturing of electronic circuits, etc. In this paper, a systematic procedure is given for generating event-timing equations directly from the machine interconnections for a generalized flow shop system. The events considered here correspond to completion times of machine operations. It is assumed that the scheduling policy is cyclic (periodic). For a given flow shop system, the open connection dynamics of the machines are derived first. Then interconnection matrices characterizing the routing of parts in the system are obtained from the given system configuration. The open connection dynamics of the machines and the interconnection matrices are then combined together to obtain the overall system dynamics given by an equation of the form X(k+1) equals A(k)X(k) B(k)V(k+1) defined over the max-plus algebra. Here the state X(k) is the vector of completion times and V(k+1) is an external input vector consisting of the arrival times of parts. It is shown that if the machines are numbered in an appropriate way and the states are selected according to certain rules, the matrix A(k) will be in a special (canonical) form. The model obtained here is useful or the analysis of system behavior and for carrying out simulations. In particular, the canonical form of A(k) enables one to study system bottlenecks and the minimal cycle time during steady-state operation. The approach presented in this paper is believed to be more straightforward compared to existing max-plus algebra formulations of flow shop systems. In particular, three advantages of the proposed approach are: (1) it yields timing equations directly from the system configuration and hence there is no need to first derive a Petri net or a digraph equivalent of the system; (2) a change in the system configuration only affects the interconnection matrices and hence does not require rederiving the entire set of equations; (3) the system model is easily put into code using existing software packages such as MATLAB.

Simulation modeling of route guidance concept

DOT National Transportation Integrated Search

1997-01-01

The methodology of a simulation model developed at the University of New South Wales, Australia, for the evaluation of performance of Dynamic Route Guidance Systems (DRGS) is described. The microscopic simulation model adopts the event update simulat...

Tiramisu: Information from Live Data Streams.

DOT National Transportation Integrated Search

2016-01-01

The primary source of information for rider safety with respect to dynamic events such as : cancelled buses, detours, traffic conditions and other factors is the transit system website. : Although technological enhancements, such as real-time trackin...

Emotion, gender, and gender typical identity in autobiographical memory.

PubMed

Grysman, Azriel; Merrill, Natalie; Fivush, Robyn

2017-03-01

Gender differences in the emotional intensity and content of autobiographical memory (AM) are inconsistent across studies, and may be influenced as much by gender identity as by categorical gender. To explore this question, data were collected from 196 participants (age 18-40), split evenly between men and women. Participants narrated four memories, a neutral event, high point event, low point event, and self-defining memory, completed ratings of emotional intensity for each event, and completed four measures of gender typical identity. For self-reported emotional intensity, gender differences in AM were mediated by identification with stereotypical feminine gender norms. For narrative use of affect terms, both gender and gender typical identity predicted affective expression. The results confirm contextual models of gender identity (e.g., Diamond, 2012 . The desire disorder in research on sexual orientation in women: Contributions of dynamical systems theory. Archives of Sexual Behavior, 41, 73-83) and underscore the dynamic interplay between gender and gender identity in the emotional expression of autobiographical memories.

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment*†

PubMed Central

Khan, Md. Ashfaquzzaman; Herbordt, Martin C.

2011-01-01

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations. PMID:21822327

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment.

PubMed

Khan, Md Ashfaquzzaman; Herbordt, Martin C

2011-07-20

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations.

Thermodynamics of rare events and impulsive relaxation events in the magnetospheric substorm dynamics

NASA Astrophysics Data System (ADS)

Consolini, Giuseppe; Kretzschmar, Matthieu

2007-12-01

The magnetosphere dynamics shows fast relaxation events following power-law distribution for many observable quantities during magnetic substorms. The emergence of such power-law distributions has been widely discussed in the framework of self-organized criticality and/or turbulence. Here, a different approach to the statistical features of these impulsive dynamical events is proposed in the framework of the thermodynamics of rare events [Lavenda, B.H., Florio, A., 1992. Thermodynamics of rare events, Int. J. Theor. Phys. 31, 1455-1475; Lavenda, B.H., 1995. Thermodynamics of Extremes. Albion]. In detail, an application of such a novel approach to the magnetospheric substorm avalanching dynamics as monitored by the auroral electroject index is discussed.

Dynamic partitioning for hybrid simulation of the bistable HIV-1 transactivation network.

PubMed

Griffith, Mark; Courtney, Tod; Peccoud, Jean; Sanders, William H

2006-11-15

The stochastic kinetics of a well-mixed chemical system, governed by the chemical Master equation, can be simulated using the exact methods of Gillespie. However, these methods do not scale well as systems become more complex and larger models are built to include reactions with widely varying rates, since the computational burden of simulation increases with the number of reaction events. Continuous models may provide an approximate solution and are computationally less costly, but they fail to capture the stochastic behavior of small populations of macromolecules. In this article we present a hybrid simulation algorithm that dynamically partitions the system into subsets of continuous and discrete reactions, approximates the continuous reactions deterministically as a system of ordinary differential equations (ODE) and uses a Monte Carlo method for generating discrete reaction events according to a time-dependent propensity. Our approach to partitioning is improved such that we dynamically partition the system of reactions, based on a threshold relative to the distribution of propensities in the discrete subset. We have implemented the hybrid algorithm in an extensible framework, utilizing two rigorous ODE solvers to approximate the continuous reactions, and use an example model to illustrate the accuracy and potential speedup of the algorithm when compared with exact stochastic simulation. Software and benchmark models used for this publication can be made available upon request from the authors.

Functional connectivity and dynamics of cortical-thalamic networks co-cultured in a dual compartment device

NASA Astrophysics Data System (ADS)

Kanagasabapathi, Thirukumaran T.; Massobrio, Paolo; Barone, Rocco Andrea; Tedesco, Mariateresa; Martinoia, Sergio; Wadman, Wytse J.; Decré, Michel M. J.

2012-06-01

Co-cultures containing dissociated cortical and thalamic cells may provide a unique model for understanding the pathophysiology in the respective neuronal sub-circuitry. In addition, developing an in vitro dissociated co-culture model offers the possibility of studying the system without influence from other neuronal sub-populations. Here we demonstrate a dual compartment system coupled to microelectrode arrays (MEAs) for co-culturing and recording spontaneous activities from neuronal sub-populations. Propagation of electrical activities between cortical and thalamic regions and their interdependence in connectivity is verified by means of a cross-correlation algorithm. We found that burst events originate in the cortical region and drive the entire cortical-thalamic network bursting behavior while mutually weak thalamic connections play a relevant role in sustaining longer burst events in cortical cells. To support these experimental findings, a neuronal network model was developed and used to investigate the interplay between network dynamics and connectivity in the cortical-thalamic system.

Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Stability and self-organization of planetary systems.

PubMed

Pakter, Renato; Levin, Yan

2018-04-01

We show that stability of planetary systems is intimately connected with their internal order. An arbitrary initial distribution of planets is susceptible to catastrophic events in which planets either collide or are ejected from the planetary system. These instabilities are a fundamental consequence of chaotic dynamics and of Arnold diffusion characteristic of many body gravitational interactions. To ensure stability over astronomical time scale of a realistic planetary system-in which planets have masses comparable to those of planets in the solar system-the motion must be quasiperiodic. A dynamical mechanism is proposed which naturally evolves a planetary system to a quasiperiodic state from an arbitrary initial condition. A planetary self-organization predicted by the theory is similar to the one found in our solar system.

Combining spiral and target wave detection to analyze excitable media dynamics

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2010-01-01

Excitable media dynamics is the lossless active transmission of waves of excitation over a field of coupled elements, such as electrical excitation in heart tissue or nerve fibers, cAMP signaling in the slime mold Dictyostelium discoideum or waves of chemical activity in the Belousov-Zhabotinsky reaction. All these systems follow essentially the same generic dynamics, including undamped wave transmission and the self-organized emergence of circular target and self-sustaining spiral waves. We combine spiral recognition, using the established phase singularity technique, and a novel three-dimensional fitting algorithm for noise-resistant target wave recognition to extract all important events responsible for the layout of the asymptotic large-scale pattern. Space-time plots of these combined events reveal signatures of events leading to spiral formation, illuminating the microscopic mechanisms at work. This strategy can be applied to arbitrary excitable media data from either models or experiments, giving insight into for example the microscopic causes for formation of pathological spiral waves in heart tissue, which could lead to novel techniques for diagnosis, risk evaluation and treatment.

Compressive Information Extraction: A Dynamical Systems Approach

DTIC Science & Technology

2016-01-24

sparsely encoded in very large data streams. (a) Target tracking in an urban canyon; (b) and (c) sample frames showing contextually abnormal events: onset...extraction to identify contextually abnormal se- quences (see section 2.2.3). Formally, the problem of interest can be stated as establishing whether a noisy...relaxations with optimality guarantees can be obtained using tools from semi-algebraic geometry. 2.2 Application: Detecting Contextually Abnormal Events

Geographic Visualization of Power-Grid Dynamics

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

Sukumar, Sreenivas R.

2015-06-18

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on themore » next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.« less

Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

2010-09-01

This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

ITS technology adoption and observed market trends from ITS deployment tracking.

DOT National Transportation Integrated Search

2010-08-03

This report examines the market dynamics and benefits associated with the deployment and diffusion of Intelligent Transportation Systems (ITS) technologies across the United States. For several ITS technologies, the current market structure, events t...

Analysis of Actin-Based Intracellular Trafficking in Pollen Tubes.

PubMed

Jiang, Yuxiang; Zhang, Meng; Huang, Shanjin

2017-01-01

Underlying rapid and directional pollen tube growth is the active intracellular trafficking system that carries materials necessary for cell wall synthesis and membrane expansion to the expanding point of the pollen tube. The actin cytoskeleton has been shown to control various intracellular trafficking events in the pollen tube, but the underlying cellular and molecular mechanisms remain poorly understood. To better understand how the actin cytoskeleton is involved in the regulation of intracellular trafficking events, we need to establish assays to visualize and quantify the distribution and dynamics of organelles, vesicles, or secreted proteins. In this chapter, we introduce methods regarding the visualization and quantification of the distribution and dynamics of organelles or vesicles in pollen tubes.

NasoNet, modeling the spread of nasopharyngeal cancer with networks of probabilistic events in discrete time.

PubMed

Galán, S F; Aguado, F; Díez, F J; Mira, J

2002-07-01

The spread of cancer is a non-deterministic dynamic process. As a consequence, the design of an assistant system for the diagnosis and prognosis of the extent of a cancer should be based on a representation method that deals with both uncertainty and time. The ultimate goal is to know the stage of development of a cancer in a patient before selecting the appropriate treatment. A network of probabilistic events in discrete time (NPEDT) is a type of Bayesian network for temporal reasoning that models the causal mechanisms associated with the time evolution of a process. This paper describes NasoNet, a system that applies NPEDTs to the diagnosis and prognosis of nasopharyngeal cancer. We have made use of temporal noisy gates to model the dynamic causal interactions that take place in the domain. The methodology we describe is general enough to be applied to any other type of cancer.

Tests of Theories of Crime in Female Prisoners.

PubMed

Lindberg, Marc A; Fugett, April; Adkins, Ashtin; Cook, Kelsey

2017-02-01

Several general theories of crime were tested with path models on 293 female prisoners in a U.S. State prison. The theories tested included Social Bond and Control, Thrill/Risk Seeking, and a new attachment-based Developmental Dynamic Systems model. A large battery of different instruments ranging from measures of risk taking, to a crime addiction scale, to Childhood Adverse Events, to attachments and clinical issues were used. The older general theories of crime did not hold up well under the rigor of path modeling. The new dynamic systems model was supported that incorporated adverse childhood events leading to (a) peer crime, (b) crime addiction, and (c) a measure derived from the Attachment and Clinical Issues Questionnaire (ACIQ) that takes individual differences in attachments and clinical issues into account. The results were discussed in terms of new approaches to Research Defined Criteria of Diagnosis (RDoC) and new approaches to intervention.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

Efficient loads analyses of Shuttle-payloads using dynamic models with linear or nonlinear interfaces

NASA Technical Reports Server (NTRS)

Spanos, P. D.; Cao, T. T.; Hamilton, D. A.; Nelson, D. A. R.

1989-01-01

An efficient method for the load analysis of Shuttle-payload systems with linear or nonlinear attachment interfaces is presented which allows the kinematics of the interface degrees of freedom at a given time to be evaluated without calculating the combined system modal representation of the Space Shuttle and its payload. For the case of a nonlinear dynamic model, an iterative procedure is employed to converge the nonlinear terms of the equations of motion to reliable values. Results are presented for a Shuttle abort landing event.

Dynamic Fault Detection Chassis

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

Mize, Jeffery J

2007-01-01

Abstract The high frequency switching megawatt-class High Voltage Converter Modulator (HVCM) developed by Los Alamos National Laboratory for the Oak Ridge National Laboratory's Spallation Neutron Source (SNS) is now in operation. One of the major problems with the modulator systems is shoot-thru conditions that can occur in a IGBTs H-bridge topology resulting in large fault currents and device failure in a few microseconds. The Dynamic Fault Detection Chassis (DFDC) is a fault monitoring system; it monitors transformer flux saturation using a window comparator and dV/dt events on the cathode voltage caused by any abnormality such as capacitor breakdown, transformer primarymore » turns shorts, or dielectric breakdown between the transformer primary and secondary. If faults are detected, the DFDC will inhibit the IGBT gate drives and shut the system down, significantly reducing the possibility of a shoot-thru condition or other equipment damaging events. In this paper, we will present system integration considerations, performance characteristics of the DFDC, and discuss its ability to significantly reduce costly down time for the entire facility.« less

Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft

NASA Technical Reports Server (NTRS)

Kifle, Muli; Andro, Monty; Tran, Quang K.; Fujikawa, Gene; Chu, Pong P.

2003-01-01

Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.

Protein Internal Dynamics Associated With Pre-System Glass Transition Temperature Endothermic Events: Investigation of Insulin and Human Growth Hormone by Solid State Hydrogen/Deuterium Exchange.

PubMed

Fang, Rui; Grobelny, Pawel J; Bogner, Robin H; Pikal, Michael J

2016-11-01

Lyophilized proteins are generally stored below their glass transition temperature (T g ) to maintain long-term stability. Some proteins in the (pure) solid state showed a distinct endotherm at a temperature well below the glass transition, designated as a pre-T g endotherm. The pre-T g endothermic event has been linked with a transition in protein internal mobility. The aim of this study was to investigate the internal dynamics of 2 proteins, insulin and human growth hormone (hGH), both of which exhibit the pre-T g endothermic event with onsets at 50°C-60°C. Solid state hydrogen/deuterium (H/D) exchange of both proteins was characterized by Fourier transform infrared spectroscopy over a temperature range from 30°C to 80°C. A distinct sigmoidal transition in the extent of H/D exchange had a midpoint of 56.1 ± 1.2°C for insulin and 61.7 ± 0.9°C for hGH, suggesting a transition to greater mobility in the protein molecules at these temperatures. The data support the hypothesis that the pre-T g event is related to a transition in internal protein mobility associated with the protein dynamical temperature. Exceeding the protein dynamical temperature is expected to activate protein internal motion and therefore may have stability consequences. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Preface: Impacts of extreme climate events and disturbances on carbon dynamics

USGS Publications Warehouse

Xiao, Jingfeng; Liu, Shuguang; Stoy, Paul C.

2016-01-01

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

Dynamically controlled crystal growth system

NASA Technical Reports Server (NTRS)

Bray, Terry L. (Inventor); Kim, Larry J. (Inventor); Harrington, Michael (Inventor); DeLucas, Lawrence J. (Inventor)

2002-01-01

Crystal growth can be initiated and controlled by dynamically controlled vapor diffusion or temperature change. In one aspect, the present invention uses a precisely controlled vapor diffusion approach to monitor and control protein crystal growth. The system utilizes a humidity sensor and various interfaces under computer control to effect virtually any evaporation rate from a number of different growth solutions simultaneously by means of an evaporative gas flow. A static laser light scattering sensor can be used to detect aggregation events and trigger a change in the evaporation rate for a growth solution. A control/follower configuration can be used to actively monitor one chamber and accurately control replicate chambers relative to the control chamber. In a second aspect, the invention exploits the varying solubility of proteins versus temperature to control the growth of protein crystals. This system contains miniature thermoelectric devices under microcomputer control that change temperature as needed to grow crystals of a given protein. Complex temperature ramps are possible using this approach. A static laser light scattering probe also can be used in this system as a non-invasive probe for detection of aggregation events. The automated dynamic control system provides systematic and predictable responses with regard to crystal size. These systems can be used for microgravity crystallization projects, for example in a space shuttle, and for crystallization work under terrestial conditions. The present invention is particularly useful for macromolecular crystallization, e.g. for proteins, polypeptides, nucleic acids, viruses and virus particles.

Dynamical Analysis and Visualization of Tornadoes Time Series

PubMed Central

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns. PMID:25790281

Dynamical analysis and visualization of tornadoes time series.

PubMed

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.

Low latitude ionospheric TEC responses to dynamical complexity quantifiers during transient events over Nigeria

NASA Astrophysics Data System (ADS)

Ogunsua, Babalola

2018-04-01

In this study, the values of chaoticity and dynamical complexity parameters for some selected storm periods in the year 2011 and 2012 have been computed. This was done using detrended TEC data sets measured from Birnin-Kebbi, Torro and Enugu global positioning system (GPS) receiver stations in Nigeria. It was observed that the significance of difference (SD) values were mostly greater than 1.96 but surprisingly lower than 1.96 in September 29, 2011. The values of the computed SD were also found to be reduced in most cases just after the geomagnetic storm with immediate recovery a day after the main phase of the storm while the values of Lyapunov exponent and Tsallis entropy remains reduced due to the influence of geomagnetic storms. It was also observed that the value of Lyapunov exponent and Tsallis entropy reveals similar variation pattern during storm period in most cases. Also recorded surprisingly were lower values of these dynamical quantifiers during the solar flare event of August 8th and 9th of the year 2011. The possible mechanisms responsible for these observations were further discussed in this work. However, our observations show that the ionospheric effects of some other possible transient events other than geomagnetic storms can also be revealed by the variation of chaoticity and dynamical complexity.

Planetary Migration and Kuiper Belt Dynamics

NASA Astrophysics Data System (ADS)

Malhotra, Renu

The Kuiper belt holds memory of the dynamical processes that shaped the architecture of the solar system, including the orbital migration history of the giant planets. We propose studies of the orbital dynamics of the Kuiper Belt in order to understand the origin of its complex dynamical structure and its link to the orbital migration history of the giant planets. By means of numerical simulations, statistical tests, as well as analytical calculations we will (1) investigate the origin of resonant Kuiper belt objects to test alternative scenarios of Neptune's migration history, (2) investigate the long term dynamical evolution of the Haumea family of Kuiper Belt objects in order to improve the age estimate of this family, and (3) investigate resonance-sticking behavior and the Kozai-Lidov mechanism and its role in the origin of the extended scattered disk. These studies directly support the goals of the NASA-OSS program by improving our understanding of the origin of the solar system's architecture. Our results will provide constraints on the nature and timing of the dynamical excitation event that is thought to have occurred in early solar system history and to have determined the architecture of the present-day solar system; our results will also provide deeper theoretical understanding of sticky mean motion resonances which contribute greatly to the longevity of many small bodies, improve our understanding of dynamical transport of planetesimals in planetary systems, and help interpret observations of other planetary systems.

Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

NASA Astrophysics Data System (ADS)

Bolhuis, Peter

Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.

PubMed

Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M

2011-09-26

A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America

Extreme value laws for fractal intensity functions in dynamical systems: Minkowski analysis

NASA Astrophysics Data System (ADS)

Mantica, Giorgio; Perotti, Luca

2016-09-01

Typically, in the dynamical theory of extremal events, the function that gauges the intensity of a phenomenon is assumed to be convex and maximal, or singular, at a single, or at most a finite collection of points in phase-space. In this paper we generalize this situation to fractal landscapes, i.e. intensity functions characterized by an uncountable set of singularities, located on a Cantor set. This reveals the dynamical rôle of classical quantities like the Minkowski dimension and content, whose definition we extend to account for singular continuous invariant measures. We also introduce the concept of extremely rare event, quantified by non-standard Minkowski constants and we study its consequences to extreme value statistics. Limit laws are derived from formal calculations and are verified by numerical experiments. Dedicated to the memory of Joseph Ford, on the twentieth anniversary of his departure.

Use of Dynamic Distortion to Predict and Alleviate Loss of Control

NASA Technical Reports Server (NTRS)

Klyde, David; Liang, Chi-Ying; Alvarez, Daniel

2011-01-01

This research has developed and evaluated the specific concepts, termed Smart-Cue and Smart-Gain, to alleviate aircraft loss of control that results from unfavorable pilot/vehicle system interactions, including pilot-induced oscillations (PIOs). Unfavorable pilot/ vehicle-system interactions have long been an aviation safety problem. While the effective aircraft dynamic properties involved in these events have been extensively studied and understood, similar scrutiny has not been paid to the many aspects of the primary manual control system that converts the pilot control inputs to motions of the control surfaces. The purpose of the Smart-Cue and Smart-Gain developments is to redress this neglect, and to develop and validate remedial manual control systems.

A complex systems analysis of stick-slip dynamics of a laboratory fault

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

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

An application of different dioids in public key cryptography

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

Durcheva, Mariana I., E-mail: mdurcheva66@gmail.com

2014-11-18

Dioids provide a natural framework for analyzing a broad class of discrete event dynamical systems such as the design and analysis of bus and railway timetables, scheduling of high-throughput industrial processes, solution of combinatorial optimization problems, the analysis and improvement of flow systems in communication networks. They have appeared in several branches of mathematics such as functional analysis, optimization, stochastic systems and dynamic programming, tropical geometry, fuzzy logic. In this paper we show how to involve dioids in public key cryptography. The main goal is to create key – exchange protocols based on dioids. Additionally the digital signature scheme ismore » presented.« less

Kinetic models for crowd dynamics. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by N. Bellomo et al.

NASA Astrophysics Data System (ADS)

Banasiak, J.

2016-09-01

There has been a hierarchy of models of crowd behaviour. One can consider the crowd at the so called microscopic level, as a collection of individuals, and derive its description in the form of a (large) system of ordinary differential equations describing the position and velocity of each individual, in parallel to the Newton's description of matter, see e.g. [10]. Another possibility is to describe crowd, in analogy to fluid dynamics, by providing its density and velocity at a given point, see e.g. [11,12]. At the same time, it is recognized that crowd is 'living, social' system that is prone to exhibit rare, not easily predictable, behaviour in response to stress induced by the perception of danger, or of the action of specific agents, see e.g. [1,2]. This high probability of the occurrence of events that are far from average, makes the crowd behaviour similar to the processes with fat-tailed distribution of events. Such unlikely events have been metaphorically termed black swans in [14], or Lévy flights in [13]. While microscopic and macroscopic models can capture many features of crowd dynamics, including obstacles, see [3,8], such models are described by differential equations that inherently are local in space. At the same time, black swan events are often caused by non-local interactions such as self-organization, learning or adherence to some averaged group behaviour. It is known that such interactions are well described by mean field models best represented by integro-differential equations, such as the Boltzmann equation of the rarefied gas theory. This has made plausible to introduce crowd models at the intermediate, (meso) scale by describing the crowd by the one particle distribution function that gives the density of individuals at any particular state; that is, at a given point in the domain and moving with a specific velocity.

A High-Speed, Event-Driven, Active Pixel Sensor Readout for Photon-Counting Microchannel Plate Detectors

NASA Technical Reports Server (NTRS)

Kimble, Randy A.; Pain, Bedabrata; Norton, Timothy J.; Haas, J. Patrick; Oegerle, William R. (Technical Monitor)

2002-01-01

Silicon array readouts for microchannel plate intensifiers offer several attractive features. In this class of detector, the electron cloud output of the MCP intensifier is converted to visible light by a phosphor; that light is then fiber-optically coupled to the silicon array. In photon-counting mode, the resulting light splashes on the silicon array are recognized and centroided to fractional pixel accuracy by off-chip electronics. This process can result in very high (MCP-limited) spatial resolution while operating at a modest MCP gain (desirable for dynamic range and long term stability). The principal limitation of intensified CCD systems of this type is their severely limited local dynamic range, as accurate photon counting is achieved only if there are not overlapping event splashes within the frame time of the device. This problem can be ameliorated somewhat by processing events only in pre-selected windows of interest of by using an addressable charge injection device (CID) for the readout array. We are currently pursuing the development of an intriguing alternative readout concept based on using an event-driven CMOS Active Pixel Sensor. APS technology permits the incorporation of discriminator circuitry within each pixel. When coupled with suitable CMOS logic outside the array area, the discriminator circuitry can be used to trigger the readout of small sub-array windows only when and where an event splash has been detected, completely eliminating the local dynamic range problem, while achieving a high global count rate capability and maintaining high spatial resolution. We elaborate on this concept and present our progress toward implementing an event-driven APS readout.

Tipping point analysis of seismological data

NASA Astrophysics Data System (ADS)

Livina, Valerie N.; Tolkova, Elena

2014-05-01

We apply the tipping point toolbox [1-7] to study sensor data of pressure variations and vertical velocity of the sea floor after two seismic events: 21 October 2010, M6.9, D10km (California) and 11 March 2011, M9.0, D30km (Japan). One type of datasets was measured by nano-resolution pressure sensor [8], while the other, for comparison, by a co-located ocean bottom seismometer. Both sensors registered the seismic wave, and we investigated the early warning and detection signals of the wave arrival for possible application with a remote and cabled tsunami warning detector network (NOAA DART system and Japan Trench Tsunami Observation System). We study the early warning and detection signals of the wave arrival using methodology that combines degenerate fingerprinting and potential analysis techniques for anticipation, detection and forecast of tipping points in a dynamical system. Degenerate fingerprinting indicator is a dynamically derived lag-1 autocorrelation, ACF (or, alternatively, short-range scaling exponent of Detrended Fluctuation Analysis, DFA [1]), which shows short-term memory in a series. When such values rise monotonically, this indicates an upcoming transition or bifurcation in a series and can be used for early warning signals analysis. The potential analysis detects a transition or bifurcation in a series at the time when it happens, which is illustrated in a special contour plot mapping the potential dynamics of the system [2-6]. The methodology has been extensively tested on artificial data and on various geophysical, ecological and industrial sensor datasets [2-5,7], and proved to be applicable to trajectories of dynamical systems of arbitrary origin [9]. In this seismological application, we have obtained early warning signals in the described series using ACF- and DFA-indicators and detected the Rayleigh wave arrival in the potential contour plots. In the case of the event in 2010, the early warning signal starts appearing about 2 min before the first peak of the Rayleigh train is detected by the sensor, whereas in the case of event of 2011, the early warning signal appears closer to the peak arrival, within 1 min. The different strength of early warning signals of the Rayleigh trains may be due to different depths of the events (10 and 30 km), which we plan to test in further analysis. References: [1] Livina and Lenton, GRL 2007; [2] Livina et al, Climate of the Past 2010; [3] Livina et al, Climate Dynamics 2011; [4] Livina et al, Physica A 2012; [5] Livina and Lenton, Cryosphere 2013; [6] Livina et al, Physica A 2013; [7] Livina et al, Journal of Civil Structural Health Monitoring, in press; [8] Tolkova and Schaad, arXiv:1401.0096v1; [9] Vaz Martins et al, PRE 2010.

On Cognition, Structured Sequence Processing, and Adaptive Dynamical Systems

NASA Astrophysics Data System (ADS)

Petersson, Karl Magnus

2008-11-01

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

Identification of human-generated forces on wheelchairs during total-body extensor thrusts.

PubMed

Hong, Seong-Wook; Patrangenaru, Vlad; Singhose, William; Sprigle, Stephen

2006-10-01

Involuntary extensor thrust experienced by wheelchair users with neurological disorders may cause injuries via impact with the wheelchair, lead to the occupant sliding out of the seat, and also damage the wheelchair. The concept of a dynamic seat, which allows movement of a seat with respect to the wheelchair frame, has been suggested as a potential solution to provide greater freedom and safety. Knowledge of the human-generated motion and forces during unconstrained extensor thrust events is of great importance in developing more comfortable and effective dynamic seats. The objective of this study was to develop a method to identify human-generated motions and forces during extensor thrust events. This information can be used to design the triggering system for a dynamic seat. An experimental system was developed to automatically track the motions of the wheelchair user using a video camera and also measure the forces at the footrest. An inverse dynamic approach was employed along with a three-link human body model and the experimental data to predict the human-generated forces. Two kinds of experiments were performed: the first experiment validated the proposed model and the second experiment showed the effects of the extensor thrust speed, the footrest angle, and the seatback angle. The proposed method was tested using a sensitivity analysis, from which a performance index was deduced to help indicate the robust region of the force identification. A system to determine human-generated motions and forces during unconstrained extensor thrusts was developed. Through experiments and simulations, the effectiveness and reliability of the developed system was established.

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

Dynamics of Metabolism and Decision Making During Alcohol Consumption: Modeling and Analysis.

PubMed

Giraldo, Luis Felipe; Passino, Kevin M; Clapp, John D; Ruderman, Danielle

2017-11-01

Heavy alcohol consumption is considered an important public health issue in the United States as over 88 000 people die every year from alcohol-related causes. Research is being conducted to understand the etiology of alcohol consumption and to develop strategies to decrease high-risk consumption and its consequences, but there are still important gaps in determining the main factors that influence the consumption behaviors throughout the drinking event. There is a need for methodologies that allow us not only to identify such factors but also to have a comprehensive understanding of how they are connected and how they affect the dynamical evolution of a drinking event. In this paper, we use previous empirical findings from laboratory and field studies to build a mathematical model of the blood alcohol concentration dynamics in individuals that are in drinking events. We characterize these dynamics as the result of the interaction between a decision-making system and the metabolic process for alcohol. We provide a model of the metabolic process for arbitrary alcohol intake patterns and a characterization of the mechanisms that drive the decision-making process of a drinker during the drinking event. We use computational simulations and Lyapunov stability theory to analyze the effects of the parameters of the model on the blood alcohol concentration dynamics that are characterized. Also, we propose a methodology to inform the model using data collected in situ and to make estimations that provide additional information to the analysis. We show how this model allows us to analyze and predict previously observed behaviors, to design new approaches for the collection of data that improves the construction of the model, and help with the design of interventions.

Activity statistics in a colloidal glass former: Experimental evidence for a dynamical transition

NASA Astrophysics Data System (ADS)

Abou, Bérengère; Colin, Rémy; Lecomte, Vivien; Pitard, Estelle; van Wijland, Frédéric

2018-04-01

In a dense colloidal suspension at a volume fraction below the glass transition, we follow the trajectories of an assembly of tracers over a large time window. We define a local activity, which quantifies the local tendency of the system to rearrange. We determine the statistics of the time integrated activity, and we argue that it develops a low activity tail that comes together with the onset of glassy-like behavior and heterogeneous dynamics. These rare events may be interpreted as the reflection of an underlying dynamic phase transition.

Simultaneous Optical and Meteor Head Echo Measurements Using the Middle Atmosphere Alomar Radar System (MAARSY)

NASA Technical Reports Server (NTRS)

Cooke, W. J.; Brown, P. G.; Stober, G.; Schult, C.; Krzeminski, Z.; Chau, J. L.

2017-01-01

We describe a two year campaign of simultaneous automated meteor optical and head echo radar measurements conducted with the Middle Atmosphere Alomar Radar System (MAARSY). This campaign was established with the following goals: Compare trajectories as measured by MAARSY and the two optical stations for a range of meteoroid masses. Compare photometric and dynamic mass measured optically with radar-derived masses (inter-calibration of mass scales). Use the best observed simultaneous events to fuse all metric, photometric and ionization estimates together and apply different ablation models to self-consistently model these highest quality events.

Using Agent-Based Modeling to Enhance System-Level Real-time Control of Urban Stormwater Systems

NASA Astrophysics Data System (ADS)

Rimer, S.; Mullapudi, A. M.; Kerkez, B.

2017-12-01

The ability to reduce combined-sewer overflow (CSO) events is an issue that challenges over 800 U.S. municipalities. When the volume of a combined sewer system or wastewater treatment plant is exceeded, untreated wastewater then overflows (a CSO event) into nearby streams, rivers, or other water bodies causing localized urban flooding and pollution. The likelihood and impact of CSO events has only exacerbated due to urbanization, population growth, climate change, aging infrastructure, and system complexity. Thus, there is an urgent need for urban areas to manage CSO events. Traditionally, mitigating CSO events has been carried out via time-intensive and expensive structural interventions such as retention basins or sewer separation, which are able to reduce CSO events, but are costly, arduous, and only provide a fixed solution to a dynamic problem. Real-time control (RTC) of urban drainage systems using sensor and actuator networks has served as an inexpensive and versatile alternative to traditional CSO intervention. In particular, retrofitting individual stormwater elements for sensing and automated active distributed control has been shown to significantly reduce the volume of discharge during CSO events, with some RTC models demonstrating a reduction upwards of 90% when compared to traditional passive systems. As more stormwater elements become retrofitted for RTC, system-level RTC across complete watersheds is an attainable possibility. However, when considering the diverse set of control needs of each of these individual stormwater elements, such system-level RTC becomes a far more complex problem. To address such diverse control needs, agent-based modeling is employed such that each individual stormwater element is treated as an autonomous agent with a diverse decision making capabilities. We present preliminary results and limitations of utilizing the agent-based modeling computational framework for the system-level control of diverse, interacting stormwater elements.

Real-time classification of signals from three-component seismic sensors using neural nets

NASA Astrophysics Data System (ADS)

Bowman, B. C.; Dowla, F.

1992-05-01

Adaptive seismic data acquisition systems with capabilities of signal discrimination and event classification are important in treaty monitoring, proliferation, and earthquake early detection systems. Potential applications include monitoring underground chemical explosions, as well as other military, cultural, and natural activities where characteristics of signals change rapidly and without warning. In these applications, the ability to detect and interpret events rapidly without falling behind the influx of the data is critical. We developed a system for real-time data acquisition, analysis, learning, and classification of recorded events employing some of the latest technology in computer hardware, software, and artificial neural networks methods. The system is able to train dynamically, and updates its knowledge based on new data. The software is modular and hardware-independent; i.e., the front-end instrumentation is transparent to the analysis system. The software is designed to take advantage of the multiprocessing environment of the Unix operating system. The Unix System V shared memory and static RAM protocols for data access and the semaphore mechanism for interprocess communications were used. As the three-component sensor detects a seismic signal, it is displayed graphically on a color monitor using X11/Xlib graphics with interactive screening capabilities. For interesting events, the triaxial signal polarization is computed, a fast Fourier Transform (FFT) algorithm is applied, and the normalized power spectrum is transmitted to a backpropagation neural network for event classification. The system is currently capable of handling three data channels with a sampling rate of 500 Hz, which covers the bandwidth of most seismic events. The system has been tested in laboratory setting with artificial events generated in the vicinity of a three-component sensor.

Radiation shelter effectiveness beyond the earth magnetosphere

NASA Astrophysics Data System (ADS)

Shurshakov, V. A.; Benghin, V. V.; Kolomensky, A. V.; Petrov, V. M.

Solar energetic particles (SEP) and galactic cosmic rays are known to be the sources of radiation hazard for missions beyond the Earth magnetosphere. An additionally shielded compartment of the mission spacecraft, called usually the radiation shelter, is considered as an important part of the radiation safety system. The shielding of the radiation shelter must be at least a few times higher than that of the remaining compartments. The mission crewmembers are supposed to stay in the radiation shelter for relatively short time of less than a day or two during SEP events only. A job-oriented radiation monitoring system (RMS) should be used on board the Martian mission spacecraft to provide the crew with necessary prediction information concerning the onset of a large SEP event. The information should be obtained independently of the ground-based support services and, hence, should be derived from online measurements of the dynamics of soft X-rays and charged energetic particles using the RMS sensors. As a result, the signal for the spacecrew members to go to the shelter gets somewhat delayed with respect to the SEP event onset, so that they appear to stay outside the shelter for some time during the event. The dependence of the crew-received dose on the SEP event prediction lag has been analyzed in terms of the standard SEP dynamics model for a typical 500-day Martian mission scenario. The Martian mission dose simulations have demonstrated a high efficiency of the radiation shelter despite the unavoidable lag of the RMS prediction signal.

What can we learn from resource pulses?

PubMed

Yang, Louie H; Bastow, Justin L; Spence, Kenneth O; Wright, Amber N

2008-03-01

An increasing number of studies in a wide range of natural systems have investigated how pulses of resource availability influence ecological processes at individual, population, and community levels. Taken together, these studies suggest that some common processes may underlie pulsed resource dynamics in a wide diversity of systems. Developing a common framework of terms and concepts for the study of resource pulses may facilitate greater synthesis among these apparently disparate systems. Here, we propose a general definition of the resource pulse concept, outline some common patterns in the causes and consequences of resource pulses, and suggest a few key questions for future investigations. We define resource pulses as episodes of increased resource availability in space and time that combine low frequency (rarity), large magnitude (intensity), and short duration (brevity), and emphasize the importance of considering resource pulses at spatial and temporal scales relevant to specific resource-onsumer interactions. Although resource pulses are uncommon events for consumers in specific systems, our review of the existing literature suggests that pulsed resource dynamics are actually widespread phenomena in nature. Resource pulses often result from climatic and environmental factors, processes of spatiotemporal accumulation and release, outbreak population dynamics, or a combination of these factors. These events can affect life history traits and behavior at the level of individual consumers, numerical responses at the population level, and indirect effects at the community level. Consumers show strategies for utilizing ephemeral resources opportunistically, reducing resource variability by averaging over larger spatial scales, and tolerating extended interpulse periods of reduced resource availability. Resource pulses can also create persistent effects in communities through several mechanisms. We suggest that the study of resource pulses provides opportunities to understand the dynamics of many specific systems, and may also contribute to broader ecological questions at individual, population, and community levels.

Stability and self-organization of planetary systems

NASA Astrophysics Data System (ADS)

Pakter, Renato; Levin, Yan

2018-04-01

We show that stability of planetary systems is intimately connected with their internal order. An arbitrary initial distribution of planets is susceptible to catastrophic events in which planets either collide or are ejected from the planetary system. These instabilities are a fundamental consequence of chaotic dynamics and of Arnold diffusion characteristic of many body gravitational interactions. To ensure stability over astronomical time scale of a realistic planetary system—in which planets have masses comparable to those of planets in the solar system—the motion must be quasiperiodic. A dynamical mechanism is proposed which naturally evolves a planetary system to a quasiperiodic state from an arbitrary initial condition. A planetary self-organization predicted by the theory is similar to the one found in our solar system.

Integration of scheduling and discrete event simulation systems to improve production flow planning

NASA Astrophysics Data System (ADS)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Calibrated acoustic emission system records M -3.5 to M -8 events generated on a saw-cut granite sample

USGS Publications Warehouse

McLaskey, Gregory C.; Lockner, David A.

2016-01-01

Acoustic emission (AE) analyses have been used for decades for rock mechanics testing, but because AE systems are not typically calibrated, the absolute sizes of dynamic microcrack growth and other physical processes responsible for the generation of AEs are poorly constrained. We describe a calibration technique for the AE recording system as a whole (transducers + amplifiers + digitizers + sample + loading frame) that uses the impact of a 4.76-mm free-falling steel ball bearing as a reference source. We demonstrate the technique on a 76-mm diameter cylinder of westerly granite loaded in a triaxial deformation apparatus at 40 MPa confining pressure. The ball bearing is dropped inside a cavity within the sample while inside the pressure vessel. We compare this reference source to conventional AEs generated during loading of a saw-cut fault in a second granite sample. All located AEs occur on the saw-cut surface and have moment magnitudes ranging from M −5.7 down to at least M −8. Dynamic events rupturing the entire simulated fault surface (stick–slip events) have measurable stress drop and macroscopic slip and radiate seismic waves similar to those from a M −3.5 earthquake. The largest AE events that do not rupture the entire fault are M −5.7. For these events, we also estimate the corner frequency (200–300 kHz), and we assume the Brune model to estimate source dimensions of 4–6 mm. These AE sources are larger than the 0.2 mm grain size and smaller than the 76 × 152 mm fault surface.

Concave Surround Optics for Rapid Multi-View Imaging

DTIC Science & Technology

2006-11-01

thus is amenable to capturing dynamic events avoiding the need to construct and calibrate an array of cameras. We demonstrate the system with a high...hard to assemble and calibrate . In this paper we present an optical system capable of rapidly moving the viewpoint around a scene. Our system...flexibility, large camera arrays are typically expensive and require significant effort to calibrate temporally, geometrically and chromatically

Mutual Information Rate and Bounds for It

PubMed Central

Baptista, Murilo S.; Rubinger, Rero M.; Viana, Emilson R.; Sartorelli, José C.; Parlitz, Ulrich; Grebogi, Celso

2012-01-01

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators. PMID:23112809

A dynamic programming approach to estimate the capacity value of energy storage

DOE PAGES

Sioshansi, Ramteen; Madaeni, Seyed Hossein; Denholm, Paul

2013-09-17

Here, we present a method to estimate the capacity value of storage. Our method uses a dynamic program to model the effect of power system outages on the operation and state of charge of storage in subsequent periods. We combine the optimized dispatch from the dynamic program with estimated system loss of load probabilities to compute a probability distribution for the state of charge of storage in each period. This probability distribution can be used as a forced outage rate for storage in standard reliability-based capacity value estimation methods. Our proposed method has the advantage over existing approximations that itmore » explicitly captures the effect of system shortage events on the state of charge of storage in subsequent periods. We also use a numerical case study, based on five utility systems in the U.S., to demonstrate our technique and compare it to existing approximation methods.« less

Inferring collective dynamical states from widely unobserved systems.

PubMed

Wilting, Jens; Priesemann, Viola

2018-06-13

When assessing spatially extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of instability in systems with propagating events. We derive a subsampling-invariant estimator, and demonstrate that it correctly infers the infectiousness of various diseases under subsampling, making it particularly useful in countries with unreliable case reports. In neuroscience, recordings are strongly limited by subsampling. Here, the subsampling-invariant estimator allows to revisit two prominent hypotheses about the brain's collective spiking dynamics: asynchronous-irregular or critical. We identify consistently for rat, cat, and monkey a state that combines features of both and allows input to reverberate in the network for hundreds of milliseconds. Overall, owing to its ready applicability, the novel estimator paves the way to novel insight for the study of spatially extended dynamical systems.

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

The 2016 Kumamoto-Oita earthquake sequence: aftershock seismicity gap and dynamic triggering in volcanic areas

NASA Astrophysics Data System (ADS)

Uchide, Takahiko; Horikawa, Haruo; Nakai, Misato; Matsushita, Reiken; Shigematsu, Norio; Ando, Ryosuke; Imanishi, Kazutoshi

2016-11-01

The 2016 Kumamoto-Oita earthquake sequence involving three large events ( M w ≥ 6) in the central Kyushu Island, southwest Japan, activated seismicities in two volcanic areas with unusual and puzzling spatial gaps after the largest earthquake ( M w 7.0) of April 16, 2016. We attempt to reveal the seismic process during the sequence by following seismological data analyses. Our hypocenter relocation result implies that the large events ruptured different faults of a complex fault system. A slip inversion analysis of the largest event indicates a large slip in the seismicity gap (Aso gap) in the caldera of Mt. Aso, which probably released accumulated stress and resulted in little aftershock production. We identified that the largest event dynamically triggered a mid-M6 event at Yufuin (80 km northeast of the epicenter), which is consistent with existence of the 20-km long zone where seismicity was activated and surface offset was observed. These findings will help us study the contribution of the identified complexity in fault geometries and the geotherm in the volcanic areas to the revealed seismic process and consequently improve our understanding of the seismo-volcano tectonics.[Figure not available: see fulltext.

Unveiling non-stationary coupling between Amazon and ocean during recent extreme events

NASA Astrophysics Data System (ADS)

Ramos, Antônio M. de T.; Zou, Yong; de Oliveira, Gilvan Sampaio; Kurths, Jürgen; Macau, Elbert E. N.

2018-02-01

The interplay between extreme events in the Amazon's precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean's temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events.

Simulation of an Extreme Off Season Rainy Event over Senegal Using WRF ARW Model: A focus on dynamic, thermodynamic processes and predictability

NASA Astrophysics Data System (ADS)

Sarr, A.

2016-12-01

This study investigates less known weather events, Off Season Rain affecting during boreal winter Western parts of Sahel region mainly, Senegal, Cape Verde and Mauritania. They are characterized by cloudy conditions at mid level, which can trigger light long lasting rains. In January 2002, an extreme case occurred from 09 to 11th producing unusual heavy rains, which had dramatic consequences on livestock and irrigated crops. The Weather and Research Forecast model (WRF ARW version 3.4) is used to simulate the event, which affected the western coast around the land/ocean interface and caused huge damages in Senegal and Mauritania. The model was able to reasonably simulate the event and its intensity 2 to 3 days in advance, demonstrating the usefulness of such a tools for early warning system (EWS), which could help mitigate the impacts. The location of the rain band was closer to the observed situation in higher resolution domains. The study showed keys dynamic and thermodynamic conditions associated with the event. Precipitable water (PW) evolution played a central role on the intensity of the event. The deep trough, associated with the disturbance, forced a northeast transport of moisture from the Inter Tropical Convergence Zone (ITCZ) over the Ocean towards Senegal and Mauritania.

Intelligent control of a planning system for astronaut training.

PubMed

Ortiz, J; Chen, G

1999-07-01

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

Flood risk changes over centuries in Rome: an empirical study

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Saccà, Smeralda; Tito Aronica, Giuseppe; Grimaldi, Salvatore; Crisci, Massimiliano

2015-04-01

Over centuries, the development of the historical city of Rome -close to one of the largest Italian rivers, the Tiber- has been intertwined with the magnitude and frequency of flooding events. The ancient Rome mostly developed on the (seven) hills, while the Tiber's floodplain was mainly exploited for agricultural purposes. A few small communities did settle in the riparian areas of the Tiber, but they had a relatively peaceful relationships with the frequent occurrence of flooding events. Nowadays, numerous people live in modern districts in the Tiber's floodplain, unaware of their exposure to potentially catastrophic flooding. The main goal of this research is to explore the dynamics of changing flood risk over the centuries between these two extreme pictures of the ancient and contemporary Rome. To this end, we carried out a socio-hydrological study by exploiting long time series of physical (flooding, river morphology) and social (urbanization, population dynamics) processes together with information about human interactions with the environment (flood defense structures). This empirical analysis showed how human and physical systems have been co-evolving over time, while being abruptly altered by the occurrence of extreme events. For instance, a large flooding event occurred in 1870 and contributed to the constructions of levees, which in turn facilitated the development of new urban areas in the Tiber's floodplain, while changed the societal memory of floods as well as the communities' perception of risk. This research work was also used to test the hypotheses of recent-developed models conceptualizing the interplay between floods and societies and simulating the long-term behavior of coupled human-water systems. The outcomes of this test provided interesting insights about the dynamics of flood risk, which are expected to support a better anticipation of future changes.

Nearshore Coastal Dynamics on a Sea-Breeze Dominated Micro-Tidal Beach (NCSAL)

NASA Astrophysics Data System (ADS)

Torres-Freyermuth, A.; Puleo, J. A.; Ruiz de Alegría-Arzaburu, A.; Figlus, J.; Mendoza, T.; Pintado-Patino, J. C.; Pieterse, A.; Chardon-Maldonado, P.; DiCosmo, N. R.; Wellman, N.; Garcia-Nava, H.; Palemón-Arcos, L.; Roberts, T.; López-González, J.; Bravo, M.; Ojeda, E.; Medellín, G.; Appendini, C. M.; Figueroa, B.; González-Leija, M.; Enriquez, C.; Pedrozo-Acuña, A.; Salles, P.

2014-12-01

A comprehensive field experiment devoted to the study of coastal processes on a micro-tidal beach was conducted from March 30th to April 12th 2014 in Sisal, Yucatán México. Wave conditions in the study area are controlled by local (i.e., sea-breezes) and meso-scale (i.e., Nortes) meteorological events. Simultaneous measurements of waves, tides, winds, currents, sediment transport, runup, and beach morphology were obtained in this experiment. Very dense nearshore instrumentation arrays allow us the study of the cross-/along- shore variability of surf/swash zone dynamics during different forcing conditions. Strong sea-breeze wind events produced a diurnal cycle with a maximum wind speed of 14 m/s. The persistent sea-breeze system forces small-amplitude (Hs<1 m) short-period (Tp<4 s) NE waves approaching with a high incidence wave angle. These wave conditions drive westward alongshore currents of up to 0.6 m/s in the inner surf zone and hence produce an active sediment transport in the swash zone. On the other hand, the more energetic (Hs>1 m) Norte event, lasting 48 hours, reached the coast on April 8th generating a long-period swell (Tp>10 s) arriving from the NNW. This event induced an eastward net sediment transport across a wide surf zone. However, long-term observations of sand impoundment at a groin located near the study area suggests that the net sediment transport in the northern Yucatan peninsula is controlled by sea-breeze events and hence swash zone dynamics play an important role in the net sediment budget of this region. A comparative study of surf and swash zone dynamics during both sea-breeze and Norte events will be presented. The Institute of Engineering of UNAM, throughout an International Collaborative Project with the University of Delaware, and CONACYT (CB-167692) provided financial support. The first author acknowledges ONR Global for providing financial support throughout the Visiting Scientist Program.

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.

Extreme events following bifurcation to spatiotemporal chaos in a spatially extended microcavity laser

NASA Astrophysics Data System (ADS)

Coulibaly, S.; Clerc, M. G.; Selmi, F.; Barbay, S.

2017-02-01

The occurrence of extreme events in a spatially extended microcavity laser has been recently reported [Selmi et al., Phys. Rev. Lett. 116, 013901 (2016), 10.1103/PhysRevLett.116.013901] to be correlated to emergence of spatiotemporal chaos. In this dissipative system, the role of spatial coupling through diffraction is essential to observe the onset of spatiotemporal complexity. We investigate further the formation mechanism of extreme events by comparing the statistical and dynamical analyses. Experimental measurements together with numerical simulations allow us to assign the quasiperiodicity mechanism as the route to spatiotemporal chaos in this system. Moreover, by investigating the fine structure of the maximum Lyapunov exponent, of the Lyapunov spectrum, and of the Kaplan-Yorke dimension of the chaotic attractor, we are able to deduce that intermittency plays a key role in the proportion of extreme events measured. We assign the observed mechanism of generation of extreme events to quasiperiodic extended spatiotemporal intermittency.

Aftershocks following crash of currency exchange rate: The case of RUB/USD in 2014

NASA Astrophysics Data System (ADS)

Usmanova, Vasilya; Lysogorskiy, Yury V.; Abe, Sumiyoshi

2018-02-01

The dynamical behavior of the currency exchange rate after its large-scale catastrophe is discussed through a case study of the rate of Russian rubles to US dollars after its crash in 2014. It is shown that, similarly to the case of the stock market crash, the relaxation is characterized by a power law, which is in analogy with the Omori-Utsu law for earthquake aftershocks. The waiting-time distribution is found to also obey a power law. Furthermore, the event-event correlation is discussed, and the aging phenomenon and scaling property are observed. Comments are made on (non-)Markovianity of the aftershock process and on a possible relevance of glassy dynamics to the market system after the crash.

Modelling indirect interactions during failure spreading in a project activity network.

PubMed

Ellinas, Christos

2018-03-12

Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of 'hidden influentials' in large-scale spreading events, and evaluate the role of direct and subsequent exposure in their emergence. Given the evidence of the importance of subsequent exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.

Causal simulation and sensor planning in predictive monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.

1989-01-01

Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

EDITORIAL: XVI Brazilian Colloquium on Orbital Dynamics

NASA Astrophysics Data System (ADS)

de Melo, Cristiano F.; Macau, Elbert E. N.; Prado, Antonio B. A.; Hetem Jnr, Annibal

2013-10-01

The XVI Brazilian Colloquium on Orbital Dynamics was held from 26-30 November 2012, at the Biazi Grand Hotel, Serra Negra, São Paulo, Brazil. The Brazilian Colloquia on Orbital Dynamics are scientific events that occur bi-annually and are designed to develop those areas of research in celestial mechanics, orbital dynamics, planetary science, fundamental astronomy, aerospace engineering, and nonlinear systems and chaos. The meeting has been held for 30 years and it brings together researchers, professors and students from South American and also from other continents. Acknowledgements National Council for Scientific and Technological Development - CNPq Coordination for the Improvement of Higher Level - CAPES São Paulo Research Foundation - FAPESP

Recent examples of mesoscale numerical forecasts of severe weather events along the east coast

NASA Technical Reports Server (NTRS)

Kocin, P. J.; Uccellini, L. W.; Zack, J. W.; Kaplan, M. L.

1984-01-01

Mesoscale numerical forecasts utilizing the Mesoscale Atmospheric Simulation System (MASS) are documented for two East Coast severe weather events. The two events are the thunderstorm and heavy snow bursts in the Washington, D.C. - Baltimore, MD region on 8 March 1984 and the devastating tornado outbreak across North and South Carolina on 28 March 1984. The forecasts are presented to demonstrate the ability of the model to simulate dynamical interactions and diabatic processes and to note some of the problems encountered when using mesoscale models for day-to-day forecasting.

A State Event Detection Algorithm for Numerically Simulating Hybrid Systems with Model Singularities

DTIC Science & Technology

2007-01-01

the case of non- constant step sizes. Therefore the event dynamics after the predictor and corrector phases are, respectively, gpk +1 = g( xk + hk+1{ m...the Extrapolation Polynomial Using a Taylor series expansion of the predicted event function eq.(6) gpk +1 = gk + hk+1 dgp dt ∣∣∣∣ (x,t)=(xk,tk) + h2k...1 2! d2gp dt2 ∣∣∣∣ (x,t)=(xk,tk) + . . . , (8) we can determine the value of gpk +1 as a function of the, yet undetermined, step size hk+1. Recalling

Avalanche Statistics Identify Intrinsic Stellar Processes near Criticality in KIC 8462852

NASA Astrophysics Data System (ADS)

Sheikh, Mohammed A.; Weaver, Richard L.; Dahmen, Karin A.

2016-12-01

The star KIC8462852 (Tabby's star) has shown anomalous drops in light flux. We perform a statistical analysis of the more numerous smaller dimming events by using methods found useful for avalanches in ferromagnetism and plastic flow. Scaling exponents for avalanche statistics and temporal profiles of the flux during the dimming events are close to mean field predictions. Scaling collapses suggest that this star may be near a nonequilibrium critical point. The large events are interpreted as avalanches marked by modified dynamics, limited by the system size, and not within the scaling regime.

MESSENGER Observations of Extreme Magnetic Tail Loading and Unloading during its Third Flyby of Mercury: Substorms?

NASA Astrophysics Data System (ADS)

Slavin, James A.; Anderson, Brian J.; Baker, Daniel N.; Benna, Mehdi; Gloeckler, George; Krimigis, Stamatios M.; McNutt, Ralph L., Jr.; Schriver, David; Solomon, Sean C.; Zurbuchen, Thomas H.

2010-05-01

During MESSENGER's third flyby of Mercury on September 29, 2009, a variable interplanetary magnetic field produced a series of several minute enhancements of the tail magnetic field by factors of ~ 2 to 3.5. The magnetic field flaring during these intervals indicates that they result from loading of the tail with magnetic flux transferred from the dayside magnetosphere. The unloading intervals were associated with plasmoids and traveling compression regions which are well known signatures of tail reconnection. The peak tail magnetic flux during the smallest loading events equaled 30% of the magnetic flux emanating from Mercury, and may have reached 100% for the largest event. In this case the dayside magnetic shielding is reduced and solar wind flux impacting the surface may be greatly enhanced. Despite the intensity of these events and their similarity to terrestrial substorm magnetic flux dynamics, no energetic charged particles with energies greater than 36 keV were observed. This absence of energetic particles constitutes a deepening puzzle for the view that the Mercury magnetosphere system is undergoing dynamical processes analogous to those at Earth during substorm events.

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Collision-induced evaporation of water clusters and contribution of momentum transfer

NASA Astrophysics Data System (ADS)

Calvo, Florent; Berthias, Francis; Feketeová, Linda; Abdoul-Carime, Hassan; Farizon, Bernadette; Farizon, Michel

2017-05-01

The evaporation of water molecules from high-velocity argon atoms impinging on protonated water clusters has been computationally investigated using molecular dynamics simulations with the reactive OSS2 potential to model water clusters and the ZBL pair potential to represent their interaction with the projectile. Swarms of trajectories and an event-by-event analysis reveal the conditions under which a specific number of molecular evaporation events is found one nanosecond after impact, thereby excluding direct knockout events from the analysis. These simulations provide velocity distributions that exhibit two main features, with a major statistical component arising from a global redistribution of the collision energy into intermolecular degrees of freedom, and another minor but non-ergodic feature at high velocities. The latter feature is produced by direct impacts on the peripheral water molecules and reflects a more complete momentum transfer. These two components are consistent with recent experimental measurements and confirm that electronic processes are not explicitly needed to explain the observed non-ergodic behavior. Contribution to the Topical Issue "Dynamics of Systems at the Nanoscale", edited by Andrey Solov'yov and Andrei Korol.

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

Costa, Liborio I., E-mail: liborio78@gmail.com

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Montemore » Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.« less

Operational fitness of box truss antennas in response to dynamic slewing

NASA Technical Reports Server (NTRS)

Bachtell, E. E.; Bettadapur, S. S.; Schartel, W. A.; Karanian, L. A.

1985-01-01

A parametric study was performed to define slewing capability of large satellites along with associated system changes or subsystem weight and complexity impacts. The satellite configuration and structural arrangement from the Earth Observation Spacecraft (EOS) study was used as the baseline spacecraft. Varying slew rates, settling times, damping, maneuver frequencies, and attitude hold times provided the data required to establish applicability to a wide range of potential missions. The key elements of the study are: (1) determine the dynamic transient response of the antenna system; (2) calculate the system errors produced by the dynamic response; (3) determine if the antenna has exceeded operational requirements at completion of the slew, and if so; (4) determine when the antenna has settled to the operational requirements. The slew event is not considered complete until the antenna is within operational limits.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

PubMed Central

Albattat, Ali; Gruenwald, Benjamin C.; Yucelen, Tansel

2016-01-01

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches. PMID:27537894

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

PubMed

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Signatures of massive collisions in debris discs. A self-consistent numerical model

NASA Astrophysics Data System (ADS)

Kral, Q.; Thébault, P.; Augereau, J.-C.; Boccaletti, A.; Charnoz, S.

2015-01-01

Context. Violent stochastic collisional events have been invoked as a possible explanation for some debris discs displaying pronounced azimuthal asymmetries or having a luminosity excess exceeding that expected for systems at collisional steady-state. So far, no thorough modelling of the consequences of such stochastic events has been carried out, mainly because of the extreme numerical challenge of coupling the dynamical and collisional evolution of the released dust. Aims: We perform the first fully self-consistent modelling of the aftermath of massive breakups in debris discs. We follow the collisional and dynamical evolution of dust released after the breakup of a Ceres-sized body at 6 AU from its central star. We investigate the duration, magnitude, and spatial structure of the signature left by such a violent event, as well as its observational detectability. Methods: We use the recently developed LIDT-DD code, which handles the coupled collisional and dynamical evolution of debris discs. The main focus is placed on the complex interplay between destructive collisions, Keplerian dynamics, and radiation pressure forces. We use the GRaTer package to estimate the system's luminosity at different wavelengths. Results: The breakup of a Ceres-sized body at 6 AU creates an asymmetric dust disc that is homogenized by the coupled action of collisions and dynamics on a timescale of a few 105 years. After a transient period where it is very steep, the particle size distribution in the system relaxes to a collisional steady-state law after ~104 years. The luminosity excess in the breakup's aftermath should be detectable by mid-IR photometry, from a 30 pc distance, over a period of ~106 years that exceeds the duration of the asymmetric phase of the disc (a few 105 years). As for the asymmetric structures, we derive synthetic images for the VLT/SPHERE and JWST/MIRI instruments, showing that they should be clearly visible and resolved from a 10 pc distance. Images at 1.6 μm (marginally), 11.4, and 15.5 μm show the inner disc structures, while 23 μm images display the outer disc asymmetries.

Forest-fire model as a supercritical dynamic model in financial systems

NASA Astrophysics Data System (ADS)

Lee, Deokjae; Kim, Jae-Young; Lee, Jeho; Kahng, B.

2015-02-01

Recently large-scale cascading failures in complex systems have garnered substantial attention. Such extreme events have been treated as an integral part of self-organized criticality (SOC). Recent empirical work has suggested that some extreme events systematically deviate from the SOC paradigm, requiring a different theoretical framework. We shed additional theoretical light on this possibility by studying financial crisis. We build our model of financial crisis on the well-known forest fire model in scale-free networks. Our analysis shows a nontrivial scaling feature indicating supercritical behavior, which is independent of system size. Extreme events in the supercritical state result from bursting of a fat bubble, seeds of which are sown by a protracted period of a benign financial environment with few shocks. Our findings suggest that policymakers can control the magnitude of financial meltdowns by keeping the economy operating within reasonable duration of a benign environment.

A Simple "Boxed Molecular Kinetics" Approach To Accelerate Rare Events in the Stochastic Kinetic Master Equation.

PubMed

Shannon, Robin; Glowacki, David R

2018-02-15

The chemical master equation is a powerful theoretical tool for analyzing the kinetics of complex multiwell potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas-surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochastic "kinetic Monte Carlo" approach and a matrix-based approach. In principle, the results yielded by both approaches are identical; the decision of which approach is better suited to a particular study depends on the details of the specific system under investigation. In this Article, we present a rigorous method for accelerating stochastic approaches by several orders of magnitude, along with a method for unbiasing the accelerated results to recover the "true" value. The approach we take in this paper is inspired by the so-called "boxed molecular dynamics" (BXD) method, which has previously only been applied to accelerate rare events in molecular dynamics simulations. Here we extend BXD to design a simple algorithmic strategy for accelerating rare events in stochastic kinetic simulations. Tests on a number of systems show that the results obtained using the BXD rare event strategy are in good agreement with unbiased results. To carry out these tests, we have implemented a kinetic Monte Carlo approach in MESMER, which is a cross-platform, open-source, and freely available master equation solver.

A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors

PubMed Central

Mishra, Abhishek; Ghosh, Rohan; Principe, Jose C.; Thakor, Nitish V.; Kukreja, Sunil L.

2017-01-01

Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available. To address these limitations, in this paper we develop a technique for generalized motion segmentation based on spatial statistics across time frames. First, we create micromotion on the platform to facilitate the separation of static and dynamic elements of a scene, inspired by human saccadic eye movements. Second, we introduce the concept of spike-groups as a methodology to partition spatio-temporal event groups, which facilitates computation of scene statistics and characterize objects in it. Experimental results show that our algorithm is able to classify dynamic objects with a moving camera with maximum accuracy of 92%. PMID:28316563

Efficient massively parallel simulation of dynamic channel assignment schemes for wireless cellular communications

NASA Technical Reports Server (NTRS)

Greenberg, Albert G.; Lubachevsky, Boris D.; Nicol, David M.; Wright, Paul E.

1994-01-01

Fast, efficient parallel algorithms are presented for discrete event simulations of dynamic channel assignment schemes for wireless cellular communication networks. The driving events are call arrivals and departures, in continuous time, to cells geographically distributed across the service area. A dynamic channel assignment scheme decides which call arrivals to accept, and which channels to allocate to the accepted calls, attempting to minimize call blocking while ensuring co-channel interference is tolerably low. Specifically, the scheme ensures that the same channel is used concurrently at different cells only if the pairwise distances between those cells are sufficiently large. Much of the complexity of the system comes from ensuring this separation. The network is modeled as a system of interacting continuous time automata, each corresponding to a cell. To simulate the model, conservative methods are used; i.e., methods in which no errors occur in the course of the simulation and so no rollback or relaxation is needed. Implemented on a 16K processor MasPar MP-1, an elegant and simple technique provides speedups of about 15 times over an optimized serial simulation running on a high speed workstation. A drawback of this technique, typical of conservative methods, is that processor utilization is rather low. To overcome this, new methods were developed that exploit slackness in event dependencies over short intervals of time, thereby raising the utilization to above 50 percent and the speedup over the optimized serial code to about 120 times.

Event triggered state estimation techniques for power systems with integrated variable energy resources.

PubMed

Francy, Reshma C; Farid, Amro M; Youcef-Toumi, Kamal

2015-05-01

For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90%. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Alternating event processes during lifetimes: population dynamics and statistical inference.

PubMed

Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng

2018-01-01

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.

Automated Dynamic Demand Response Implementation on a Micro-grid

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

Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less

Dynamic Triggering of Seismic Events and Their Relation to Slow Slip in Interior Alaska

NASA Astrophysics Data System (ADS)

Sims, N. E.; Holtkamp, S. G.

2017-12-01

We conduct a search for dynamically triggered events in the Minto Flats Fault Zone (MFFZ), a left-lateral strike-slip zone expressed as multiple, partially overlapping faults, in central Alaska. We focus on the MFFZ because we have observed slow slip processes (earthquake swarms and Very Low Frequency Earthquakes) and interaction between earthquake swarms and larger main-shock (MS) events in this area before. We utilize the Alaska Earthquake Center catalog to identify potential earthquake swarms and dynamically triggered foreshock and mainshock events along the fault zone. We find 30 swarms occurring in the last two decades, five of which we classify as foreshock (FS) swarms due to their close proximity in both time and space to MS events. Many of the earthquake swarms cluster around 15-20 km depth, which is near the seismic-aseismic transition along this fault zone. Additionally, we observe instances of large teleseismic events such as the M8.6 2012 Sumatra earthquake and M7.4 2012 Guatemala earthquake triggering seismic events within the MFFZ, with the Sumatra earthquake triggering a mainshock event that was preceded by an ongoing earthquake swarm and the Guatemala event triggering earthquake swarms that subsequently transition into a larger mainshock event. In both cases an earthquake swarm transitioned into a mainshock-aftershock event and activity continued for several days after the teleseismic waves had passed, lending some evidence to delayed dynamic triggering of seismic events. We hypothesize that large dynamic transient strain associated with the passage of teleseismic surface waves is triggering slow slip processes near the base of the seismogenic zone. These triggered aseismic transient events result in earthquake swarms, which sometimes lead to the nucleation of larger earthquakes. We utilize network matched filtering to build more robust catalogs of swarm earthquake families in this region to search for additional swarm-like or triggered activity in response to teleseismic surface waves, and to test dynamic triggering hypotheses.

Design and implementation of the flight dynamics system for COMS satellite mission operations

NASA Astrophysics Data System (ADS)

Lee, Byoung-Sun; Hwang, Yoola; Kim, Hae-Yeon; Kim, Jaehoon

2011-04-01

The first Korean multi-mission geostationary Earth orbit satellite, Communications, Ocean, and Meteorological Satellite (COMS) was launched by an Ariane 5 launch vehicle in June 26, 2010. The COMS satellite has three payloads including Ka-band communications, Geostationary Ocean Color Imager, and Meteorological Imager. Although the COMS spacecraft bus is based on the Astrium Eurostar 3000 series, it has only one solar array to the south panel because all of the imaging sensors are located on the north panel. In order to maintain the spacecraft attitude with 5 wheels and 7 thrusters, COMS should perform twice a day wheel off-loading thruster firing operations, which affect on the satellite orbit. COMS flight dynamics system provides the general on-station functions such as orbit determination, orbit prediction, event prediction, station-keeping maneuver planning, station-relocation maneuver planning, and fuel accounting. All orbit related functions in flight dynamics system consider the orbital perturbations due to wheel off-loading operations. There are some specific flight dynamics functions to operate the spacecraft bus such as wheel off-loading management, oscillator updating management, and on-station attitude reacquisition management. In this paper, the design and implementation of the COMS flight dynamics system is presented. An object oriented analysis and design methodology is applied to the flight dynamics system design. Programming language C# within Microsoft .NET framework is used for the implementation of COMS flight dynamics system on Windows based personal computer.

Exploring the evolution of node neighborhoods in Dynamic Networks

NASA Astrophysics Data System (ADS)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Human-flood interactions in Rome over the past 150 years

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Saccà, Smeralda; Tito Aronica, Giuseppe; Grimaldi, Salvatore; Ciullo, Alessio; Crisci, Massimiliano

2017-02-01

Throughout history, the socio-economic development of the city of Rome has been intertwined with the magnitude and frequency of flooding events from the Tiber, one of Italy's largest rivers. Ancient Rome mostly developed on the hills, while the Tiber's floodplain was mainly exploited for agricultural purposes. A few small communities did settle in the riparian areas of the Tiber, but they had a relatively peaceful relationship with the frequent occurrence of flooding events. Instead, numerous people live nowadays in modern districts in the Tiber's floodplain, unaware of their exposure to potentially catastrophic flooding. This research work aims to explore the dynamics of changing flood risk between these two opposite pictures of ancient and contemporary Rome. To this end, we carried out a socio-hydrological study by using long time series of hydrological (extreme flood events) and social (human population dynamics) processes, along with information about human interactions with the environment (flood defence structures). The historical analysis showed how human and water systems have been co-evolving over time, while being abruptly altered by the occurrence of an extreme flood event in 1870, just before Rome became the capital of a recently unified Italy. The outcomes of this study were then compared to the results of a socio-hydrological model simulating the dynamics emerging from the mutual shaping of floods and societies.

Automation for deep space vehicle monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1991-01-01

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Time Warp Operating System, Version 2.5.1

NASA Technical Reports Server (NTRS)

Bellenot, Steven F.; Gieselman, John S.; Hawley, Lawrence R.; Peterson, Judy; Presley, Matthew T.; Reiher, Peter L.; Springer, Paul L.; Tupman, John R.; Wedel, John J., Jr.; Wieland, Frederick P.;

Statistics of rocky coast erosion and percolation theory

NASA Astrophysics Data System (ADS)

Baldassarri, A.; Sapoval, B.

2012-04-01

The dynamics of rocky coasts is an erratic phenomenon featuring numerous small erosion events, but sometimes large dramatic collapses. In this sense, its study should not limit or rely on average erosion rates. Recent studies, based on historical as well as recent data, have indicated that the frequency of magnitude of erosion events display long tail distribution, similar to what observed in landslide. In other words the time evolution of a coast morphology does not enter the classical category of Gaussian process, but rather that of critical systems in physics. We recently proposed a minimal dynamical model of rocky coast erosion which is able to reproduce the diversity of rocky coast morphologies and their dynamics. This model is based on a single, simple ingredient, the retroaction of the coast morphology on the erosive power of the sea. It follows from the idea that erosion can spontaneously create irregular seashores, but, in turn, the geometrical irregularity of the coast participates to the damping of sea-waves, decreasing the average wave amplitude and erosive power. The resulting mutual self-stabilization dynamics of the sea erosion power and coastal irregular morphology leads spontaneously the system to a critical dynamics. Our results indicate then that rocky coast erosion and the statistical theory of percolation are closely related. In this framework, the sometimes fractal geometry of coastlines can be recovered and understood in terms of fractal dimension of the external perimeter of a percolation cluster. From a more practical point of view, the analogy with percolation interfaces means that the coast constitutes a strong, but possibly fragile, barrier to sea erosion, emerging from a self-organised selection process. Accordingly, the effect of a slow weathering degradation of the rocks mechanical properties, as well as other perturbations from natural or human cause, can trigger random and large erosion events difficult to predict and control. To the extent that these ideas apply, natural coasts should be "preserved" and managed with care.

Black liquor and the hangover effect: fish assemblage recovery dynamics following a pulse disturbance

PubMed Central

Piller, Kyle R; Geheber, Aaron D

2015-01-01

Anthropogenic perturbations impact aquatic systems causing wide-ranging responses, from assemblage restructuring to assemblage recovery. Previous studies indicate the duration and intensity of disturbances play a role in the dynamics of assemblage recovery. In August 2011, the Pearl River, United States, was subjected to a weak black liquor spill from a paper mill which resulted in substantial loss of fish in a large stretch of the main channel. We quantified resilience and recovery of fish assemblage structure in the impacted area following the event. We compared downstream (impacted) assemblages to upstream (unimpacted) assemblages to determine initial impacts on structure. Additionally, we incorporated historic fish collections (1988–2011) to examine impacts on assemblage structure across broad temporal scales. Based on NMDS, upstream and downstream sites generally showed similar assemblage structure across sample periods with the exception of the 2 months postdischarge, where upstream and downstream sites visually differed. Multivariate analysis of variance (PERMANOVA) indicated significant seasonal variation among samples, but found no significant interaction between impacted and unimpacted assemblages following the discharge event. However, multivariate dispersion (MVDISP) showed greater variance among assemblage structure following the discharge event. These results suggest that 2 months following the disturbance represent a time period of stochasticity in regard to assemblage structure dynamics, and this was followed by rapid recovery. We term this dynamic the “hangover effect” as it represents the time frame from the cessation of the perturbation to the assemblage's return to predisturbance conditions. The availability and proximity of tributaries and upstream refugia, which were not affected by the disturbance, as well as the rapid recovery of abiotic parameters likely played a substantial role in assemblage recovery. This study not only demonstrates rapid recovery in an aquatic system, but further demonstrates the value of continuous, long-term, data collections which enhance our understanding of assemblage dynamics. PMID:26120432

100J Pulsed Laser Shock Driver for Dynamic Compression Research

NASA Astrophysics Data System (ADS)

Wang, X.; Sethian, J.; Bromage, J.; Fochs, S.; Broege, D.; Zuegel, J.; Roides, R.; Cuffney, R.; Brent, G.; Zweiback, J.; Currier, Z.; D'Amico, K.; Hawreliak, J.; Zhang, J.; Rigg, P. A.; Gupta, Y. M.

2017-06-01

Logos Technologies and the Laboratory for Laser Energetics (LLE, University of Rochester) - in partnership with Washington State University - have designed, built and deployed a one of a kind 100J pulsed UV (351 nm) laser system to perform real-time, x-ray diffraction and imaging experiments in laser-driven compression experiments at the Dynamic Compression Sector (DCS) at the Advanced Photon Source, Argonne National Laboratory. The laser complements the other dynamic compression drivers at DCS. The laser system features beam smoothing for 2-d spatially uniform loading of samples and four, highly reproducible, temporal profiles (total pulse duration: 5-15 ns) to accommodate a wide variety of scientific needs. Other pulse shapes can be achieved as the experimental needs evolve. Timing of the laser pulse is highly precise (<200 ps) to allow accurate synchronization of the x-rays with the dynamic compression event. Details of the laser system, its operating parameters, and representative results will be presented. Work supported by DOE/NNSA.

Distributed augmented reality with 3-D lung dynamics--a planning tool concept.

PubMed

Hamza-Lup, Felix G; Santhanam, Anand P; Imielińska, Celina; Meeks, Sanford L; Rolland, Jannick P

2007-01-01

Augmented reality (AR) systems add visual information to the world by using advanced display techniques. The advances in miniaturization and reduced hardware costs make some of these systems feasible for applications in a wide set of fields. We present a potential component of the cyber infrastructure for the operating room of the future: a distributed AR-based software-hardware system that allows real-time visualization of three-dimensional (3-D) lung dynamics superimposed directly on the patient's body. Several emergency events (e.g., closed and tension pneumothorax) and surgical procedures related to lung (e.g., lung transplantation, lung volume reduction surgery, surgical treatment of lung infections, lung cancer surgery) could benefit from the proposed prototype.

Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.

PubMed

Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano

2016-11-15

Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.

Critical care nursing: Embedded complex systems.

PubMed

Trinier, Ruth; Liske, Lori; Nenadovic, Vera

2016-01-01

Variability in parameters such as heart rate, respiratory rate and blood pressure defines healthy physiology and the ability of the person to adequately respond to stressors. Critically ill patients have lost this variability and require highly specialized nursing care to support life and monitor changes in condition. The critical care environment is a dynamic system through which information flows. The critical care unit is typically designed as a tree structure with generally one attending physician and multiple nurses and allied health care professionals. Information flow through the system allows for identification of deteriorating patient status and timely interventionfor rescue from further deleterious effects. Nurses provide the majority of direct patient care in the critical care setting in 2:1, 1:1 or 1:2 nurse-to-patient ratios. The bedside nurse-critically ill patient relationship represents the primary, real-time feedback loop of information exchange, monitoring and treatment. Variables that enhance information flow through this loop and support timely nursing intervention can improve patient outcomes, while barriers can lead to errors and adverse events. Examining patient information flow in the critical care environment from a dynamic systems perspective provides insights into how nurses deliver effective patient care and prevent adverse events.

A High-Speed, Event-Driven, Active Pixel Sensor Readout for Photon-Counting Microchannel Plate Detectors

NASA Technical Reports Server (NTRS)

Kimble, Randy A.; Pain, B.; Norton, T. J.; Haas, P.; Fisher, Richard R. (Technical Monitor)

2001-01-01

Silicon array readouts for microchannel plate intensifiers offer several attractive features. In this class of detector, the electron cloud output of the MCP intensifier is converted to visible light by a phosphor; that light is then fiber-optically coupled to the silicon array. In photon-counting mode, the resulting light splashes on the silicon array are recognized and centroided to fractional pixel accuracy by off-chip electronics. This process can result in very high (MCP-limited) spatial resolution for the readout while operating at a modest MCP gain (desirable for dynamic range and long term stability). The principal limitation of intensified CCD systems of this type is their severely limited local dynamic range, as accurate photon counting is achieved only if there are not overlapping event splashes within the frame time of the device. This problem can be ameliorated somewhat by processing events only in pre-selected windows of interest or by using an addressable charge injection device (CID) for the readout array. We are currently pursuing the development of an intriguing alternative readout concept based on using an event-driven CMOS Active Pixel Sensor. APS technology permits the incorporation of discriminator circuitry within each pixel. When coupled with suitable CMOS logic outside the array area, the discriminator circuitry can be used to trigger the readout of small sub-array windows only when and where an event splash has been detected, completely eliminating the local dynamic range problem, while achieving a high global count rate capability and maintaining high spatial resolution. We elaborate on this concept and present our progress toward implementing an event-driven APS readout.

Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

NASA Astrophysics Data System (ADS)

Ellappan, Vijayan; Ashwini, J.

2017-11-01

In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

Interpreting the power spectrum of Dansgaard-Oeschger events via stochastic dynamical systems

NASA Astrophysics Data System (ADS)

Mitsui, Takahito; Lenoir, Guillaume; Crucifix, Michel

2017-04-01

Dansgaard-Oeschger (DO) events are abrupt climate shifts, which are particularly pronounced in the North Atlantic region during glacial periods [Dansgaard et al. 1993]. The signals are most clearly found in δ 18O or log [Ca2+] records of Greenland ice cores. The power spectrum S(f) of DO events has attracted attention over two decades with debates on the apparent 1.5-kyr periodicity [Grootes & Stuiver 1997; Schultz et al. 2002; Ditlevsen et al. 2007] and scaling property over several time scales [Schmitt, Lovejoy, & Schertzer 1995; Rypdal & Rypdal 2016]. The scaling property is written most simply as S(f)˜ f-β , β ≈ 1.4. However, physical as well as underlying dynamics of the periodicity and the scaling property are still not clear. Pioneering works for modelling the spectrum of DO events are done by Cessi (1994) and Ditlevsen (1999), but their model-data comparisons of the spectra are rather qualitative. Here, we show that simple stochastic dynamical systems can generate power spectra statistically consistent with the observed spectra over a wide range of frequency from orbital to the Nyquist frequency (=1/40 yr-1). We characterize the scaling property of the spectrum by defining a local scaling exponentβ _loc. For the NGRIP log [Ca2+] record, the local scaling exponent β _loc increases from ˜ 1 to ˜ 2 as the frequency increases from ˜ 1/5000 yr-1 to ˜ 1/500 yr-1, and β _loc decreases toward zero as the frequency increases from ˜ 1/500 yr-1 to the Nyquist frequency. For the δ 18O record, the local scaling exponent β _loc increases from ˜ 1 to ˜ 1.5 as the frequency increases from ˜ 1/5000 yr^{-1 to ˜ 1/1000 yr-1, and β _loc decreases toward zero as the frequency increases from ˜ 1/1000 yr-1 to the Nyquist frequency. This systematic breaking of a single scaling is reproduced by the simple stochastic models. Especially, the models suggest that the flattening of the spectra starting from multi-centennial scale and ending at the Nyquist frequency results from both non-dynamical (or non-system) noise and 20-yr binning of the ice core records. The modelling part of this research is partially based on the following work: Takahito Mitsui and Michel Crucifix, Influence of external forcings on abrupt millennial-scale climate changes: a statistical modelling study, Climate Dynamics (first online). doi:10.1007/s00382-016-3235-z

Evolution of Linux operating system network

NASA Astrophysics Data System (ADS)

Xiao, Guanping; Zheng, Zheng; Wang, Haoqin

2017-01-01

Linux operating system (LOS) is a sophisticated man-made system and one of the most ubiquitous operating systems. However, there is little research on the structure and functionality evolution of LOS from the prospective of networks. In this paper, we investigate the evolution of the LOS network. 62 major releases of LOS ranging from versions 1.0 to 4.1 are modeled as directed networks in which functions are denoted by nodes and function calls are denoted by edges. It is found that the size of the LOS network grows almost linearly, while clustering coefficient monotonically decays. The degree distributions are almost the same: the out-degree follows an exponential distribution while both in-degree and undirected degree follow power-law distributions. We further explore the functionality evolution of the LOS network. It is observed that the evolution of functional modules is shown as a sequence of seven events (changes) succeeding each other, including continuing, growth, contraction, birth, splitting, death and merging events. By means of a statistical analysis of these events in the top 4 largest components (i.e., arch, drivers, fs and net), it is shown that continuing, growth and contraction events occupy more than 95% events. Our work exemplifies a better understanding and describing of the dynamics of LOS evolution.

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

Dynamics of metastable breathers in nonlinear chains in acoustic vacuum

NASA Astrophysics Data System (ADS)

Sen, Surajit; Mohan, T. R. Krishna

2009-03-01

The study of the dynamics of one-dimensional chains with both harmonic and nonlinear interactions, as in the Fermi-Pasta-Ulam and related problems, has played a central role in efforts to identify the broad consequences of nonlinearity in these systems. Nevertheless, little is known about the dynamical behavior of purely nonlinear chains where there is a complete absence of the harmonic term, and hence sound propagation is not admissible, i.e., under conditions of “acoustic vacuum.” Here we study the dynamics of highly localized excitations, or breathers, which are known to be initiated by the quasistatic stretching of the bonds between adjacent particles. We show via detailed particle-dynamics-based studies that many low-energy pulses also form in the vicinity of the perturbation, and the breathers that form are “fragile” in the sense that they can be easily delocalized by scattering events in the system. We show that the localized excitations eventually disperse, allowing the system to attain an equilibrium-like state that is realizable in acoustic vacuum. We conclude with a discussion of how the dynamics is affected by the presence of acoustic oscillations.

Assessing dry weather flow contribution in TSS and COD storm events loads in combined sewer systems.

PubMed

Métadier, M; Bertrand-Krajewski, J L

2011-01-01

Continuous high resolution long term turbidity measurements along with continuous discharge measurements are now recognised as an appropriate technique for the estimation of in sewer total suspended solids (TSS) and Chemical Oxygen Demand (COD) loads during storm events. In the combined system of the Ecully urban catchment (Lyon, France), this technique is implemented since 2003, with more than 200 storm events monitored. This paper presents a method for the estimation of the dry weather (DW) contribution to measured total TSS and COD event loads with special attention devoted to uncertainties assessment. The method accounts for the dynamics of both discharge and turbidity time series at two minutes time step. The study is based on 180 DW days monitored in 2007-2008. Three distinct classes of DW days were evidenced. Variability analysis and quantification showed that no seasonal effect and no trend over the year were detectable. The law of propagation of uncertainties is applicable for uncertainties estimation. The method has then been applied to all measured storm events. This study confirms the interest of long term continuous discharge and turbidity time series in sewer systems, especially in the perspective of wet weather quality modelling.

Results of the first continuous meteor head echo survey at polar latitudes

NASA Astrophysics Data System (ADS)

Schult, Carsten; Stober, Gunter; Janches, Diego; Chau, Jorge L.

2017-11-01

We present the first quasi continuous meteor head echo measurements obtained during a period of over two years using the Middle Atmosphere ALOMAR Radar System (MAARSY). The measurements yield information on the altitude, trajectory, vector velocity, radar cross section, deceleration and dynamical mass of every single event. The large statistical amount of nearly one million meteor head detections provide an excellent overview of the elevation, altitude, velocity and daily count rate distributions during different times of the year at polar latitudes. Only 40% of the meteors were detected within the full width half maximum of the specific sporadic meteor sources. Our observation of the sporadic meteors are compared to the observations with other radar systems and a meteor input function (MIF). The best way to compare different radar systems is by comparing the radar cross section (RCS), which is the main detection criterion for each system. In this study we aim to compare our observations with a MIF, which provides information only about the meteoroid mass. Thus, we are using a statistical approach for the elevation and velocity dependent visibility and a specific mass selection. The predicted absolute count rates from the MIF are in a good agreement with the observation when it is assumed that the radar system is only sensitive to meteoroids with masses higher than one microgram. The analysis of the dynamic masses seems to be consistent with this assumption since the count rate of events with smaller masses are low and decrease even more by using events with relatively small errors.

Recent Results on "Approximations to Optimal Alarm Systems for Anomaly Detection"

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

An optimal alarm system and its approximations may use Kalman filtering for univariate linear dynamic systems driven by Gaussian noise to provide a layer of predictive capability. Predicted Kalman filter future process values and a fixed critical threshold can be used to construct a candidate level-crossing event over a predetermined prediction window. An optimal alarm system can be designed to elicit the fewest false alarms for a fixed detection probability in this particular scenario.

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

A mobile water analysis laboratory for the study of stream nutrient and DOC dynamics

NASA Astrophysics Data System (ADS)

Echevarria Roman, Y.; Pullin, M. J.; Schwingle, R.; Gabrielsen, P. J.

2013-12-01

The dynamics of nutrient and dissolved organic carbon (DOC) quantity and composition in streams vary with season and in response to hydrologic events. Periodic grab sampling can capture some of this variation, but has also been shown to miss high flow events. Sampling during winter, during thunderstorms, and at night is difficult and sometimes hazardous. For these reasons, we have developed a mobile laboratory that autonomously determines pH, Eh, conductivity, dissolved oxygen, turbidity, nitrate, phosphate, DOC, DIC, as well as DOC fluorescence and absorbance continuously on a minutes timescale. The laboratory includes a Labview operated computer system that allows remote control and interaction with pumps, pressure, temperature, and flow sensors as well as the analytical instruments. Climate control allows for operation in winter. The design and operation of this laboratory will be presented. We will also discuss example data showing diurnal changes and responses to hydrologic events in DOC quantity and quality in the East Fork of the Jemez River, New Mexico.

Fault Diagnosis System of Wind Turbine Generator Based on Petri Net

NASA Astrophysics Data System (ADS)

Zhang, Han

Petri net is an important tool for discrete event dynamic systems modeling and analysis. And it has great ability to handle concurrent phenomena and non-deterministic phenomena. Currently Petri nets used in wind turbine fault diagnosis have not participated in the actual system. This article will combine the existing fuzzy Petri net algorithms; build wind turbine control system simulation based on Siemens S7-1200 PLC, while making matlab gui interface for migration of the system to different platforms.

Hydrodynamic predictions for 5.44 TeV Xe+Xe collisions

NASA Astrophysics Data System (ADS)

Giacalone, Giuliano; Noronha-Hostler, Jacquelyn; Luzum, Matthew; Ollitrault, Jean-Yves

2018-03-01

We argue that relativistic hydrodynamics is able to make robust predictions for soft particle production in Xe+Xe collisions at the CERN Large Hadron Collider (LHC). The change of system size from Pb+Pb to Xe+Xe provides a unique opportunity to test the scaling laws inherent to fluid dynamics. Using event-by-event hydrodynamic simulations, we make quantitative predictions for several observables: mean transverse momentum, anisotropic flow coefficients, and their fluctuations. Results are shown as a function of collision centrality.

Design of Flight Vehicle Management Systems

NASA Technical Reports Server (NTRS)

Meyer, George; Aiken, Edwin W. (Technical Monitor)

1994-01-01

As the operation of large systems becomes ever more dependent on extensive automation, the need for an effective solution to the problem of design and validation of the underlying software becomes more critical. Large systems possess much detailed structure, typically hierarchical, and they are hybrid. Information processing at the top of the hierarchy is by means of formal logic and sentences; on the bottom it is by means of simple scalar differential equations and functions of time; and in the middle it is by an interacting mix of nonlinear multi-axis differential equations and automata, and functions of time and discrete events. The lecture will address the overall problem as it relates to flight vehicle management, describe the middle level, and offer a design approach that is based on Differential Geometry and Discrete Event Dynamic Systems Theory.

Role of dynamics in enzyme catalysis: substantial versus semantic controversies.

PubMed

Kohen, Amnon

2015-02-17

CONSPECTUS: The role of the enzyme's dynamic motions in catalysis is at the center of heated contemporary debates among both theoreticians and experimentalists. Resolving these apparent disputes is of both intellectual and practical importance: incorporation of enzyme dynamics could be critical for any calculation of enzymatic function and may have profound implications for structure-based drug design and the design of biomimetic catalysts. Analysis of the literature suggests that while part of the dispute may reflect substantial differences between theoretical approaches, much of the debate is semantic. For example, the term "protein dynamics" is often used by some researchers when addressing motions that are in thermal equilibrium with their environment, while other researchers only use this term for nonequilibrium events. The last cases are those in which thermal energy is "stored" in a specific protein mode and "used" for catalysis before it can dissipate to its environment (i.e., "nonstatistical dynamics"). This terminology issue aside, a debate has arisen among theoreticians around the roles of nonstatistical vs statistical dynamics in catalysis. However, the author knows of no experimental findings available today that examined this question in enzyme catalyzed reactions. Another source of perhaps nonsubstantial argument might stem from the varying time scales of enzymatic motions, which range from seconds to femtoseconds. Motions at different time scales play different roles in the many events along the catalytic cascade (reactant binding, reprotonation of reactants, structural rearrangement toward the transition state, product release, etc.). In several cases, when various experimental tools have been used to probe catalytic events at differing time scales, illusory contradictions seem to have emerged. In this Account, recent attempts to sort the merits of those questions are discussed along with possible future directions. A possible summary of current studies could be that enzyme, substrate, and solvent dynamics contribute to enzyme catalyzed reactions in several ways: first via mutual "induced-fit" shifting of their conformational ensemble upon binding; then via thermal search of the conformational space toward the reaction's transition-state (TS) and the rare event of the barrier crossing toward products, which is likely to be on faster time scales then the first and following events; and finally via the dynamics associated with products release, which are rate-limiting for many enzymatic reactions. From a chemical perspective, close to the TS, enzymatic systems seem to stiffen, restricting motions orthogonal to the chemical coordinate and enabling dynamics along the reaction coordinate to occur selectively. Studies of how enzymes evolved to support those efficient dynamics at various time scales are still in their infancy, and further experiments and calculations are needed to reveal these phenomena in both enzymes and uncatalyzed reactions.

Live-cell imaging combined with immunofluorescence, RNA, or DNA FISH to study the nuclear dynamics and expression of the X-inactivation center.

PubMed

Pollex, Tim; Piolot, Tristan; Heard, Edith

2013-01-01

Differentiation of embryonic stem cells is accompanied by changes of gene expression and chromatin and chromosome dynamics. One of the most impressive examples for these changes is inactivation of one of the two X chromosomes occurring upon differentiation of mouse female embryonic stem cells. With a few exceptions, these events have been mainly studied in fixed cells. In order to better understand the dynamics, kinetics, and order of events during differentiation, one needs to employ live-cell imaging techniques. Here, we describe a combination of live-cell imaging with techniques that can be used in fixed cells (e.g., RNA FISH) to correlate locus dynamics or subnuclear localization with, e.g., gene expression. To study locus dynamics in female ES cells, we generated cell lines containing TetO arrays in the X-inactivation center, the locus on the X chromosome regulating X-inactivation, which can be visualized upon expression of TetR fused to fluorescent proteins. We will use this system to elaborate on how to generate ES cell lines for live-cell imaging of locus dynamics, how to culture ES cells prior to live-cell imaging, and to describe typical live-cell imaging conditions for ES cells using different microscopes. Furthermore, we will explain how RNA, DNA FISH, or immunofluorescence can be applied following live-cell imaging to correlate gene expression with locus dynamics.

Damage spreading and opinion dynamics on scale-free networks

NASA Astrophysics Data System (ADS)

Fortunato, Santo

2005-03-01

We study damage spreading among the opinions of a system of agents, subjected to the dynamics of the Krause-Hegselmann consensus model. The damage consists in a sharp change of the opinion of one or more agents in the initial random opinion configuration, supposedly due to some external factors and/or events. This may help to understand for instance under which conditions special shocking events or targeted propaganda are able to influence the results of elections. For agents lying on the nodes of a Barabási-Albert network, there is a damage spreading transition at a low value εd of the confidence bound parameter. Interestingly, we find as well that there is some critical value εs above which the initial perturbation manages to propagate to all other agents.

Self-organization in leaky threshold systems: The influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting

PubMed Central

Rundle, J. B.; Tiampo, K. F.; Klein, W.; Sá Martins, J. S.

2002-01-01

Threshold systems are known to be some of the most important nonlinear self-organizing systems in nature, including networks of earthquake faults, neural networks, superconductors and semiconductors, and the World Wide Web, as well as political, social, and ecological systems. All of these systems have dynamics that are strongly correlated in space and time, and all typically display a multiplicity of spatial and temporal scales. Here we discuss the physics of self-organization in earthquake threshold systems at two distinct scales: (i) The “microscopic” laboratory scale, in which consideration of results from simulations leads to dynamical equations that can be used to derive the results obtained from sliding friction experiments, and (ii) the “macroscopic” earthquake fault-system scale, in which the physics of strongly correlated earthquake fault systems can be understood by using time-dependent state vectors defined in a Hilbert space of eigenstates, similar in many respects to the mathematics of quantum mechanics. In all of these systems, long-range interactions induce the existence of locally ergodic dynamics. The existence of dissipative effects leads to the appearance of a “leaky threshold” dynamics, equivalent to a new scaling field that controls the size of nucleation events relative to the size of background fluctuations. At the macroscopic earthquake fault-system scale, these ideas show considerable promise as a means of forecasting future earthquake activity. PMID:11875204

Reconstruction of the evolution of microbial defense systems.

PubMed

Puigbò, Pere; Makarova, Kira S; Kristensen, David M; Wolf, Yuri I; Koonin, Eugene V

2017-04-04

Evolution of bacterial and archaeal genomes is a highly dynamic process that involves intensive loss of genes as well as gene gain via horizontal transfer, with a lesser contribution from gene duplication. The rates of these processes can be estimated by comparing genomes that are linked by an evolutionary tree. These estimated rates of genome dynamics events substantially differ for different functional classes of genes. The genes involved in defense against viruses and other invading DNA are among those that are gained and lost at the highest rates. We employed a stochastic birth-and-death model to obtain maximum likelihood estimates of the rates of gain and loss of defense genes in 35 groups of closely related bacterial genomes and one group of archaeal genomes. We find that on average, the defense genes experience 1.4 fold higher flux than the rest of microbial genes. This excessive flux of defense genes over the genomic mean is consistent across diverse microbial groups. The few exceptions include intracellular parasites with small, degraded genomes that possess few defense systems which are more stable than in other microbes. Generally, defense genes follow the previously established pattern of genome dynamics, with gene family loss being about 3 times more common than gain and an order of magnitude more common than expansion or contraction of gene families. Case by case analysis of the evolutionary dynamics of defense genes indicates frequent multiple events in the same locus and widespread involvement of mobile elements in the gain and loss of defense genes. Evolution of microbial defense systems is highly dynamic but, notwithstanding the host-parasite arms race, generally follows the same trends that have been established for the rest of the genes. Apart from the paucity and the low flux of defense genes in parasitic bacteria with deteriorating genomes, there is no clear connection between the evolutionary regime of defense systems and microbial life style.

Transient Optical Sky survey

NASA Astrophysics Data System (ADS)

Hadjiyska, Elena Ivanova

2009-06-01

Optical transients have been studied in isolated cases, but never mapped into a comprehensive data base in the past. These events vary in duration and signature, yet they are united under the umbrella of time varying observables and represent a significant portion of the dynamical processes in the universe. The Transient Optical Sky Survey (TOSS) System is a dedicated, ground-based system of small optical telescopes, observing nightly at fixed Declination while gathering 90 sec exposures and thus creating a repeated partial map of the sky. Presented here is a brief overview of some of the signatures of transient events and a description of the TOSS system along with the data acquired during the 2008-2009 observing campaign, potentially producing over 100,000 light curves.

A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2018-07-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Speculation and replication in temperature accelerated dynamics

DOE PAGES

Zamora, Richard J.; Perez, Danny; Voter, Arthur F.

2018-02-12

Accelerated Molecular Dynamics (AMD) is a class of MD-based algorithms for the long-time scale simulation of atomistic systems that are characterized by rare-event transitions. Temperature-Accelerated Dynamics (TAD), a traditional AMD approach, hastens state-to-state transitions by performing MD at an elevated temperature. Recently, Speculatively-Parallel TAD (SpecTAD) was introduced, allowing the TAD procedure to exploit parallel computing systems by concurrently executing in a dynamically generated list of speculative future states. Although speculation can be very powerful, it is not always the most efficient use of parallel resources. In this paper, we compare the performance of speculative parallelism with a replica-based technique, similarmore » to the Parallel Replica Dynamics method. A hybrid SpecTAD approach is also presented, in which each speculation process is further accelerated by a local set of replicas. Finally and overall, this work motivates the use of hybrid parallelism whenever possible, as some combination of speculation and replication is typically most efficient.« less

Speculation and replication in temperature accelerated dynamics

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

Zamora, Richard J.; Perez, Danny; Voter, Arthur F.

Accelerated Molecular Dynamics (AMD) is a class of MD-based algorithms for the long-time scale simulation of atomistic systems that are characterized by rare-event transitions. Temperature-Accelerated Dynamics (TAD), a traditional AMD approach, hastens state-to-state transitions by performing MD at an elevated temperature. Recently, Speculatively-Parallel TAD (SpecTAD) was introduced, allowing the TAD procedure to exploit parallel computing systems by concurrently executing in a dynamically generated list of speculative future states. Although speculation can be very powerful, it is not always the most efficient use of parallel resources. In this paper, we compare the performance of speculative parallelism with a replica-based technique, similarmore » to the Parallel Replica Dynamics method. A hybrid SpecTAD approach is also presented, in which each speculation process is further accelerated by a local set of replicas. Finally and overall, this work motivates the use of hybrid parallelism whenever possible, as some combination of speculation and replication is typically most efficient.« less

Dynamical Networks Characterization of Space Weather Events

NASA Astrophysics Data System (ADS)

Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show our first results that use network properties such as cliques and clustering coefficients to map these highly dynamic changes in ionospheric current patterns.[l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).

Network analysis applications in hydrology

NASA Astrophysics Data System (ADS)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Phasor Measurement Unit and Its Application in Modern Power Systems

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

Ma, Jian; Makarov, Yuri V.; Dong, Zhao Yang

2010-06-01

The introduction of phasor measuring units (PMUs) in power systems significantly improves the possibilities for monitoring and analyzing power system dynamics. Synchronized measurements make it possible to directly measure phase angles between corresponding phasors in different locations within the power system. Improved monitoring and remedial action capabilities allow network operators to utilize the existing power system in a more efficient way. Improved information allows fast and reliable emergency actions, which reduces the need for relatively high transmission margins required by potential power system disturbances. In this chapter, the applications of PMU in modern power systems are presented. Specifically, the topicsmore » touched in this chapter include state estimation, voltage and transient stability, oscillation monitoring, event and fault detection, situation awareness, and model validation. A case study using Characteristic Ellipsoid method based on PMU to monitor power system dynamic is presented.« less

Accelerated molecular dynamics: A promising and efficient simulation method for biomolecules

NASA Astrophysics Data System (ADS)

Hamelberg, Donald; Mongan, John; McCammon, J. Andrew

2004-06-01

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.

Unexpected Control Structure Interaction on International Space Station

NASA Technical Reports Server (NTRS)

Gomez, Susan F.; Platonov, Valery; Medina, Elizabeth A.; Borisenko, Alexander; Bogachev, Alexey

2017-01-01

On June 23, 2011, the International Space Station (ISS) was performing a routine 180 degree yaw maneuver in support of a Russian vehicle docking when the on board Russian Segment (RS) software unexpectedly declared two attitude thrusters failed and switched thruster configurations in response to unanticipated ISS dynamic motion. Flight data analysis after the maneuver indicated that higher than predicted structural loads had been induced at various locations on the United States (U.S.) segment of the ISS. Further analysis revealed that the attitude control system was firing thrusters in response to both structural flex and rigid body rates, which resonated the structure and caused high loads and fatigue cycles. It was later determined that the thruster themselves were healthy. The RS software logic, which was intended to react to thruster failures, had instead been heavily influenced by interaction between the control system and structural flex. This paper will discuss the technical aspects of the control structure interaction problem that led to the RS control system firing thrusters in response to structural flex, the factors that led to insufficient preflight analysis of the thruster firings, and the ramifications the event had on the ISS. An immediate consequence included limiting which thrusters could be used for attitude control. This complicated the planning of on-orbit thruster events and necessitated the use of suboptimal thruster configurations that increased propellant usage and caused thruster lifetime usage concerns. In addition to the technical aspects of the problem, the team dynamics and communication shortcomings that led to such an event happening in an environment where extensive analysis is performed in support of human space flight will also be examined. Finally, the technical solution will be presented, which required a multidisciplinary effort between the U.S. and Russian control system engineers and loads and dynamics structural engineers to develop and implement an extensive modification in the RS software logic for ISS attitude control thruster firings.

Modeling, Forecasting and Mitigating Extreme Earthquakes

NASA Astrophysics Data System (ADS)

Ismail-Zadeh, A.; Le Mouel, J.; Soloviev, A.

2012-12-01

Recent earthquake disasters highlighted the importance of multi- and trans-disciplinary studies of earthquake risk. A major component of earthquake disaster risk analysis is hazards research, which should cover not only a traditional assessment of ground shaking, but also studies of geodetic, paleoseismic, geomagnetic, hydrological, deep drilling and other geophysical and geological observations together with comprehensive modeling of earthquakes and forecasting extreme events. Extreme earthquakes (large magnitude and rare events) are manifestations of complex behavior of the lithosphere structured as a hierarchical system of blocks of different sizes. Understanding of physics and dynamics of the extreme events comes from observations, measurements and modeling. A quantitative approach to simulate earthquakes in models of fault dynamics will be presented. The models reproduce basic features of the observed seismicity (e.g., the frequency-magnitude relationship, clustering of earthquakes, occurrence of extreme seismic events). They provide a link between geodynamic processes and seismicity, allow studying extreme events, influence of fault network properties on seismic patterns and seismic cycles, and assist, in a broader sense, in earthquake forecast modeling. Some aspects of predictability of large earthquakes (how well can large earthquakes be predicted today?) will be also discussed along with possibilities in mitigation of earthquake disasters (e.g., on 'inverse' forensic investigations of earthquake disasters).

Architectural Analysis of Dynamically Reconfigurable Systems

NASA Technical Reports Server (NTRS)

Lindvall, Mikael; Godfrey, Sally; Ackermann, Chris; Ray, Arnab; Yonkwa, Lyly

2010-01-01

oTpics include: the problem (increased flexibility of architectural styles decrease analyzability, behavior emerges and varies depending on the configuration, does the resulting system run according to the intended design, and architectural decisions can impede or facilitate testing); top down approach to architecture analysis, detection of defects and deviations, and architecture and its testability; currently targeted projects GMSEC and CFS; analyzing software architectures; analyzing runtime events; actual architecture recognition; GMPUB in Dynamic SAVE; sample output from new approach; taking message timing delays into account; CFS examples of architecture and testability; some recommendations for improved testablity; and CFS examples of abstract interfaces and testability; CFS example of opening some internal details.

Photon-counting intensified random-access charge injection device

NASA Astrophysics Data System (ADS)

Norton, Timothy J.; Morrissey, Patrick F.; Haas, Patrick; Payne, Leslie J.; Carbone, Joseph; Kimble, Randy A.

1999-11-01

At NASA GSFC we are developing a high resolution solar-blind photon counting detector system for UV space based astronomy. The detector comprises a high gain MCP intensifier fiber- optically coupled to a charge injection device (CID). The detector system utilizes an FPGA based centroiding system to locate the center of photon events from the intensifier to high accuracy. The photon event addresses are passed via a PCI interface with a GPS derived time stamp inserted per frame to an integrating memory. Here we present imaging performance data which show resolution of MCP tube pore structure at an MCP pore diameter of 8 micrometer. This data validates the ICID concept for intensified photon counting readout. We also discuss correction techniques used in the removal of fixed pattern noise effects inherent in the centroiding algorithms used and present data which shows the local dynamic range of the device. Progress towards development of a true random access CID (RACID 810) is also discussed and astronomical data taken with the ICID detector system demonstrating the photon event time-tagging mode of the system is also presented.

Stochastic Adaptive Estimation and Control.

DTIC Science & Technology

1994-10-26

Marcus, "Language Stability and Stabilizability of Discrete Event Dynamical Systems ," SIAM Journal on Control and Optimization, 31, September 1993...in the hierarchical control of flexible manufacturing systems ; in this problem, the model involves a hybrid process in continuous time whose state is...of the average cost control problem for discrete- time Markov processes. Our exposition covers from finite to Borel state and action spaces and

First-Principles Molecular Dynamics Studies of Organometallic Complexes and Homogeneous Catalytic Processes.

PubMed

Vidossich, Pietro; Lledós, Agustí; Ujaque, Gregori

2016-06-21

Computational chemistry is a valuable aid to complement experimental studies of organometallic systems and their reactivity. It allows probing mechanistic hypotheses and investigating molecular structures, shedding light on the behavior and properties of molecular assemblies at the atomic scale. When approaching a chemical problem, the computational chemist has to decide on the theoretical approach needed to describe electron/nuclear interactions and the composition of the model used to approximate the actual system. Both factors determine the reliability of the modeling study. The community dedicated much effort to developing and improving the performance and accuracy of theoretical approaches for electronic structure calculations, on which the description of (inter)atomic interactions rely. Here, the importance of the model system used in computational studies is highlighted through examples from our recent research focused on organometallic systems and homogeneous catalytic processes. We show how the inclusion of explicit solvent allows the characterization of molecular events that would otherwise not be accessible in reduced model systems (clusters). These include the stabilization of nascent charged fragments via microscopic solvation (notably, hydrogen bonding), transfer of charge (protons) between distant fragments mediated by solvent molecules, and solvent coordination to unsaturated metal centers. Furthermore, when weak interactions are involved, we show how conformational and solvation properties of organometallic complexes are also affected by the explicit inclusion of solvent molecules. Such extended model systems may be treated under periodic boundary conditions, thus removing the cluster/continuum (or vacuum) boundary, and require a statistical mechanics simulation technique to sample the accessible configurational space. First-principles molecular dynamics, in which atomic forces are computed from electronic structure calculations (namely, density functional theory), is certainly the technique of choice to investigate chemical events in solution. This methodology is well established and thanks to advances in both algorithms and computational resources simulation times required for the modeling of chemical events are nowadays accessible, though the computational requirements use to be high. Specific applications reviewed here include mechanistic studies of the Shilov and Wacker processes, speciation in Pd chemistry, hydrogen bonding to metal centers, and the dynamics of agostic interactions.

Dynamic ambulance reallocation for the reduction of ambulance response times using system status management.

PubMed

Lam, Sean Shao Wei; Zhang, Ji; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock

2015-02-01

Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly. Copyright © 2014 Elsevier Inc. All rights reserved.

A Data-Driven, Integrated Flare Model Based on Self-Organized Criticality

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.

2013-09-01

We interpret solar flares as events originating in solar active regions having reached the self-organized critical state, by alternatively using two versions of an "integrated flare model" - one static and one dynamic. In both versions the initial conditions are derived from observations aiming to investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. In the static model, we first apply a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular-automaton evolution rules. Subsequent loading and relaxation steps lead the system to self-organized criticality, after which the statistical properties of the simulated events are examined. In the dynamic version we deploy an enhanced driving mechanism, which utilizes the observed evolution of active regions, making use of sequential vector magnetograms. We first apply the static cellular automaton model to consecutive solar vector magnetograms until the self-organized critical state is reached. We then evolve the magnetic field inbetween these processed snapshots through spline interpolation, acting as a natural driver in the dynamic model. The identification of magnetically unstable sites as well as their relaxation follow the same rules as in the static model after each interpolation step. Subsequent interpolation/driving and relaxation steps cover all transitions until the end of the sequence. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately satisfied in both versions of the model. We obtain robust power laws in the distribution functions of the modelled flaring events with scaling indices in good agreement with observations. We therefore conclude that well-known statistical properties of flares are reproduced after active regions reach self-organized criticality. The significant enhancement in both the static and the dynamic integrated flare models is that they initiate the simulation from observations, thus facilitating energy calculation in physical units. Especially in the dynamic version of the model, the driving of the system is based on observed, evolving vector magnetograms, allowing for the separation between MHD and kinetic timescales through the assignment of distinct MHD timestamps to each interpolation step.

The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX): First results

NASA Astrophysics Data System (ADS)

Craig, George; Schäfler, Andreas; Ament, Felix; Arbogast, Philippe; Crewell, Susanne; Doyle, James; Hirsch, Lutz; Mayer, Bernhard; McTaggart-Cowan, Ron; Methven, John; Rahm, Stephan; Rautenhaus, Marc; Reitebuch, Oliver; Rivière, Gwendal; Vaughan, Geraint; Wendisch, Manfred; Wernli, Heini; Wirth, Martin; Witschas, Benjamin

2017-04-01

First results will be presented from the NAWDEX experiment, an international field campaign with the overall goal of increasing the physical understanding and quantifying the effects of diabatic processes on disturbances to the jet stream over the North Atlantic, their influence on downstream propagation, and consequences for high-impact weather in Europe. The campaign took place from 19 September to 18 October 2016, and deployed a variety of remote-sensing and in-situ instruments that provided an extraordinarily detailed picture of the interacting dynamics and thermodynamics. Thirteen intensive observation periods took place over the course of the campaign, including moisture inflow and diabatic processes in warm conveyor belts, cloud and dynamical structure in outflow and ridge-building events, as well as other events This presentation will briefly review the weather events that were observed during NAWDEX and give a preliminary evaluation of how the observations contribute to new understanding of midlatitude weather systems. As an example, an analysis of the structure and evolution of ex-Tropical Storm Karl will be presented. This system was observed by a sequence of aircraft flights over a period of six days, as it moved from the subtropics into the midlatitudes off the coast of North America, reintensified explosively as a midlatitude cyclone south of Greenland, and eventually contributed to poor precipitation forecasts for Norway.

Craton stability and continental lithosphere dynamics during plume-plate interaction

NASA Astrophysics Data System (ADS)

Wang, H.; Van Hunen, J.; Pearson, D.

2013-12-01

Survival of thick cratonic roots in a vigorously convecting mantle system for billions of years has long been studied by the geodynamical community. A high cratonic root strength is generally considered to be the most important factor. We first perform and discuss new numerical models to investigate craton stability in both Newtonian and non-Newtonian rheology in the stagnant lid regime. The results show that only a modest compositional rheological factor of Δη=10 with non-Newtonian rheology is required for the survival of cratonic roots in a stagnant lid regime. A larger rheological factor (100 or more) is needed to maintain similar craton longevity in a Newtonian rheology environment. Furthermore, chemical buoyancy plays an important role on craton stability and its evolution, but could only work with suitable compositional rheology. During their long lifespan, cratons experienced a suite of dynamic, tectonothermal events, such as nearby subduction and mantle plume activity. Cratonic nuclei are embedded in shorter-lived, more vulnerable continental areas of different thickness, composition and rheology, which would influence the lithosphere dynamic when tectonothermal events happen nearby. South Africa provides a very good example to investigate such dynamic processes as it hosts several cratons and there are many episodic thermal events since the Mesozoic as indicated by a spectrum of magmatic activity. We numerically investigate such an integrated system using the topographic evolution of cratons and surrounding lithosphere as a diagnostic observable. The post-70Ma thinning of pericratonic lithosphere by ~50km around Kaapvaal craton (Mather et al., 2011) is also investigated through our numerical models. The results show that the pericratonic lithosphere cools and grows faster than cratons do, but is also more likely to be effected by episodic thermal events. This leads to surface topography change that is significantly larger around the craton than within the craton itself. Given the considerable debate on the uplift history of southern African plateau (Nyblade and Sleep, 2003), our numerical models that encompass lithospheric heterogeneity within cratons could help to achieve a better understanding of this issue.

Visualizing Parallel Computer System Performance

NASA Technical Reports Server (NTRS)

Malony, Allen D.; Reed, Daniel A.

1988-01-01

Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

Reducing usage of the computational resources by event driven approach to model predictive control

NASA Astrophysics Data System (ADS)

Misik, Stefan; Bradac, Zdenek; Cela, Arben

2017-08-01

This paper deals with a real-time and optimal control of dynamic systems while also considers the constraints which these systems might be subject to. Main objective of this work is to propose a simple modification of the existing Model Predictive Control approach to better suit needs of computational resource-constrained real-time systems. An example using model of a mechanical system is presented and the performance of the proposed method is evaluated in a simulated environment.

On line instrument systems for monitoring steam turbogenerators

NASA Astrophysics Data System (ADS)

Clapis, A.; Giorgetti, G.; Lapini, G. L.; Benanti, A.; Frigeri, C.; Gadda, E.; Mantino, E.

A computerized real time data acquisition and data processing for the diagnosis of malfunctioning of steam turbogenerator systems is described. Pressure, vibration and temperature measurements are continuously collected from standard or special sensors including startup or stop events. The architecture of the monitoring system is detailed. Examples of the graphics output are presented. It is shown that such a system allows accurate diagnosis and the possibility of creating a data bank to describe the dynamic characteristics of the machine park.

THYME: Toolkit for Hybrid Modeling of Electric Power Systems

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

Nutaro Kalyan Perumalla, James Joseph

2011-01-01

THYME is an object oriented library for building models of wide area control and communications in electric power systems. This software is designed as a module to be used with existing open source simulators for discrete event systems in general and communication systems in particular. THYME consists of a typical model for simulating electro-mechanical transients (e.g., as are used in dynamic stability studies), data handling objects to work with CDF and PTI formatted power flow data, and sample models of discrete sensors and controllers.

Detection of timescales in evolving complex systems

PubMed Central

Darst, Richard K.; Granell, Clara; Arenas, Alex; Gómez, Sergio; Saramäki, Jari; Fortunato, Santo

2016-01-01

Most complex systems are intrinsically dynamic in nature. The evolution of a dynamic complex system is typically represented as a sequence of snapshots, where each snapshot describes the configuration of the system at a particular instant of time. This is often done by using constant intervals but a better approach would be to define dynamic intervals that match the evolution of the system’s configuration. To this end, we propose a method that aims at detecting evolutionary changes in the configuration of a complex system, and generates intervals accordingly. We show that evolutionary timescales can be identified by looking for peaks in the similarity between the sets of events on consecutive time intervals of data. Tests on simple toy models reveal that the technique is able to detect evolutionary timescales of time-varying data both when the evolution is smooth as well as when it changes sharply. This is further corroborated by analyses of several real datasets. Our method is scalable to extremely large datasets and is computationally efficient. This allows a quick, parameter-free detection of multiple timescales in the evolution of a complex system. PMID:28004820

Time-dependent inertia analysis of vehicle mechanisms

NASA Astrophysics Data System (ADS)

Salmon, James Lee

Two methods for performing transient inertia analysis of vehicle hardware systems are developed in this dissertation. The analysis techniques can be used to predict the response of vehicle mechanism systems to the accelerations associated with vehicle impacts. General analytical methods for evaluating translational or rotational system dynamics are generated and evaluated for various system characteristics. The utility of the derived techniques are demonstrated by applying the generalized methods to two vehicle systems. Time dependent acceleration measured during a vehicle to vehicle impact are used as input to perform a dynamic analysis of an automobile liftgate latch and outside door handle. Generalized Lagrange equations for a non-conservative system are used to formulate a second order nonlinear differential equation defining the response of the components to the transient input. The differential equation is solved by employing the fourth order Runge-Kutta method. The events are then analyzed using commercially available two dimensional rigid body dynamic analysis software. The results of the two analytical techniques are compared to experimental data generated by high speed film analysis of tests of the two components performed on a high G acceleration sled at Ford Motor Company.

Listening in on Friction: Stick-Slip Acoustical Signatures in Velcro

NASA Astrophysics Data System (ADS)

Hurtado Parra, Sebastian; Morrow, Leslie; Radziwanowski, Miles; Angiolillo, Paul

2013-03-01

The onset of kinetic friction and the possible resulting stick-slip motion remain mysterious phenomena. Moreover, stick-slip dynamics are typically accompanied by acoustic bursts that occur temporally with the slip event. The dry sliding dynamics of the hook-and-loop system, as exemplified by Velcro, manifest stick-slip behavior along with audible bursts that are easily micrphonically collected. Synchronized measurements of the friction force and acoustic emissions were collected as hooked Velcro was driven at constant velocity over a bed of looped Velcro in an anechoic chamber. Not surprising, the envelope of the acoustic bursts maps well onto the slip events of the friction force time series and the intensity of the bursts trends with the magnitude of the difference of the friction force during a stick-slip event. However, the analysis of the acoustic emission can serve as a sensitive tool for revealing some of the hidden details of the evolution of the transition from static to kinetic friction. For instance, small acoustic bursts are seen prior to the Amontons-Coulomb threshold, signaling precursor events prior to the onset of macroscopically observed motion. Preliminary spectral analysis of the acoustic emissions including intensity-frequency data will be presented.

An analysis of high-impact, low-predictive skill severe weather events in the northeast U.S

NASA Astrophysics Data System (ADS)

Vaughan, Matthew T.

An objective evaluation of Storm Prediction Center slight risk convective outlooks, as well as a method to identify high-impact severe weather events with poor-predictive skill are presented in this study. The objectives are to assess severe weather forecast skill over the northeast U.S. relative to the continental U.S., build a climatology of high-impact, low-predictive skill events between 1980--2013, and investigate the dynamic and thermodynamic differences between severe weather events with low-predictive skill and high-predictive skill over the northeast U.S. Severe storm reports of hail, wind, and tornadoes are used to calculate skill scores including probability of detection (POD), false alarm ratio (FAR) and threat scores (TS) for each convective outlook. Low predictive skill events are binned into low POD (type 1) and high FAR (type 2) categories to assess temporal variability of low-predictive skill events. Type 1 events were found to occur in every year of the dataset with an average of 6 events per year. Type 2 events occur less frequently and are more common in the earlier half of the study period. An event-centered composite analysis is performed on the low-predictive skill database using the National Centers for Environmental Prediction Climate Forecast System Reanalysis 0.5° gridded dataset to analyze the dynamic and thermodynamic conditions prior to high-impact severe weather events with varying predictive skill. Deep-layer vertical shear between 1000--500 hPa is found to be a significant discriminator in slight risk forecast skill where high-impact events with less than 31-kt shear have lower threat scores than high-impact events with higher shear values. Case study analysis of type 1 events suggests the environment over which severe weather occurs is characterized by high downdraft convective available potential energy, steep low-level lapse rates, and high lifting condensation level heights that contribute to an elevated risk of severe wind.

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Pressure wave charged repetitively pulsed gas laser

DOEpatents

Kulkarny, Vijay A.

1982-01-01

A repetitively pulsed gas laser in which a system of mechanical shutters bracketing the laser cavity manipulate pressure waves resulting from residual energy in the cavity gas following a lasing event so as to draw fresh gas into the cavity and effectively pump spent gas in a dynamic closed loop.

A Pulsatile Cardiovascular Computer Model for Teaching Heart-Blood Vessel Interaction.

ERIC Educational Resources Information Center

Campbell, Kenneth; And Others

1982-01-01

Describes a model which gives realistic predictions of pulsatile pressure, flow, and volume events in the cardiovascular system. Includes computer oriented laboratory exercises for veterinary and graduate students; equations of the dynamic and algebraic models; and a flow chart for the cardiovascular teaching program. (JN)

Moving Stormwater Infrastructure from Real-time Control to Smart Systems

NASA Astrophysics Data System (ADS)

Wadzuk, B.; Bryant, S.; Lewellyn, C.; Zaremba, G.; Traver, R.

2017-12-01

Urban areas, especially combined sewer communities, are using green infrastructure (GI) systems (e.g. rain gardens, green roofs) to mitigate stormwater runoff volume, rate, and quality issues. Most municipal guidance and regulation limits these systems to static, passive designs that neither fully utilize the active hydrology of a GI system during and after a rainfall event, nor enable dynamic operational control. Real-time control (RTC) applied to GI is emerging, and under ideal model conditions has shown improved performance (i.e., greater volumes managed while minimizing downstream impact). There are a few RTC pilot field projects with promising results, such as on a cistern - green roof system there were only 30 overflow events out of 126 rain events and at a rain garden - cistern system only 1 of 81 events resulted in overflow. However, RTC does not get to a fully dynamic system as the initiation and consequent action is preset and static. In stormwater RTC systems, the initiation is typically a rain forecast or a sensor reading. At a rain garden - cistern system, a cistern that fills when raining is hard set to pump water to the rain garden 24 hours after the predicted rain ends. There have been instances where there is rain occurring or only a minimal amount of dry time for the rain garden to reestablish capacity for the pumped stored water. There is also no mechanism to automatically change the pump initiation time based on season or ambient conditions. A cistern - green roof system that uses stored water in an upstream cistern for green roof irrigation is initiated on a set soil moisture reading or a set irrigation volume daily. The soil moisture reading was rarely reached, so irrigation was often not initiated and the set daily irrigation volume did not vary over season. Moving from RTC to a smart system uses longer term and/or historical data to inform decisions beyond what a short-term forecast or real-time sensor can provide to give more context and flexibility in the initiation - consequent action logic. The use of the Standardized Precipitation Evapotranspiration Index as a back-cast and forecast tool to calculate an appropriate irrigation volume based on what rainfall is pending and whether the system is in drought state is used and discussed to move the GI systems into smart control.

Low-Frequency Extensions of the Saturn Kilometric Radiation as a Proxy for Magnetospheric Dynamics

NASA Astrophysics Data System (ADS)

Reed, J. J.; Jackman, C. M.; Lamy, L.; Kurth, W. S.; Whiter, D. K.

2018-01-01

Saturn Kilometric Radiation (SKR) is an auroral radio emission which can be detected quasi-continuously by the Cassini spacecraft. It has been shown to respond to magnetotail reconnection and to changes in solar wind conditions and thus offers the potential to be used as a remote proxy for magnetospheric dynamics. This work has developed criteria for the selection of low-frequency extensions (LFEs), powerful intensifications of the main SKR emission, accompanied by an expansion of the SKR to lower frequencies. Upon examination of data from the Cassini Radio and Plasma Wave Science instrument, we detect 282 LFE events which are further grouped into two categories. Shorter events (<20 h) associated with tail reconnection have a median waiting time of ˜10 h, a median duration of 3.1 h and a strong correlation with the northern and southern SKR phase systems. The 60% of the short LFEs have a reconnection event within the preceding 6 h. Longer events (>20 h), associated with increases in solar wind dynamic pressure, can last multiple planetary rotations, have a median waiting time of ˜20 days, and show no relationship with SKR phase. An analysis of the power emitted during LFEs suggests that tail reconnection is not always observed or detected in situ which may partially explain the low correlation between LFEs and tail reconnection. We conclude that short LFEs are a good proxy for reconnection in the tail.

Towards Smart Grid Dynamic Ratings

NASA Astrophysics Data System (ADS)

Cheema, Jamal; Clark, Adrian; Kilimnik, Justin; Pavlovski, Chris; Redman, David; Vu, Maria

2011-08-01

The energy distribution industry is giving greater attention to smart grid solutions as a means for increasing the capabilities, efficiency and reliability of the electrical power network. The smart grid makes use of intelligent monitoring and control devices throughout the distribution network to report on electrical properties such as voltage, current and power, as well as raising network alarms and events. A further aspect of the smart grid embodies the dynamic rating of electrical assets of the network. This fundamentally involves a rating of the load current capacity of electrical assets including feeders, transformers and switches. The mainstream approach to rate assets is to apply the vendor plate rating, which often under utilizes assets, or in some cases over utilizes when environmental conditions reduce the effective rated capacity, potentially reducing lifetime. Using active intelligence we have developed a rating system that rates assets in real time based upon several events. This allows for a far more efficient and reliable electrical grid that is able to extend further the life and reliability of the electrical network. In this paper we describe our architecture, the observations made during development and live deployment of the solution into operation. We also illustrate how this solution blends with the smart grid by proposing a dynamic rating system for the smart grid.

Using natural archives to detect climate and environmental tipping points in the Earth System

NASA Astrophysics Data System (ADS)

Thomas, Zoë A.

2016-11-01

'Tipping points' in the Earth system are characterised by a nonlinear response to gradual forcing, and may have severe and wide-ranging impacts. Many abrupt events result from simple underlying system dynamics termed 'critical transitions' or 'bifurcations'. One of the best ways to identify and potentially predict threshold behaviour in the climate system is through analysis of natural ('palaeo') archives. Specifically, on the approach to a tipping point, early warning signals can be detected as characteristic fluctuations in a time series as a system loses stability. Testing whether these early warning signals can be detected in highly complex real systems is a key challenge, since much work is either theoretical or only tested with simple models. This is particularly problematic in palaeoclimate and palaeoenvironmental records with low resolution, non-equidistant data, which can limit accurate analysis. Here, a range of different datasets are examined to explore generic rules that can be used to detect such dramatic events. A number of key criteria are identified to be necessary for the reliable identification of early warning signals in natural archives, most crucially, the need for a low-noise record of sufficient data length, resolution and accuracy. A deeper understanding of the underlying system dynamics is required to inform the development of more robust system-specific indicators, or to indicate the temporal resolution required, given a known forcing. This review demonstrates that time series precursors from natural archives provide a powerful means of forewarning tipping points within the Earth System.

Adjustable Autonomy Testbed

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schrenkenghost, Debra K.

2001-01-01

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Stress imparted by the great 2004 Sumatra earthquake shut down transforms and activated rifts up to 400 km away in the Andaman Sea

USGS Publications Warehouse

Sevilgen, Volkan; Stein, Ross S.; Pollitz, Fred F.

2012-01-01

The origin and prevalence of triggered seismicity and remote aftershocks are under debate. As a result, they have been excluded from probabilistic seismic hazard assessment and aftershock hazard notices. The 2004 M = 9.2 Sumatra earthquake altered seismicity in the Andaman backarc rift-transform system. Here we show that over a 300-km-long largely transform section of the backarc, M≥4.5 earthquakes stopped for five years, and over a 750-km-long backarc section, the rate of transform events dropped by two-thirds, while the rate of rift events increased eightfold. We compute the propagating dynamic stress wavefield and find the peak dynamic Coulomb stress is similar on the rifts and transforms. Long-period dynamic stress amplitudes, which are thought to promote dynamic failure, are higher on the transforms than on the rifts, opposite to the observations. In contrast to the dynamic stress, we calculate that the mainshock brought the transform segments approximately 0.2 bar (0.02 MPa) farther from static Coulomb failure and the rift segments approximately 0.2 bar closer to static failure, consistent with the seismic observations. This accord means that changes in seismicity rate are sufficiently predictable to be included in post-mainshock hazard evaluations.

Stress imparted by the great 2004 Sumatra earthquake shut down transforms and activated rifts up to 400 km away in the Andaman Sea

USGS Publications Warehouse

Sevilgen, Volkan; Stein, Ross S.; Pollitz, Fred F.

2012-01-01

The origin and prevalence of triggered seismicity and remote aftershocks are under debate. As a result, they have been excluded from probabilistic seismic hazard assessment and aftershock hazard notices. The 2004 M = 9.2 Sumatra earthquake altered seismicity in the Andaman backarc rift-transform system. Here we show that over a 300-km-long largely transform section of the backarc, M ≥ 4.5 earthquakes stopped for five years, and over a 750-km-long backarc section, the rate of transform events dropped by two-thirds, while the rate of rift events increased eightfold. We compute the propagating dynamic stress wavefield and find the peak dynamic Coulomb stress is similar on the rifts and transforms. Long-period dynamic stress amplitudes, which are thought to promote dynamic failure, are higher on the transforms than on the rifts, opposite to the observations. In contrast to the dynamic stress, we calculate that the mainshock brought the transform segments approximately 0.2 bar (0.02 MPa) farther from static Coulomb failure and the rift segments approximately 0.2 bar closer to static failure, consistent with the seismic observations. This accord means that changes in seismicity rate are sufficiently predictable to be included in post-mainshock hazard evaluations.

Structural transitions and hysteresis in clump- and stripe-forming systems under dynamic compression.

PubMed

McDermott, Danielle; Olson Reichhardt, Cynthia J; Reichhardt, Charles

2016-11-28

Using numerical simulations, we study the dynamical evolution of particles interacting via competing long-range repulsion and short-range attraction in two dimensions. The particles are compressed using a time-dependent quasi-one dimensional trough potential that controls the local density, causing the system to undergo a series of structural phase transitions from a low density clump lattice to stripes, voids, and a high density uniform state. The compression proceeds via slow elastic motion that is interrupted with avalanche-like bursts of activity as the system collapses to progressively higher densities via plastic rearrangements. The plastic events vary in magnitude from small rearrangements of particles, including the formation of quadrupole-like defects, to large-scale vorticity and structural phase transitions. In the dense uniform phase, the system compresses through row reduction transitions mediated by a disorder-order process. We characterize the rearrangement events by measuring changes in the potential energy, the fraction of sixfold coordinated particles, the local density, and the velocity distribution. At high confinements, we find power law scaling of the velocity distribution during row reduction transitions. We observe hysteresis under a reversal of the compression when relatively few plastic rearrangements occur. The decompressing system exhibits distinct phase morphologies, and the phase transitions occur at lower compression forces as the system expands compared to when it is compressed.

Structural transitions and hysteresis in clump- and stripe-forming systems under dynamic compression

DOE PAGES

McDermott, Danielle; Olson Reichhardt, Cynthia J.; Reichhardt, Charles

2016-11-11

In using numerical simulations, we study the dynamical evolution of particles interacting via competing long-range repulsion and short-range attraction in two dimensions. The particles are compressed using a time-dependent quasi-one dimensional trough potential that controls the local density, causing the system to undergo a series of structural phase transitions from a low density clump lattice to stripes, voids, and a high density uniform state. The compression proceeds via slow elastic motion that is interrupted with avalanche-like bursts of activity as the system collapses to progressively higher densities via plastic rearrangements. The plastic events vary in magnitude from small rearrangements ofmore » particles, including the formation of quadrupole-like defects, to large-scale vorticity and structural phase transitions. In the dense uniform phase, the system compresses through row reduction transitions mediated by a disorder-order process. We also characterize the rearrangement events by measuring changes in the potential energy, the fraction of sixfold coordinated particles, the local density, and the velocity distribution. At high confinements, we find power law scaling of the velocity distribution during row reduction transitions. We observe hysteresis under a reversal of the compression when relatively few plastic rearrangements occur. The decompressing system exhibits distinct phase morphologies, and the phase transitions occur at lower compression forces as the system expands compared to when it is compressed.« less

Multi-event capture–recapture modeling of host–pathogen dynamics among European rabbit populations exposed to myxoma and Rabbit Hemorrhagic Disease Viruses: common and heterogeneous patterns

PubMed Central

2014-01-01

Host–pathogen epidemiological processes are often unclear due both to their complexity and over-simplistic approaches used to quantify them. We applied a multi-event capture–recapture procedure on two years of data from three rabbit populations to test hypotheses about the effects on survival of, and the dynamics of host immunity to, both myxoma virus and Rabbit Hemorrhagic Disease Virus (MV and RHDV). Although the populations shared the same climatic and management conditions, MV and RHDV dynamics varied greatly among them; MV and RHDV seroprevalences were positively related to density in one population, but RHDV seroprevalence was negatively related to density in another. In addition, (i) juvenile survival was most often negatively related to seropositivity, (ii) RHDV seropositives never had considerably higher survival, and (iii) seroconversion to seropositivity was more likely than the reverse. We suggest seropositivity affects survival depending on trade-offs among antibody protection, immunosuppression and virus lethality. Negative effects of seropositivity might be greater on juveniles due to their immature immune system. Also, while RHDV directly affects survival through the hemorrhagic syndrome, MV lack of direct lethal effects means that interactions influencing survival are likely to be more complex. Multi-event modeling allowed us to quantify patterns of host–pathogen dynamics otherwise difficult to discern. Such an approach offers a promising tool to shed light on causative mechanisms. PMID:24708296

Meta-T: TetrisⓇ as an experimental paradigm for cognitive skills research.

PubMed

Lindstedt, John K; Gray, Wayne D

2015-12-01

Studies of human performance in complex tasks using video games are an attractive prospect, but many existing games lack a comprehensive way to modify the game and track performance beyond basic levels of analysis. Meta-T provides experimenters a tool to study behavior in a dynamic task environment with time-stressed decision-making and strong perceptual-motor elements, offering a host of experimental manipulations with a robust and detailed logging system for all user events, system events, and screen objects. Its experimenter-friendly interface provides control over detailed parameters of the task environment without need for programming expertise. Support for eye-tracking and computational cognitive modeling extend the paradigm's scope.

Lava Eruption and Emplacement: Using Clues from Hawaii and Iceland to Probe the Lunar Past

NASA Technical Reports Server (NTRS)

Needham, Debra Hurwitz; Hamilton, C. W.; Bleacher, J. E.; Whelley, P. L.; Young, K. E.; Scheidt, S. P.; Richardson, J. A.; Sutton, S. S.

2017-01-01

Investigating recent eruptions on Earth is crucial to improving understanding of relationships between eruption dynamics and final lava flow morphologies. In this study, we investigated eruptions in Holuhraun, Iceland, and Kilauea, Hawaii to gain insight into the lava dynamics near the source vent, the initiation of lava channels, and the origin of down-channel features. Insights are applied to Rima Bode on the lunar nearside to deduce the sequence of events that formed this lunar sinuous rille system. These insights are crucial to correctly interpreting whether the volcanic features associated with Rima Bode directly relate to eruption conditions at the vent and, thus, can help us understand those eruption dynamics, or, alternatively, whether the features formed as a result of more localized influences on lava flow dynamics. For example, if the lava channel developed early in the eruption and was linked to pulses in vent activity, its morphology can be analyzed to interpret the flux and duration of the eruption. Conversely, if the lava channel initiated late in the eruption as the result of a catastrophic breaching of lava that had previously pooled within the vent [e.g., 1], then the final channel morphology will not indicate eruption dynamics but rather local dynamics associated with that breach event. Distinguishing between these two scenarios is crucial for correctly interpreting the intensity and duration of volcanic history on the Moon.

Lava Eruption and Emplacement: Using Clues from Hawaii and Iceland to Probe the Lunar Past

NASA Technical Reports Server (NTRS)

Needham, D. H.; Hamilton, C. W.; Bleacher, J. E.; Whelley, P. L.; Young, K. E.; Scheidt, S. P.; Richardson, J. A.; Sutton, S. S.

2017-01-01

Investigating recent eruptions on Earth is crucial to improving understanding of relationships between eruption dynamics and final lava flow morphologies. In this study, we investigated eruptions in Holuhraun, Iceland, and Kilauea, Hawaii to gain insight into the lava dynamics near the source vent, the initiation of lava channels, and the origin of down-channel features. Insights are applied to Rima Bode on the lunar nearside to deduce the sequence of events that formed this lunar sinuous rille system.These insights are crucial to correctly interpreting whether the volcanic features associated with Rima Bode directly relate to eruption conditions at the vent and, thus, can help us understand those eruption dynamics, or, alternatively, whether the features formed as a result of more localized influences on lava flow dynamics. For example, if the lava channel developed early in the eruption and was linked to pulses in vent activity, its morphology can be analyzed to interpret the flux and duration of the eruption. Conversely, if the lava channel initiated late in the eruption as the result of a catastrophic breaching of lava that had previously pooled within the vent [e.g., 1], then the final channel morphology will not indicate eruption dynamics but rather local dynamics associated with that breach event. Distinguishing between these two scenarios is crucial for correctly interpreting the intensity and duration of volcanic history on the Moon.

The dynamic simulation of the Progetto Energia combined cycle power plants

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

Giglio, R.; Cerabolini, M.; Pisacane, F.

1996-12-31

Over the next four years, the Progetto Energia project is building several cogeneration plants to satisfy the increasing demands of Italy`s industrial complex and the country`s demand for electrical power. Located at six different sites within Italy`s borders these Combined Cycle Cogeneration Plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50 MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipmentmore » performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam de-superheating performance. Simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The paper discusses the Combined Cycle plant configuration, its operating modes and control system, the dynamic model representation, the simulation results and project benefits.« less

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.

Fungal Iron Availability during Deep Seated Candidiasis Is Defined by a Complex Interplay Involving Systemic and Local Events

PubMed Central

Potrykus, Joanna; Stead, David; MacCallum, Donna M.; Urgast, Dagmar S.; Raab, Andrea; van Rooijen, Nico; Feldmann, Jörg; Brown, Alistair J. P.

2013-01-01

Nutritional immunity – the withholding of nutrients by the host – has long been recognised as an important factor that shapes bacterial-host interactions. However, the dynamics of nutrient availability within local host niches during fungal infection are poorly defined. We have combined laser ablation-inductively coupled plasma mass spectrometry (LA-ICP MS), MALDI imaging and immunohistochemistry with microtranscriptomics to examine iron homeostasis in the host and pathogen in the murine model of systemic candidiasis. Dramatic changes in the renal iron landscape occur during disease progression. The infection perturbs global iron homeostasis in the host leading to iron accumulation in the renal medulla. Paradoxically, this is accompanied by nutritional immunity in the renal cortex as iron exclusion zones emerge locally around fungal lesions. These exclusion zones correlate with immune infiltrates and haem oxygenase 1-expressing host cells. This local nutritional immunity decreases iron availability, leading to a switch in iron acquisition mechanisms within mature fungal lesions, as revealed by laser capture microdissection and qRT-PCR analyses. Therefore, a complex interplay of systemic and local events influences iron homeostasis and pathogen-host dynamics during disease progression. PMID:24146619

Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

NASA Astrophysics Data System (ADS)

Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

2016-11-01

Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

Killing mediated spatial structure in V. Cholerae biofilms

NASA Astrophysics Data System (ADS)

Yanni, David

Most bacteria live in biofilms, which are implicated in 60 - 80 % of microbial infections in the body. The spatial structure of a biofilm confers advantages to its member-cells, such as antibiotic resistance, and is strongly affected by competition between strains and taxa. However, A complete picture of how competition affects the self-organized structure of these complex, far-from-equilibrium systems, is yet to emerge. To that end, we investigate phase separation dynamics driven by T6SS-facilitated bacterial warfare in a system composed of two strains of mutually antagonistic V. cholerae. T6SS is a contact mediated killing mechanism present in 25 % of all gram negative bacteria, and has been shown by recent work to play a major role in the spatial assortment of biofilms. T6SS events induce lysis, causing variations in local mechanical pressure, and acting as thermalizing events. We study cells immobilized in biofilms at the air-solid interface, so our experimental system represents a different type active matter, wherein activity is due to cell death and reproduction, not mobility. Here, we show how that activity imposes a constraint of minimal curvature on strain-strain interfaces; an effective Laplace pressure is characterized which governs interfacial dynamics.

Dynamical and thermodynamic processes contributing to thundersnow events over the northeast U.S

NASA Astrophysics Data System (ADS)

Meier, Kyle J.

Thundersnow often occurs in conjunction with mesoscale snowbands and may be associated with regions of locally heavy snowfall (15--30 cm) and intense snowfall rates (5--10 cm/h). The availability of the National Lightning Detection Network (NLDN) system and operational Doppler weather radars during the past 20 years has allowed meteorologists to produce comprehensive national lightning maps and to identify localized areas of enhanced snowfall associated with thundersnow. The purpose of this thesis is to take advantage of the NLDN data and other contemporary observing systems in order to construct climatological, composite, and case study analyses of the atmospheric environment during thundersnow occurrence. Emphasis was placed on determining the dynamical and thermodynamic processes that contribute to thundersnow events over the northeast U.S. All instances of thundersnow in the contiguous U.S. spanning the years 1994--2012 were identified from archived METAR observations. The Intermountain West, central U.S., Great Lakes, and New England coast were determined to be preferred regions for thundersnow occurrence in the contiguous U.S. Separately, all Nor'easter and lake-effect thundersnow events in the northeast U.S. during 1994--2011 were subjectively identified using surface weather map, radar reflectivity, and NLDN data. Gridded data from the 0.5° resolution NCEP Climate Forecast System Reanalysis were used to construct composite and case study analyses in order to identify common environmental features associated with each thundersnow event type. Results from the composite and case study analyses indicate that snowbands associated with Nor'easter thundersnow events often occur within a region of strong quasi-geostrophic forcing for ascent and frontogenesis in the presence of conditional or conditional symmetric instability. Lake-effect thundersnow events tend to occur in the presence of a prevailing wind that parallels the long axis of the lake, steep lapse rates, and the passage of a midlevel short-wave trough. Both thundersnow event types exhibit near-saturated conditions within the lower-to-middle troposphere and large upward vertical velocities that intersect the dendritic growth zone and mixed-phase regions, consistent with intense snowfall rates and lightning generation. Individual case studies for both event types were associated with relatively small (< 300 J/kg -1) CAPE values.

On the transient dynamics of piezoelectric-based, state-switched systems

NASA Astrophysics Data System (ADS)

Lopp, Garrett K.; Kelley, Christopher R.; Kauffman, Jeffrey L.

2018-01-01

This letter reports on the induced mechanical transients for piezoelectric-based, state-switching approaches utilizing both experimental tests and a numerical model that more accurately captures the dynamics associated with a switch between stiffness states. Currently, switching models instantaneously dissipate the stored piezoelectric voltage, resulting in a discrete change in effective stiffness states and a discontinuity in the system dynamics during the switching event. The proposed model allows for a rapid but continuous voltage dissipation and the corresponding variation between stiffness states, as one sees in physical implementations. This rapid variation in system stiffness when switching at a point of non-zero strain leads to high-frequency, large-amplitude transients in the system acceleration response. Utilizing a fundamental piezoelectric bimorph, a comparison between the numerical and experimental results reveals that these mechanical transients are much stronger than originally anticipated and masked by measurement hardware limitations, thus highlighting the significance of an appropriate system model governing the switch dynamics. Such a model enables designers to analyze systems that incorporate piezoelectric-based state switching with greater accuracy to ensure that these transients do not degrade the intended performance. Finally, if the switching does create unacceptable transients, controlling the duration of voltage dissipation enables control over the frequency content and peak amplitudes associated with the switch-induced acceleration transients.

Modulations of 'late' event-related brain potentials in humans by dynamic audiovisual speech stimuli.

PubMed

Lebib, Riadh; Papo, David; Douiri, Abdel; de Bode, Stella; Gillon Dowens, Margaret; Baudonnière, Pierre-Marie

2004-11-30

Lipreading reliably improve speech perception during face-to-face conversation. Within the range of good dubbing, however, adults tolerate some audiovisual (AV) discrepancies and lipreading, then, can give rise to confusion. We used event-related brain potentials (ERPs) to study the perceptual strategies governing the intermodal processing of dynamic and bimodal speech stimuli, either congruently dubbed or not. Electrophysiological analyses revealed that non-coherent audiovisual dubbings modulated in amplitude an endogenous ERP component, the N300, we compared to a 'N400-like effect' reflecting the difficulty to integrate these conflicting pieces of information. This result adds further support for the existence of a cerebral system underlying 'integrative processes' lato sensu. Further studies should take advantage of this 'N400-like effect' with AV speech stimuli to open new perspectives in the domain of psycholinguistics.

Raman imaging of molecular dynamics during cellular events

NASA Astrophysics Data System (ADS)

Fujita, Katsumasa

2017-07-01

To overcome the speed limitation in Raman imaging, we have developed a microscope system that detects Raman spectra from hundreds of points in a sample simultaneously. The sample was illuminated by a line-shaped focus, and Raman scattering from the illuminated positions was measured simultaneously by an imaging spectrophotometer. We applied the line-illumination technique to observe the dynamics of intracellular molecules during cellular events. We found that intracellular cytochrome c can be clearly imaged by resonant Raman scattering. We demonstrated label-free imaging of redistribution of cytochrome c during apoptosis and osteoblastic mineralization. We also proposed alkyne-tagged Raman imaging to observe small molecules in living cells. Due to its small size and the unique Raman band, alkyne can tag molecules without strong perturbation to molecular functions and with the capability to be detected separately from endogenous molecules.

Retrospective Analysis of Communication Events - Understanding the Dynamics of Collaborative Multi-Party Discourse

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

Cowell, Andrew J.; Haack, Jereme N.; McColgin, Dave W.

2006-06-08

This research is aimed at understanding the dynamics of collaborative multi-party discourse across multiple communication modalities. Before we can truly make sig-nificant strides in devising collaborative communication systems, there is a need to understand how typical users utilize com-putationally supported communications mechanisms such as email, instant mes-saging, video conferencing, chat rooms, etc., both singularly and in conjunction with traditional means of communication such as face-to-face meetings, telephone calls and postal mail. Attempting to un-derstand an individual’s communications profile with access to only a single modal-ity is challenging at best and often futile. Here, we discuss the development of RACE –more » Retrospective Analysis of Com-munications Events – a test-bed prototype to investigate issues relating to multi-modal multi-party discourse.« less

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

"Price-quakes" shaking the world's stock exchanges.

PubMed

Andersen, Jørgen Vitting; Nowak, Andrzej; Rotundo, Giulia; Parrott, Lael; Martinez, Sebastian

2011-01-01

Systemic risk has received much more awareness after the excessive risk taking by major financial instituations pushed the world's financial system into what many considered a state of near systemic failure in 2008. The IMF for example in its yearly 2009 Global Financial Stability Report acknowledged the lack of proper tools and research on the topic. Understanding how disruptions can propagate across financial markets is therefore of utmost importance. Here, we use empirical data to show that the world's markets have a non-linear threshold response to events, consistent with the hypothesis that traders exhibit change blindness. Change blindness is the tendency of humans to ignore small changes and to react disproportionately to large events. As we show, this may be responsible for generating cascading events--pricequakes--in the world's markets. We propose a network model of the world's stock exchanges that predicts how an individual stock exchange should be priced in terms of the performance of the global market of exchanges, but with change blindness included in the pricing. The model has a direct correspondence to models of earth tectonic plate movements developed in physics to describe the slip-stick movement of blocks linked via spring forces. We have shown how the price dynamics of the world's stock exchanges follows a dynamics of build-up and release of stress, similar to earthquakes. The nonlinear response allows us to classify price movements of a given stock index as either being generated internally, due to specific economic news for the country in question, or externally, by the ensemble of the world's stock exchanges reacting together like a complex system. The model may provide new insight into the origins and thereby also prevent systemic risks in the global financial network.

Tests of the Attachment and Developmental Dynamic Systems Theory of Crime (ADDSTOC): Toward a Differential RDoC Diagnostic and Treatment Approach.

PubMed

Lindberg, Marc A; Zeid, Dana

2018-01-01

The Attachment and Developmental Dynamic Systems Theory of Crime was tested on 206 male inmates. They completed measures tapping attachments, clinical issues, adverse childhood events, peer crime, and crime addictions. A significant path model was found, going from insecure parental attachments to adverse childhood events, and then on to the behavioral crime addiction and criminal peers scales. Peer crime was also predicted by insecure parent attachments and the crime addiction scale. Finally, the crime addiction, peer crime, and insecure parental attachment scales predicted frequencies of criminal behavior. The model also fit a sample of 239 female inmates. The notions of crime addiction, in this context of adverse events and insecure parental attachments, offered newer and more powerful explanations than previously offered by social learning theories on why some individuals are more likely to associate with peers engaging in criminal behavior, and also how these combine to predict degrees of criminal behavior. By moving beyond main effects models, it was found that a focus on systems of interactions was robust in theory and application. However, profile data from the Attachment and Clinical Issues Questionnaire showed that individual differences in Research Domain Criteria diagnoses are fundamental to treatment settings. Such approaches to reducing rates of recidivism and substance abuse should also enhance outcomes in many domains, including HIV prevention, costs to health care, and at the same time increase overall public safety.

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

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

Auld, Joshua; Hope, Michael; Ley, Hubert

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typicallymore » done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.« less

Rapamycin-based inducible translocation systems for studying phagocytosis.

PubMed

Bohdanowicz, Michal; Fairn, Gregory D

2011-01-01

Phagocytosis is an immune receptor-mediated process whereby cells engulf large particles. The process is dynamic and requires several localized factors acting in concert with and sequentially after the engagement of immune receptors to envelope the particle. Once the particle is internalized, the nascent -phagosome undergoes a series of events leading to its maturation to the microbicidal phagolysosome. Investigating these dynamic and temporally controlled series of events in live cells requires noninvasive methods. The ability to rapidly recruit the proteins of interest to the sites of phagocytosis or to nascent phagosomes would help dissect the regulatory mechanisms involved during phagocytosis. Here, we describe a general approach to express in RAW264.7 murine macrophages, a genetically encoded rapamycin--induced heterodimerization system. In the presence of rapamycin, tight association between FK506-binding protein (FKBP) and FKBP rapamycin-binding protein (FRB) is observed. Based on this principle, a synthetic system consisting of a targeting domain attached to FKBP can recruit a protein of interest fused to FRB upon the addition of rapamycin. Previously, this technique has been used to target lipid-modifying enzymes and small GTPases to the phagosome or plasma membrane. The recruitment of the FRB module can be monitored by fluorescent microscopy if a fluorescent protein is fused to the FRB sequence. While the focus of this chapter is on phagocytic events, this method can be employed to study any organelle of interest when the appropriate targeting sequence is used.

ldentifying Episodes of Earth Science Phenomena Using a Big-Data Technology

NASA Technical Reports Server (NTRS)

Kuo, Kwo-Sen; Oloso, Amidu; Rushing, John; Lin, Amy; Fekete, Gyorgy; Ramachandran, Rahul; Clune, Thomas; Dunny, Daniel

2014-01-01

A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.

High-frequency in situ optical measurements during a storm event: Assessing relationships between dissolved organic matter, sediment concentrations, and hydrologic processes

USGS Publications Warehouse

Saraceno, John F.; Pellerin, Brian A.; Downing, Bryan D.; Boss, Emmanuel; Bachand, Philip A. M.; Bergamaschi, Brian A.

2009-01-01

Dissolved organic matter (DOM) dynamics during storm events has received considerable attention in forested watersheds, but the extent to which storms impart rapid changes in DOM concentration and composition in highly disturbed agricultural watersheds remains poorly understood. In this study, we used identical in situ optical sensors for DOM fluorescence (FDOM) with and without filtration to continuously evaluate surface water DOM dynamics in a 415 km2agricultural watershed over a 4 week period containing a short-duration rainfall event. Peak turbidity preceded peak discharge by 4 h and increased by over 2 orders of magnitude, while the peak filtered FDOM lagged behind peak turbidity by 15 h. FDOM values reported using the filtered in situ fluorometer increased nearly fourfold and were highly correlated with dissolved organic carbon (DOC) concentrations (r2 = 0.97), providing a highly resolved proxy for DOC throughout the study period. Discrete optical properties including specific UV absorbance (SUVA254), spectral slope (S290–350), and fluorescence index (FI) were also strongly correlated with in situ FDOM and indicate a shift toward aromatic, high molecular weight DOM from terrestrially derived sources during the storm. The lag of the peak in FDOM behind peak discharge presumably reflects the draining of watershed soils from natural and agricultural landscapes. Field and experimental evidence showed that unfiltered FDOM measurements underestimated filtered FDOM concentrations by up to ∼60% at particle concentrations typical of many riverine systems during hydrologic events. Together, laboratory and in situ data provide insights into the timing and magnitude of changes in DOM quantity and quality during storm events in an agricultural watershed, and indicate the need for sample filtration in systems with moderate to high suspended sediment loads.

Scale-free avalanches in the multifractal random walk

NASA Astrophysics Data System (ADS)

Bartolozzi, M.

2007-06-01

Avalanches, or Avalanche-like, events are often observed in the dynamical behaviour of many complex systems which span from solar flaring to the Earth's crust dynamics and from traffic flows to financial markets. Self-organized criticality (SOC) is one of the most popular theories able to explain this intermittent charge/discharge behaviour. Despite a large amount of theoretical work, empirical tests for SOC are still in their infancy. In the present paper we address the common problem of revealing SOC from a simple time series without having much information about the underlying system. As a working example we use a modified version of the multifractal random walk originally proposed as a model for the stock market dynamics. The study reveals, despite the lack of the typical ingredients of SOC, an avalanche-like dynamics similar to that of many physical systems. While, on one hand, the results confirm the relevance of cascade models in representing turbulent-like phenomena, on the other, they also raise the question about the current state of reliability of SOC inference from time series analysis.

Rotational and constitutional dynamics of caged supramolecules

PubMed Central

Kühne, Dirk; Klappenberger, Florian; Krenner, Wolfgang; Klyatskaya, Svetlana; Ruben, Mario; Barth, Johannes V.

2010-01-01

The confinement of molecular species in nanoscale environments leads to intriguing dynamic phenomena. Notably, the organization and rotational motions of individual molecules were controlled by carefully designed, fully supramolecular host architectures. Here we use an open 2D coordination network on a smooth metal surface to steer the self-assembly of discrete trimeric guest units, identified as noncovalently bound dynamers. Each caged chiral supramolecule performs concerted, chirality-preserving rotary motions within the template honeycomb pore, which are visualized and quantitatively analyzed using temperature-controlled scanning tunneling microscopy. Furthermore, with higher thermal energies, a constitutional system dynamics appears, which is revealed by monitoring repetitive switching events of the confined supramolecules’ chirality signature, reflecting decay and reassembly of the caged units. PMID:21098303

Low Power Shoe Integrated Intelligent Wireless Gait Measurement System

NASA Astrophysics Data System (ADS)

Wahab, Y.; Mazalan, M.; Bakar, N. A.; Anuar, A. F.; Zainol, M. Z.; Hamzah, F.

2014-04-01

Gait analysis measurement is a method to assess and identify gait events and the measurements of dynamic, motion and pressure parameters involving the lowest part of the body. This significant analysis is widely used in sports, rehabilitation as well as other health diagnostic towards improving the quality of life. This paper presents a new system empowered by Inertia Measurement Unit (IMU), ultrasonic sensors, piezoceramic sensors array, XBee wireless modules and Arduino processing unit. This research focuses on the design and development of a low power ultra-portable shoe integrated wireless intelligent gait measurement using MEMS and recent microelectronic devices for foot clearance, orientation, error correction, gait events and pressure measurement system. It is developed to be cheap, low power, wireless, real time and suitable for real life in-door and out-door environment.

Validation of BlueSky Smoke Prediction System using surface and satellite observations during major wildland fire events in Northern California

Treesearch

Lesley Fusina; Sharon Zhong; Julide Koracin; Tim Brown; Annie Esperanza; Leland Tarney; Haiganoush Preisler

2007-01-01

The BlueSky Smoke Prediction System developed by the U.S. Department of Agriculture, Forest Service, AirFire Team under the National Fire Plan is a modeling framework that integrates tools, knowledge of fuels, moisture, combustion, emissions, plume dynamics, and weather to produce real-time predictions of the cumulative impacts of smoke from wildfires, prescribed fires...

Meso-Cenozoic tectonic evolution of the SE Brazilian continental margin: Petrographic, kinematic and dynamic analysis of the onshore Araruama Lagoon Fault System

NASA Astrophysics Data System (ADS)

Souza, Pricilla Camões Martins de; Schmitt, Renata da Silva; Stanton, Natasha

2017-09-01

The Ararauama Lagoon Fault System composes one of the most prominent set of lineaments of the SE Brazilian continental margin. It is located onshore in a key tectonic domain, where the basement inheritance rule is not followed. This fault system is characterized by ENE-WSW silicified tectonic breccias and cataclasites showing evidences of recurrent tectonic reactivations. Based on field work, microtectonic, kinematic and dynamic analysis, we reconstructed the paleostresses in the region and propose a sequence of three brittle deformational phases accountable for these reactivations: 1) NE-SW dextral transcurrence; 2) NNW-SSE dextral oblique extension that evolved to NNW-SSE "pure" extension; 3) ENE-WSW dextral oblique extension. These phases are reasonably correlated with the tectonic events responsible for the onset and evolution of the SE onshore rift basins, between the Neocretaceous and Holocene. However, based on petrographic studies and supported by regional geological correlations, we assume that the origin of this fault system is older, related to the Early Cretaceous South Atlantic rifting. This study provides significant information about one of the main structural trends of the SE Brazilian continental margin and the tectonic events that controlled its segmentation, since the Gondwana rifting, and compartmentalization of its onshore sedimentary deposits during the Cenozoic.

Analyzing the Possibility of Dynamic Earthquake Triggering in Socorro, New Mexico

NASA Astrophysics Data System (ADS)

Morton, E.; Bilek, S. L.

2011-12-01

The release of energy during an earthquake changes the stress state and seismicity both locally and remotely. Far-field stress changes can lead to triggered earthquakes coinciding with the arrival of the surface waves. This dynamic triggering is found to occur in a variety of tectonic settings, but in particular magmatic regions. Here we test whether the Socorro Magma Body region in central New Mexico hosts triggered seismicity. Preliminary inspection of continuous network data in central New Mexico suggested a local triggered event with the passage of surface waves from an MW 6.9 event in 2009. For a more comprehensive view, we examine data from 379 earthquakes MW ≥ 6.0 between January 15, 2008 to March 13, 2010 recorded on the EarthScope USArray Transportable Network stations located within New Mexico and providing more dense coverage for better detectability. Waveforms from twenty EarthScope stations were windowed around the time of the large event, high-pass filtered at 5 Hz to remove low frequency signals and analyzed to detect high frequency triggered local earthquakes. For each possible trigger detected, waveforms from nine short-period stations in the Socorro Seismic Network were added to aid in locating the events. In the time period analyzed, twelve triggered events were detected. Only one of these events, on August 30, 2009, corresponded to the arrival of surface waves, occurring about a minute after their arrival. The majority of the triggered events occur well after the arrival of the surface waves, indicating that they are either independent of the main shock or the result of delayed dynamic triggering. Delayed dynamic triggering can occur hours or days after the passage of surface waves, and are marked by an increase in seismicity relative to background. Only one of the events, on September 18, 2009, occurred within the Socorro Magma Body area. The rest of these events occur spread throughout New Mexico. The widely spread distribution of possibly triggered events and the low ratio of triggers to main shocks indicates that the rifted magmatic region above the Socorro Magma Body is not particularly susceptible to dynamic triggering from remote main shocks. The lack of direct correspondence to a seismic phase can mean that the detected events may be independent (not triggered events), or the result of delayed dynamic triggering. A comparison to randomly chosen waveforms within the time period as background will reveal if the possible events are a result of delayed dynamic triggering or part of the background.

The LUX experiment - trigger and data acquisition systems

NASA Astrophysics Data System (ADS)

Druszkiewicz, Eryk

2013-04-01

The Large Underground Xenon (LUX) detector is a two-phase xenon time projection chamber designed to detect interactions of dark matter particles with the xenon nuclei. Signals from the detector PMTs are processed by custom-built analog electronics which provide properly shaped signals for the trigger and data acquisition (DAQ) systems. During calibrations, both systems must be able to handle high rates and have large dynamic ranges; during dark matter searches, maximum sensitivity requires low thresholds. The trigger system uses eight-channel 64-MHz digitizers (DDC-8) connected to a Trigger Builder (TB). The FPGA cores on the digitizers perform real-time pulse identification (discriminating between S1 and S2-like signals) and event localization. The TB uses hit patterns, hit maps, and maximum response detection to make trigger decisions, which are reached within few microseconds after the occurrence of an event of interest. The DAQ system is comprised of commercial digitizers with customized firmware. Its real-time baseline suppression allows for a maximum event acquisition rate in excess of 1.5 kHz, which results in virtually no deadtime. The performance of the trigger and DAQ systems during the commissioning runs of LUX will be discussed.

Field Observations of Swash-Zone Dynamics on a Sea-Breeze Dominated Beach at the Yucatán Peninsula, México

NASA Astrophysics Data System (ADS)

Chardon-Maldonado, P.; Puleo, J. A.; Torres-Freyermuth, A.

2016-02-01

Sea breezes can modify the nearshore processes and alter beach morphology depending on the geographical location. Prior studies have shown that surf zone wave energy intensifies during strong sea-breeze conditions (wind speeds > 10 ms-1) and the impact on the coast can be similar to a small storm. However, few research efforts have investigated the coastal dynamics on sea-breeze dominated beaches (e.g., Masselink and Pattiaratchi, 1998, Mar. Geol.; Pattiaratchi et al., 1997, Cont. Shelf Res.) and, to the authors' knowledge, only one study has focused on swash-zone processes (Sonu et al., 1973, EOS). A field study was performed on a microtidal, low wave energy, sea-breeze dominated sandy beach in order to investigate the effects of local (sea breeze) and synoptic (storm) scale meteorological events on swash-zone dynamics. In-situ measurements of swash-zone hydrodynamics and sediment transport processes were collected from March 31st to April 12th, 2014 in Sisal, Yucatán located on the northern coast of the Yucatán Peninsula. Flow velocities and suspended sediment concentrations were measured concurrently, at multiple cross-shore and alongshore locations, using Vectrino-II profiling velocimeters and optical backscatter sensors, respectively. The high resolution data allowed the quantification of bed shear stress, turbulent dissipation rate, sediment loads and sediment flux during a mesoscale frontal system (cold-front passage referred to as an El Norte) and local sea-breeze cycles. Field observations showed that strong swash-zone bed shear stresses, turbulence intensity and sediment suspension occur during energetic conditions (i.e., El Norte event). On the other hand, despite milder energy conditions during the sea-breeze events, the alongshore component of bed-shear stresses and velocities can be significant owing to the high incidence wave angle associated with the sea-breeze system in the study area. The increased forcing in the swash zone induced sediment suspension, eroding the foreshore and causing accretion in the surf zone. The preliminary analysis demonstrates that strong sea-breeze events induce a significant alongshore swash-zone sediment transport that may be more important than that observed during an El Norte event.

Planetary Hypothesis, sub-Milankovitch frequencies and Holocene cold events

NASA Astrophysics Data System (ADS)

Compagnucci, R. H.; Cionco, R. G.; Agosta, E.; Wanner, H.

2013-05-01

The Planetary Hypothesis of solar cycles proposes that the movement of the Sun around the solar system barycenter modulates the solar cycles at several times scales. Using a 3-D model of the solar system (Cionco and Compagnucci, 2012) we derived the solar barycentric motion and various dynamic parameters such as the angular momentum (L= Lx, Ly, Lz) for the Holocene. Angular momentum inversions are sporadic and important events in the dynamics of the MSB: Lz becomes negative and giant planets are nearly aligned. These episodes are related to some grand solar grand minima such as Maunder and Dalton, and also to the recent deep minimum 2007-2010 which was preceded by a Lz inversion in 1990. During the Holocene several negative Lz episodes occur that are grouped in approximately millennia to centuries long periods. Each group is separated by ~2000 years where the Lz values remain positive, both generating a cycle between 1500 and 2500 years. The spectral analysis shows significant peaks at sub-Milankovitch frequencies. Furthermore, the analysis of the spatiotemporal variability of temperature defined six specific cold events (8200, 6300, 4700, 2700, 1550 and 550 years BP) during the Holocene (Wanner et al, 2011). During, and /or before, of these major climates cooling, a group of negative Lz episodes were presented. Oppositely the resulted during the warms periods were the lack of the angular movement inversion together with the extremes of positive Lz . Therefore, the origin of Holocene cold events seems to be linked to the gravitational influence of the planets, that is to say the planetary torque that has a non-negligible effect on the causes of the solar magnetic cycle. Acknowledgements:The support of the Grants PID-UTN1351, UBACYT N_:20020100101049, CONICET PIP PIP 114-201001-00250 and MINCYT-MEYS ARC/11/09. References Cionco, R.G.; Compagnucci,R.H. (2012) Dynamical characterization of the last prolonged solar minima , Advances in Space Research 50(10), 1434-1444 Wanner, H.; Solomina, O.; Grosjean, M.; Ritz, S. P.; Jetel, M. (2011) Structure and origin of Holocene cold events.Quat. Sci. Rev. 30, 3109-3123.;

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Impact adding bifurcation in an autonomous hybrid dynamical model of church bell

NASA Astrophysics Data System (ADS)

Brzeski, P.; Chong, A. S. E.; Wiercigroch, M.; Perlikowski, P.

2018-05-01

In this paper we present the bifurcation analysis of the yoke-bell-clapper system which corresponds to the biggest bell "Serce Lodzi" mounted in the Cathedral Basilica of St Stanislaus Kostka, Lodz, Poland. The mathematical model of the system considered in this work has been derived and verified based on measurements of dynamics of the real bell. We perform numerical analysis both by direct numerical integration and path-following method using toolbox ABESPOL (Chong, 2016). By introducing the active yoke the position of the bell-clapper system with respect to the yoke axis of rotation can be easily changed and it can be used to probe the system dynamics. We found a wide variety of periodic and non-periodic solutions, and examined the ranges of coexistence of solutions and transitions between them via different types of bifurcations. Finally, a new type of bifurcation induced by a grazing event - an "impact adding bifurcation" has been proposed. When it occurs, the number of impacts between the bell and the clapper is increasing while the period of the system's motion stays the same.

Characterization of Strombolian events by using independent component analysis

NASA Astrophysics Data System (ADS)

Ciaramella, A.; de Lauro, E.; de Martino, S.; di Lieto, B.; Falanga, M.; Tagliaferri, R.

2004-10-01

We apply Independent Component Analysis (ICA) to seismic signals recorded at Stromboli volcano. Firstly, we show how ICA works considering synthetic signals, which are generated by dynamical systems. We prove that Strombolian signals, both tremor and explosions, in the high frequency band (>0.5 Hz), are similar in time domain. This seems to give some insights to the organ pipe model generation for the source of these events. Moreover, we are able to recognize in the tremor signals a low frequency component (<0.5 Hz), with a well defined peak corresponding to 30s.

A computer model of context-dependent perception in a very simple world

NASA Astrophysics Data System (ADS)

Lara-Dammer, Francisco; Hofstadter, Douglas R.; Goldstone, Robert L.

2017-11-01

We propose the foundations of a computer model of scientific discovery that takes into account certain psychological aspects of human observation of the world. To this end, we simulate two main components of such a system. The first is a dynamic microworld in which physical events take place, and the second is an observer that visually perceives entities and events in the microworld. For reason of space, this paper focuses only on the starting phase of discovery, which is the relatively simple visual inputs of objects and collisions.

Forthcoming Occultations of Astrometric Radio Sources by Planets

NASA Technical Reports Server (NTRS)

L'vov, Victor; Malkin, Zinovy; Tsekmeister, Svetlana

2010-01-01

Astrometric observations of radio source occultations by solar system bodies may be of large interest for testing gravity theories, dynamical astronomy, and planetary physics. In this paper, we present an updated list of the occultations of astrometric radio sources by planets expected in the coming years. Such events, like solar eclipses, generally speaking can only be observed in a limited region. A map of the shadow path is provided for the events that will occurr in regions with several VLBI stations and hence will be the most interesting for radio astronomy experiments.

Understanding the rapidity of subsurface storm flow response from a fracture-oriented shallow vadose through a new perspective

NASA Astrophysics Data System (ADS)

Zhao, Peng; Zhao, Pei; Liang, Chuan; Li, Tianyang; Zhou, Baojia

2017-01-01

Velocity and celerity in hydrologic systems are controlled by different mechanisms. Efforts were made through joint sample collection and the use of hydrographs and tracers to understand the rapidity of the subsurface flow response to rainstorms on hourly time scales. Three deep subsurface flows during four natural rainstorm events were monitored. The results show that (1) deeper discharge was observed early in responding rainfall events and yielded a high hydrograph amplitude; (2) a ratio index, k, reflecting the dynamic change of the rainfall perturbation intensity in subsurface flow, might reveal inner causal relationships between the flow index and the tracer signal index. Most values of k were larger than 1 at the perturbation stage but approximated 1 at the no-perturbation stage; and (3) for statistical analysis of tracer signals in subsurface flows, the total standard deviation was 17.2, 11.9, 7.4 and 3.5 at perturbation stages and 4.4, 2.5, 1.1, and 0.95 at the non-perturbation stage for observed events. These events were 3-7 times higher in the former rather than the later, reflecting that the variation of tracer signals primarily occurred under rainfall perturbation. Thus, we affirmed that the dynamic features of rainfall have a key effect on rapid processes because, besides the gravity, mechanical waves originating from dynamic rainfall features are another driving factor for conversion between different types of rainfall mechanical energy. A conceptual model for pressure wave propagation was proposed, in which virtual subsurface flow processes in a heterogeneous vadose zone under rainfall are analogous to the water hammer phenomenon in complex conduit systems. Such an analogy can allow pressure in a shallow vadose to increase and decrease and directly influence the velocity and celerity of the flow reflecting a mechanism for rapid subsurface hydrologic response processes in the shallow vadose zone.

Towards the reliable calculation of residence time for off-lattice kinetic Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Alexander, Kathleen C.; Schuh, Christopher A.

2016-08-01

Kinetic Monte Carlo (KMC) methods have the potential to extend the accessible timescales of off-lattice atomistic simulations beyond the limits of molecular dynamics by making use of transition state theory and parallelization. However, it is a challenge to identify a complete catalog of events accessible to an off-lattice system in order to accurately calculate the residence time for KMC. Here we describe possible approaches to some of the key steps needed to address this problem. These include methods to compare and distinguish individual kinetic events, to deterministically search an energy landscape, and to define local atomic environments. When applied to the ground state  ∑5(2 1 0) grain boundary in copper, these methods achieve a converged residence time, accounting for the full set of kinetically relevant events for this off-lattice system, with calculable uncertainty.

Re-scheduling as a tool for the power management on board a spacecraft

NASA Technical Reports Server (NTRS)

Albasheer, Omar; Momoh, James A.

1995-01-01

The scheduling of events on board a spacecraft is based on forecast energy levels. The real time values of energy may not coincide with the forecast values; consequently, a dynamic revising to the allocation of power is needed. The re-scheduling is also needed for other reasons on board a spacecraft like the addition of new event which must be scheduled, or a failure of an event due to many different contingencies. This need of rescheduling is very important to the survivability of the spacecraft. In this presentation, a re-scheduling tool will be presented as a part of an overall scheme for the power management on board a spacecraft from the allocation of energy point of view. The overall scheme is based on the optimal use of energy available on board a spacecraft using expert systems combined with linear optimization techniques. The system will be able to schedule maximum number of events utilizing most energy available. The outcome is more events scheduled to share the operation cost of that spacecraft. The system will also be able to re-schedule in case of a contingency with minimal time and minimal disturbance of the original schedule. The end product is a fully integrated planning system capable of producing the right decisions in short time with less human error. The overall system will be presented with the re-scheduling algorithm discussed in detail, then the tests and results will be presented for validations.

Post-tsunami beach recovery in Thailand: A case for punctuated equilibrium in coastal dynamics

NASA Astrophysics Data System (ADS)

Switzer, Adam D.; Gouramanis, Chris; Bristow, Charles; Yeo, Jeffrey; Kruawun, Jankaew; Rubin, Charles; Sin Lee, Ying; Tien Dat, Pham

2017-04-01

A morpho-geophysical investigation of two beaches in Thailand over the last decade shows that they have completely recovered from the 2004 Indian Ocean tsunami (IOT) without any human intervention. Although the beach systems show contrasting styles of recovery in both cases natural processes have reconstructed the beaches to comparable pre-tsunami morphologies in under a decade, demonstrating the existence of punctuated equilibrium in coastal systems and the resilience of natural systems to catastrophic events. Through a combination of remote sensing, field surveys and shallow geophysics we reconstruct the post-event recovery of beaches at Phra Thong Island, a remote, near pristine site that was severely impacted by the IOT. We identify periods of aggradation, progradation and washover sedimentation that match with local events including a storm in November 2007. The rapid recovery of these systems implies that majority of sediment scoured by the tsunami was not transported far offshore but remained in the littoral zone within reach of fair-weather waves that returned it (the sediment) to the beach naturally.

POSEIDON: An integrated system for analysis and forecast of hydrological, meteorological and surface marine fields in the Mediterranean area

NASA Astrophysics Data System (ADS)

Speranza, A.; Accadia, C.; Casaioli, M.; Mariani, S.; Monacelli, G.; Inghilesi, R.; Tartaglione, N.; Ruti, P. M.; Carillo, A.; Bargagli, A.; Pisacane, G.; Valentinotti, F.; Lavagnini, A.

2004-07-01

The Mediterranean area is characterized by relevant hydrological, meteorological and marine processes developing at horizontal space-scales of the order of 1-100 km. In the recent past, several international programs have been addressed (ALPEX, POEM, MAP, etc.) to "resolving" the dynamics of such motions. Other projects (INTERREG-Flooding, MEDEX, etc.) are at present being developed with special emphasis on catastrophic events with major impact on human society that are, quite often, characterized in their manifestation by processes with the above-mentioned scales of motion. In the dynamical evolution of such events, however, equally important is the dynamics of interaction of the local (and sometimes very damaging) processes with others developing at larger scales of motion. In fact, some of the most catastrophic events in the history of Mediterranean countries are associated with dynamical processes covering all the range of space-time scales from planetary to local. The Prevision Operational System for the mEditerranean basIn and the Defence of the lagOon of veNice (POSEIDON) is an integrated system for the analysis and forecast of hydrological, meteorological, oceanic fields specifically designed and set up in order to bridge the gap between global and local scales of motion, by modeling explicitly the above referred to dynamical processes in the range of scales from Mediterranean to local. The core of POSEIDON consists of a "cascade" of numerical models that, starting from global scale numerical analysis-forecast, goes all the way to very local phenomena, like tidal propagation in Venice Lagoon. The large computational load imposed by such operational design requires necessarily parallel computing technology: the first model in the cascade is a parallelised version of BOlogna Limited Area Model (BOLAM) running on a Quadrics 128 processors computer (also known as QBOLAM). POSEIDON, developed in the context of a co-operation between the Italian Agency for New technologies, Energy and Environment (Ente per le Nuove tecnologie, l'Energia e l'Ambiente, ENEA) and the Italian Agency for Environmental Protection and Technical Services (Agenzia per la Protezione dell'Ambiente e per i Servizi Tecnici, APAT), has become operational in 2000 and we are presently in the condition of drawing some preliminary conclusions about its performance. In the paper we describe the scientific concepts that were at the basis of the original planning, the structure of the system, its operational cycle and some preliminary scientific and technical evaluations after two years of experimentation.

Channel disturbances and morpho-dynamics: linking hydraulics, topographic changes and human impacts in a highly dynamic wandering river at multiple temporal scales

NASA Astrophysics Data System (ADS)

Vericat, Damià; Llena, Manel; Muñoz, Efrén; Ramos, Ester; Béjar, María; Brasington, James; Gibbins, Chris; Batalla, Ramon J.; Tena, Álvaro; Martínez-Casasnovas, José A.; Wheaton, Joe

2015-04-01

Episodic erosion, transport and deposition of sediments produce changes in river's channel morphology. These changes, although are directly related to flow hydraulics and bed material availability, supply and transport, could also be highly influenced by structural and local human impacts. Dams cut the continuity of sediment transfer and alter flood magnitude and frequency. In-channel gravel mining, however, disturbs channel beds locally, with a direct influence in upstream and downstream reaches. In this paper we present some of the preliminary results obtained in the background of MorphSed (www.morphsed.es). Morphsed is analysing the morpho-sedimentary dynamics of a mountain fluvial system located in the foothills of the Pyrenees, Iberian Peninsula. The study system is suffering major local alterations due to gravel mining. Changes on bed topography along a 12-km river reach have been analysed at two temporal scales: (i) decadal or historical and (ii) flood-based or contemporary. The study reach has suffered natural and human channel disturbances (i.e. major flood events, and gravel extractions and channel embankments, respectively). Preliminary results show how gravel mining occurred after the large flood event registered in October 1982 created a sedimentary disequilibrium in the reach. Additionally, the channel was heavily constrained associated to channel narrowing by embankments. The river has reached a new dynamic equilibrium by means of bed coarsening and channel incision, and changing from a braided to a wandering pattern. Contemporary competent flood events, however, cause severe damages in some of the embankments (i.e. lateral erosion). Gravel extractions in these sites are performed to protect these infrastructures and, in turn, are influencing local channel morpho-dynamics, increasing the sedimentary disequilibrium, exacerbating local channel incision processes, and modifying channel roughness and sediment transport dynamics. 2d hydraulic models show as these contemporary extractions influence on the magnitude and variability of hydraulic forces and, in turn, modify the conveyance of water and sediments through the study reach. All these changes have a direct influence on the ecological status of the river at different temporal and spatial scales. These links will be a key goal for progress towards the understanding of the interactions between river bed disturbance and ecological responses at multiple scales, and provide the basis for an integrated methodology that can be used to aid prediction, management and restoration of human stressed fluvial systems.

Subsampling effects in neuronal avalanche distributions recorded in vivo

PubMed Central

Priesemann, Viola; Munk, Matthias HJ; Wibral, Michael

2009-01-01

Background Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system's avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma = 1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task. Results Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity. Conclusion Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives. PMID:19400967

Impact of Active Control on Passive Safety Response Characteristics of Sodium-Cooled Fast Reactors: II-Model Implementation and Simulations

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

Ponciroli, Roberto; Passerini, Stefano; Vilim, Richard B.

Advanced reactors are often claimed to be passively safe against unprotected upset events. In common practice, these events are not considered in the context of the plant control system, i.e., the reactor is subjected to classes of unprotected upset events while the normally programmed response of the control system is assumed not to be present. However, this approach constitutes an oversimplification since, depending on the upset involving the control system, an actuator does not necessarily go in the same direction as needed for safety. In this work, dynamic simulations are performed to assess the degree to which the inherent self-regulatingmore » plant response is safe from active control system override. The simulations are meant to characterize the resilience of the plant to unprotected initiators. The initiators were represented and modeled as an actuator going to a hard limit. Consideration of failure is further limited to individual controllers as there is no cross-connect of signals between these controllers. The potential for passive safety override by the control system is then relegated to the single-input single-output controllers. Here, the results show that when the plant control system is designed by taking into account and quantifying the impact of the plant control system on accidental scenarios there is very limited opportunity for the preprogrammed response of the control system to override passive safety protection in the event of an unprotected initiator.« less

Impact of Active Control on Passive Safety Response Characteristics of Sodium-Cooled Fast Reactors: II-Model Implementation and Simulations

DOE PAGES

Ponciroli, Roberto; Passerini, Stefano; Vilim, Richard B.

2017-06-21

Advanced reactors are often claimed to be passively safe against unprotected upset events. In common practice, these events are not considered in the context of the plant control system, i.e., the reactor is subjected to classes of unprotected upset events while the normally programmed response of the control system is assumed not to be present. However, this approach constitutes an oversimplification since, depending on the upset involving the control system, an actuator does not necessarily go in the same direction as needed for safety. In this work, dynamic simulations are performed to assess the degree to which the inherent self-regulatingmore » plant response is safe from active control system override. The simulations are meant to characterize the resilience of the plant to unprotected initiators. The initiators were represented and modeled as an actuator going to a hard limit. Consideration of failure is further limited to individual controllers as there is no cross-connect of signals between these controllers. The potential for passive safety override by the control system is then relegated to the single-input single-output controllers. Here, the results show that when the plant control system is designed by taking into account and quantifying the impact of the plant control system on accidental scenarios there is very limited opportunity for the preprogrammed response of the control system to override passive safety protection in the event of an unprotected initiator.« less

Peculiarities of the atmospheric blocking events over the Siberia and Russian Far East region during summertime

NASA Astrophysics Data System (ADS)

Antokhina, Olga Yu.; Devjatova, Elena V.; Mordvinov, Vladimir I.

2017-11-01

We study the atmospheric blocking event evolution peculiarities over the Siberia and Far Eastern region (Russia) during summertime. Compared are two methods to identify blockings: from the 500 hPa (Z500) isobaric surface height distribution, and from the potential temperature at the dynamic tropopause (PV-θ) for every July 1979 through 2016. We revealed the situations, where blockings are identified only in one of the characteristics. Blocking identification by the PV-θ characteristics is complicated in the cases, when its cyclonic part appears to be filled with air masses of the southern origin, due to which there is no meridional gradient reversal in the PV-θ region. In the Z500 region, the difficulties to identify blocking events may arise in those cases, when the baric field fails to adapt to rapid changes in the temperature field associated with the air mass advection. For example, such events often occur over the ocean surface. We performed a synoptic analysis for several blocking events from the data on the velocity field dynamics at 850 hPa and PV-θ supplemented by the analysis of the observational rainfall data at the stations during those events. Distinguished were several stages of the blocking evolution over the Siberia and Far Eastern region that involved air masses from the East Asian summer monsoon region: 1. The formation of a blocking over Western Siberia; 2. Cold inflow on the blocking eastern periphery, the East Asian summer monsoon front activation, and a cyclone formation (east of Lake Baikal), in whose system the monsoon air was actively involved. Such monsoon cyclones, as a rule, are deep long-living formations, and they bring abnormal precipitations; 3. The formation of a ridge or anticyclone east of the monsoon cyclone, caused by the advection of the same monsoon flow, whose part is involved in a cyclone system. In general, the East Asian summer monsoon influence comes to the effects of regeneration and intensification of the blocking circulating systems. Those effects are often accompanied by strong droughts in some regions and floods in others.

Seedling establishment in a dynamic sedimentary environment: a conceptual framework using mangroves

PubMed Central

Balke, Thorsten; Webb, Edward L; van den Elzen, Eva; Galli, Demis; Herman, Peter M J; Bouma, Tjeerd J

2013-01-01

1. Vegetated biogeomorphic systems (e.g. mangroves, salt marshes, dunes, riparian vegetation) have been intensively studied for the impact of the biota on sediment transport processes and the resulting self-organization of such landscapes. However, there is a lack of understanding of physical disturbance mechanisms that limit primary colonization in active sedimentary environments. 2. This study elucidates the effect of sediment disturbance during the seedling stage of pioneer vegetation, using mangroves as a model system. We performed mesocosm experiments that mimicked sediment disturbance as (i) accretion/burial of plants and (ii) erosion/excavation of plants of different magnitudes and temporal distribution in combination with water movement and inundation stress. 3. Cumulative sediment disturbance reduced seedling survival, with the faster-growing Avicennia alba showing less mortality than the slower-growing Sonneratia alba. The presence of the additional stressors (inundation and water movement) predominantly reduced the survival of S. alba. 4. Non-lethal accretion treatments increased shoot biomass of the seedlings, whereas non-lethal erosion treatments increased root biomass allocation. This morphological plasticity in combination with the abiotic disturbance history determined how much maximum erosion the seedlings were able to withstand. 5. Synthesis and applications. Seedling survival in dynamic sedimentary environments is determined by the frequency and magnitude of sediment accretion or erosion events, with non-lethal events causing feedbacks to seedling stability. Managers attempting restoration of mangroves, salt marshes, dunes and riparian vegetation should recognize sediment dynamics as a main bottleneck to primary colonization. The temporal distribution of erosion and accretion events has to be evaluated against the ability of the seedlings to outgrow or adjust to disturbances. Our results suggest that selecting fast-growing pioneer species and measures to enhance seedling growth or temporary reduction in sediment dynamics at the restoration site can aid restoration success for vegetated biogeomorphic ecosystems. PMID:23894211

Experimental fire increases soil carbon dioxide efflux in a grassland long-term multifactor global change experiment.

PubMed

Strong, Aaron L; Johnson, Tera P; Chiariello, Nona R; Field, Christopher B

2017-05-01

Numerous studies have demonstrated that soil respiration rates increase under experimental warming, although the long-term, multiyear dynamics of this feedback are not well constrained. Less is known about the effects of single, punctuated events in combination with other longer-duration anthropogenic influences on the dynamics of soil carbon (C) loss. In 2012 and 2013, we assessed the effects of decadal-scale anthropogenic global change - warming, increased nitrogen (N) deposition, elevated carbon dioxide (CO 2 ), and increased precipitation - on soil respiration rates in an annual-dominated Mediterranean grassland. We also investigated how controlled fire and an artificial wet-up event, in combination with exposure to the longer-duration anthropogenic global change factors, influenced the dynamics of C cycling in this system. Decade-duration surface soil warming (1-2 °C) had no effect on soil respiration rates, while +N addition and elevated CO 2 concentrations increased growing-season soil CO 2 efflux rates by increasing annual aboveground net primary production (NPP) and belowground fine root production, respectively. Low-intensity experimental fire significantly elevated soil CO 2 efflux rates in the next growing season. Based on mixed-effects modeling and structural equation modeling, low-intensity fire increased growing-season soil respiration rates through a combination of three mechanisms: large increases in soil temperature (3-5 °C), significant increases in fine root production, and elevated aboveground NPP. Our study shows that in ecosystems where soil respiration has acclimated to moderate warming, further increases in soil temperature can stimulate greater soil CO 2 efflux. We also demonstrate that punctuated short-duration events such as fire can influence soil C dynamics with implications for both the parameterization of earth system models (ESMs) and the implementation of climate change mitigation policies that involve land-sector C accounting. © 2016 John Wiley & Sons Ltd.

Cross scale interactions, nonlinearities, and forecasting catastrophic events

USGS Publications Warehouse

Peters, Debra P.C.; Pielke, Roger A.; Bestelmeyer, Brandon T.; Allen, Craig D.; Munson-McGee, Stuart; Havstad, Kris M.

2004-01-01

Catastrophic events share characteristic nonlinear behaviors that are often generated by cross-scale interactions and feedbacks among system elements. These events result in surprises that cannot easily be predicted based on information obtained at a single scale. Progress on catastrophic events has focused on one of the following two areas: nonlinear dynamics through time without an explicit consideration of spatial connectivity [Holling, C. S. (1992) Ecol. Monogr. 62, 447–502] or spatial connectivity and the spread of contagious processes without a consideration of cross-scale interactions and feedbacks [Zeng, N., Neeling, J. D., Lau, L. M. & Tucker, C. J. (1999) Science 286, 1537–1540]. These approaches rarely have ventured beyond traditional disciplinary boundaries. We provide an interdisciplinary, conceptual, and general mathematical framework for understanding and forecasting nonlinear dynamics through time and across space. We illustrate the generality and usefulness of our approach by using new data and recasting published data from ecology (wildfires and desertification), epidemiology (infectious diseases), and engineering (structural failures). We show that decisions that minimize the likelihood of catastrophic events must be based on cross-scale interactions, and such decisions will often be counterintuitive. Given the continuing challenges associated with global change, approaches that cross disciplinary boundaries to include interactions and feedbacks at multiple scales are needed to increase our ability to predict catastrophic events and develop strategies for minimizing their occurrence and impacts. Our framework is an important step in developing predictive tools and designing experiments to examine cross-scale interactions.

An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks.

PubMed

Salis, Howard; Kaznessis, Yiannis N

2005-12-01

Stochastic chemical kinetics more accurately describes the dynamics of "small" chemical systems, such as biological cells. Many real systems contain dynamical stiffness, which causes the exact stochastic simulation algorithm or other kinetic Monte Carlo methods to spend the majority of their time executing frequently occurring reaction events. Previous methods have successfully applied a type of probabilistic steady-state approximation by deriving an evolution equation, such as the chemical master equation, for the relaxed fast dynamics and using the solution of that equation to determine the slow dynamics. However, because the solution of the chemical master equation is limited to small, carefully selected, or linear reaction networks, an alternate equation-free method would be highly useful. We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. We demonstrate the accuracy and efficiency of the method using multiple interesting examples, including a highly nonlinear protein-protein interaction network. The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.

Modelling the dynamics of traits involved in fighting-predators-prey system.

PubMed

Kooi, B W

2015-12-01

We study the dynamics of a predator-prey system where predators fight for captured prey besides searching for and handling (and digestion) of the prey. Fighting for prey is modelled by a continuous time hawk-dove game dynamics where the gain depends on the amount of disputed prey while the costs for fighting is constant per fighting event. The strategy of the predator-population is quantified by a trait being the proportion of the number of predator-individuals playing hawk tactics. The dynamics of the trait is described by two models of adaptation: the replicator dynamics (RD) and the adaptive dynamics (AD). In the RD-approach a variant individual with an adapted trait value changes the population's strategy, and consequently its trait value, only when its payoff is larger than the population average. In the AD-approach successful replacement of the resident population after invasion of a rare variant population with an adapted trait value is a step in a sequence changing the population's strategy, and hence its trait value. The main aim is to compare the consequences of the two adaptation models. In an equilibrium predator-prey system this will lead to convergence to a neutral singular strategy, while in the oscillatory system to a continuous singular strategy where in this endpoint the resident population is not invasible by any variant population. In equilibrium (low prey carrying capacity) RD and AD-approach give the same results, however not always in a periodically oscillating system (high prey carrying-capacity) where the trait is density-dependent. For low costs the predator population is monomorphic (only hawks) while for high costs dimorphic (hawks and doves). These results illustrate that intra-specific trait dynamics matters in predator-prey dynamics.

Tracking a Solar Wind Dynamic Pressure Pulses' Impact Through the Magnetosphere Using the Heliophysics System Observatory

NASA Astrophysics Data System (ADS)

Vidal-Luengo, S.; Moldwin, M.

2017-12-01

During northward Interplanetary Magnetic Field (IMF) Bz conditions, the magnetosphere acts as a closed "cavity" and reacts to solar wind dynamic pressure pulses more simply than during southward IMF conditions. Effects of solar wind dynamic pressure have been observed as geomagnetic lobe compressions depending on the characteristics of the pressure pulse and the spacecraft location. One of the most important aspects of this study is the incorporation of simultaneous observations by different missions, such as WIND, CLUSTER, THEMIS, MMS, Van Allen Probes and GOES as well as magnetometer ground stations that allow us to map the magnetosphere response at different locations during the propagation of a pressure pulse. In this study we used the SYM-H as an indicator of dynamic pressure pulses occurrence from 2007 to 2016. The selection criteria for events are: (1) the increase in the index must be bigger than 10 [nT] and (2) the rise time must be in less than 5 minutes. Additionally, the events must occur under northward IMF and at the same time at least one spacecraft has to be located in the magnetosphere nightside. Using this methodology we found 66 pressure pulse events for analysis. Most of them can be classified as step function pressure pulses or as sudden impulses (increase followed immediately by a decrease of the dynamic pressure). Under these two categories the results show some systematic signatures depending of the location of the spacecraft. For both kind of pressure pulse signatures, compressions are observed on the dayside. However, on the nightside compressions and/or South-then-North magnetic signatures can be observed for step function like pressure pulses, meanwhile for the sudden impulse kind of pressure pulses the magnetospheric response seems to be less global and more dependent on the local conditions.

A System Dynamics Model for Planning Cardiovascular Disease Interventions

PubMed Central

Homer, Jack; Evans, Elizabeth; Zielinski, Ann

2010-01-01

Planning programs for the prevention and treatment of cardiovascular disease (CVD) is a challenge to every community that wants to make the best use of its limited resources. Selecting programs that provide the greatest impact is difficult because of the complex set of causal pathways and delays that link risk factors to CVD. We describe a system dynamics simulation model developed for a county health department that incorporates and tracks the effects of those risk factors over time on both first-time and recurrent events. We also describe how the model was used to evaluate the potential impacts of various intervention strategies for reducing the county's CVD burden and present the results of those policy tests. PMID:20167899

Optical turbulence and transverse rogue waves in a cavity with triple-quantum-dot molecules

NASA Astrophysics Data System (ADS)

Eslami, M.; Khanmohammadi, M.; Kheradmand, R.; Oppo, G.-L.

2017-09-01

We show that optical turbulence extreme events can exist in the transverse dynamics of a cavity containing molecules of triple quantum dots under conditions close to tunneling-induced transparency. These nanostructures, when coupled via tunneling, form a four-level configuration with tunable energy-level separations. We show that such a system exhibits multistability and bistability of Turing structures in instability domains with different critical wave vectors. By numerical simulation of the mean-field equation that describes the transverse dynamics of the system, we show that the simultaneous presence of two transverse solutions with opposite nonlinearities gives rise to a series of turbulent structures with the capability of generating two-dimensional rogue waves.

Flight dynamics and control modelling of damaged asymmetric aircraft

NASA Astrophysics Data System (ADS)

Ogunwa, T. T.; Abdullah, E. J.

2016-10-01

This research investigates the use of a Linear Quadratic Regulator (LQR) controller to assist commercial Boeing 747-200 aircraft regains its stability in the event of damage. Damages cause an aircraft to become asymmetric and in the case of damage to a fraction (33%) of its left wing or complete loss of its vertical stabilizer, the loss of stability may lead to a fatal crash. In this study, aircraft models for the two damage scenarios previously mentioned are constructed using stability derivatives. LQR controller is used as a direct adaptive control design technique for the observable and controllable system. Dynamic stability analysis is conducted in the time domain for all systems in this study.

Scale Invariance in Lateral Head Scans During Spatial Exploration.

PubMed

Yadav, Chetan K; Doreswamy, Yoganarasimha

2017-04-14

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Scale Invariance in Lateral Head Scans During Spatial Exploration

NASA Astrophysics Data System (ADS)

Yadav, Chetan K.; Doreswamy, Yoganarasimha

2017-04-01

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

The Storytelling Organization: A Study of Story Performance in an Office-Supply Firm.

ERIC Educational Resources Information Center

Boje, David M.

1991-01-01

Analyzes how employees in a large office supply firm performed stories to make sense of events, introduce change, and gain political advantage. These stories were dynamic, varied by context, and were often challenged and reinterpreted by listeners. The collective story telling system allowed members to supplement individual memories with…

A DGS Gesture Dictionary for Modelling on Mobile Devices

ERIC Educational Resources Information Center

Isotani, Seiji; Reis, Helena M.; Alvares, Danilo; Brandão, Anarosa A. F.; Brandão, Leônidas O.

2018-01-01

Interactive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model…

Role of Dynamics in Enzyme Catalysis: Substantial versus Semantic Controversies

PubMed Central

2015-01-01

Conspectus The role of the enzyme’s dynamic motions in catalysis is at the center of heated contemporary debates among both theoreticians and experimentalists. Resolving these apparent disputes is of both intellectual and practical importance: incorporation of enzyme dynamics could be critical for any calculation of enzymatic function and may have profound implications for structure-based drug design and the design of biomimetic catalysts. Analysis of the literature suggests that while part of the dispute may reflect substantial differences between theoretical approaches, much of the debate is semantic. For example, the term “protein dynamics” is often used by some researchers when addressing motions that are in thermal equilibrium with their environment, while other researchers only use this term for nonequilibrium events. The last cases are those in which thermal energy is “stored” in a specific protein mode and “used” for catalysis before it can dissipate to its environment (i.e., “nonstatistical dynamics”). This terminology issue aside, a debate has arisen among theoreticians around the roles of nonstatistical vs statistical dynamics in catalysis. However, the author knows of no experimental findings available today that examined this question in enzyme catalyzed reactions. Another source of perhaps nonsubstantial argument might stem from the varying time scales of enzymatic motions, which range from seconds to femtoseconds. Motions at different time scales play different roles in the many events along the catalytic cascade (reactant binding, reprotonation of reactants, structural rearrangement toward the transition state, product release, etc.). In several cases, when various experimental tools have been used to probe catalytic events at differing time scales, illusory contradictions seem to have emerged. In this Account, recent attempts to sort the merits of those questions are discussed along with possible future directions. A possible summary of current studies could be that enzyme, substrate, and solvent dynamics contribute to enzyme catalyzed reactions in several ways: first via mutual “induced-fit” shifting of their conformational ensemble upon binding; then via thermal search of the conformational space toward the reaction’s transition-state (TS) and the rare event of the barrier crossing toward products, which is likely to be on faster time scales then the first and following events; and finally via the dynamics associated with products release, which are rate-limiting for many enzymatic reactions. From a chemical perspective, close to the TS, enzymatic systems seem to stiffen, restricting motions orthogonal to the chemical coordinate and enabling dynamics along the reaction coordinate to occur selectively. Studies of how enzymes evolved to support those efficient dynamics at various time scales are still in their infancy, and further experiments and calculations are needed to reveal these phenomena in both enzymes and uncatalyzed reactions. PMID:25539442

Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.

2016-04-01

A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during the Little Ice Age. Traditional theories of stochastic processes and dynamical systems are grounded on the existence of so-called dynamical invariants; properties that remain unchanged as the dynamics unfold, assuming structural invariance and ergodicity of the underlying system. However, such theories are no longer optimal when trying to understand and model long-term historical records of coevolutionary systems. A new paradigm is thus needed. Therefore, we introduce a new class of dynamical systems that reinvent themselves as the dynamics unfold. Rather than only changing variables and parameters under a rigid framework, the governing laws are malleable themselves. The novel formulation captures and explains the coevolutionary dynamics of multiscale hydroclimatic systems, bringing along a physically sound understanding of their regimes, transitions and extremes over a long-term history.

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems.

PubMed

Mattei, Tobias A

2014-12-01

In self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

Real-time measurements, rare events and photon economics

NASA Astrophysics Data System (ADS)

Jalali, B.; Solli, D. R.; Goda, K.; Tsia, K.; Ropers, C.

2010-07-01

Rogue events otherwise known as outliers and black swans are singular, rare, events that carry dramatic impact. They appear in seemingly unconnected systems in the form of oceanic rogue waves, stock market crashes, evolution, and communication systems. Attempts to understand the underlying dynamics of such complex systems that lead to spectacular and often cataclysmic outcomes have been frustrated by the scarcity of events, resulting in insufficient statistical data, and by the inability to perform experiments under controlled conditions. Extreme rare events also occur in ultrafast physical sciences where it is possible to collect large data sets, even for rare events, in a short time period. The knowledge gained from observing rare events in ultrafast systems may provide valuable insight into extreme value phenomena that occur over a much slower timescale and that have a closer connection with human experience. One solution is a real-time ultrafast instrument that is capable of capturing singular and randomly occurring non-repetitive events. The time stretch technology developed during the past 13 years is providing a powerful tool box for reaching this goal. This paper reviews this technology and discusses its use in capturing rogue events in electronic signals, spectroscopy, and imaging. We show an example in nonlinear optics where it was possible to capture rare and random solitons whose unusual statistical distribution resemble those observed in financial markets. The ability to observe the true spectrum of each event in real time has led to important insight in understanding the underlying process, which in turn has made it possible to control soliton generation leading to improvement in the coherence of supercontinuum light. We also show a new class of fast imagers which are being considered for early detection of cancer because of their potential ability to detect rare diseased cells (so called rogue cells) in a large population of healthy cells.

Towards Hybrid Online On-Demand Querying of Realtime Data with Stateful Complex Event Processing

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

Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor K.

Emerging Big Data applications in areas like e-commerce and energy industry require both online and on-demand queries to be performed over vast and fast data arriving as streams. These present novel challenges to Big Data management systems. Complex Event Processing (CEP) is recognized as a high performance online query scheme which in particular deals with the velocity aspect of the 3-V’s of Big Data. However, traditional CEP systems do not consider data variety and lack the capability to embed ad hoc queries over the volume of data streams. In this paper, we propose H2O, a stateful complex event processing framework,more » to support hybrid online and on-demand queries over realtime data. We propose a semantically enriched event and query model to address data variety. A formal query algebra is developed to precisely capture the stateful and containment semantics of online and on-demand queries. We describe techniques to achieve the interactive query processing over realtime data featured by efficient online querying, dynamic stream data persistence and on-demand access. The system architecture is presented and the current implementation status reported.« less

C3Winds: A Novel 3D Wind Observing System to Characterize Severe Weather Events

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Wu, D. L.; Yee, J. H.; Boldt, J.; Demajistre, R.; Reynolds, E.; Tripoli, G. J.; Oman, L.; Prive, N.; Heidinger, A. K.; Wanzong, S.

2015-12-01

The CubeSat Constellation Cloud Winds (C3Winds) is a NASA Earth Venture Instrument (EV-I) concept with the primary objective to resolve high-resolution 3D dynamic structures of severe wind events. Rapid evolution of severe weather events highlights the need for high-resolution mesoscale wind observations. Yet mesoscale observations of severe weather dynamics are quite rare, especially over the ocean where extratropical and tropical cyclones (ETCs and TCs) can undergo explosive development. Measuring wind velocity at the mesoscale from space remains a great challenge, but is critically needed to understand and improve prediction of severe weather and tropical cyclones. Based on compact, visible/IR imagers and a mature stereoscopic technique, C3Winds has the capability to measure high-resolution (~2 km) cloud motion vectors and cloud geometric heights accurately by tracking cloud features from two formation-flying CubeSats, separated by 5-15 minutes. Complementary to lidar wind measurements from space, C3Winds will provide high-resolution wind fields needed for detailed investigations of severe wind events in occluded ETCs, rotational structures inside TC eyewalls, and ozone injections associated with tropopause folding events. Built upon mature imaging technologies and long history of stereoscopic remote sensing, C3Winds provides an innovative, cost-effective solution to global wind observations with the potential for increased diurnal sampling via CubeSat constellation.

Direct test of static stress versus dynamic stress triggering of aftershocks

USGS Publications Warehouse

Pollitz, F.F.; Johnston, M.J.S.

2006-01-01

Aftershocks observed over time scales of minutes to months following a main shock are plausibly triggered by the static stress change imparted by the main shock, dynamic shaking effects associated with passage of seismic waves from the main shock, or a combination of the two. We design a direct test of static versus dynamic triggering of aftershocks by comparing the near-field temporal aftershock patterns generated by aseismic and impulsive events occurring in the same source area. The San Juan Bautista, California, area is ideally suited for this purpose because several events of both types of M???5 have occurred since 1974. We find that aftershock rates observed after impulsive events are much higher than those observed after aseismic events, and this pattern persists for several weeks after the event. This suggests that, at least in the near field, dynamic triggering is the dominant cause of aftershocks, and that it generates both immediate and delayed aftershock activity.

Impact of Serine/Threonine Protein Kinases on the Regulation of Sporulation in Bacillus subtilis.

PubMed

Pompeo, Frédérique; Foulquier, Elodie; Galinier, Anne

2016-01-01

Bacteria possess many kinases that catalyze phosphorylation of proteins on diverse amino acids including arginine, cysteine, histidine, aspartate, serine, threonine, and tyrosine. These protein kinases regulate different physiological processes in response to environmental modifications. For example, in response to nutritional stresses, the Gram-positive bacterium Bacillus subtilis can differentiate into an endospore; the initiation of sporulation is controlled by the master regulator Spo0A, which is activated by phosphorylation. Spo0A phosphorylation is carried out by a multi-component phosphorelay system. These phosphorylation events on histidine and aspartate residues are labile, highly dynamic and permit a temporal control of the sporulation initiation decision. More recently, another kind of phosphorylation, more stable yet still dynamic, on serine or threonine residues, was proposed to play a role in spore maintenance and spore revival. Kinases that perform these phosphorylation events mainly belong to the Hanks family and could regulate spore dormancy and spore germination. The aim of this mini review is to focus on the regulation of sporulation in B. subtilis by these serine and threonine phosphorylation events and the kinases catalyzing them.

Beaver Mediated Water Table Dynamics in Mountain Peatlands

NASA Astrophysics Data System (ADS)

Karran, D. J.; Westbrook, C.; Bedard-Haughn, A.

2016-12-01

Water table dynamics play an important role in the ecological and biogeochemical processes that regulate carbon and water storage in peatlands. Beaver are common in these habitats and the dams they build have been shown to raise water tables in other environments. However, the impact of beaver dams in peatlands, where water tables rest close to the surface, has yet to be determined. We monitored a network of 50 shallow wells in a Canadian Rocky Mountain peatland for 6 years. During this period, a beaver colony was maintaining a number of beaver ponds for four years until a flood event removed the colony from the area and breached some of the dams. Two more years of data were collected after the flood event to assess whether the dams enhanced groundwater storage. Beaver dams raised water tables just as they do in other environments. Furthermore, water tables within 100 meters of beaver dams were more stable than those further away and water table stability overall was greater before the flood event. Our results suggest the presence/absence of beaver in peatlands has implications for groundwater water storage and overall system function.

[Nitrate storage and transport within a typical karst aquifer system in the paralleled ridge-valley of east Sichuan].

PubMed

Yang, Ping-Heng; Yuan, Dao-Xian; Ren, You-Rong; Xie, Shi-You; He, Qiu-Fang; Hu, Xiao-Feng

2012-09-01

In order to investigate the nitrate storage and transport in the karst aquifer system, the hydrochemical dynamics of Qingmuguan underground river system was monitored online by achieving high-resolution data during storm events and monthly data in normal weather. The principal component analysis was employed to analyze the karst water geochemistry. Results showed that nitrate in Jiangjia spring did not share the same source with soluble iron, manganese and aluminum, and exhibited different geochemical behaviors. Nitrate was derived from land surface and infiltrated together with soil water, which was mainly stored in fissure, pore and solution crack of karst unsaturated zone, whereas soluble iron, manganese and aluminum were derived from soil erosion and directly recharged the underground river through sinkholes and shafts. Nitrate transport in the karst aquifer system could be ideally divided into three phases, including input storage, fast output and re-inputting storage. Under similar external conditions, the karstification intensity of vadose zone was the key factor to determine the dynamics of nitrate concentrations in the groundwater during storm events. Nitrate stored in the karst vadose zone was easily released, which would impair the aquatic ecosystem and pose seriously threats to the local health. Thus, to strengthen the management of ecological system, changing the land-use patterns and scientifically applying fertilizer could effectively make a contribution to controlling mass nutrient input from the surface.

Confirmation of Small Dynamical and Stellar Masses for Extreme Emission Line Galaxies at z Approx. 2

NASA Technical Reports Server (NTRS)

Maseda, Michael V.; van Der Wel, Arjen; da Cunha, Elisabete; Rix, Hans-Walter; Pacifici, Camilla; Momcheva, Ivelina; Brammer, Gabriel B.; Franx, Marijn; van Dokkum, Pieter; Bell, Eric F.;

Event-by-Event Study of Space-Time Dynamics in Flux-Tube Fragmentation

DOE PAGES

Wong, Cheuk-Yin

2017-05-25

In the semi-classical description of the flux-tube fragmentation process for hadron production and hadronization in high-energymore » $e^+e^-$ annihilations and $pp$ collisions, the rapidity-space-time ordering and the local conservation laws of charge, flavor, and momentum provide a set of powerful tools that may allow the reconstruction of the space-time dynamics of quarks and mesons in exclusive measurements of produced hadrons, on an event-by-event basis. We propose procedures to reconstruct the space-time dynamics from event-by-event exclusive hadron data to exhibit explicitly the ordered chain of hadrons produced in a flux tube fragmentation. As a supplementary tool, we infer the average space-time coordinates of the $q$-$$\\bar q$$ pair production vertices from the $$\\pi^-$$ rapidity distribution data obtained by the NA61/SHINE Collaboration in $pp$ collisions at $$\\sqrt{s}$$ = 6.3 to 17.3 GeV.« less

Event-by-Event Study of Space-Time Dynamics in Flux-Tube Fragmentation

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

Wong, Cheuk-Yin

In the semi-classical description of the flux-tube fragmentation process for hadron production and hadronization in high-energymore » $e^+e^-$ annihilations and $pp$ collisions, the rapidity-space-time ordering and the local conservation laws of charge, flavor, and momentum provide a set of powerful tools that may allow the reconstruction of the space-time dynamics of quarks and mesons in exclusive measurements of produced hadrons, on an event-by-event basis. We propose procedures to reconstruct the space-time dynamics from event-by-event exclusive hadron data to exhibit explicitly the ordered chain of hadrons produced in a flux tube fragmentation. As a supplementary tool, we infer the average space-time coordinates of the $q$-$$\\bar q$$ pair production vertices from the $$\\pi^-$$ rapidity distribution data obtained by the NA61/SHINE Collaboration in $pp$ collisions at $$\\sqrt{s}$$ = 6.3 to 17.3 GeV.« less

Multi-frame X-ray Phase Contrast Imaging (MPCI) for Dynamic Experiments

NASA Astrophysics Data System (ADS)

Iverson, Adam; Carlson, Carl; Sanchez, Nathaniel; Jensen, Brian

2017-06-01

Recent advances in coupling synchrotron X-ray diagnostics to dynamic experiments are providing new information about the response of materials at extremes. For example, propagation based X-ray Phase Contrast Imaging (PCI) which is sensitive to differences in density has been successfully used to study a wide range of phenomena, e.g. jet-formation, compression of additive manufactured (AM) materials, and detonator dynamics. In this talk, we describe the current multi-frame X-ray phase contrast imaging (MPCI) system which allows up to eight frames per experiment, remote optimization, and an improved optical design that increases optical efficiency and accommodates dual-magnification during a dynamic event. Data will be presented that used the dual-magnification feature to obtain multiple images of an exploding foil initiator. In addition, results from static testing will be presented that used a multiple scintillator configuration required to extend the density retrieval to multi-constituent, or heterogeneous systems. The continued development of this diagnostic is fundamentally important to capabilities at the APS including IMPULSE and the Dynamic Compression Sector (DCS), and will benefit future facilities such as MaRIE at Los Alamos National Laboratory.

Statistical Mechanical Theory of Coupled Slow Dynamics in Glassy Polymer-Molecule Mixtures

NASA Astrophysics Data System (ADS)

Zhang, Rui; Schweizer, Kenneth

The microscopic Elastically Collective Nonlinear Langevin Equation theory of activated relaxation in one-component supercooled liquids and glasses is generalized to polymer-molecule mixtures. The key idea is to account for dynamic coupling between molecule and polymer segment motion. For describing the molecule hopping event, a temporal casuality condition is formulated to self-consistently determine a dimensionless degree of matrix distortion relative to the molecule jump distance based on the concept of coupled dynamic free energies. Implementation for real materials employs an established Kuhn sphere model of the polymer liquid and a quantitative mapping to a hard particle reference system guided by the experimental equation-of-state. The theory makes predictions for the mixture dynamic shear modulus, activated relaxation time and diffusivity of both species, and mixture glass transition temperature as a function of molecule-Kuhn segment size ratio and attraction strength, composition and temperature. Model calculations illustrate the dynamical behavior in three distinct mixture regimes (fully miscible, bridging, clustering) controlled by the molecule-polymer interaction or chi-parameter. Applications to specific experimental systems will be discussed.

Modeling study of radiation effects on thrombocytopoietic and granulocytopoietic systems in humans

NASA Astrophysics Data System (ADS)

Smirnova, O. A.

2011-07-01

Biologically motivated mathematical models, which describe the dynamics of thrombocytopoiesis and granulocytopoiesis in nonirradiated and irradiated humans, are developed. These models, being based on conventional biological theories, are implemented as the systems of nonlinear differential equations whose variables and constant parameters have clear biological meaning. Thorough analytical and numerical analysis of the proposed models is performed. It is found that the models on hand are capable of reproducing the dynamical regimes which are typical for the thrombocytopoiesis and granulocytopoiesis in the norm and in the case of hematological disorders, such as cyclic thrombocytopenia and cyclic neutropenia. The elaborated models are applied to investigate the dynamics of thrombocytopoiesis and granulocytopoiesis in astronauts exposed to space radiation during long-term missions such as voyages to Mars. The dose rate equivalent for space radiation (galactic cosmic rays (GCR) and solar particles event (SPE)) is taken as a variable parameter of the models. It is revealed that the thrombocytopoietic and granulocytopoietic systems can adapt themselves to GCR exposure. It is also shown that an SPE causes damped oscillations of the "effective" radiosensitivity of these cell systems that, in turn, determines the strength of their responses to the subsequent SPE. Specifically, depending on the time interval between SPEs, the preceding SPE can induce either radiosensitization or radioprotection effects on the thrombocytopoietic and granulocytopoietic systems. In the last case, adaptive responses to the subsequent SPE in these systems occur. All this testifies to the efficiency of employment of the developed models in investigation and prediction of effects of space radiation on the thrombocytopoietic and granulocytopoietic systems. The developed models of these vital body systems provide a better understanding of the risks to health from the solar particles events and enable one to evaluate the need of operational applications of countermeasures for astronauts in the long-term space missions.

Evaluation of cool season precipitation event characteristics over the Northeast US in a suite of downscaled climate model hindcasts

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Kim, Jinwon; Ferraro, Robert

2017-08-01

Cool season precipitation event characteristics are evaluated across a suite of downscaled climate models over the northeastern US. Downscaled hindcast simulations are produced by dynamically downscaling the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2) using the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (WRF) regional climate model (RCM) and the Goddard Earth Observing System Model, Version 5 (GEOS-5) global climate model. NU-WRF RCM simulations are produced at 24, 12, and 4-km horizontal resolutions using a range of spectral nudging schemes while the MERRA2 global downscaled run is provided at 12.5-km. All model runs are evaluated using four metrics designed to capture key features of precipitation events: event frequency, event intensity, even total, and event duration. Overall, the downscaling approaches result in a reasonable representation of many of the key features of precipitation events over the region, however considerable biases exist in the magnitude of each metric. Based on this evaluation there is no clear indication that higher resolution simulations result in more realistic results in general, however many small-scale features such as orographic enhancement of precipitation are only captured at higher resolutions suggesting some added value over coarser resolution. While the differences between simulations produced using nudging and no nudging are small, there is some improvement in model fidelity when nudging is introduced, especially at a cutoff wavelength of 600 km compared to 2000 km. Based on the results of this evaluation, dynamical regional downscaling using NU-WRF results in a more realistic representation of precipitation event climatology than the global downscaling of MERRA2 using GEOS-5.

Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics.

PubMed

Doshi, Urmi; Hamelberg, Donald

2015-05-01

Accelerated molecular dynamics (aMD) has been proven to be a powerful biasing method for enhanced sampling of biomolecular conformations on general-purpose computational platforms. Biologically important long timescale events that are beyond the reach of standard molecular dynamics can be accessed without losing the detailed atomistic description of the system in aMD. Over other biasing methods, aMD offers the advantages of tuning the level of acceleration to access the desired timescale without any advance knowledge of the reaction coordinate. Recent advances in the implementation of aMD and its applications to small peptides and biological macromolecules are reviewed here along with a brief account of all the aMD variants introduced in the last decade. In comparison to the original implementation of aMD, the recent variant in which all the rotatable dihedral angles are accelerated (RaMD) exhibits faster convergence rates and significant improvement in statistical accuracy of retrieved thermodynamic properties. RaMD in conjunction with accelerating diffusive degrees of freedom, i.e. dual boosting, has been rigorously tested for the most difficult conformational sampling problem, protein folding. It has been shown that RaMD with dual boosting is capable of efficiently sampling multiple folding and unfolding events in small fast folding proteins. RaMD with the dual boost approach opens exciting possibilities for sampling multiple timescales in biomolecules. While equilibrium properties can be recovered satisfactorily from aMD-based methods, directly obtaining dynamics and kinetic rates for larger systems presents a future challenge. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Environmental modeling in data-sparse regions: Mozambique demonstrator case

NASA Astrophysics Data System (ADS)

Schumann, G.; Niebuhr, E.; Rashid, K.; Escobar, V. M.; Andreadis, K.; Njoku, E. G.; Neal, J. C.; Voisin, N.; Pappenberger, F.; Phanthuwongpakdee, N.; Bates, P. D.; Chao, Y.; Moller, D.; Paron, P.

2014-12-01

Long time-series computations of seasonal and flood event inundation volumes from archived forecast rainfall events for the Lower Zambezi basin (Mozambique), using a coupled hydrology-hydrodynamic model, are correlated and regressed with satellite soil moisture observations and NWP rainfall forecasts as predictors for inundation volumes. This dynamic library of volume predictions can then be re-projected onto the topography to generate the corresponding floodplain and wetland inundation dynamics, including periods of flood and low flows. Especially for data-poor regions, the application potential of such a library of data is invaluable as the modeling chain is greatly simplified and readily available. The library is flexible, portable and transitional. Furthermore, deriving environmental indicators from this dynamic look-up catalogue would be relatively straightforward. Application fields are various and here we present conceptually a few that we plan to research in more detail and on some of which we already collaborate with other scientists and international institutions, though at the moment largely on an unfunded basis. The primary application is to implement an early warning system for flood inundation relief operations and flood inundation mitigation and resilience. Having this flood inundation warning system set up adequately would also allow looking into long-term predictions of crop productivity and consequently food security. Another potentially high-impact application is to relate flood inundation dynamics to disease modeling for public health monitoring and prediction, in particular focusing on Malaria. Last but not least, the dynamic inundation library we are building can be validated and complemented with advanced airborne radar imagery of flooding and inundated wetlands to study changes in wetland ecology and biodiversity with unprecedented detail in data-poor regions, in this case in particular the important wetlands of the Zambezi Delta.

Seasonal and flow-driven dynamics of particulate and dissolved mercury and methylmercury in a stream impacted by an industrial mercury source

DOE PAGES

Riscassi, Ami; Miller, Carrie; Brooks, Scott

2015-11-17

Sediments and floodplain soils in the East Fork Poplar Creek watershed (Oak Ridge, TN, USA) are contaminated with high levels of mercury (Hg) from an industrial source at the headwaters. Although baseflow conditions have been monitored, concentrations of Hg and methylmercury (MeHg) during high-flow storm events, when the stream is more hydrologically connected to the floodplain, have yet to be assessed. This paper evaluated baseflow and event-driven Hg and MeHg dynamics in East Fork Poplar Creek, 5 km upstream of the confluence with Poplar Creek, to determine the importance of hydrology to in-stream concentrations and downstream loads and to ascertainmore » whether the dynamics are comparable to those of systems without an industrial Hg source. Particulate Hg and MeHg were positively correlated with discharge (r 2 = 0.64 and 0.58, respectively) and total suspended sediment (r 2 = 0.97 and 0.89, respectively), and dissolved Hg also increased with increasing flow (r 2 = 0.18) and was associated with increases in dissolved organic carbon (r 2 = 0.65), similar to the dynamics observed in uncontaminated systems. Dissolved MeHg decreased with increases in discharge (r 2 = 0.23) and was not related to dissolved organic carbon concentrations (p = 0.56), dynamics comparable to relatively uncontaminated watersheds with a small percentage of wetlands (<10%). Finally, although stormflows exert a dominant control on particulate Hg, particulate MeHg, and dissolved Hg concentrations and loads, baseflows were associated with the highest dissolved MeHg concentration (0.38 ng/L) and represented the majority of the annual dissolved MeHg load.« less

The effect of food portion sizes on the obesity prevention using system dynamics modelling

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Hj; Zaibidi, Nerda Zura

2014-09-01

The rise in income and population growth have increased the demand for food and induced changes in food habits, food purchasing and consumption patterns in Malaysia. With this transition, one of the plausible causes of weight gain and obesity is the frequent consumption of outside food which is synonymous with bigger portion size. Therefore, the aim of this paper is to develop a system dynamics model to analyse the effect of reducing food portion size on weight and obesity prevention. This study combines the different strands of knowledge comprise of nutrition, physical activity and body metabolism. These elements are synthesized into a system dynamics model called SIMULObese. Findings from this study suggested that changes in eating behavior should not emphasize only on limiting the food portion size consumption. The efforts should also consider other eating events such as controlling the meal frequency and limiting intake of high-calorie food in developing guidelines to prevent obesity.

Who is Crossing Where?: Infants’ Discrimination of Figures and Grounds in Events

PubMed Central

Göksun, Tilbe; Hirsh-Pasek, Kathy; Golinkoff, Roberta Michnick; Imai, Mutsumi; Konishi, Haruka; Okada, Hiroyuki

2011-01-01

To learn relational terms such as verbs and prepositions, children must first dissect and process dynamic event components. This paper investigates the way in which 8- to 14-month-old English-reared infants notice the event components, figure (i.e., the moving entity) and ground (i.e., stationary setting), in both dynamic (Experiment 1) and static representations of events (Experiment 2) for categorical ground distinctions expressed in Japanese, but not in English. We then compare both 14- and 19-month-old English- and Japanese-reared infants’ processing of grounds to understand how language learning interacts with the conceptualization of these constructs (Experiment 3). Results suggest that 1) infants distinguish between figures and grounds in events; 2) they do so differently for static vs. dynamic displays; 3) early in the second year, children from diverse language environments form nonnative - perhaps universal - event categories; and 4) these event categories shift over time as children have more exposure to their native tongue. PMID:21839990

Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

NASA Astrophysics Data System (ADS)

Subramanian, Aneesh C.; Palmer, Tim N.

2017-06-01

Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.