997 resultados para movement simulation


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Nowadays, train control in-lab simulation tools play a crucial role in reducing extensive and expensive on-site railway testing activities. In this paper, we present our contribution in this arena by detailing the internals of our European Railway Train Management System in-lab demonstrator. This demonstrator is built over a general-purpose simulation framework, Riverbed Modeler, previously Opnet Modeler. Our framework models both ERTMS subsystems, the Automatic Train Protection application layer based on movement authority message exchange and the telecommunication subsystem based on GSM-R communication technology. We provide detailed information on our modelling strategy. We also validate our simulation framework with real trace data. To conclude, under current industry migration scenario from GSM-R legacy obsolescence to IP-based heterogeneous technologies, our simulation framework represents a singular tool to railway operators. As an example, we present the assessment of related performance indicators for a specific railway network using a candidate replacement technology, LTE, versus current legacy technology. To the best of our knowledge, there is no similar initiative able to measure the impact of the telecommunication subsystem in the railway network availability.

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The LPT (Lanzhou Penning Trap) is under construction and its task is to perforin direct mass measurement of fusion-evaporation residue, and if possible for heavy isotopes. Detailed simulations have been clone for a good understanding to the ion's movement and mechanics in the trap. The optimizal ion of the LPT is also performed based on the simulation. With a scale of 0.5 mm per grid used in the, simulation and many other limitations a highest mass resolution has been achieved to be 1.9 x 10(-5). An unexpected behavioin in the simulation related to magnetron motion has been found.

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We applied a primitive equation ocean model to simulate submesoscale activities and processes over the shelf of the northern South China Sea (NSCS) with a one-way nesting technology for downscaling. The temperature and density fields showed that submesoscale activities were ubiquitous in the NSCS shelf. The vertical velocity was considerably enhanced in submesoscale processes and could reach an average of 58 m per day in the subsurface. At this point, the mixed layer depth also was deepened along the front, and the surface kinetic energy also increased with the intense vertical movement induced by submesoscale activity. Thus, submesoscale stirring/mixing is important for tracers, such as temperature, salinity, nutrients, dissolved organic, and inorganic carbon. This result may have implication for climate and biogeochemical investigations.

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A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.

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Simulation of pedestrian evacuations of smart buildings in emergency is a powerful tool for building analysis, dynamic evacuation planning and real-time response to the evolving state of evacuations. Macroscopic pedestrian models are low-complexity models that are and well suited to algorithmic analysis and planning, but are quite abstract. Microscopic simulation models allow for a high level of simulation detail but can be computationally intensive. By combining micro- and macro- models we can use each to overcome the shortcomings of the other and enable new capability and applications for pedestrian evacuation simulation that would not be possible with either alone. We develop the EvacSim multi-agent pedestrian simulator and procedurally generate macroscopic flow graph models of building space, integrating micro- and macroscopic approaches to simulation of the same emergency space. By “coupling” flow graph parameters to microscopic simulation results, the graph model captures some of the higher detail and fidelity of the complex microscopic simulation model. The coupled flow graph is used for analysis and prediction of the movement of pedestrians in the microscopic simulation, and investigate the performance of dynamic evacuation planning in simulated emergencies using a variety of strategies for allocation of macroscopic evacuation routes to microscopic pedestrian agents. The predictive capability of the coupled flow graph is exploited for the decomposition of microscopic simulation space into multiple future states in a scalable manner. By simulating multiple future states of the emergency in short time frames, this enables sensing strategy based on simulation scenario pattern matching which we show to achieve fast scenario matching, enabling rich, real-time feedback in emergencies in buildings with meagre sensing capabilities.

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The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

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Molecular dynamics has been employed to model the fracture of a twodimensional triangular atomic lattice. The N-body Sutton-Chen potential developed for fcc metals and its extended version (Rafii-Tabar and Sutton) for fcc random binary alloys were used for the interatomic interactions. It is shown that at low temperatures cleavage fractures can occur in both an elemental metal and an alloy. At elevated temperatures the nucleation of dislocations is shown to cause a brittle-to-ductile transition. For the brittle crack propagation in the elemental metal, crack propagation speeds have been computed for different stress rates, and a crack instability found to exist as the speed reaches a critical value of about 32% of the Rayleigh wave speed. For the random alloy, we find that the dislocation movement can be affected by the distorted lattice.

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We present here a decoupling technique to tackle the entanglement of the nonlinear boundary condition and the movement of the char/virgin front for a thermal pyrolysis model for charring materials. Standard numerical techniques to solve moving front problems — often referred to as Stefan problems — encounter difficulties when dealing with nonlinear boundaries. While special integral methods have been developed to solve this problem, they suffer from several limitations which the technique described here overcomes. The newly developed technique is compared with the exact analytical solutions for some simple ideal situations which demonstrate that the numerical method is capable of producing accurate numerical solutions. The pyrolysis model is also used to simulate the mass loss process from a white pine sample exposed to a constant radiative flux in a nitrogen atmosphere. Comparison with experimental results demonstrates that the predictions of mass loss rates and temperature profile within the solid material are in good agreement with the experiment.

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Molecular dynamics has been employed to model the fracture of a two dimensional triangular atomic lattice. The N-body Sutton-Chen potential developed for fcc metals and its extended version (Rafii-Tabar and Sutton) for fcc random binary alloys were used for the interatomic interactions. It is shown that at low temperatures cleavage fractures can occur in both an elemental metal and an alloy. At elevated temperatures the nucleation of dislocations is shown to cause a brittle-to-ductile transition. For the brittle crack propagation in the elemental metal, crack propagation speeds have been computed for different stress rates, and a crack instability found to exist as the speed reaches a critical value of about 32% of the Rayleigh wave speed. For the random alloy, we find that the dislocation movement can be affected by the distorted lattice.

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This paper describes work carried out in the FIRE EXIT research project. FIRE EXIT aims to develop an Evacuation Simulator, capable of addressing issues of mustering, ship motions, fire and abandonment. In achieving these aims, FIRE EXIT took as its starting point the state-of-the-art in ship evacuation simulation (the maritimeEXODUS software), fire simulation (the SMARTFIRE software) and large-scale experimental facilities (the SHEBA facility). It then significantly enhanced these capabilities. A number of new technologies have been developed in achieving these objectives. The innovations include directly linking CFD fire simulation with evacuation and abandonment software and automatic data transfer from concept design software allowing rapid generation of ship simulation models. Software usability was augmented by a module for interpretation of evacuation software output. Enhancements to a ship evacuation testing rig have resulted in a unique facility, capable of providing passenger movement data for realistic evacuation scenarios and large scale tests have provided meaningful data for the evacuation simulation.

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In 1998, Swissair Flight I I I (SR111) developed an in-flight fire shortly after take-off which resulted in the loss of the aircraft, a McDonnell Douglas MD-I 1, and all passengers and crew. The Transportation Safety Board (TSB) of Canada, Fire and Explosion Group launched a four year investigation into the incident in an attempt to understand the cause and subsequent mechanisms which lead to the rapid spread of the in-flight fire. As part of this investigation, the SMARTFIRE Computational Fluid Dynamics (CFD) software was used to predict the 'possible' development of the fire and associated smoke movement. In this paper the CFD fire simulations are presented and model predictions compared with key findings from the investigation. The model predictions are shown to be consistent with a number of the investigation findings associated with the early stages of the fire development. The analysis makes use of simulated pre-fire airflow conditions within the MD-11 cockpit and above ceiling region presented in an earlier publication (Part 1) which was published in The Aeronautical Journal in January 2006(4).

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An individual-based model (IBM) for the simulation of year-to-year survival during the early life-history stages of the north-east Atlantic stock of mackerel (Scomber scombrus) was developed within the EU funded Shelf-Edge Advection, Mortality and Recruitment (SEAMAR) programme. The IBM included transport, growth and survival and was used to track the passive movement of mackerel eggs, larvae and post-larvae and determine their distribution and abundance after approximately 2 months of drift. One of the main outputs from the IBM, namely distributions and numbers of surviving post-larvae, are compared with field data as recruit (age-0/age-1 juveniles) distribution and abundance for the years 1998, 1999 and 2000. The juvenile distributions show more inter-annual and spatial variability than the modelled distributions of survivors; this may be due to the restriction of using the same initial egg distribution for all 3 yr of simulation. The IBM simulations indicate two main recruitment areas for the north-east Atlantic stock of mackerel, these being Porcupine Bank and the south-eastern Bay of Biscay. These areas correspond to areas of high juvenile catches, although the juveniles generally have a more widespread distribution than the model simulations. The best agreement between modelled data and field data for distribution (juveniles and model survivors) is for the year 1998. The juvenile catches in different representative nursery areas are totalled to give a field abundance index (FAI). This index is compared with a model survivor index (MSI) which is calculated from the total of survivors for the whole spawning season. The MSI compares favourably with the FAI for 1998 and 1999 but not for 2000; in this year, juvenile catches dropped sharply compared with the previous years but there was no equivalent drop in modelled survivors.

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This study aims to replicate Apple’s stock market movement by modeling major investment profiles and investors. The present model recreates a live exchange to forecast any predictability in stock price variation, knowing how investors act when it concerns investment decisions. This methodology is particularly relevant if, just by observing historical prices and knowing the tendencies in other players’ behavior, risk-adjusted profits can be made. Empirical research made in the academia shows that abnormal returns are hardly consistent without a clear idea of who is in the market in a given moment and the correspondent market shares. Therefore, even when knowing investors’ individual investment profiles, it is not clear how they affect aggregate markets.

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Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

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Do we view the world differently if it is described to us in figurative rather than literal terms? An answer to this question would reveal something about both the conceptual representation of figurative language and the scope of top-down influences oil scene perception. Previous work has shown that participants will look longer at a path region of a picture when it is described with a type of figurative language called fictive motion (The road goes through the desert) rather than without (The road is in the desert). The current experiment provided evidence that such fictive motion descriptions affect eye movements by evoking mental representations of motion. If participants heard contextual information that would hinder actual motion, it influenced how they viewed a picture when it was described with fictive motion. Inspection times and eye movements scanning along the path increased during fictive motion descriptions when the terrain was first described as difficult (The desert is hilly) as compared to easy (The desert is flat); there were no such effects for descriptions without fictive motion. It is argued that fictive motion evokes a mental simulation of motion that is immediately integrated with visual processing, and hence figurative language can have a distinct effect on perception. (c) 2005 Elsevier B.V. All rights reserved.