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[en] Cellular automata by definition consist of a finite or infinite number of cells, say of unit length, with each cell having the same transition function. These cells are usually considered as the smallest elements and so the space filled with these cells becomes discrete. Nevertheless, large pictures created by such cellular automata look very fractal. So we try to replace each cell by a couple of smaller cells, which have the same transition functions as the large ones. There are automata where this replacement does not destroy the macroscopic structure. In these cases this nesting process can be iterated. The paper contains large classes of automata with the above properties. In the case of one dimensional automata with two states and next neighbour interaction and a nesting function of the same type a complete classification is given. (author)
[en] This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project
[en] In June of 2003, about 250 computational scientists and mathematicians being funded by the DOE Office of Science met in Arlington, VA, to attend a 2-day workshop on the Science Case for Large-scale Simulation (SCaLeS). This document was the output of the Plasma Science Section of that workshop. The conclusion is that exciting and important progress can be made in the field of Plasma Science if computer power continues to grow and algorithmic development continues to occur at the rate that it has in the past. Full simulations of burning plasma experiments could be possible in the 5-10 year time frame if an aggressive growth program is launched in this area
[en] A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method
[en] The Turbine-99 test case, a Kaplan draft tube model, aimed to determine the state of the art within draft tube simulation. Three workshops were organized on the matter in 1999, 2001 and 2005 where the geometry and experimental data were provided as boundary conditions to the participants. Since the last workshop, computational power and flow modelling have been developed and the available data completed with unsteady pressure measurements and phase resolved velocity measurements in the cone. Such new set of data together with the corresponding phase resolved velocity boundary conditions offer new possibilities to validate unsteady numerical simulations in Kaplan draft tube. The present work presents simulation of the Turbine-99 test case with time dependent angular resolved inlet velocity boundary conditions. Different grids and time steps are investigated. The results are compared to experimental time dependent pressure and velocity measurements.
[en] A desktop computer program used at Sandia National Laboratories, Albuquerque, NM simulates a user-defined lighting configuration. This program is an engineering tool developed to aid the designer in verifying a particular exterior lighting configuration defined by a site/system specification. Although primarily for perimeter security lighting systems, this program has potential use in any application where the light is approximated by a point source. A data base of luminaire photometric information is maintained for use with this program. The user defines the simulation configuration with a rectangular grid and specified luminaire positions. Illumination calculations for regularly spaced points in that area and for isocandela contour plots are performed. The numerical and graphical output for a particular site model are then available for analysis to verify the site specifications. The amount of time spent on point illumination computations with this program is much less than that required for tedious hand calculations. The ease with which various parameters can be interactively modified with the program also reduces the time and labor expended. This program has been used to air designers in several lighting scenarios for both foreign and domestic projects. Good results have been obtained in the field from using the program simulations as a design aid
[en] The last decade has seen an unprecedented growth in artificial intelligence and photonic technologies, both of which drive the limits of modern-day computing devices. In line with these recent developments, this work brings together the state of the art of both fields within the framework of reinforcement learning. We present the blueprint for a photonic implementation of an active learning machine incorporating contemporary algorithms such as SARSA, Q-learning, and projective simulation. We numerically investigate its performance within typical reinforcement learning environments, showing that realistic levels of experimental noise can be tolerated or even be beneficial for the learning process. Remarkably, the architecture itself enables mechanisms of abstraction and generalization, two features which are often considered key ingredients for artificial intelligence. The proposed architecture, based on single-photon evolution on a mesh of tunable beamsplitters, is simple, scalable, and a first integration in quantum optical experiments appears to be within the reach of near-term technology. (paper)
[en] We present an analysis and visualization prototype using the concept of a flow topology graph (FTG) for characterization of flow in constrained networks, with a focus on discrete fracture networks (DFN), developed collaboratively by geoscientists and visualization scientists. Our method allows users to understand and evaluate flow and transport in DFN simulations by computing statistical distributions, segment paths of interest, and cluster particles based on their paths. The new approach enables domain scientists to evaluate the accuracy of the simulations, visualize features of interest, and compare multiple realizations over a specific domain of interest. Geoscientists can simulate complex transport phenomena modeling large sites for networks consisting of several thousand fractures without compromising the geometry of the network. However, few tools exist for performing higher-level analysis and visualization of simulated DFN data. The prototype system we present addresses this need. Here, we demonstrate its effectiveness for increasingly complex examples of DFNs, covering two distinct use cases - hydrocarbon extraction from unconventional resources and transport of dissolved contaminant from a spent nuclear fuel repository.