In this paper a procedure for systematic a priori derivation of the lattice Boltzmann models for nonideal gases from the Enskog equation (the modified Boltzmann equation for dense gases) is presented. This treatment p...
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In this paper a procedure for systematic a priori derivation of the lattice Boltzmann models for nonideal gases from the Enskog equation (the modified Boltzmann equation for dense gases) is presented. This treatment provides a unified theory of lattice Boltzmann models for nonideal gases. The lattice Boltzmann equation is systematically obtained by discretizing the Enskog equation in phase space and time. The lattice Boltzmann model derived in this paper is thermodynamically consistent up to the order of discretization error. Existing lattice Boltzmann models for nonideal gases are analyzed and compared in detail. An evaluation of these models is made in light of the general procedure to construct the lattice Boltzmann model for nonideal gases presented in this work.
In current matched field processing (MFP) methods all the algorithms concentrate on generating a single high fidelity replica for matching the received signals. Several well known sources of mismatch limit this, so on...
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ISBN:
(纸本)0780365143
In current matched field processing (MFP) methods all the algorithms concentrate on generating a single high fidelity replica for matching the received signals. Several well known sources of mismatch limit this, so one must accept some degree of signal gain degradation in most experiments. Generally, less than 5 dB is acceptable, but beyond this the power leaks into too many other resolution cells and MFP usually does not "focus" on the target even when the "in bin" signal to noise ratio at a single sensor is large. Here we accept that the ocean is an uncertain environment and use a stochastic representation for the signal which spans more than one spatial dimension. We first examine the covariance structure of signals propagating In a random medium. This can be done both analytically using results in the acoustics literature or by simulations which incorporate the ocean physics of random fluctuations. Next, we consider a generalization of MFP, which we term stochastic matched field processing (SMFP) which attempts to focus the power from all the signal dimensions. Finally, we consider the deeper question of when does an uncertain ocean medium randomize the spatial structure so much that localization cannot be done. Probably a more important application of stochastic signal models is for robust nulling techniques. Many existing arrays do not achieve their full potential for nulling because the environment is not stationary over the time scales required for adaptive methods, commonly termed the "snap-shot deficient" situation. If one attempts parametric methods, the spatial signals leading to the array manifold do not span the space of the interfering signals because the ocean has randomized them. Higher dimensional nulling such as adjacent resolution cells has been done, but it is not clear if this is the appropriate physical model for spanning the interference. Here we use acoustic propagation models for this and examine nulling techniques which are robust to the u
This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the Unive...
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This paper surveys control architectures proposed in the literature and describes a control architecture that is being developed for a semi-autonomous underwater vehicle for intervention missions (SAUVIM) at the University of Hawaii. Conceived as hybrid, this architecture has been organized in three layers: planning, control and execution. The mission is planned with a sequence of subgoals. Each subgoal has a related task supervisor responsible for arranging a set of pre-programmed task modules in order to achieve the subgoal. Task modules are the key concept of the architecture. They are the main building blocks and can be dynamically re-arranged by the task supervisor. In our architecture, deliberation takes place at the planning layer while reaction is dealt through the parallel execution of the task modules. Hence, the system presents both a hierarchical and an heterarchical decomposition, being able to show a predictable response while keeping rapid reactivity to the dynamic environment.
Linear theory analysis and particle-in-cell simulations show that a spatial transverse gradient in the ion drift parallel to the magnetic field, dVdi/dx≤Ωi, where Ωi is the ion cyclotron frequency, can generate a b...
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Linear theory analysis and particle-in-cell simulations show that a spatial transverse gradient in the ion drift parallel to the magnetic field, dVdi/dx≤Ωi, where Ωi is the ion cyclotron frequency, can generate a broadband multimode spectrum extending from ω≪Ωi to ω≫Ωi. Nonlinearly, these waves lead to multiscale spatially coherent structures, substantial cross-field transport, ion energization, and phase-space diffusion. Large spikes are formed in the parallel electric field time series. These signatures are similar to the Fast Auroral Snapshot satellite observations in the upward current region.
In this paper, we investigate the existence of higher-order dynamics in lattice-based models. We have identified two conditions that determine whether a model would allow some Burnett-like equations when the Chapman-E...
In this paper, we investigate the existence of higher-order dynamics in lattice-based models. We have identified two conditions that determine whether a model would allow some Burnett-like equations when the Chapman-Enskog expansion is used. These two conditions are the number of the conserved quantity as well as the space and time discretization. We shall demonstrate these conditions by discussing (1) pure diffusion equation and (2) hydrodynamic equations. While the fact that diffusion equation allows the higher-order dynamics can be shown easily, we will illustrate that care must be taken when deriving Burnett-like equations for lattice-based hydrodynamics models using the Chapman-Enskog method.
In this paper, we investigate the existence of higher-order dynamics in lattice-based models. We have identified two conditions that determine whether a model would allow some Burnett-like equations when the Chapman-E...
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Opus is a new programming language designed to assist in coordinating the execution of multiple, independent program modules. With the help of Opus, coarse grained task parallelism between data parallel modules can be...
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This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing ove...
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ISBN:
(纸本)0780359011
This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing over 18 million tetrahedra, allows us to extend our performance results to a problem which is more than 30 times larger than the one we examined previously. This high resolution dataset also allows us to see fine, three-dimensional features in the flow field. All our tests were performed on the SGI/Cray T3E operated by NASA's Goddard Space Flight Center. Using 511 processors, a rendering rate of almost 9 million tetrahedra/second was achieved with a parallel overhead of 26%.
In this study we propose an efficient method to parallelize high-order compact numerical algorithms for the solution of three-dimensional PDEs in a spacetime domain. The proposed parallelization method includes 3-D pa...
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This paper describes work-in-progress on developing parallel visualization strategies for 3D Adaptive Mesh Refinement (AMR) data. AMR is a simple and powerful tool for modeling many important scientific and engineerin...
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ISBN:
(纸本)0769500870
This paper describes work-in-progress on developing parallel visualization strategies for 3D Adaptive Mesh Refinement (AMR) data. AMR is a simple and powerful tool for modeling many important scientific and engineering problems. However visualization tools for 3D AMR data are not generally available. Converting AMR data onto a uniform mesh would result in high storage requirements, and rendering the uniform-mesh data on an average graphics workstation can be painfully slow if not impossible. The adaptive nature of the embedded mesh demands sophisticated visualization calculations. In this work, we compare the performance and storage requirements of a parallel volume renderer for regular-mesh data with a new parallel renderer based on adaptive sampling. While both renderers can achieve interactive visualization, the new approach offers significant performance gains, as indicated by our experiments on the SGI/Cray T3E.
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