A practical adaptive-grid method for complex fluid-flow problems

A practical solution, adaptive-grid method utilizing a tension and torsion spring analogy is proposed for multidimensional fluid flow problems. The tension spring, which connects adjacent grid points to each other, controls grid spacings. The torsion spring, which is attached to each grid node, controls inclinations of coordinate lines and grid skewness. A marching procedure was used that results in a simple tridiagonal system of equations at each coordinate line to determine grid-point distribution. Multidirectional adaptation is achieved by successive applications of one-dimensional adaptation. Examples of applications for axisymmetric afterbody flow fields and two dimensional transonic airfoil flow fields are shown

Modeling Human Understanding of Complex Intentional Action with a Bayesian Nonparametric Subgoal Model

Most human behaviors consist of multiple parts, steps, or subtasks. These structures guide our action planning and execution, but when we observe others, the latent structure of their actions is typically unobservable, and must be inferred in order to learn new skills by demonstration, or to assist others in completing their tasks. For example, an assistant who has learned the subgoal structure of a colleague's task can more rapidly recognize and support their actions as they unfold. Here we model how humans infer subgoals from observations of complex action sequences using a nonparametric Bayesian model, which assumes that observed actions are generated by approximately rational planning over unknown subgoal sequences. We test this model with a behavioral experiment in which humans observed different series of goal-directed actions, and inferred both the number and composition of the subgoal sequences associated with each goal. The Bayesian model predicts human subgoal inferences with high accuracy, and significantly better than several alternative models and straightforward heuristics. Motivated by this result, we simulate how learning and inference of subgoals can improve performance in an artificial user assistance task. The Bayesian model learns the correct subgoals from fewer observations, and better assists users by more rapidly and accurately inferring the goal of their actions than alternative approaches.Comment: Accepted at AAAI 1

Simulation of complex three-dimensional flows

The concept of splitting is used extensively to simulate complex three dimensional flows on modern computer architectures. Used in all aspects, from initial grid generation to the determination of the final converged solution, splitting is used to enhance code vectorization, to permit solution driven grid adaption and grid enrichment, to permit the use of concurrent processing, and to enhance data flow through hierarchal memory systems. Three examples are used to illustrate these concepts to complex three dimensional flow fields: (1) interactive flow over a bump; (2) supersonic flow past a blunt based conical afterbody at incidence to a free stream and containing a centered propulsive jet; and (3) supersonic flow past a sharp leading edge delta wing at incidence to the free stream

トンプソンの組織論と不確実性問題

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ORの実施問題にたいする相互理解アプローチについて

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総合生産計画モデルの発展 : 問題解決手法の類型(2)

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