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Andrews, Alison E.

Publications and source records attributed to Andrews, Alison E..

Knowledge-based zonal grid generation for computational fluid dynamics

Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

Andrews, Alison E.

Knowledge-based flow field zoning

Automation flow field zoning in two dimensions is an important step towards easing the three-dimensional grid generation bottleneck in computational fluid dynamics. A knowledge based approach works well, but certain aspects of flow field zoning make the use of such an approach challenging. A knowledge based flow field zoner, called EZGrid, was implemented and tested on representative two-dimensional aerodynamic configurations. Results are shown which illustrate the way in which EZGrid incorporates the effects of physics, shape description, position, and user bias in a flow field zoning.

Andrews, Alison E.

Knowledge-based flow field zoning

Automation flow field zoning in two dimensions is an important step towards easing the three-dimensional grid generation bottleneck in computational fluid dynamics. A knowledge based approach works well, but certain aspects of flow field zoning make the use of such an approach challenging. A knowledge based flow field zoner, called EZGrid, was implemented and tested on representative two-dimensional aerodynamic configurations. Results are shown which illustrate the way in which EZGrid incorporates the effects of physics, shape description, position, and user bias in a flow field zoning.

Andrews, Alison E.

Theoretical analysis of aircraft afterbody flow

Computational methods solving the thin shear layer formulation of the compressible, Reynolds-averaged Navier-Stokes equations are presently used to investigate the strongly interactive flow field about aircraft afterbodies. Solutions for a variety of axisymmetric afterbody and nozzle geometries are solved by means of a time-dependent implicit numerical algorithm for both subsonic and supersonic external flows, and the results obtained are compared with experimental data. A novel adaptive-grid technique is used to resolve flow regimes having large gradients, as well as to improve the accuracy and efficiency of the computational scheme.

Deiwert, George S.

Progress and challenges in the application of artificial intelligence to computational fluid dynamics

An approach to analyzing CFD knowledge-based systems is proposed which is based, in part, on the concept of knowledge-level analysis. Consideration is given to the expert cooling fan design system, the PAN AIR knowledge system, grid adaptation, and expert zonal grid generation. These AI/CFD systems demonstrate that current AI technology can be successfully applied to well-formulated problems that are solved by means of classification or selection of preenumerated solutions.

Andrews, Alison E.

AI at Ames: Artificial Intelligence research and application at NASA Ames Research Center, Moffett Field, California, February 1985

Charts are given that illustrate function versus domain for artificial intelligence (AI) applications and interests and research area versus project number for AI research. A list is given of project titles with associated project numbers and page numbers. Also, project descriptions, including title, participants, and status are given.

Andrews, Alison E.