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

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

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

Applicant Attraction Strategies: An Organizational Perspective

Developing labor shortages are expected to increase the importance of applicant attraction into the next century. Unfonunately, previous research has provided little in the way of unified theory or operational guidelines for organizations confronted with attraction difficulties. In part, this is because much research has been framed from the applicant\u27s, rather than the organization\u27s, perspective. In addition, attraction-related theories and research are scattered across a variety of literatures, and often identified primarily with topics other than attraction per se (e.g., wage, motivation, or discrimination theories). The present paper draws on multiple literatures to develop a model of applicant attraction from the organization\u27s perspective. In it, we (1) outline three general strategies for enhancing applicant attraction, (2) propose broad categories of contingency factors expected to affect the choice (and potential effectiveness) of alternative strategies, (3) suggest probable interrelationships among the strategies, (4) link applicant attraction strategies to other human resource practices, (5) outline various dimensions of attraction outcomes (e.g. qualitative and quantitative, attitudinal and behavioral, temporal), and (6) discuss implications for future attraction research