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Corporate memory contribution to integrated design and analysis systems

Published online by Cambridge University Press:  03 February 2016

M. R. Mendenhall
M. R. Mendenhall*
Affiliation:
Nielsen Engineering & Research, Mountain View, CA, USA
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Abstract

The recent decline in the USA aerospace industry has resulted in fewer programs, fewer engineers, and a potential loss of capability for future technology development. As engineers retire or leave the industry, their corporate memory or retained knowledge must be preserved for future use. A process to capture their expert knowledge is described, and a framework which provides a means to retrieve and use this valuable technical information is shown. Four examples of integrated design and analysis systems for four diverse technologies and applications are discussed.

Type
Research Article
Information
The Aeronautical Journal , Volume 110 , Issue 1106 , April 2006 , pp. 257 - 263
Copyright
Copyright © Royal Aeronautical Society 2006 

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References

1. McClure, G.F., Is aerospace worth saving? IEEE, Today’s Engineer, July 2003.Google Scholar
2. Shaw, G.P. and Smith, D.Y., Don’t let knowledge and experience fly away: Leveraging scarce expertise to support ongoing competitiveness in the aerospace and defense industry, Accenture, 2003.Google Scholar
3. Pulham, E.G., Space and the work force of the future, Space News, 7 October 2002, p 17.Google Scholar
4. Final Report from the Commission on the Future of the United States Aerospace Industry, www.ita.doc.gov/td/aerospace/aerospacecom-mission/, November 2002.Google Scholar
5. Hart, A., Knowledge Acquisition for Expert Systems, 1992, Second Edition, McGraw-Hill.Google Scholar
6. Mcgraw, K.L. and Harbison-Briggs, K., Knowledge Acquisition: Principals and Guidelines, 1989, Prentice Hall.Google Scholar
7. Mendenhall, M.R., Hegedus, M.C., Rodman, L.C. and Faltz, J.A., Integrated Aerodynamic Design and Analysis of Advanced Launch Vehicles, July 2001, Vol I Technical Report, Nielsen Engineering & Research, NEAR TR 566.Google Scholar
8. Hegedus, M.C., Mendenhall, M.R., Perkins, S.C., Stremel, P.M. and Faltz, J.A., Engineering analysis for rocket sled aerodynamics, AIAA 2006-0664, January 2006.Google Scholar
9. Perkins, S.C., Wardlaw, A.B., Priolo, A.B. and Baltakis, F., NEARZEUS User Manual, May 1996, Vol I: Operational Instructions, Nielsen Engineering and Research, NEAR TR 459.Google Scholar
10. Mendenhall, M.R., Stremel, P M., Hegedus, M.C. and Faltz, J.A., BPX — A Best-Practices Expert System for CFD, September 2005, Nielsen Engineering & Research, NEAR TR 614.Google Scholar
11. Lee, J.R., Certainty in Stockpile Computing: Recommending a Verification and Validation Program for Scientific Software, November 1998, SAND98-2420, Sandia National Laboratories.Google Scholar
12. Hegedus, M.C. and Mendenhall, M.R., An Intelligent Data Retrieval and Analysis Tool, September 2004, Nielsen Engineering & Research, NEAR TR 608.Google Scholar