Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-20T00:36:44.540Z Has data issue: false hasContentIssue false
  • English
  • Français

An Artificial Intelligence Approach to Real Time control of carbonization

Published online by Cambridge University Press:  22 February 2011

William J. Pardee ,
Kwang Chung  and
Ming Shong Lan
William J. Pardee
Affiliation:
Rockwell International Science Center, 1085 Camino Dos Rios, Thousand Oaks, CA, 91360.
Kwang Chung
Affiliation:
Rockwell International Science Center, 1085 Camino Dos Rios, Thousand Oaks, CA, 91360.
Ming Shong Lan
Affiliation:
Rockwell International Science Center, 1085 Camino Dos Rios, Thousand Oaks, CA, 91360.
Get access

Extract

Carbonization of carbon-carbon composites is presently a slow, costly process. The failure rate and the variation in final material properties are both excessive. The complex physical and chemical changes require new control methods. Real time sensing of material properties can, in combination with a priori expert knowledge, be used to improve real time model estimates of process outcome and to revise the process. The basic elements of the control strategy for real time control of carbonization based on thermal, acoustic, conductivity, and gas chemistry sensors are described. Preliminary results relate real time gas analysis to physical changes.

Type
Research Article
Information
MRS Online Proceedings Library (OPL) , Volume 117: Symposium C – Process Diagnostics: Materials, Combustion, Fusion , 1988 , 103
Copyright
Copyright © Materials Research Society 1988

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Brown, S.C., Bhe, S.T., Clemons, K.T., Reese, H.F., and Sreenivasan, T.N.,”Process Science for 2D Carbon-Carbon Exit Cones”, AFWAL-TR-86–4028 (1986).Google Scholar

2 Pardee, W. J. and Shaff, M. A., “Architecture for Reasoning about Materials Processes”, submitted to AAAI.Google Scholar

3 Corkill, D. D., Gallagher, K. Q., and Johnson., P.M. “Achieving flexibility, efficiency, and generality in blackboard architectures”. Proceedings of AAAI-87,:18–23 (1987).Google Scholar