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Computer-aided rehabilitation design

Published online by Cambridge University Press:  27 February 2009

Teresa Adams ,
Chris Hendrickson  and
Paul Christiano
Teresa Adams
Affiliation:
Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, Wl 53706, U.S.A.
Chris Hendrickson
Affiliation:
Department of Civil Engineering, Carnegie–Mellon University, Pittsburgh, PA 15213, U.S.A.
Paul Christiano
Affiliation:
Carnegie Institute of Technology, Carnegie–Mellon University, Pittsburgh, PA 15213, U.S.A.
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Abstract

The conventional engineering design process consisting of three phases, synthesis, analysis and evaluation can be extended for solving rehabilitation problems by including a diagnosis phase during which abnormalities and malfunctions are identified and characterized. After diagnosis, the design objectives are clearly specified and the conventional engineering design process can begin. Different problem solving strategies, information representation, and processing are useful for the different phases of rehabilitation design. This paper describes the RETAIN knowledge-based rehabilitation design system which integrates a relational database, production rules and algorithmic functions. RETAIN diagnoses retaining wall failures and synthesizes preliminary rehabilitation designs and cost estimates. Its framework and methodology may be applied to other infrastructure components such as pavements, water and sewage networks, bridge piers and marine structures. RETAIN decomposes rehabilitation problems into influencing failure modes then identifies a set of rehabilitation strategies such that each strategy remedies one or more failure modes. Complete rehabilitation solutions are formed by searching and combining strategy components. Conceptual knowledge for design synthesis is organized in relational database tables. The paper includes an example of design synthesis with relational operations for selecting rehabilitation strategies and forming complete rehabilitation solutions.

Information

Type
Research Article
Information
AI EDAM , Volume 5 , Issue 2 , May 1991 , pp. 65 - 75
Copyright
Copyright © Cambridge University Press 1991

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