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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 13
ARTIFICIAL INTELLIGENCE AND STRUCTURAL ENGINEERING
Edited by: B.H.V. Topping
Paper IV.1

Reasoning About Constructibility: Representing Construction Knowledge and Project Data

M. Fischer

Center for Integrated Facility Engineering, Stanford University, Stanford, USA

Full Bibliographic Reference for this paper
M. Fischer, "Reasoning About Constructibility: Representing Construction Knowledge and Project Data", in B.H.V. Topping, (Editor), "Artificial Intelligence and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 105-112, 1991. doi:10.4203/ccp.13.4.1
Abstract
Due to the fragmentation in the construction industry, structural engineers rarely use explicit constructibility knowledge when making decisions about the layout and dimensioning of structural elements. An on-line construction expert offers the opportunity to allow use of efficient construction methods on a project by interfacing with a CAD representation of the design and by providing decision support in the form of construction knowledge. I developed such an expert system called COKE (Construction Knowledge Expert) by acquiring constructibility knowledge from field experts, formalizing and organizing this knowledge base in a way suitable for input to the design process, specifying a symbolic model of a reinforced concrete structure that supports constructibility reasoning, and implementing a software prototype that links a CAD system to an expert system. When providing constructibility feedback, COKE first uses high level application heuristics to determine whether a construction method is applicable or not. It then compares the project data in the symbolic model with specific constraints about the layout and dimensioning of structural elements, and alerts the designer about mismatches between these constraints and the structure. This research shows that software technology can be used to integrate downstream project constraints into the work environment of design engineers. Object-oriented programming offers a computing paradigm to support this cross-functional integration. Once implemented, such integrated intelligent tools offer the opportunity to solve problems in early project stages at a fraction of the cost of making changes in the construction or operation phases of a facility.

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