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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 35
DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping
Paper X.2
Knowledge-Based Assistance for the Analysis, Design and Optimization of Civil Structures H.A. Smith*, S. Masri#, J.L. Beck** and T. Tsugawa**
*Department of Civil Engineering, Stanford University, Stanford, USA
H.A. Smith, S. Masri, J.L. Beck, T. Tsugawa, "Knowledge-Based Assistance for the Analysis, Design and Optimization of Civil Structures", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 183-196, 1995. doi:10.4203/ccp.35.10.2
Abstract
An on-going project is described which bas as its goal
the development of an AI-based software package to assist
in structural analysis and optimal design while explicitly
treating uncertain risks. For preliminary design
of a proposed structural system, it is desirable to search
through a large design space to evaluate possible choices
oil the basis of multiple criteria, so that the most promising
choice can be selected for detailed design. The goal of
this project is to increase efficiency, fully integrate, and
partially automate the design/build decision process by
using AI-based methodologies such as knowledge base expert
systems, object-oriented programming, fuzzy reliability,
multi-criteria decision theory and stochastic optimization.
The methodology developed in this study allows
the user to rapidly evaluate and improve a proposed
conceptual design while taking into account the major
factors affecting decisions related to design, construction,
and operation in the presence of uncertain risk. These factors
include not only structural engineering criteria, but
also social, political, legal, and economic considerations.
The first stage of this on-going project involved the development
of a working prototype of an interfaced suite
of knowledge-base expert systems consisting of analysis,
design and optimization tools with user interactive features.
The second stage of the project involves extending
the capabilities of the software tools and introducing an
explicit treatment of risk.
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