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Exploratory design using constraints

Published online by Cambridge University Press:  27 February 2009

Weng Tat Chan  and
Boyd C. Paulson Jr
Weng Tat Chan
Affiliation:
Department of Civil Engineering, National University of Singapore, Kent Ridge, Singapore 0511
Boyd C. Paulson Jr
Affiliation:
Department of Civil Engineering, Stanford University, Stanford, CA 94305-4020, USA.
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Abstract

Engineering design involves the evaluation and satisfaction of a wide variety of constraints. The ability to represent and process these constraints in a computer is important for the verification of the output produced by computer-aided design programs. Constraints need not only check designs but can also be used to derive design solution s that satisfy constraints. The paper discusses how to represent the dual nature of constraints so that design consistency is maintained as the design evolves.

Assumptions and rules of thumb are used frequently in design to propose initial solutions. We represent the logic behind the derivation of these assumptions as heuristic procedures and maintain the dependencies between these assumptions and their consequents as an aid to the management of design consistency. We also propose a simple scheme, involving the partitioning of the design modules, to effect design changes when constraint violations occur. An example from structural design illustrates the methodology.

Type
Research Article
Information
AI EDAM , Volume 1 , Issue 1 , February 1987 , pp. 59 - 71
Copyright
Copyright © Cambridge University Press 1987

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References

Borning, A. 1979. Thing Lab—A Constraint-oriented Simulation Laboratory, Ph.D thesis, Deptartment of Computer Science, Stanford University, California.Google Scholar
Chan, W. T. 1986. Logic programming for managing constraint-based engineering design, Ph.D. thesis, Department of Civil Engineering, Stanford University, California.Google Scholar
Clocksin, W. F. and Mellish, C. S. 1984. Programming in Prolog, 2nd ed., Springer-Verlag, Berlin.Google Scholar
de Kleer, J. and Sussman, G. J. 1978. Propagation of Constraints Applied to Circuit Synthesis, M.I.T. Artificial Laboratory Memo 485, Cambridge, MA.Google Scholar
Hogger, C. J. 1984. Introduction to Logic Programming, APIC Studies in Data Processing 21, London: Academic Press.Google Scholar
Holtz, N. M. 1982. Symbolic manipulation of design constraints—an aid to consistency management, Ph.D. dissertation, Department of Civil Engineering, Carnegie–Mellon University, Pittsburgh, PA.Google Scholar
Maher, M. L. 1984. HI-RISE: An expert system for the preliminary structural design of high rise buildings, Ph.D. dissertation, Department of Civil Engineering, Carnegie–Mellon University, Pittsburgh, PA.Google Scholar
McCabe, F. G., Clark, K. L. and Steel, B. D. 1985. micro-Prolog Professional 1.2 Programmer's Reference Manual, Logic Programming Associates, Ltd.Google Scholar
Mostow, J. 1985. Toward better models of the design process, Al Magazine, Spring, 44–57.Google Scholar
Popplestone, R. J. 1984. The application of artificial intelligence techniques to design systems. In: International Symposium on Design and Synthesis, Tokyo: Japan Society of Precision Engineering.Google Scholar
Rasdorf, W. J., Ulberg, K. J. and Baugh, J. W. 1987. A structure-based model of semantic integrity constraints for relational databases, Engineering with Computers 2(1), 31–39.CrossRefGoogle Scholar
Rasdorf, W. J. and Fenves, S. J. 1986. Constraint enforcement in structural design databases, Journal of the Structural Division 112(12), 2565–2577.CrossRefGoogle Scholar
Stallman, R. M. and Sussman, G. J. 1977. Forward reasoning and dependency-directed backtracking in a system for computer-aided circuit analysis, Artificial Intelliglence, 9, 135–196.CrossRefGoogle Scholar
Sussman, J. G. and Steele, G. L.., Jr, 1980. CONSTRAINTS—A language for expressing almost-hierarchical descriptions, Artificial Intelligence 14(1), 1–39.CrossRefGoogle Scholar