Articles

Intelligent automated quality control for computational simulation

Andrew Gelsey^a1

^a1 Computer Science Department, Rutgers University, New Brunswick, NJ 08903, U.S.A.

Abstract

Computational simulation of physical systems generally requires human experts to set up a simulation, run it, evaluate the quality of the simulation output, and repeatedly invoke the simulator with modified input until a satisfactory output quality is achieved. This reliance on human experts makes use of simulators by other programs difficult and unreliable, though invocation of simulators by other programs is critical for important tasks such as automated engineering design optimization. Presented is a framework for constructing intelligent controllers for computational simulators that can automatically detect a wide variety of problems that lead to low-quality simulation output, using a set of evaluation methods based on knowledge of physics and numerical analysis stored in a data/knowledgebase of models and simulations. An experimental implementation of this framework in an intelligent automated controller for a widely used computational fluid dynamics simulator is described.

(Received August 22 1994)

(Accepted March 27 1995)

Keywords

• Artificial Intelligence (AI);
• Simulation;
• Computational Fluid Dynamics (CFD);
• Design Optimization

Andrew Gelsey holds an A.B. degree in Physics from Harvard University (1980), a M.S. degree in Mathematics from the Courant Institute of Mathematical Sciences at New York University (1984), and a Ph.D. degree in Computer Science from Yale University (1990). He has been an Assistant Professor in the Computer Science Department at Rutgers University since receiving his Ph.D. Professor Gelsey's research interests include Artificial Intelligence, automated reasoning about physical systems, and the use of AI approaches to improve the engineering design process.