Integrating Experimental Data and Mathematical Models in the Simulation of Physical Systems
Boris A. Zeldin and Andrew J. Meade, Jr.,
Submitted to AIAA Journal, 1996.
Keywords:: experimental data analysis, mathematical models, response surface, artificial neural networks, Tikhonov regularization.
Abstract: A method is developed for integrating experimental data and mathematical models so that a comprehensive description of a physical system can be constructed for engineering analysis. The computational requirements of the method can be modest depending on the computational complexity of the associated mathematical models. Using a feedforward artificial neural network architecture, numerical examples involving the extrapolation of a physical system response at unmeasured coordinates and processing of noisy experimental measurements demonstrate the utility of the method.
This work was supported under Office of Naval Research grant N00014-95-1-0741.