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The concept of using actual flight reconstruction as a flight simulation training and research tool is introduced. Flight reconstruction for flight simulation (FRFFS) has several benefits for training and research including the recreation of visual instrument displays of the recorded flight and the reconstruction of state data which are useful in the detailed re-examination of a training flight. A Kalman filter design was used in the study as a state estimator flight simulator driver.

The feasibility of using artificial neural networks in the solution of inverse design problems in aerodynamics. Experiments were carried out wherein an airfoil design problem and a minimum length supersonic nozzle design problem were examined using a trained neural network running on an IBM RS/6000 workstation. Results indicate that the proposed method outperforms standard techniques commonly used in the solution aerodynamic design problems.