Prediction of Store Separation Characteristics Using CFD and Validation with Flight Test Results

Abstract

The design, integration and certification of a store configuration to a fighter aircraft involve extensive and expensive wind tunnel and flight testing with the objective of determining the operational and deployment envelopes for safe separation. Computational trajectory prediction techniques have shown to have the potential not only to reduce the number of flight/wind tunnel tests but also to design an intelligent test matrix. In this paper a Cartesian grid based Euler code-PARAS coupled with trajectory evaluation module (a 6-DOF time integration module) developed at ADA has been used to predict the separation trajectory of an external store from Jaguar fighter aircraft. Coupled 6-DOF Cartesian grid based methods provide reasonably accurate results with low turnaround time. A traditional multi block structured grid usually provides a better result, however handling qualities and robustness in terms of complexity of configuration and range of flight conditions makes Cartesian grid based methods an ideal choice. The current method is capable of simulating store separations without user interventions. Trajectory from the flight test has been generated using photogrammetric methods, data for which has been generated using on-board high speed camera fitted on the special POD. The computed store trajectory results are validated with flight tests and found to be in good agreement. This computational approach is further applied to predict the trajectory for higher Mach number release configurations.