Secure, Compressed Multimedia Data over Variable Bit Rate, ATM Adaptation Layer (AAL) Algorithm

Not Available Missile defense systems rely heavily on plume signature recognition to help identify and neutralize hostile missiles. Unfortunately, plume signature modeling has proven to be extremely difficult, with modelers struggling to obtain good agreement between predictions and data. The modeled exhaust conditions display a significant lack of fidelity as compared to the actual constituents exiting the engine. In particular, soot concentration, which as a continuum radiator in the IR spectrum is extremely important to good signature prediction, varies considerably within the plume because it is dependent upon the soot producing, fuel-rich regions in the exhaust. Fuel-rich regions have proven especially difficult to model. Johnson Rockets, along with the Naval Postgraduate School, has been developing methods for accurately predicting soot concentrations in exhaust plumes. Expansion of this work will vastly increase both the modeling capabilities of the chemical kinetics of hydrocarbon combustion and our understanding of O/F variation in the combustion chamber. Increasing our modeling capabilities with respect to these combustion phenomena will provide methods for predicting soot production that are essential for plume recognition modeling