Applying a disparate network of models for complex airspace problems

Modeling and simulation in the aviation community is characterized by specialized models built to solve specific problems. Some models are statistically-based, relying on averages and distribution functions using Monte-Carlo techniques to answer policy questions. Others are physics-based, relying on differential equations describing such phenomena as the physics of flight, communication errors and frequency congestion, noise production, atmospheric wake generation, and other phenomena to provide detailed insight into study questions. Several years ago, researchers at Intelligent Automation, Incorporated (IAI) recognized that many of the physics-based aviation models, while conceptually similar, were difficult to interoperate because of varying assumptions regarding particular aspects of flight dynamics. Despite this difficulty, the aviation community routinely use these diverse physics-based models for a single coherent study. IAI researchers have since constructed an automated method for interoperating these models in a manner that produces consistent, coherent, and comparable results even with computations that otherwise use different assumptions.