5. For output data, RFS generates an event log file that stores approximately four kilobytes (KB) of data for the 12 airplanes, most of which go through at least one turbulence event and collectively generate 10 CAT-related PIREPs triggered both by CAT event experiences and by sensor alerts.

6. The simulation as we have modeled it has a high computational intensity in that each aircraft has to determine its position with reference to each turbulence boundary at each step of the simulation, and the air traffic controllers have to determine each aircraft’s position with reference to the sector boundaries.  In addition, the amount of memory used is fairly high (roughly 750 KB per aircraft in the absence of weather events, plus about 2.5 MB per aircraft per turbulence encounter).  The run with 12 aircraft that produced 10 PIREPs (where a PIREP is issued for each turbulence encounter and each sensor alert) used about 35 megabytes of memory.  This memory requirement is considered high because it limits the scalability of the model to handle full traffic loads in one or more sectors (i.e., far greater than 12 aircraft), as could be required in practical applications.  Further refinements can make use of the RFS Memory Management Object (developed too late to be incorporated into this modeling effort) to reduce the frequency of computational updates; also, there are opportunities for more efficient coding of the agent models to further reduce the resource requirements per update.

Agent-Based Simulation with RFS and HLA
7. HLA Run-Time Interface (RTI) appears to be a very efficient networking solution.  Its strength is its flexibility; it is entirely up to the implementer what the RTI will be like. 

8. Agent-based simulation is a very effective tool for modeling large systems, including both Monte Carlo and deterministic simulations.  In RFS, once all agents are defined and coded, the model becomes very easy to use, and its versatility and flexibility for modeling systems at various levels of focus and fidelity (breadth and depth) is only limited by the available agent models.  

9. The design of RFS makes it a good generalization of the agent-based simulation approach to aviation systems simulation.  For one thing, RFS uses dynamic linked libraries (DLLs) as agents, all controlled by one executable (simulator.exe), which runs the DLLs.  In addition, configuration of the simulation run is defined by a script file (a text file a user can easily set up), and all agents are instantiated as required by that file.  For large simulations, the script files can be “nested” like subroutines.  What’s more, the user can always pause the simulation and add another script file, thus changing the initial conditions in the process of running the model.

10. The learning curve to develop agents in RFS was found to be quite steep, particularly to customize previously developed agents to the needs of this scenario of multiple aircraft flying in and out of three nested turbulence areas with air-ground communications.  In addition, complicated workarounds had to be created to interface vehicle and non-vehicle agents in ways not needed for the aircraft-flight-simulation purposes for which RFS was originally developed.

Modeling Human Agents with MIDAS
11. MIDAS has been developed to simulate the cognitive, sensory, and motor performance of human operators to a great degree of fidelity, precision, and accuracy in both fast-time and real-time (human-in-the-loop) experiments.  Its design was tailored to applications in well-defined, narrowly focused research experiments, e.g., to assess the impacts on human operator performance of a new display layout or mechanical control device.  For this reason, the MIDAS modeling of the chosen scenario's controller and flight crew tasks and procedures and developing the HLA federates to implement the link with RFS proved to be much more challenging than anticipated.  None of the many technical and conceptual issues that arose was intractable, however -- only time consuming.  Priority was given to effecting the dynamic linkage, so that the flight crew and controller modeling was only partially completed, although sufficiently so to demonstrate the linkage.
　
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