Some considerations for data gathering for simulation data bases

Simulations and simulators require a variety of data categories. The authors discuss the contents of categories such as aerodynamic properties; features and specifics of avionics down to pulse width, frequency, and color of items on the cockpit panels; logistic concerns, such as Weibull distribution parameters for failure rate computations, cost of spares, and mean-time-to-repair (MTTR) figures; order of battle; and natural environment. Specifics depend on whether the simulation is at a coarse, medium, or fine level of emulation. Coarse models use mathematical formulas, while fine models may use Monte Carlo techniques and Eulerian/Lagrangian schemes to build up valid long-term statistics from individual case simulations. The authors examine the relative importance of data items to the simulation, and the considerations and pitfalls of various sources of data. Model sensitivity and the possibility of substituting heuristic models for actual data are examined. Methods of validation and the choice of test data versus operational data are discussed. The enhancement of the general data archive and the enhancement of the documentation of the characteristics and errors in known models and archives are also considered