Flight simulators have been used to train pilots for over 100 years. During this time, simulators have evolved from basic wooden contraptions, good for little more than cockpit familiarization, to $20M machines capable of "zero flight time" training - and everything in-between. Modern devices typically incorporate aircraft-specific flight models which are validated against flight test data and integrated with visual, aural, and motion cueing equipment. The scope of simulator training tasks is constantly expanding, with the newest devices approved for full stall, icing, and upset recovery training. Training simulation is also changing in response to increasing complexity and automation in the cockpit, new aircraft categories such as eVTOL and tilt-rotor, and new technologies such as VR.
We'll explore the development process and major components associated with a typical flight simulator manufactured by Frasca International in Urbana, Illinois. The Aeronautical Engineering group at Frasca is responsible for flight test, flight modeling (aerodynamics, kinematics, engines, and ground reactions), control force cueing, motion and vibration cueing, autopilot modeling, integration with hardware and aircraft systems models, subjective tuning with pilots, certification, and various R&D. Aircraft models range from single-engine Cessnas and Robinsons to regional jets and heavy helicopters, with customers including flight schools, universities, military, law enforcement, air medical, and oil-and-gas.
Creating a training simulator which simultaneously meets objective data-matching requirements and pilot subjective expectations can be challenging, particularly for devices with limited visual and motion cueing. We'll discuss the role of sensory cues and other factors on pilot perception and performance, as well as methods for reconciling pilot perceptions with aircraft data. We'll also present some technologies used to mitigate cueing limitations in mid-fidelity rotorcraft simulators, including a small-stroke motion cueing system and adaptive stability augmentation.
