DIGITAL-SIMULATION OF ATMOSPHERIC-TURBULENCE FOR DRYDEN AND VONKARMAN MODELS

Algorithms are presented for generating discrete sample time histories of random atmospheric turbulence having statistical characteristics as prescribed by the Dryden and von Karman models defined in MIL-F-8785C. When these algorithms are incorporated into a dynamic simulation, response of an aircraft to the turbulence can be predicted. Such information is useful both in the design stage and during the development phase of the aircraft. The von Karman model is generated using a variation of the sum-of-sinusoids method, modified to reduce computation time. Techniques for improving computational speed are considered, and results of test runs are presented. The Dryden model is generated by passing band-limited white noise through appropriate linear filters. The input variance required to produce the desired output variance is determined as a function of the sample frequency. Generation of roll gust velocities is also addressed, as well as the application of lateral and vertical velocities to the computation of yaw and pitch moments on an aircraft.