By W.H.J.J. Van Staveren

It is a Ph.D. dissertation. The reaction of airplane to stochastic atmospheric turbulence performs a massive position in, for instance, plane layout (load calculations) and flight simulation (handling features examine and pilot training). as a way to simulate those airplane responses, a correct mathematical version is needed. classical versions can be mentioned during this thesis that's the Delft collage of know-how (DUT) version and the 4 aspect airplane (FPA) version. even if they're good demonstrated, their constancy continues to be vague. The reason lies in a single of the necessities for process id; it has continuously been essential to relate inputs to outputs to figure out, or establish, procedure dynamic features. From experiments, utilizing either the measured enter and the measured output, a mathematical version of any process should be obtained.When contemplating an input-output process comparable to an airplane subjected to stochastic atmospheric turbulence, an enormous challenge emerges. in the course of flight exams, no functional hassle arises measuring the aircraft-system's outputs, comparable to the angle-of-attack, the pitch-angle, the roll-angle, and so on. in spite of the fact that, a big challenge arises while the enter to the aircraft-system is taken into account; this enter is stochastic atmospheric turbulence during this thesis. at the moment, it nonetheless is still super tough to spot the whole flowfield round an aircraft's geometry subjected to a turbulent box of circulation; an enormous quantity of sensors will be required to spot the atmospheric turbulence pace component's distribution (the enter) over it. subsequently, it's tough, if now not most unlikely, to spot atmospheric turbulence versions from flight checks.

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**Sample text**

4) where Φ is the outer flow region’s potential and x, y and z denote Cartesian ordinates in the frame Faero . 5) where Φi is the inner flow region’s potential and x, y and z also denote Cartesian ordinates in the frame Faero . 5). The velocity components U∞ , V∞ , W∞ are taken to be positive along the Xaero -, Yaero - and Zaero -axis, respectively. 1 where the frame Faero is given, including the definition of the undisturbed velocity components [U∞ , V∞ , W∞ ]T in it. With respect to the boundary conditions, for the submerged configuration the airflow velocity is tangential to the configuration.

13: The 2D PSD function Su2 u2 (Ω1 Lg , Ω2 Lg ). 14: The 2D PSD function Su1 u2 (Ω1 Lg , Ω2 Lg ). 15: The 2D PSD function Su3 u3 (Ω1 Lg , Ω2 Lg ). 16: The 1D PSD function Su1 u1 (Ω1 Lg ). 17: The 1D PSD function Su2 u2 (Ω1 Lg ). 18: The 1D PSD function Su3 u3 (Ω1 Lg ). 1: Classification of the atmospheric turbulence intensity given in terms of the standard deviation and the variance, taken from reference [3]. 5 Atmospheric turbulence model parameters Throughout this thesis the gust scale length Lg is chosen as Lg = 300 [m], a value representative for high altitude atmospheric turbulence, see references [1, 3, 30].

1. 6 Remarks In chapters 7 and 8 (panel) aircraft models will be flown through both elementary symmetrical and elementary anti-symmetrical atmospheric turbulence fields in order to determine the aerodynamic forces and moments acting upon them. After the aircraft model identification process is completed, the parametric aircraft models will be used to calculate the aircraft’s response to atmospheric turbulence. As presented in this chapter, the atmospheric turbulence PSD functions will be used as input for these parametric aircraft models.