Master's Thesis - Studierstube Augmented Reality Project - Graz ...
Master's Thesis - Studierstube Augmented Reality Project - Graz ...
Master's Thesis - Studierstube Augmented Reality Project - Graz ...
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2.1 Technical Visualization<br />
Visualizing glyphs, arrows and color maps are based on rendering of simple geometrical<br />
structures at each point of the grid. Therefore these techniques do not need<br />
further explanations. The next step will be to make a definition of particle movements<br />
in steady or unsteady flows.<br />
Related trajectories can be calculated by different approaches.<br />
This thesis concentrates on discrete particle injection methods and finite<br />
differences approximations. Texture based advection techniques which are based on<br />
Lagrangian approaches were not implemented.<br />
∂x<br />
∂t = v(x(t), τ), x(t 0) = x 0 , x : R → R n (2.1)<br />
denotes the continuous movement of a massless particle under the influence of a even<br />
varying vector field, [Kipfer2004; Krueger2005; Weiskopf2007]. v describes a sampled<br />
vector field whose sampled values depend on the current position of an particle x(t).<br />
In the case of a time varying vector field, which equals unsteady flow, τ serves as<br />
parameterization of the time. Together with the initial condition x(t 0 ) this differential<br />
equation is complete. Keeping in mind that the measurement method from chapter 3<br />
produces a vector field defined on a regular spaced lattice and that general programming<br />
approaches cannot solve differential equations in complete form, numerical integration<br />
methods have to be used.<br />
The simplest form to solve the initial value problem 2.1 numerically is the standard<br />
explicit Euler-approach [Euler1768]. Choosing a discretization step size ∆t = h > 0 for<br />
t k+1 = t k + h, (2.2)<br />
leads to an approximation for the exact solution of<br />
x k+1 = x k + hv(x k , t k , τ). (2.3)<br />
The accuracy depends on the selected step size ∆t which is indirect proportional to the<br />
computational costs for the same length of a certain trajectory.<br />
To reduce the integration error or the computation effort of the former described numerical<br />
solution, several correction mechanisms can be added. One example is the well<br />
known Runge-Kutta method [Runge1895; Kutta1901] of a certain order [Albrecht1996;<br />
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