Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

E. Fleris, A. Preh:
"Wurf_live: Demonstration Of A Stohastic Numerical Rockfall Code In 3d";
Vortrag: GeoTirol 2016, Innsbruck; 25.09.2016 - 28.09.2016; in: "ABSTRACT VOLUME GeoTirol 2016", (2016), 1 S.

Kurzfassung englisch:
Rockfall is a natural phenomenon with a characteristic kinematic signature which distinguishes it among other
types of mass movements. It can significantly contribute in the geomorphological evolvement of natural slopes and
the formation of talus deposits. On the other hand it poses a great risk to human activities and constructions in
mountainous areas and quarries.
Numerical modelling can assist in, a better understanding of the phenomenon, the selection of case specific risk
mitigation strategies and the design as well as optimization of any necessary protective structures. Although the
law of physics controlling rockfall, at first might seem completely determining the process, immediately significant
complexity and uncertainty arise in defining the necessary parameters and their distribution over a natural terrain
with an appropriate spatial resolution. Random behaviour is a challenging feature of rockfall, which must be
invastigated in a modelling approach.
Wurf_ is a numerical code, implemented in python, that simulates rockfall trajectories and kinematics in full three
dimensional space. At its initial stage of development, it adopts a lumped mass approach to describe a boulder as
a projectile and implements a ray tracing computational algorithm to precisely calculate impacts with a terrain,
represented by a TIN model. It accounts for random behaviour, arising from parameters such as the exact
projectile´s shape and slope´s roughness, by stochastically variating the orientation of the impact surface. Upon
impact detection, kinematics are determined through Goldsmith´s solution for a collinear impact of a sphere on a
planar surface.Coefficients of restitution are beeing calculated through hyperbolic functions, according to size and
the kinetic energy of the projectile.
The few unknown variables controlling the response of the model, can be estimated through a back analysis of
data derived from physical experiments. So far the code has been calibrated against a campaign of drop tests
contacted at Austrian and Canadian quarries, exhibiting a remarkable predictive ability for its simplicity.

Rockfall, Computer Modelling, Stohasticity, Ray Tracing

Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.