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A more realistic random field representation of the material uncertainties is achieved, compared to classical scalar random variable approaches.
In the present study, the focus is on the biomechanically realistic random variation in the track shape and load.
Kinetic Monte Carlo (KMC) simulation is used for generating realistic random distribution of active As atoms in Si NWs.
Kinetic Monte Carlo simulation is used for generating realistic random distribution of active As atoms in Si NWs.
Fifthly and lastly, we conducted simulations on more realistic random topologies with a large number of nodes.
The toughness of realistic random microstructures is then obtained using DEM simulations and compared to experimental data.
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While realistic random-walk-like trajectories were predicted by the simulation for Daphnia, distinct circling trajectories and nonzero peaks in the turning angle distributions were predicted for larger species, such as paddlefish.
As there is always acquisition noise introduced into the camera outputs, in order to make the simulation more realistic, simulated random shot noise and quantization noise are introduced.
We finally investigate the trade-off between the above parameters, in case of ideal conditions (uniform distance of all sensors from target, optimal orientation of sensor arrays) or realistic conditions (random distance and orientation).
This approach resulted in ecologically realistic, non-random assemblages that reflected the trophic structure, dispersal, disturbance, and other processes of a natural system.
The effects of these singularities on a more realistic system with random uncertainties is then presented.
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