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The optimum depends on the simulation model namely on what one assumes for the boundary layer on the cone face.
However, this flow seeking behavior largely depends on the simulation parameters and might not always be true.
The runtime of the virtual screening method depends on the simulation method used on the assigned computing node.
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Thus, whereas a deterministic simulation will not identify this rare event potassium outside the cell ends because it captures only average behaviors, the stochastic simulation approach may not capture traces where it happens, depending on the simulation time and on the number of simulated traces.
Each calculation included the simulation of between ~1 and 4 × 106 photon trajectories, depending on the simulation wavelength.
Different complexity levels are applicable depending on the simulation scale, computational time limitations, input data and knowledge about the parameters.
The simulation results from the second and third methods contained some inaccuracy, but depending on the simulation objective, their simulation results may be acceptable.
They consist of a two-dimensional array of cells that "evolve" step-by-step according to the state of neighbouring cells and certain rules that depend on the simulation.
Optimizing buildings as a portfolio achieved up to seven additional percentage points of cost savings over individually optimized cases, depending on the simulation case study.
Depending on the simulation type, the computation time order of magnitude can vary from 0.1 s (simple radiographic projection) up to several hours (3D tomography) on a PC, with a 400 MHz microprocessor.
The numerical results showed that the optimized shape of the cathode electrolyte interface varied depending on the simulation conditions and that the cell performance could be improved by applying non-flat design to the cathode electrolyte interface for the same amount of cathode/electrolyte materials.
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