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Hundreds of thousands of grains can be simulated using a small number of signed distance functions (in this work, 32 in two dimensions and 64 in three dimensions are more than sufficient) using modest computational hardware.
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This delivers a fast and computationally efficient method and it is shown for pipes buried in sand or soil that relevant eigenmodes can be computed and sorted in less than one second using relatively modest computer hardware.
To this end, we estimated the speed of Sma3s analysis using the modest computer hardware (see Materials and Methods for details).
Computational experiments demonstrate that high-quality solutions are obtained while modest computational overheads are incurred.
All is still within very reasonable calculation times on modest computational resources.
The analytical model shows fair agreement with numerical data at modest computational cost.
Low memory requirements and modest computational complexity facilitates calculations on high-resolution three-dimensional models.
The numerical routines require modest computational efforts and demonstrate excellent convergence characteristics.
The objective is to achieve this goal with modest computational effort.
Large-scale problems, with thousands of grains, are solved using modest computational resources.
This extends the range of the method by approximately 53, 144 and 851 log-units, respectively, using modest computational resources.
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