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A numerical efficiency comparison is provided.
This reduction provides high numerical efficiency of the developed method.
The SLW model is the best alternative regarding the compromise between accuracy and numerical efficiency.
This numerical efficiency is characterized by the method's demand for memory and CPU-time.
The balance between numerical accuracy and numerical efficiency is determined by the choice of these subspaces.
The numerical efficiency of the model is illustrated through a set of representative simulations.
The numerical efficiency of the new approach is discussed in case of this example system.
The results are compared in view of information content and numerical efficiency.
The excellent numerical efficiency and parallelisability are shown in comparison to two classical homogenisation methods.
Important remarks about the completeness and numerical efficiency of the selected basis are also provided.
For numerical efficiency particle sub-time stepping and an implicit finite-volume solver are applied.
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