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Robust mesh generation is a fundamental component required for developing simulations with high accuracy.
In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics.
The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds.
Here we use Random Matrix Theory to analyze a series of short-time molecular dynamics experiments which are specifically designed to be simulations with high cosine content.
The measured results are in good agreement with simulations with high absorptivities of more than 90% at all six absorption frequencies.
The solution of a relatively large power system shows the ability of the new dynamic model to carry out large-scale power system simulations with high efficiency.
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To move beyond the 'average patient' that is typically simulated by molecularly-detailed mechanistic computational models, we have integrated mechanistic simulations with high-throughput data to create a population of tumor models that can simulate variability in receptor activation and response to treatment.
Figure 5 presents the results of the simulations with high-resolution methods.
The insertion of a synthetic Hurricane Wilma shows the technique works with modern simulations with high-data resolution, giving us more confidence in the hindcast and forecast projections.
The use of an artificial bulk viscosity for shock stabilization is a common approach employed in turbulence simulations with high-order numerics.
Numerical simulations with high-order compact difference schemes depict more accurate solution values on variable meshes as compared to some high-order compact scheme on a uniform mesh network.
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