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We have assessed our method on several challenging benchmark problems for one- and two-dimensional Euler equations and the scheme has proven to be robust and to achieve the theoretically predicted high order of accuracy on smooth solutions.
We also demonstrate our method on several synthetic and real scenes, including 3D printed objects with known ground truth geometry.
In this paper, an analysis of the parallel implementation of this method on several computer architectures and for several programming paradigms is presented.
The proposed method is compared with analytical solution and the meshless local Petrov Galerkin method on several test problems taken from the literature.
We verify the accuracy and stability of the numerical method on several test cases, which indicate the potential of the method to predict multiphase flow processes.
Numerical results are presented, aimed at verifying the formal order of accuracy of the scheme and to assess the performance of the method on several realistic test problems.
Similar(32)
We also tested the method proposed on several one and two dimensional problems with very promising results.
We have tested the methods on several examples and have obtained fast, stable, robust convergence.
We illustrate the above methods on several ligand protein systems, including cytochromes and G-protein-coupled receptors.
We present some experiments validating the approach for unite and conquer restarted Krylov methods on several parallel and distributed platforms.
We also compare the performance of the present method with the Streamline-upwind Petrov Galerkin (SUPG) and the Residual-Free Bubbles (RFB) methods on several benchmark problems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com