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This study focuses on model-related uncertainties due to model characteristics, discretization schemes, delineation methods, and particle tracking algorithms.
Presently, there are numerous applications for non-destructive techniques like emission tomography, laser based methods and particle image velocimetry that are used to study flame characteristics.
The effects of supporting methods and particle morphological parameters, such as pore size and length, on the catalyst impregnation were systematically investigated.
Furthermore, the effects of different absorbent-catalyst coupling methods and particle sizes on the reactant diffusion were also discussed, finding that in-situ enhancement and moderate particle sizes (20 40 mesh) were beneficial for the reaction system.
This work presents a general approach, coined "Spy Element Method" (SEM), for parallelising workloads to run on manycore processors and featuring dynamic dependencies between different data items, such as graph traversals, remeshing methods and particle simulations.
Different response surface methodology (RSM) methods and particle swarm optimization (PSO) methods are studied initially on a 4 degrees-of-freedom (4DOF) dynamic system on their performance in terms of speed and accuracy.
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Using a combination of analytical methods and Particle-In-Cell (PIC) simulations, we discuss the properties of a coherent, nonlinear, electromagnetic wave propagating in a neutron star wind.
Residence time distribution characteristics are obtained by gas tracer injection method, and particle tracking method.
For this purpose, the Monte Carlo Simulation Method and Particle Swarm Optimization Algorithm have been used in this article.
The core spreading method and particle strength exchange were selected as the viscous diffusion scheme.
Cerium oxide nanoparticles (CeO-NPs) may act as both an oxidant and an antioxidant, depending on the preparation method and particle size.
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