Current Issue : April - June Volume : 2016 Issue Number : 2 Articles : 6 Articles
This paper presents a modified grey model GMC(1,...
Nador lagoon is a coastal system connected to the sea through a narrow and shallow inlet; understanding its hydraulic performance\nis required for its design and operation. This paper investigates the hydrodynamic impacts of the whole lagoon due to tidal waves\nusing a numerical approach. In this study we use a two-dimensional, depth-averaged hydrodynamic model based on so-called\nshallow water equations solved within triangular mesh by a developed efficient finite volume method. The method was calibrated\nand validated against observed data and applied to analyze and predict water levels, tidal currents, and wind effects within the\nlagoon. Two typical idealized scenarios were investigated: tide only and tide with wind forcing. The predicted sea surface elevations\nand current speeds have been presented during a typical tidal period and show correct physics in different scenarios....
The proper generalized decomposition (PGD) requires separability of the input data\n(e.g. physical properties, source term, boundary conditions, initial state). In many cases\nthe input data is not expressed in a separated form and it has to be replaced by some\nseparable approximation. These approximations constitute a new error source that, in\nsome cases, may dominate the standard ones (discretization, truncation. . .) and control\nthe final accuracy of the PGD solution. In this work the relation between errors in the\nseparated input data and the errors induced in the PGD solution is discussed. Error\nestimators proposed for homogenized problems and oscillation terms are adapted to\nasses the behaviour of the PGD errors resulting from approximated input data. The PGD\nis stable with respect to error in the separated data, with no critical amplification of the\nperturbations. Interestingly, we identified a high sensitiveness of the resulting accuracy\non the selection of the sampling grid used to compute the separated data. The\nseparation has to be performed on the basis of values sampled at integration points:\nsampling at the nodes defining the functional interpolation results in an important loss\nof accuracy. For the case of a Poisson problem separated in the spatial coordinates (a\ncomplex diffusivity function requires a separable approximation), the final PGD error is\nlinear with the truncation error of the separated data. This relation is used to estimate\nthe number of terms required in the separated data, that has to be in good agreement\nwith the truncation error accepted in the PGD truncation (tolerance for the stoping\ncriteria in the enrichment procedure). A sensible choice for the prescribed accuracy of\nthe PGD solution has to be kept within the limits set by the errors in the separated\ninput data....
Background: Cell adhesion is a process that involves the interaction between the cell\nmembrane and another surface, either a cell or a substrate. Unlike experimental tests,\ncomputer models can simulate processes and study the result of experiments in a\nshorter time and lower costs. One of the tools used to simulate biological processes is\nthe cellular automata, which is a dynamic system that is discrete both in space and time.\nMethod: This work describes a computer model based on cellular automata for the\nadhesion process and cell proliferation to predict the behavior of a cell population in\nsuspension and adhered to a substrate. The values of the simulated system were\nobtained through experimental tests on fibroblast monolayer cultures.\nResults: The results allow us to estimate the cells settling time in culture as well as the\nadhesion and proliferation time. The change in the cells morphology as the adhesion\nover the contact surface progress was also observed. The formation of the initial link\nbetween cell and the substrate of the adhesion was observed after 100 min where the\ncell on the substrate retains its spherical morphology during the simulation. The cellular\nautomata model developed is, however, a simplified representation of the steps in the\nadhesion process and the subsequent proliferation.\nConclusion: A combined framework of experimental and computational simulation\nbased on cellular automata was proposed to represent the fibroblast adhesion on\nsubstrates and changes in a macro-scale observed in the cell during the adhesion\nprocess. The approach showed to be simple and efficient....
CFD (Computational Fluid Dynamics) simulations are widely used nowadays to predict the behaviour of fluids in pure research\nand in industrial applications. This approach makes it possible to get quantitatively meaningful results, often in good agreement\nwith the experimental ones. The aim of this paper is to show how CFD calculations can help to understand the time evolution\nof two possible CBRNe (Chemical-Biological-Radiological-Nuclear-explosive) events: (1) hazardous dust mobilization due to the\ninteraction between a jet of air and a metallic powder in case of a LOVA (Loss Of Vacuum Accidents) that is one of the possible\naccidents that can occur in experimental nuclear fusion plants; (2) toxic gas release in atmosphere. The scenario analysed in the\npaper has consequences similar to those expected in case of a release of dangerous substances (chemical or radioactive) in enclosed\nor open environment during nonconventional events (like accidents or man-made or natural disasters)....
The geometric layout is the key factor for enhancing the efficiency of the fluid mixing in passive micromixers. Therefore, by adjusting\nthe geometric design and by controlling the geometric parameters, one can enhance the mixing process. However, through any\nfabrication process, the geometric parameters present slight, inherent variation from the designed values than might affect the\nperformance of the micromixer.This paper proposes a numerical study on the influence of the unavoidable geometric tolerances\non the mixing efficiency in passive micromixers. A probabilistic simulation model, based on the Monte Carlo method, is developed\nand implemented for this purpose. An uncertainty simulation model shows that significant deviations from the deterministic design\ncan appear due to small variations in the geometric parameters values and demonstrates how a more realistic mixing performance\ncan be estimated....
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