A reconstruction algorithm with flexible stencils for anisotropic diffusion equations on 2D skewed meshes

2014 ◽  
Vol 256 ◽  
pp. 484-500 ◽  
Author(s):  
Lina Chang
2013 ◽  
Vol 125 (3) ◽  
pp. 387-417 ◽  
Author(s):  
Clément Cancès ◽  
Mathieu Cathala ◽  
Christophe Le Potier

2012 ◽  
Vol 10 (1) ◽  
pp. 1-31 ◽  
Author(s):  
Pierre Degond ◽  
Fabrice Deluzet ◽  
Alexei Lozinski ◽  
Jacek Narski ◽  
Claudia Negulescu

2021 ◽  
Vol 47 (2) ◽  
Author(s):  
Hanz Martin Cheng ◽  
Jan ten Thije Boonkkamp

AbstractIn this paper, we consider separating the discretisation of the diffusive and advective fluxes in the complete flux scheme. This allows the combination of several discretisation methods for the homogeneous flux with the complete flux (CF) method. In particular, we explore the combination of the hybrid mimetic mixed (HMM) method and the CF method, in order to utilise the advantages of each of these methods. The usage of HMM allows us to handle anisotropic diffusion tensors on generic polygonal (polytopal) grids, whereas the CF method provides a framework for the construction of a uniformly second-order method, even when the problem is advection dominated.


2016 ◽  
Vol 19 (1) ◽  
pp. 53-93 ◽  
Author(s):  
K. B. Nakshatrala ◽  
H. Nagarajan ◽  
M. Shabouei

AbstractTransient diffusion equations arise in many branches of engineering and applied sciences (e.g., heat transfer and mass transfer), and are parabolic partial differential equations. It is well-known that these equations satisfy important mathematical properties like maximum principles and the non-negative constraint, which have implications in mathematical modeling. However, existing numerical formulations for these types of equations do not, in general, satisfy maximum principles and the non-negative constraint. In this paper, we present a methodology for enforcing maximum principles and the non-negative constraint for transient anisotropic diffusion equation. The proposed methodology is based on the method of horizontal lines in which the time is discretized first. This results in solving steady anisotropic diffusion equation with decay equation at every discrete time-level. We also present other plausible temporal discretizations, and illustrate their shortcomings in meeting maximum principles and the non-negative constraint. The proposed methodology can handle general computational grids with no additional restrictions on the time-step. We illustrate the performance and accuracy of the proposed methodology using representative numerical examples. We also perform a numerical convergence analysis of the proposed methodology. For comparison, we also present the results from the standard single-field semi-discrete formulation and the results from a popular software package, which all will violate maximum principles and the non-negative constraint.


2012 ◽  
Vol 7 (6) ◽  
pp. 1113-1124 ◽  
Author(s):  
Ehsan Nadernejad ◽  
Sara Sharifzadeh ◽  
Søren Forchhammer

2020 ◽  
pp. 251-256
Author(s):  
И.А. Белянов ◽  
П.Н. Звягин

Изображения, получаемые при проведении экспериментов в ледовом бассейне, как правило, содержат многочисленные блики от средств искусственного освещения и естественных источников света. Вследствие зернистой структуры моделированного льда, в рамках одного блика яркие пиксели чередуются с более темными. Такие дефекты изображений препятствуют их автоматическому распознаванию. В статье предложены способы локализации данных дефектов и алгоритм их исключения с восстановлением изображения. Метод локализации замещаемой области основан на использовании функции концентрации пикселей с высокими значениями интенсивности. Алгоритм восстановления изображения основан на итеративном применении методов интерполяции и анизотропной диффузии. Эффективность предложенного способа продемонстрирована на примере восстановления изображений поверхности моделированного льда, приготовленного по технологии Fine Grain в ледовом бассейне Крыловского государственного научного центра (Санкт-Петербург). Images obtained during experiments in an ice tank as a rule contain a lot of glare from artificial lighting and photo equipment. Due to the grainy structure of model ice, bright pixels alternate with darker ones. Therefore, such defects prevent automatic recognition of images. The article suggests the method for localization of light spots on the surface of model ice as well as the algorithm for their elimination and image restoration. The method of area replacement is based on the use of high intensity pixel concentration function and delta concentration function. The image reconstruction algorithm is based on iterative application of interpolation and anisotropic diffusion methods to the part of an image with localized light spot. The effectiveness of the proposed method is demonstrated by the example of restoring images of the surface of simulated ice prepared in accordance with the Fine Grain technology in the ice tank of the Krylov State Research Centre (Saint Petersburg).


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