Special Issue "Computational Fluid Dynamics"
A special issue of Mathematics (ISSN 2227-7390).
Deadline for manuscript submissions: 30 September 2019
Assc. Prof. Mostafa Safdari Shadloo
Hitherto, experimental approaches have been widely considered as the main source of information for predicting the physical behavior of fluid flow problems. However, in many applications, due to the complexities in fluid behavior regarding to its nonlinearity, multiscale status, multiphase, etc., experimental means have become either extremely expensive, subjected to scaling issues or, in some cases, impossible. Under these constraints, the only alternative method of scrutinizing this physical phenomenon seems to be through numerical tools.
This Special Issue focuses on computational fluid dynamics (CFD) research, with an emphasis on its recent advancements and its use in many industrial/academic applications. Papers ranging from new physical modeling and discoveries to the correct treatment of difficulties inherent in numerical modeling of fluid flow systems are invited for submission. These include but are not limited to: (i) Correct and effective models of the physical boundary conditions; (ii) mass and energy conservations; (iii) realistically treating the complicated physical phenomena; (iv) extendibility to dealing with more multiphysics phenomena, such as those in magnetohydrodynamics (MHD), electrohydrodynamics (EHD), non-Newtonian flows, phase change, nanofluidic, etc. problems; and finally, (v) the extension of aforementioned methodologies to three-dimensional modeling and massively parallel computing in order to handle the real-life problems.
We concisely invite manuscripts that focus on the use of conventional numerical methods, such as finite difference (FDM), finite volume (FVM), and finite element (FEM), to elaborate on their differences, similarities, advantages, and drawbacks. As such, the development and validation of less established and newly attracting numerical methodologies, such as smoothed particle hydrodynamics (SPH), moving particle semi-implicit (MPS), Lattice Boltzmann (LBM) methods, etc. are also in the core scope of this research topic. Manuscripts dealing with the benchmarking of new test cases, optimizing flow, fluid, geometrical parameters, as well as using data-driven approaches, such as reduced order methods and machine learning (ML), are of great interest. This Special Issue also welcomes related novel inter-/multidisciplinary works in the emerging area of mechanical, chemical, process, and energy engineering.
Prof. Mostafa Safdari Shadloo
Manuscript Submission Information
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