TY  - GEN
AU  - San,Omer
AU  - San,Omer
TI  - Recent Numerical Advances in Fluid Mechanics
SN  - books978-3-03936-403-9
PY  - 2020///
CY  - Basel, Switzerland
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - History of engineering & technology
KW  - bicssc
KW  - fluid–structure interaction
KW  - monolithic method
KW  - Updated Lagrangian
KW  - Arbitrary Lagrangian Eulerian
KW  - computational aerodynamics
KW  - Kutta condition
KW  - compressible flow
KW  - stream function
KW  - non-linear Schrödinger equation
KW  - cubic B-spline basis functions
KW  - Galerkin method
KW  - pressure tunnel
KW  - hydraulic fracturing
KW  - transient flow
KW  - finite element method (FEM)
KW  - Abaqus Finite Element Analysis (FEA)
KW  - computational fluid dynamics
KW  - RANS closures
KW  - uncertainty quantification
KW  - Reynolds stress tensor
KW  - backward-facing step
KW  - OpenFOAM
KW  - large eddy simulations (LES)
KW  - shock capturing
KW  - adaptive filter
KW  - explicit filtering
KW  - jet
KW  - proper orthogonal decomposition
KW  - coherent structures
KW  - turbulence
KW  - vector flow fields
KW  - PIV
KW  - buildings
KW  - urban area
KW  - pollution dispersion
KW  - Large Eddy Simulation (LES)
KW  - multiple drop impact
KW  - computational fluid dynamics (CFD) simulation
KW  - volume-of-fluid
KW  - crater dimensions
KW  - vorticity
KW  - transient incompressible Navier-Stokes
KW  - meshless point collocation method
KW  - stream function-vorticity formulation
KW  - strong form
KW  - explicit time integration
KW  - wall layer model
KW  - LES
KW  - separated flow
KW  - body fitted
KW  - immersed boundary
KW  - reduced order modeling
KW  - Kolmogorov n-width
KW  - Galerkin projection
KW  - turbulent flows
KW  - reduced order model
KW  - closure model
KW  - variational multiscale method
KW  - deep residual neural network
KW  - internal combustion engines
KW  - liquid-cooling system
KW  - heat transfer
KW  - n/a
N1  - Open Access
N2  - In recent decades, the field of computational fluid dynamics has made significant advances in enabling advanced computing architectures to understand many phenomena in biological, geophysical, and engineering fluid flows. Almost all research areas in fluids use numerical methods at various complexities: from molecular to continuum descriptions; from laminar to turbulent regimes; from low speed to hypersonic, from stencil-based computations to meshless approaches; from local basis functions to global expansions, as well as from first-order approximation to high-order with spectral accuracy. Many successful efforts have been put forth in dynamic adaptation strategies, e.g., adaptive mesh refinement and multiresolution representation approaches. Furthermore, with recent advances in artificial intelligence and heterogeneous computing, the broader fluids community has gained the momentum to revisit and investigate such practices. This Special Issue, containing a collection of 13 papers, brings together researchers to address recent numerical advances in fluid mechanics
UR  - https://mdpi.com/books/pdfview/book/2480
UR  - https://directory.doabooks.org/handle/20.500.12854/68714
ER  -