Your English writing platform
Discover LudwigSimilar(60)
The numerical scheme used to solve the low-Mach-number reacting flow equations is an operator-split projection scheme which incorporates ISAT by a Strang subsplitting procedure.
A stiff,1 operator-split projection scheme is constructed for the simulation of unsteady two-dimensional reacting flow with detailed kinetics.
The method is coupled with a block-structured adaptive mesh refinement (SAMR) framework and a low-Mach number operator-split projection algorithm.
Capturing the multiple time scales, length scales and flame-wall thermal interaction was done using a low Mach number operator-split projection algorithm, coupled with a block-structured adaptive mesh refinement and an immersed boundary method for the solid body.
For DG methods applied to the dual splitting projection method, instabilities have recently been reported that occur for small time step sizes.
We demonstrate the resulting splitting on a second-order Crank-Nicolson discretization and point out its intimate relationship to some existing second-order accurate splitting (projection) methods.
Splitting projection data for multiple reconstructions in CT leads to a higher noise level on the single frames.
In Section 3, the fast split Bregman projection method (SBPM), augmented Lagrangian projection method (ALPM), dual split Bregman projection method (DSBPM), dual augmented Lagrangian projection method (DALPM) are presented.
In this paper, by investigating the relationship between the L1-based TV regularizer term of Chan-Vese model and the constraint on LSF and introducing some auxiliary variables, we design fast split Bregman projection method (SBPM), augmented Lagrangian projection method (ALPM), dual split Bregman projection method (DSBPM), and dual augmented Lagrangian projection method (DALPM).
dual split Bregman projection method.
In this paper we split the projection techniques into two groups, global and local techniques, conduct an analysis of them, and present a novel local technique specially designed for projecting heavy tail distance distributions, such as the one produced by high-dimensional sparse spaces.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com