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20032022
most citedRobust and Efficient Modular Grad-Div Stabilization

54 citations · 90 across the 17 of their papers we have counts for

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17 papers · 1 filter

math.NA2022

Conditioning of linear systems arising from penalty methods

William Layton, Shuxian Xu

Penalizing incompressibility in the Stokes problem leads, under mild assumptions, to matrices with condition numbers , pena…

math.NA2021

Stability in 3d of a sparse grad-div approximation of the Navier-Stokes equations

William Layton, Shuxian Xu

Inclusion of a term , forcing to be pointwise small, is an effective tool for improving mass conservation in discretizations of incompressibl…

math.NA2021

Refactorization of a variable step, unconditionally stable method of Dahlquist, Liniger and Nevanlinna

William Layton, Wenlong Pei, Catalin Trenchea

The one-leg, two-step time-stepping scheme proposed by Dahlquist, Liniger and Nevanlinna has clear advantages in complex, stiff numerical simulations: unconditional -stability f…

math.NA2020

A general linear method approach to the design and optimization of efficient, accurate, and easily implemented time-stepping methods in CFD

Victor DeCaria, Sigal Gottlieb, Zachary J. Grant +1

In simulations of fluid motion time accuracy has proven to be elusive. We seek highly accurate methods with strong enough stability properties to deal with the richness of scales o…

math.NA2020

Analysis of the variable step method of Dahlquist, Liniger and Nevanlinna for fluid flow

William Layton, Wenlong Pei, Yi Qin +1

The two-step time discretization proposed by Dahlquist, Liniger and Nevanlinna is variable step -stable. (In contrast, for increasing time steps, the BDF2 method loses -stabi…

math.NA2019

Diagnostics for Eddy Viscosity Models of Turbulence Including Data-Driven/Neural Network Based Parameterizations

William Layon, Michael Schneier

Classical eddy viscosity models add a viscosity term with turbulent viscosity coefficient whose specification varies from model to model. Turbulent viscosity coefficient approximat…