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W. Layton

20 papers hereh-index 487.3k citations212 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author8
  • middle author8
  • last author3

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • math.NA17
  • physics.flu-dyn2
  • math-ph1
same name
  • W. Layton — 3 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20032022
most citedRobust and Efficient Modular Grad-Div Stabilization

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

collaborators
Showing 2019 · math.NAShow all

4 papers · 2 filters

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…

math.NA2019★ 1 cited

On URANS Congruity with Time Averaging: Analytical laws suggest improved models

William Layton, Michael McLaughlin

The standard 1−equation model \ of turbulence was first derived by Prandtl and has evolved to be a common method for practical flow simulations. Five fundamental laws that any UR…

math.NA2019

Doubly-Adaptive Artificial Compression Methods for Incompressible Flow

William Layton, Michael McLaughlin

This report presents adaptive artificial compression methods in which the time-step and artificial compression parameter ε are independently adapted. The resulting alg…

math.NA2019

An Artificial Compression Reduced Order Model

Victor DeCaria, Traian Iliescu, William Layton +2

We propose a novel artificial compression, reduced order model (AC-ROM) for the numerical simulation of viscous incompressible fluid flows. The new AC-ROM provides approximations n…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.