activity
20102023
most citedExplicit physics-informed neural networks for non-linear upscaling closure: the case of transport in tissues

12 citations · 32 across the 8 of their papers we have counts for

collaborators

8 papers

math.HO2023★ 1 cited

Introduction to Engineering Mathematics and Analysis: Modeling Physical Systems Using the Language of Mathematics

Brian D Wood

An introduction to applied mathematics written for students in engineering and science. Focus is on a rigorous presentation that also builds understanding by discussion, analogy, a…

math-ph2022★ 1 cited

A Note on the Gibbsian Representation of the Gradient of a Vector Field

Brian D. Wood, Peeter Joot, Stephen Whitaker

In this note, we provide a important considerations of a familiar topic: the gradient of a vector field. The gradient of a vector field is a common quantity represented in continuu…

physics.comp-ph2021★ 12 cited

Explicit physics-informed neural networks for non-linear upscaling closure: the case of transport in tissues

Ehsan Taghizadeh, Helen M. Byrne, Brian D. Wood

In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in a multiscale tissue. Th…

physics.flu-dyn2018★ 7 cited

A hierarchy of models for simulating experimental results from a 3D heterogeneous porous medium

Daniel Vogler, Sassan Ostvar, Rebecca Paustian +1

In this work we examine the dispersion of conservative tracers (bromide and fluorescein) in an experimentally-constructed three-dimensional dual-porosity porous medium. The medium…

math.AP2015

Series Solutions for Orthotropic Diffusion in a Cube

Brian D. Wood, Sassan Ostvar

Analytical solutions to heat or diffusion type equations are numerous, but there are rather few explicit solutions for conditions where the thermal conductivity or diffusion tensor…

math.PR2012★ 1 cited

Interfacial Phenomena and Natural Local Time

Thilanka Appuhamillage, Vrushali Bokil, Enrique Thomann +2

This article addresses a modification of local time for stochastic processes, to be referred to as `natural local time'. It is prompted by theoretical developments arising in mathe…