Characteristic time scales for diffusion processes through layers and across interfaces

TL;DR

This paper introduces a straightforward method using mean action time to estimate the characteristic timescale for diffusion through layered media, aiding understanding of heat, flow, and drug diffusion processes.

Contribution

It provides simple algebraic expressions for the diffusion timescale in layered media based on physical properties, enhancing analysis of complex multilayer diffusion systems.

Findings

Expressions depend on diffusivities and layer lengths.

Method offers insights into parameter effects on diffusion time.

Numerical examples validate the approach.

Abstract

This paper presents a simple tool for characterising the timescale for continuum diffusion processes through layered heterogeneous media. This mathematical problem is motivated by several practical applications such as heat transport in composite materials, flow in layered aquifers and drug diffusion through the layers of the skin. In such processes, the physical properties of the medium vary across layers and internal boundary conditions apply at the interfaces between adjacent layers. To characterise the timescale, we use the concept of mean action time, which provides the mean timescale at each position in the medium by utilising the fact that the transition of the transient solution of the underlying partial differential equation model, from initial state to steady state, can be represented as a cumulative distribution function of time. Using this concept, we define the characteristic timescale for a multilayer diffusion process as the maximum value of the mean action time across the layered medium. For given initial conditions and internal and external boundary conditions, this approach leads to simple algebraic expressions for characterising the timescale that depend on the physical and geometrical properties of the medium, such as the diffusivities and lengths of the layers. Numerical examples demonstrate that these expressions provide useful insight into explaining how the parameters in the model affect the time it takes for a multilayer diffusion process to reach steady state.