Modeling Pressure Drop Using Generalized Scaffold Characteristics in an Axial-Flow Bioreactor for Soft Tissue Regeneration

Abstract

The goal of this study was to better understand how analytical permeability models based on scaffold architecture can facilitate a non-invasive technique to real time monitoring of pressure drop in bioreactors. In particular, we evaluated the permeability equations for electrospun and freeze dried scaffolds via pressure drop comparison in an axial-flow bioreactor using computational fluid dynamic (CFD) and experimentation. The polycaprolactone-cellulose acetate fibers obtained by co-axial electrospinning technique and Chitosan-Gelatin scaffolds prepared using freeze-drying techniques were utilized. Initially, the structural properties (fiber size, pore size and porosity) and mechanical properties (elastic modulus and Poisson's ratio) of scaffolds in phosphate buffered saline at 37 °C were evaluated. The CFD simulations were performed by coupling fluid flow, described by Brinkman equation, with structural mechanics using a moving mesh. The experimentally obtained pressure drop values for both 1 mm thick and 2 mm thick scaffolds agreed with simulation results. To evaluate the effect of permeability and elastic modulus on pressure drop, CFD predictions were extended to a broad range of permeabilities spanning synthetic scaffolds and tissues, elastic moduli, and Poisson's ratio. Results indicated an increase in pressure drop with increase in permeability. Scaffolds with higher elastic modulus performed better and the effect of Poisson's ratio was insignificant. Flow induced deformation was negligible in axial-flow bioreactor. In summary, scaffold permeabilities can be calculated using scaffold microarchitecture and can be used in non-invasive monitoring of tissue regeneration.

Multiple approaches to predicting oxygen and glucose consumptions by HepG2 cells on porous scaffolds in an axial‐flow bioreactor

“…Hence the system allows validating the computational models. Further, using the same bioreactor configuration used previously, the CFD simulation predictions of fluid dynamic behavior were validated with the experimental measured pressure drop results (Podichetty et al, ). Flow through the porous medium in the axial‐flow bioreactor was simulated using Brinkman equation to account for the losses at the interface of scaffold and fluid.…”

“…Further, these also help in regenerating clinically relevant large tissues such as bladder, abdominal wall, liver lobules, skin, and cartilage. Based on this concept, previous publications reported on fluid dynamic modeling coupled with structural mechanics in the axial‐flow bioreactors (Podichetty et al, ) and flow‐through reactors (Podichetty and Madihally, ). Since permeability is expressed as a k factor using Kozeny–Carman equation, definition for variety of tissues has been summarized in previously (Swartz and Fleury, ), equations for determining k values using generalized scaffold pore architecture were utilized and validated by pressure drop measurement.…”

Applications of Computational Modelling and Simulation of Porous Medium in Tissue Engineering

“…κ " 3r 2 20`1´ε p˘`´l n`1´ε p˘´0 .931˘ (19) where r is the radius of the fibers. Since these scaffolds are very thin relative to their surface area, one could assume negligible porosity across the thickness.…”

“…Then, porosity can be estimated using digital micrographs collected from scanning electron microscopy. Image analysis is performed to calculate the ratio of the open pore area to the total area of the image analyzed, which is considered as the porosity of the scaffold [19]. If the fiber sizes are large, another correlation is developed using Lattice-Boltzmann method.…”

A Dual–Mixed Finite Element Method for the Brinkman Problem

“…Such efforts have been undertaken by by Mardal, Tai, and Winther [23], Tai and Winther [33] for the The Brinkman model is also employed in several application areas, including filtration [28], groundwater flow through permeable membranes [10], liquid and vapor flow in heat pipes [21], flow through permeable textile microstructures [14], computational fuel cell dynamics [37], vascular tissue engineering [3], and bioreactors for tissue regeneration [30,34].…”