Title

Eco-Efficiency Of Construction Materials: Data Envelopment Analysis

Keywords

Bioreactor; Computational fluid dynamics; Modeling; Plug flow; Residence time distribution; Simulation; Transport; Visualization

Abstract

Microreactors experience significant deviations from plug flow due to the no-slip boundary condition at the walls of the chamber. The development of stagnation zones leads to widening of the residence time distribution at the outlet of the reactor. A hybrid design optimization process that combines modeling and experiments has been utilized to minimize the width of the residence time distribution in a microreactor. The process was used to optimize the design of a microfluidic system for an in vitro model of the lung alveolus. Circular chambers to accommodate commercial membrane supported cell constructs are a particularly challenging geometry in which to achieve a uniform residence time distribution. Iterative computational fluid dynamics (CFD) simulations were performed to optimize the microfluidic structures for two different types of chambers. The residence time distributions of the optimized chambers were significantly narrower than those of non-optimized chambers, indicating that the final chambers better approximate plug flow. Qualitative and quantitative visualization experiments with dye indicators demonstrated that the CFD results accurately predicted the residence time distributions within the bioreactors. The results demonstrate that such a hybrid optimization process can be used to design microreactors that approximate plug flow for in vitro tissue engineered systems. This technique has broad application for optimization of microfluidic body-on-a-chip systems for drug and toxin studies. © 2012 Biomedical Engineering Society.

Publication Date

6-1-2012

Publication Title

Journal of Construction Engineering and Management

Volume

138

Issue

6

Number of Pages

733-741

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1061/(ASCE)CO.1943-7862.0000484

Socpus ID

84862134402 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84862134402

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