AI Article Synopsis
- The shape and dimensions of a micromixer are crucial for determining its mixing efficiency and performance in various applications.
- This study explores two methods for evaluating mixing efficiency: a numerical model and an image processing-based experimental model, offering flexibility in approach based on available resources and data.
- Results indicate that both methods yield similar outcomes, with discrepancies of only 0 to 6% in the efficiency calculations across all tested points, enhancing confidence in their reliability.
Article Abstract
The shape and dimensions of a micromixer are key elements in the mixing process. Accurately quantifying the mixing efficiency enables the evaluation of the performance of a micromixer and the selection of the most suitable one for specific applications. In this paper, two methods are investigated to evaluate the mixing efficiency: a numerical model and an experimental model with a software image processing technique. Using two methods to calculate the mixing efficiency, in addition to corroborating the results and increasing their reliability, creates various possible approaches that can be selected depending on the circumstances, resources, amount of data to be processed and processing time. Image processing is an easy-to-implement tool, is applicable to different programming languages, is flexible, and provides a quick response that allows the calculation of the mixing efficiency using a process of filtering of images and quantifying the intensity of the color, which is associated with the percentage of mixing. The results showed high similarity between the two methods, with a difference ranging between 0 and 6% in all the evaluated points.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469598 | PMC |
| http://dx.doi.org/10.3390/mi12091102 | DOI Listing |
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