Elie Magnon

Mr. Elie Magnon


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
14 April 2021 in Fluids
Verified
Journal Article
Open access
PDF file
EMElie Magnon
Elie Magnon
ECEric Cayeux
Eric Cayeux
Accurate characterization of the rheological behavior of non-Newtonian fluids is critical in a wide range of industries as it governs process efficiency, safety, and end-product quality. When the rheological behavior of fluid may vary substantially over a relatively short period of time, it is desirable to measure its viscous properties on a more continuous basis than relying on spot measurements made with a viscometer on a few samples. An attractive solution for inline rheological measurements is to measure pressure gradients while circulating fluid at different bulk velocities in a circular pipe. Yet, extracting the rheological model parameters may be challenging as measurement uncertainty may influence the precision of the model fitting. In this paper, we present a method to calibrate the Herschel-Bulkley rheological model to a series of differential pressure measurements made at variable bulk velocities using a combination of physics-based equations and nonlinear optimization. Experimental validation of the method is conducted on non-Newtonian shear-thinning fluid based on aqueous solutions of polymers and the results are compared to those obtained with a scientific rheometer. It is found that using a physics-based method to estimate the parameters contributes to reducing prediction errors, especially at low flow rates. With the tested polymeric fluid, the proportion difference between the estimated Herschel-Bulkley parameters and those obtained using the scientific rheometer are −24% for the yield stress, 0.26% for the consistency index, and 0.30% for the flow behavior index. Finally, the computation requires limited resources, and the algorithm can be implemented on low-power devices such as an embedded single-board computer or a mobile device.