Virtual Sensor Development for Continuous Microfluidic Processes

In continuous microfluidic processes, such as factory-on-chips, most valuable variables to be sensed for implementing an optimal control are usually not accessible. This is, for instance, the case of the shape and position tracking of the flow interfaces in a flow-focusing microdevice. In this conte...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industrial informatics 2020-12, Vol.16 (12), p.7774-7781
Main Authors: Garcia-Camprubi, Maria, Bengoechea-Cuadrado, Cristina, Izquierdo, Salvador
Format: Article
Language:English
Subjects:
Analytical models
CAE
Computational fluid dynamics (CFD)
Computer aided engineering
Computer simulation
control
Flow velocity
Fluids
Hydrodynamics
Mathematical model
Microfluidics
Model reduction
Numerical models
Optimal control
reduced order model (ROM)
Reservoirs
Sensors
virtual sensor
Virtual sensors
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In continuous microfluidic processes, such as factory-on-chips, most valuable variables to be sensed for implementing an optimal control are usually not accessible. This is, for instance, the case of the shape and position tracking of the flow interfaces in a flow-focusing microdevice. In this context, virtual sensors are promising tools to improve the current control systems aiming at a zero-defect strategy. This article presents a methodology for building an accurate virtual sensor, based on computer-aided engineering simulations, both analytical and numerical, and model order reduction techniques. The methodology is applied to a given flow-focusing microchip. The outcome is a real-time model (virtual sensor) able to predict the shape and location of the multiphase fluid interfaces from the volumetric flow rate measured in the system. Results are successfully validated against the experimental data. The main challenge of this approach is to minimize uncertainties associated with the microfluidics setup.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2020.2972111