TWO PHASE MICROFLUIDICS: NEW TREND IN MODEL IDENTIFICATION

The aim of the research is to give a proper understanding of the physical aspects involved in two-phase microfluidic systems: from the theoretical point of view to the development of numerical solutions for the flow field by Computational Modeling (CM) issue studies devoted to standard droplet generator for separation and segmented flow, bubble and drop formation, breakup and coalescence and then with increasing complexity in large scale microfluidic processors, bubble logic i.e. bubble to bubble hydrodynamic interaction provides an on-chip process control mechanism integrating chemistry and computation. This concept has been implemented using COMSOL multiphysics 3.5a software. These show the non-linearity, gain, bistability and programmability required for scalable universal computation. Alongside experimental work, numerical tools, such as computational fluid dynamics (CFD), allow us to study and analyses the behavior of immiscible fluids within microchannels. Good understanding of these microfluidic flows provides us with leverage when utilized in chemical and biological applications. The study in the context of micro-optofluidics analysis have allowed to define in some detail the integrated system used to Thorlabs has provided for the experiments in micro-optofluidics. In particular, the characterization of the microfluidic detection devices has been used in the experimental studies of two-phase flow. In addition, the analysis carried out in the various micro-channels fixed unique features in terms of flow rates for each dimensions. The key issue is finally the study and designs of an embedded system optofluidics in micro-optics Lab-On-Chip (LOC), which allows achieving very narrow spaces in a microfluidic system, ensuring a degree of portability, which it integrates optical realizing therefore, the right balance between the two disciplines. Played as part of a global project in which design and manufacture of micro devices LOC, and experimental studies within micro-optofluidics could easily fit in a biochemical analysis of the microscopic scale of biological particles of various kinds. The dynamical model identification of the asymptotic Time signals belonging to a microfluidic Two-Phase Flow process is presented. The experimental time series are used to synchronize another system with known mathematical model but unknown parameters: the Chua s oscillator. This system has been chosen for its simple mathematical structure and for the Possibility, respect to other chaotic systems, of mapping various non-linear experimental phenomena. A genetic algorithm was exploited for parameters estimation in relation to an optimization index that takes into an account of synchronization of master (microfluidic system) and slave system (Chua s oscillator).