Virtual prototyping of pressure driven microfluidic systems with SystemC-AMS extensions
Resumen: The design of "Lab on a Chip" microfluidic devices is, typically, preceded by a long and costly period of prototyping stages in which the system is gradually refined by an iterative process, involving the manufacturing of a physical prototype and the making of a lot of laboratory experiments. In this scenario, a virtual prototyping framework which allows the emulation of the behavior of the complete system is greatly welcome. This paper presents such a framework and details a virtual prototyping methodology able to soundly handle microfluidic behavior based on SystemC-AMS extensions. The use of these extensions will permit the communication of the developed microfluidic models with external digital or mixed signal devices. This allows the emulation of the whole Lab on a Chip system as it usually includes a digital control and a mixed-signal reading environment. Moreover, as SystemC-AMS is also being extended to cover other physical domains within the CATRENE CA701 project, interactions with these domains will be possible, for example, with electromechanical or optical parts, should they be part of the system. The presented extensions that can manage the modeling of a micro-fluidic system are detailed. Two approaches have been selected: to model the fluid analytically based on the Poiseuille flow theory and to model the fluid numerically following the SPH (Smoothed Particle Hydrodynamics) approach. Both modeling techniques are, by now, encapsulated under the TDF (Timed Data Flow) MoC (Model of Computation) of SystemC-AMS.
Idioma: Inglés
DOI: 10.1016/j.micpro.2015.07.007
Año: 2015
Publicado en: MICROPROCESSORS AND MICROSYSTEMS 39, 8 (2015), 854-865
ISSN: 0141-9331

Factor impacto JCR: 0.471 (2015)
Categ. JCR: COMPUTER SCIENCE, HARDWARE & ARCHITECTURE rank: 44 / 51 = 0.863 (2015) - Q4 - T3
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 215 / 257 = 0.837 (2015) - Q4 - T3
Categ. JCR: COMPUTER SCIENCE, THEORY & METHODS rank: 97 / 105 = 0.924 (2015) - Q4 - T3

Factor impacto SCIMAGO: 0.25 - Artificial Intelligence (Q3) - Software (Q3) - Hardware and Architecture (Q3) - Computer Networks and Communications (Q3)

Financiación: info:eu-repo/grantAgreement/EUR/CATRENE-CA701-H-INCEPTION
Tipo y forma: Artículo (PostPrint)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)

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