The present study introduces a lumped-parameter model for designing lab-on-a-chip (LOC) devices in micro/nanofluidics, aiming to reduce the extensive time and computational demands of traditional 2D or 3D simulations or experiments. Drawing from established literature and the electrical analogy applied to channel flows, this model effectively simplifies the analysis of developing laminar flow regimes within LOC microchannels. It accurately captures nonlinear pressure drops, crucial for determining the system’s driving pressure, with an error margin of up to 1% and significantly faster computational times. The model divides the domain into finite segments, applying 1D governing equations to each segment. The model’s utility extends to analyzing blood flow in vascular systems and optimizing coolant circulation in electronic components, demonstrating its broad applicability in scientific and engineering contexts. This rapid analysis approach is particularly beneficial in time-sensitive fields like medicine.

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Lumped-Parameter Modeling of Laminar Developing Flow in a Microchannel

  • Advaith R. Nair,
  • A. Aswin,
  • M. Gokul Sunu,
  • K. Nandakumar Chandran,
  • S. Kumar Ranjith

摘要

The present study introduces a lumped-parameter model for designing lab-on-a-chip (LOC) devices in micro/nanofluidics, aiming to reduce the extensive time and computational demands of traditional 2D or 3D simulations or experiments. Drawing from established literature and the electrical analogy applied to channel flows, this model effectively simplifies the analysis of developing laminar flow regimes within LOC microchannels. It accurately captures nonlinear pressure drops, crucial for determining the system’s driving pressure, with an error margin of up to 1% and significantly faster computational times. The model divides the domain into finite segments, applying 1D governing equations to each segment. The model’s utility extends to analyzing blood flow in vascular systems and optimizing coolant circulation in electronic components, demonstrating its broad applicability in scientific and engineering contexts. This rapid analysis approach is particularly beneficial in time-sensitive fields like medicine.