Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep-learning Assisted Extraction of Fluid Velocity from Scalar Signal
  Transport in a Shallow Microfluidic Channel   Precise measurement of flow velocity in microfluidic channels is of
importance in microfluidic applications, such as quantitative chemical
analysis, sample preparation and drug synthesis. However, simple approaches for
quickly and precisely measuring the flow velocity in microchannels are still
lacking. Herein, we propose a deep neural networks assisted scalar image
velocimetry (DNN-SIV) for quick and precise extraction of fluid velocity in a
shallow microfluidic channel with a high aspect ratio, which is a basic
geometry for cell culture, from a dye concentration field with spatiotemporal
gradients. DNN-SIV is built on physics-informed neural networks and residual
neural networks that integrate data of scalar field and physics laws to
determine the velocity in the height direction. The underlying enforcing
physics laws are derived from the Navier-Stokes equation and the scalar
transport equation. Apart from this, dynamic concentration boundary condition
is adopted to improve the velocity measurement of laminar flow with small
Reynolds Number in microchannels. The proposed DNN-SIV is validated and
analyzed by numerical simulations. Compared to integral minimization algorithm
used in conventional SIV, DNN-SIV is robust to noise in the measured scalar
field and more efficiently allowing real-time flow visualization. Furthermore,
the fundamental significance of rational construction of concentration field in
microchannels is also underscored. The proposed DNN-SIV in this paper is
agnostic to initial and boundary conditions that can be a promising velocity
measurement approach for many potential applications in microfluidic chips.

8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
1
The categories of this paper are: cs
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph