Compound Droplet Modeling for Circulating Tumor Cell Microfiltration With Adaptive Meshing Refinement

2020 ◽  
Vol 142 (11) ◽  
Author(s):  
Mohammad Abul Hashem ◽  
Arian Aghilinejad ◽  
Xiaolin Chen ◽  
Hua Tan
Keyword(s):  
Flow Rate ◽  
Adaptive Mesh Refinement ◽  
Low Cost ◽  
Adaptive Mesh ◽  
Pressure Profile ◽  
Circulating Tumor Cell ◽  
Adaptive Meshing ◽  
Droplet Dynamics ◽  
Fundamental Understanding ◽  
Compound Droplet

Abstract Advances in microfluidics inaugurate a new possibility of designing diagnostic devices for early cancer detection. There is a growing interest in deformation-based microfiltration for capturing circulating tumor cells (CTCs) from peripheral blood due to its simplicity and low cost. Fundamental understanding of CTC passing through a microfilter is critical, as it helps optimize the design for achieving high isolation purity. Previous research has modeled CTC as a simple droplet for deformation-based CTC separation. Here, we use a compound droplet model to study the flow dynamics more realistically. An adaptive-mesh-refinement (AMR) method is used here, using the open-source code, gerris, after modification for droplet dynamics and contact angle model. The developed code is validated with results compared with ansysfluent and available theory. The effects of various parameters such as the nuclear-to-cytoplasmic (N/C) ratio, operating flow rate, and cell viscosity are investigated. It is found that the compound droplet behaves like a homogeneous droplet when the nucleus size is smaller than the filtering channel. However, the pressure profile is greatly influenced by the nucleus when it is larger than the channel size. In addition, there is a linear correlation between the pressure drop in the channel and the operating flow rate. Similarly, critical passing pressure increases linearly with the increase of the cell viscosity. Our study suggests that for having an accurate prediction of cell transport behavior inside the microchannel, it is of great importance to consider the effects of the nucleus and its possible deformation.

Dynamics of Compound Droplet Passing Through a Conical CTC Microfilter

2019 ◽  
Author(s):  
Pengliang Chang ◽  
Mohammad Abul Hashem ◽  
Xiaolin Chen ◽  
Hua Tan
Keyword(s):  
Cancer Detection ◽  
Flow Rate ◽  
Cross Sections ◽  
Adaptive Mesh Refinement ◽  
Early Stage ◽  
Physical Property ◽  
Adaptive Mesh ◽  
Droplet Model ◽  
Transport Behavior ◽  
Compound Droplet

Abstract Circulating tumor cells (CTCs) are important biomarkers which can be used for early-stage cancer detection and treatment. Developing an efficient approach to detect CTCs from peripheral blood is a challenging problem due to their extreme rarity. The CTC microfiltration provides a good solution as a critical method based on the physical property of CTCs. In this study, we employed a compound droplet model to investigate the transport behavior of a CTC squeezing through a conical-shaped microfilter. The compound droplet model of CTC is composed of a cortical membrane, cytoplasm and the nucleus. Numerically, we used the octree-based Adaptive-Mesh-Refinement (AMR) to analyze the deformable CTC flowing through a microfilter with non-uniform cross-sections. We investigated the pressure-deformability behavior of the cell with different nuclear to cytoplasmic ratio (N/C ratio). Our study revealed that the nucleus smaller than the filter pore did not affect the pressure behaviors significantly. However, when the nucleus is larger than the filter pore size, the pressure behaviors are greatly affected. We also studied the effects of the flow rate on the cell squeezing process. We found that the critical pressure increases significantly with the flow rate. Our study can provide valuable information about cell transport behavior in conical-shaped microfilters.

Coupled Level Set Volume of Fluid Simulations of Prefilming Airblast Atomization With Adaptive Meshing

2020 ◽  
Author(s):  
Jack R. J. Wetherell ◽  
Andrew Garmory ◽  
Maciej Skarysz
Keyword(s):  
Level Set ◽  
Adaptive Mesh Refinement ◽  
Experimental Testing ◽  
Fluid Model ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Volume Of Fluid ◽  
Computational Method ◽  
Fuel Injector ◽  
Adaptive Meshing

Abstract The fuel atomisation process and the resultant spray affects nearly all aspects of combustion system performance, and must be well understood to enable the design of future combustion systems. The design of a fuel injector makes both numerical and experimental testing difficult, so simplified test pieces are often used, however, this does not accurately capture atomisation mechanisms and fuel distributions. This paper presents a computational method combining a Coupled Level Set Volume of Fluid model with Adaptive Mesh Refinement. A simple prefilmer has been used to validate the method. Comparisons of the flow field and ligament length distributions show good agreement with published DNS data. The use of AMR allows a lower total cell count, and so a reduction in computational cost of over 60% compared to previously reported results for the same case has been achieved. Further work will look to apply this method to more realistic injector geometry.

Dynamic structural analysis of connecting rod through adaptive mesh refinement for different materials

2018 ◽  
Vol 50 (04) ◽  
pp. 561-570
Author(s):  
I. A. QAZI ◽  
A. F. ABBASI ◽  
M. S. JAMALI ◽  
INTIZAR INTIZAR ◽  
A. TUNIO ◽  
...  
Keyword(s):  
Structural Analysis ◽  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Connecting Rod ◽  
Dynamic Structural Analysis

scholarly journals Insights into the physics when modelling cold gas clouds in a hot plasma

2019 ◽  
Vol 490 (1) ◽  
pp. L52-L56
Author(s):  
Bastian Sander ◽  
Gerhard Hensler
Keyword(s):  
Adaptive Mesh Refinement ◽  
Adaptive Mesh ◽  
Careful Consideration ◽  
Necessary Condition ◽  
Interstellar Clouds ◽  
Hot Plasma ◽  
Magnetic Dipole Field ◽  
Set Up ◽  
Self Gravity ◽  
Cold Gas

ABSTRACT This paper aims at studying the reliability of a few frequently raised, but not proven, arguments for the modelling of cold gas clouds embedded in or moving through a hot plasma and at sensitizing modellers to a more careful consideration of unavoidable acting physical processes and their relevance. At first, by numerical simulations we demonstrate the growing effect of self-gravity on interstellar clouds and, by this, moreover argue against their initial set-up as homogeneous. We apply the adaptive-mesh refinement code flash with extensions to metal-dependent radiative cooling and external heating of the gas, self-gravity, mass diffusion, and semi-analytic dissociation of molecules, and ionization of atoms. We show that the criterion of Jeans mass or Bonnor–Ebert mass, respectively, provides only a sufficient but not a necessary condition for self-gravity to be effective, because even low-mass clouds are affected on reasonable dynamical time-scales. The second part of this paper is dedicated to analytically study the reduction of heat conduction by a magnetic dipole field. We demonstrate that in this configuration, the effective heat flow, i.e. integrated over the cloud surface, is suppressed by only 32 per cent by magnetic fields in energy equipartition and still insignificantly for even higher field strengths.

scholarly journals Convergence and quasi-optimal cost of adaptive algorithms for nonlinear operators including iterative linearization and algebraic solver

2021 ◽  
Author(s):  
Alexander Haberl ◽  
Dirk Praetorius ◽  
Stefan Schimanko ◽  
Martin Vohralík
Keyword(s):  
Adaptive Algorithm ◽  
Adaptive Mesh Refinement ◽  
Elliptic Boundary ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Picard Iteration ◽  
Optimal Rate ◽  
Stopping Criteria ◽  
Element Discretization ◽  
Fully Adaptive

AbstractWe consider a second-order elliptic boundary value problem with strongly monotone and Lipschitz-continuous nonlinearity. We design and study its adaptive numerical approximation interconnecting a finite element discretization, the Banach–Picard linearization, and a contractive linear algebraic solver. In particular, we identify stopping criteria for the algebraic solver that on the one hand do not request an overly tight tolerance but on the other hand are sufficient for the inexact (perturbed) Banach–Picard linearization to remain contractive. Similarly, we identify suitable stopping criteria for the Banach–Picard iteration that leave an amount of linearization error that is not harmful for the residual a posteriori error estimate to steer reliably the adaptive mesh-refinement. For the resulting algorithm, we prove a contraction of the (doubly) inexact iterates after some amount of steps of mesh-refinement/linearization/algebraic solver, leading to its linear convergence. Moreover, for usual mesh-refinement rules, we also prove that the overall error decays at the optimal rate with respect to the number of elements (degrees of freedom) added with respect to the initial mesh. Finally, we prove that our fully adaptive algorithm drives the overall error down with the same optimal rate also with respect to the overall algorithmic cost expressed as the cumulated sum of the number of mesh elements over all mesh-refinement, linearization, and algebraic solver steps. Numerical experiments support these theoretical findings and illustrate the optimal overall algorithmic cost of the fully adaptive algorithm on several test cases.

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