Velibor Isailović, Miljan Milošević, Nikola Kojić, Miloš Kojić (DOI: 10.24874/jsscm.2025.19.01.15)

 

Abstract

 

Finite element (FE) modeling the motion of deformable bodies within a fluid, as well as the interaction between the bodies, has been a continuous challenge over the years. There are in principle two approaches – loose and strong coupling between the FE models of the two domains, with their advantages and drawbacks. We here present our concept of strong coupling which we thoroughly tested in the past, particularly with respect to the accuracy of the model, Theoretical background and computational procedure are briefly described and then illustrated on two typical applications, among numerous in our references. One is related to the microfluidic chip and another – to conditions of the passing of the circulating tumor cells (CTCs) through a capillary narrowing; both are significant in biomedical engineering. Regarding the first example, we have that in recent years, attention has been paid to the creation of the so-called microfluidic chips. These devices are used for testing very small blood samples. There, blood is passed through a micro-device in which cells are separated according to cell stiffness under precisely controlled laminar flow conditions. The development of the microfluidic chip can be significantly accelerated and simplified by building its computational replica - a computer program designed for modeling the chip's geometry and topology, as well as simulating the processes occurring within it. In the second example, we explored the parameter space, where a relationship between the capillary blood pressure gradient and the circulating tumor cells (CTCs) mechanical properties (size and stiffness) was determined for the CTC arrest in a capillary. The presented computational platform, along with the derived pressure–size–stiffness relationship, serves as a valuable tool for investigating the biomechanical conditions underlying capillary arrest of circulating tumor cells (CTCs) and CTC clusters, enabling predictive modeling of metastatic progression based on biophysical CTC parameters, and supporting the rational design of size-based CTC isolation technologies that account for large CTC deformations under high pressure gradients.

 

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