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This paper represents a detailed and systematic review of one of the most ongoing applications of computational fluid dynamics (CFD) in biomedical applications. Beyond its various engineering applications, CFD has started to establish a presence in the biomedical field. Cardiac abnormality, a familiar health issue, is an essential point of investigation by research analysts. Diagnostic modalities provide cardiovascular structural information but give insufficient information about the hemodynamics of blood. The study of hemodynamic parameters can be a potential measure for determining cardiovascular abnormalities. Numerous studies have explored the rheological behavior of blood experimentally and numerically. This paper provides insight into how researchers have incorporated the pulsatile nature of the blood experimentally, numerically, or through various simulations over the years. It focuses on how machine learning platforms derive outputs based on mass and momentum conservation to predict the velocity and pressure profile, analyzing various cardiac diseases for clinical applications. This will pave the way toward responsive AI in cardiac healthcare, improving productivity and quality in the healthcare industry. The paper shows how CFD is a vital tool for efficiently studying the flow in arteries. The review indicates this biomedical simulation and its applications in healthcare using machine learning and AI. Developing AI-based CFD models can impact society and foster the advancement towards responsive AI. [ABSTRACT FROM AUTHOR]

In this paper, the fluid-structure interaction problem: vortex-induced vibration of a cooled circular cylinder involving thermal buoyancy is numerically investigated. The elastically mounted cylinder having a temperature lower than the flowing fluid is modelled using mass-spring-damper hence allowed to vibrate in the transverse direction to the flow direction. The gravity is acting opposite to the flow direction. In-house fluid-structure interaction solver is developed based on Harten Lax and van Leer with contact for artificial compressibility Riemann solver. The arbitrarily Lagrangian-Eulerian formulation is employed here, and the mesh is dynamically moved using radial basis function-based interpolation. The solution-dependent weighted least squares based gradient calculations are developed to achieve higher-order accuracy over unstructured meshes. The laminar incompressible flow at Reynolds number, Re = 200, and Prandtl number, Pr = 0.71, is simulated for the mass ratio of 1 and reduced damping coefficient of 0.001. The flow is investigated for Richardson number (-1, 0) and over a wide range of natural frequencies of the cylinder. The heat transfer characteristics from a cylinder are captured and compared with the existing literature results. From the study, it can be observed that in the presence of the thermal boundary layer, the oscillation of the cylinder increases to its maximum amplitude, particularly for values of natural frequencies (0.063 – 0.3).