Biofluid dynamics and the representation of physiological flows have been fascinating to the thinkers of their time for centuries. Two well-known examples are Leonardo da Vinci's 16th-century sketches of blood in an aortic valve and William Harvey's published work on “An anatomical study of the motion of the heart and of the blood of animals” (1628) [1,2].

In the last 50 years or so, scientists, physicians, and engineers developed mathematical models and corresponding simulation tools for describing and quantifying physiological flows and their interaction with body structures. Driven by the advancements in high-performance computing, data-driven methodologies, and using a multiphysics-based approach, computational biofluid dynamics have experienced tremendous growth. This multidisciplinary discipline enables us today to enhance our understanding of underlying mechanisms of biofluid dynamics associated with the physiology and pathophysiologies of circulatory and respiratory flows.

This Special Issue comprises original research and reviews articles in the research area of computational biofluid dynamics, fluid–structure interaction, and acoustic phenomena of relevance to confined, unsteady, transitional, or turbulent fluid flow scenarios in the human body. The selected papers in this issue represent several trends in biofluid mechanics. The scope of the papers ranges from extending numerical methodology for handling the interaction between the flow and the vessel (fluid–structure interactions, FSI) to using computational tools to guide intervention in clinical situations.

Research studies analyzing the interaction between the flow and surrounding structures by using combined computational fluid dynamics and fluid–structure interaction (CFD/FSI) approaches are complemented by reviews of the method when applied to, for example, cerebrovascular pathophysiology by Thiyagarajah et al. and Achey et al. The paper by Shine et al. considers aspects of aneurysm initiation at the circle of Willis due to fluid-structure interaction, explored using computational modeling. Sundström and Tretter studied using CFD/FSI the functionally bicuspid aortic valve, the associated hemodynamics, and tissue biomechanics, assessing the medical impact of the theoretical results as well. The flow in the thoracic aorta is primarily unidirectional. Notably, it has been exposed that retrograde flow may occur during the cardiac cycle and its importance depends on heart rate and cardiac output as presented by Fuchs et al. The phenomenon may explain the clinical observation of embolus transport from the descending aorta to the neck arteries and the brain. The mixing in the right atrium of the heart considering the flows from the inferior and superior vena cava has been quantified using different computational modeling approaches by Parker et al. The characteristic of a transitional flow has been exposed using large eddy simulations.

The paper by Falk et al. describes drug delivery by inhalation, which has several practical and clinical advantages. Nonetheless, the flow in the upper parts of the human airways is highly three-dimensional, unsteady, and extremely complex due to its dependency on the surrounding geometrical complexity, the presence of a viscoelastic mucus layer, and the respiratory cycle. Numerical simulations are useful to assess aerosol dispersion during medical examinations. Nasal droplet deposition associated with intranasal corticosteroid sprays is studied by using two-phase CFD tools by Sundström et al. Among the considered sensitivity effects one can mention the nostril side, insertion depth, insertion angle, cone spray angle, inhaling rates, as well as the wall treatment. As modeling quality improves, computational tools may become a clinical tool for assisting and guiding physicians in clinical decision-making. Virtual surgery of the nasal cavity has been considered by using a combined lattice Boltzmann method with a level set approach by Waldmann et al. Phonation process and the impact of vocal fold models optimized for glottal closure were studied in Thomson and Taylor. Within this context, a genetic algorithm-based optimization approach is used to determine optimal geometric and material characteristics of a multilayer vocal fold model.

A current clinical trend is to introduce “patient specific” treatment. Computational tools can have a natural role in clinical decision-making as patient-specific data (based on computed tomography, magnetic resonance imaging, and/or ultrasound) are available. Currently, the main weaknesses of such an approach include the lack of well-resolved data and understanding of the properties of cells and tissues and their dynamic response to fluid mechanical forces acting on them. It is highly probable that using machine learning algorithms and tools applied to clinical and computational data will enable a better understanding of the underlying processes, whereby the reliability of numerical simulations will reach the level needed for qualified clinical decision making.


, “
Leonardo da Vinci's Laboratory: Studies in Flow
), pp.
, and
Applied BioFluid Mechanics
McGraw-Hill Companies
, New York.