Computational Fluid-structure Interaction Model Research Articles

Effect of TAVR commissural alignment on coronary flow: A fluid-structure interaction analysis

Background and ObjectivesCoronary obstruction is a complication that may affect patients receiving Transcatheter Aortic Valve Replacement (TAVR), with catastrophic consequences and long-term negative effects. To enable healthy coronary perfusion, it is fundamental to appropriately position the device with respect to the coronary ostia. Nonetheless, most TAVR delivery systems do not control commissural alignment to do so. Moreover, no in silico study has directly assessed the effect of commissural alignment on coronary perfusion. This work aims to evaluate the effect of TAVR commissural alignment on coronary perfusion and device performance. MethodsA two-way computational fluid-structure interaction model is used to predict coronary perfusion at different commissural alignments. Moreover, in each scenario, hemodynamic biomarkers are evaluated to assess device performance. ResultsCommissural misalignment is shown to reduce the total coronary perfusion by −3.2% and the flow rate to a single coronary branch by −6.8%. It is also observed to impair valvular function by reducing the systolic geometric orifice area by −2.5% and increasing the systolic transvalvular pressure gradients by +5.3% and the diastolic leaflet stresses by +16.0%. ConclusionsThe present TAVR patient model indicates that coronary perfusion, hemodynamic and structural performance are minimized when the prosthesis commissures are fully misaligned with the native ones. These results support the importance of enabling axial control in new TAVR delivery catheter systems and defining recommended values of commissural alignment in upcoming clinical treatment guidelines.

Simulating the mechanical stimulation of cells on a porous hydrogel scaffold using an FSI model to predict cell differentiation.

3D-structured hydrogel scaffolds are frequently used in tissue engineering applications as they can provide a supportive and biocompatible environment for the growth and regeneration of new tissue. Hydrogel scaffolds seeded with human mesenchymal stem cells (MSCs) can be mechanically stimulated in bioreactors to promote the formation of cartilage or bone tissue. Although in vitro and in vivo experiments are necessary to understand the biological response of cells and tissues to mechanical stimulation, in silico methods are cost-effective and powerful approaches that can support these experimental investigations. In this study, we simulated the fluid-structure interaction (FSI) to predict cell differentiation on the entire surface of a 3D-structured hydrogel scaffold seeded with cells due to dynamic compressive load stimulation. The computational FSI model made it possible to simultaneously investigate the influence of both mechanical deformation and flow of the culture medium on the cells on the scaffold surface during stimulation. The transient one-way FSI model thus opens up significantly more possibilities for predicting cell differentiation in mechanically stimulated scaffolds than previous static microscale computational approaches used in mechanobiology. In a first parameter study, the impact of the amplitude of a sinusoidal compression ranging from 1% to 10% on the phenotype of cells seeded on a porous hydrogel scaffold was analyzed. The simulation results show that the number of cells differentiating into bone tissue gradually decreases with increasing compression amplitude, while differentiation into cartilage cells initially multiplied with increasing compression amplitude in the range of 2% up to 7% and then decreased. Fibrous cell differentiation was predicted from a compression of 5% and increased moderately up to a compression of 10%. At high compression amplitudes of 9% and 10%, negligible areas on the scaffold surface experienced high stimuli where no cell differentiation could occur. In summary, this study shows that simulation of the FSI system is a versatile approach in computational mechanobiology that can be used to study the effects of, for example, different scaffold designs and stimulation parameters on cell differentiation in mechanically stimulated 3D-structured scaffolds.

Deciphering the connection between upstream obstacles, wake structures, and root signals in seal whisker array sensing using interpretable neural networks.

This study presents a novel method that combines a computational fluid-structure interaction model with an interpretable deep-learning model to explore the fundamental mechanisms of seal whisker sensing. By establishing connections between crucial signal patterns, flow characteristics, and attributes of upstream obstacles, the method has the potential to enhance our understanding of the intricate sensing mechanisms. The effectiveness of the method is demonstrated through its accurate prediction of the location and orientation of a circular plate placed in front of seal whisker arrays. The model also generates temporal and spatial importance values of the signals, enabling the identification of significant temporal-spatial signal patterns crucial for the network's predictions. These signal patterns are further correlated with flow structures, allowing for the identification of important flow features relevant for accurate prediction. The study provides insights into seal whiskers' perception of complex underwater environments, inspiring advancements in underwater sensing technologies.

Fluid-structure interaction analysis of eccentricity and leaflet rigidity on thrombosis biomarkers in bioprosthetic aortic valve replacements.

This work intends to study the effect of aortic annulus eccentricity and leaflet rigidity on the performance, thrombogenic risk and calcification risk in bioprosthetic aortic valve replacements (BAVRs). To address these questions, a two-way immersed fluid-structure interaction (FSI) computational model was implemented in a high-performance computing (HPC) multi-physics simulation software, and validated against a well-known FSI benchmark. The aortic valve bioprosthesis model is qualitatively contrasted against experimental data, showing good agreement in closed and open states. Regarding the performance of BAVRs, the model predicts that increasing eccentricities yield lower geometric orifice areas (GOAs) and higher normalized transvalvular pressure gradients (TPGs) for healthy cardiac outputs during systole, agreeing with in vitro experiments. Regions with peak values of residence time are observed to grow with eccentricity in the sinus of Valsalva, indicating an elevated risk of thrombus formation for eccentric configurations. In addition, the computational model is used to analyze the effect of varying leaflet rigidity on both performance, thrombogenic and calcification risks with applications to tissue-engineered prostheses. For more rigid leaflets it predicts an increase in systolic and diastolic TPGs, and decrease in systolic GOA, which translates to decreased valve performance. The peak shear rate and residence time regions increase with leaflet rigidity, but their volume-averaged values were not significantly affected. Peak solid stresses are also analyzed, and observed to increase with rigidity, elevating risk of valve calcification and structural failure. To the authors' knowledge this is the first computational FSI model to study the effect of eccentricity or leaflet rigidity on thrombogenic biomarkers, providing a novel tool to aid device manufacturers and clinical practitioners.

Neuromechanical wave resonance in jellyfish swimming

For organisms to have robust locomotion, their neuromuscular organization must adapt to constantly changing environments. In jellyfish, swimming robustness emerges when marginal pacemakers fire action potentials throughout the bell's motor nerve net, which signals the musculature to contract. The speed of the muscle activation wave is dictated by the passage times of the action potentials. However, passive elastic material properties also influence the emergent kinematics, with time scales independent of neuromuscular organization. In this multimodal study, we examine the interplay between these two time scales during turning. A three-dimensional computational fluid-structure interaction model of a jellyfish was developed to determine the resulting emergent kinematics, using bidirectional muscular activation waves to actuate the bell rim. Activation wave speeds near the material wave speed yielded successful turns, with a 76-fold difference in turning rate between the best and worst performers. Hyperextension of the margin occurred only at activation wave speeds near the material wave speed, suggesting resonance. This hyperextension resulted in a 34-fold asymmetry in the circulation of the vortex ring between the inside and outside of the turn. Experimental recording of the activation speed confirmed that jellyfish actuate within this range, and flow visualization using particle image velocimetry validated the corresponding fluid dynamics of the numerical model. This suggests that neuromechanical wave resonance plays an important role in the robustness of an organism's locomotory system and presents an undiscovered constraint on the evolution of flexible organisms. Understanding these dynamics is essential for developing actuators in soft body robotics and bioengineered pumps.

Fluid-Structure Interaction Analyses of Biological Systems Using Smoothed-Particle Hydrodynamics.

Simple SummaryComputational simulations of biological systems are an intrinsic element of engineering in medicine, allowing physicians the ability to visualize the pathophysiology behind a disease. Many biomedical applications require fluid–structure interaction analyses. This paper provides a review of fluid–structure interaction methods using smoothed-particle hydrodynamics to analyze the dynamics of biological processes.Due to the inherent complexity of biological applications that more often than not include fluids and structures interacting together, the development of computational fluid–structure interaction models is necessary to achieve a quantitative understanding of their structure and function in both health and disease. The functions of biological structures usually include their interactions with the surrounding fluids. Hence, we contend that the use of fluid–structure interaction models in computational studies of biological systems is practical, if not necessary. The ultimate goal is to develop computational models to predict human biological processes. These models are meant to guide us through the multitude of possible diseases affecting our organs and lead to more effective methods for disease diagnosis, risk stratification, and therapy. This review paper summarizes computational models that use smoothed-particle hydrodynamics to simulate the fluid–structure interactions in complex biological systems.

Bioprosthetic aortic valve diameter and thickness are directly related to leaflet fluttering: Results from a combined experimental and computational modeling study

ObjectiveBioprosthetic heart valves (BHVs) are commonly used in surgical and percutaneous valve replacement. The durability of percutaneous valve replacement is unknown, but surgical valves have been shown to require reintervention after 10 to 15 years. Further, smaller-diameter surgical BHVs generally experience higher rates of prosthesis–patient mismatch, which leads to higher rates of failure. Bioprosthetic aortic valves can flutter in systole, and fluttering is associated with fatigue and failure in flexible structures. The determinants of flutter in BHVs have not been well characterized, despite their potential to influence durability. MethodsWe use an experimental pulse duplicator and a computational fluid-structure interaction model of this system to study the role of device geometry on BHV dynamics. The experimental system mimics physiological conditions, and the computational model enables precise control of leaflet biomechanics and flow conditions to isolate the effects of variations in BHV geometry on leaflet dynamics. ResultsBoth experimental and computational models demonstrate that smaller-diameter BHVs yield markedly higher leaflet fluttering frequencies across a range of conditions. The computational model also predicts that fluttering frequency is directly related to leaflet thickness. A scaling model is introduced that rationalizes these findings. ConclusionsWe systematically characterize the influence of BHV diameter and leaflet thickness on fluttering dynamics. Although this study does not determine how flutter influences device durability, increased flutter in smaller-diameter BHVs may explain how prosthesis–patient mismatch could induce BHV leaflet fatigue and failure. Ultimately, understanding the effects of device geometry on leaflet kinematics may lead to more durable valve replacements.

Mechanism of Coup and Contrecoup Injuries Induced by a Knock-Out Punch

Primary Objective: The interaction of cerebrospinal fluid with the brain parenchyma in an impact scenario is studied. Research Design: A computational fluid-structure interaction model is used to simulate the interaction of cerebrospinal fluid with a comprehensive brain model. Methods and Procedures: The method of smoothed particle hydrodynamics is used to simulate the fluid flow, induced by the impact, simultaneously with finite element analysis to solve the large deformations in the brain model. Main Outcomes and Results: Mechanism of injury resulting in concussion is demonstrated. The locations with the highest stress values on the brain parenchyma are shown. Conclusions: Our simulations found that the damage to the brain resulting from the contrecoup injury is more severe than that resulting from the coup injury. Additionally, we show that the contrecoup injury does not always appear on the side opposite from where impact occurs.

Biomechanics of the soft-palate in sleep apnea patients with polycystic ovarian syndrome

Highly compliant tissue supporting the pharynx and low muscle tone enhance the possibility of upper airway occlusion in children with obstructive sleep apnea (OSA). The present study describes subject-specific computational modeling of flow-induced velopharyngeal narrowing in a female child with polycystic ovarian syndrome (PCOS) with OSA and a non-OSA control. Anatomically accurate three-dimensional geometries of the upper airway and soft-palate were reconstructed for both subjects using magnetic resonance (MR) images. A fluid-structure interaction (FSI) shape registration analysis was performed using subject-specific values of flow rate to iteratively compute the biomechanical properties of the soft-palate. The optimized shear modulus for the control was 38 percent higher than the corresponding value for the OSA patient. The proposed computational FSI model was then employed for planning surgical treatment for the apneic subject. A virtual surgery comprising of a combined adenoidectomy, palatoplasty and genioglossus advancement was performed to estimate the resulting post-operative patterns of airflow and tissue displacement. Maximum flow velocity and velopharyngeal resistance decreased by 80 percent and 66 percent respectively following surgery. Post-operative flow-induced forces on the anterior and posterior faces of the soft-palate were equilibrated and the resulting magnitude of tissue displacement was 63 percent lower compared to the pre-operative case. Results from this pilot study indicate that FSI computational modeling can be employed to characterize the mechanical properties of pharyngeal tissue and evaluate the effectiveness of various upper airway surgeries prior to their application.

Collision of the glass shards with the eye: A computational fluid-structure interaction model

The main stream of blunt trauma injuries has been reported to be related to the automobile crashes, sporting activities, and military operations. Glass shards, which can be induced due to car accident, earthquake, gunshot, etc., might collide with the eye and trigger substantial scarring and, consequently, permanently affect the vision. The complications as a result of the collision with the eye and its following injuries on each component of the eye are difficult to be diagnosed. The objective of this study was to employ a Three-Dimensional (3D) computational Fluid-Structure Interaction (FSI) model of the human eye to assess the results of the glass shards collision with the eye. To do this, a rigid steel-based object hit a Smoothed-Particle Hydrodynamics (SPH) glass wall at the velocities of 100, 150, and 200 m/s and, subsequently, the resultant glass shards moved toward the eye. The amount of injury, then, quantified in terms of the stresses and strains. The results revealed the highest amount of stress in the cornea while the lowest one was observed in the vitreous body. It was also found that increasing the speed of the glass shards amplifies the amount of the stress in the components which are located in the central anterior zone of the eye, such as the cornea, aqueous body, and iris. However, regarding those components located in the peripheral/posterior side of the eye, especially the optic nerve, by increasing the amount of velocity a reduction in the stresses was observed and the optic nerve is hardly damaged. These findings have associations not only for understanding the amount of stresses/strains in the eye components at three different velocities, but also for providing preliminary information for the ophthalmologists to have a better diagnosis after glass shards (small objects impact) injuries to the eye.

Computing the influences of different Intraocular Pressures on the human eye components using computational fluid-structure interaction model.

Intraocular Pressure (IOP) is defined as the pressure of aqueous in the eye. It has been reported that the normal range of IOP should be within the 10-20 mmHg with an average of 15.50 mmHg among the ophthalmologists. Keratoconus is an anti-inflammatory eye disorder that debilitated cornea unable to reserve the normal structure contrary to the IOP in the eye. Consequently, the cornea would bulge outward and invoke a conical shape following by distorted vision. In addition, it is known that any alterations in the structure and composition of the lens and cornea would exceed a change of the eye ball as well as the mechanical and optical properties of the eye. Understanding the precise alteration of the eye components' stresses and deformations due to different IOPs could help elucidate etiology and pathogenesis to develop treatments not only for keratoconus but also for other diseases of the eye. In this study, at three different IOPs, including 10, 20, and 30 mmHg the stresses and deformations of the human eye components were quantified using a Three-Dimensional (3D) computational Fluid-Structure Interaction (FSI) model of the human eye. The results revealed the highest amount of von Mises stress in the bulged region of the cornea with 245 kPa at the IOP of 30 mmHg. The lens was also showed the von Mises stress of 19.38 kPa at the IOPs of 30 mmHg. In addition, by increasing the IOP from 10 to 30 mmHg, the radius of curvature in the cornea and lens was increased accordingly. In contrast, the sclera indicated its highest stress at the IOP of 10 mmHg due to over pressure phenomenon. The variation of IOP illustrated a little influence in the amount of stress as well as the resultant displacement of the optic nerve. These results can be used for understanding the amount of stresses and deformations in the human eye components due to different IOPs as well as for clarifying significant role of IOP on the radius of curvature of the cornea and the lens.

Effect of Outflow Graft Size on Flow in the Aortic Arch and Cerebral Blood Flow in Continuous Flow Pumps: Possible Relevance to Strokes.

One of the most devastating complications of continuous flow left ventricular devices (CFLVADS) is stroke, with a higher incidence in HeartWare Ventricular Assist Device (HVAD) as compared with HEARTMATE II. The reason for the observed difference in stroke rates is unclear. Because outflow graft diameters are different, we hypothesized that this could contribute to the difference in stroke rates. A computational fluid-structure interaction model was created from the computed tomography (CT) scan of a patient. Pressures were used as the boundary condition and the flow through the cerebral vessels was derived as outputs. Flow into the innominate artery was very sensitive to the anastomosis angle for a 10 mm as compared with a 14 mm graft, with the net innominate flow severely compromised with a 10 mm graft at 45° angle. Aortic insufficiency seems to affect cerebral blood flow nonlinearly with an 80% decrease at certain angles of outflow graft anastomosis. Arterial return in to the arch through a narrow graft has important jet effects and results in significant flow perturbations in the aortic arch and cerebral vessels and stasis. A 10 mm graft is more sensitive to angle of insertion than a 14 mm graft. Under some conditions, serious hypoperfusion of the innominate artery is possible. Aortic incompetence results in significant decrease of cerebral blood flow. No stasis was found in the pulsatile flow compared with LVAD flow.

A computational fluid-structure interaction model to predict the biomechanical properties of the artificial functionally graded aorta.

In the present study, three layers of the ascending aorta in respect to the time and space at various blood pressures have been simulated. Two well-known commercial finite element (FE) software have used to be able to provide a range of reliable numerical results while independent on the software type. The radial displacement compared with the time as well as the peripheral stress and von Mises stress of the aorta have calculated. The aorta model was validated using the differential quadrature method (DQM) solution and, then, in order to design functionally graded materials (FGMs) with different heterogeneous indexes for the artificial vessel, two different materials have been employed. Fluid–structure interaction (FSI) simulation has been carried out on the FGM and a natural vessel of the human body. The heterogeneous index defines the variation of the length in a function. The blood pressure was considered to be a function of both the time and location. Finally, the response characteristics of functionally graded biomaterials (FGBMs) models with different values of heterogeneous material parameters were determined and compared with the behaviour of a natural vessel. The results showed a very good agreement between the numerical findings of the FGM materials and that of the natural vessel. The findings of the present study may have implications not only to understand the performance of different FGMs in bearing the stress and deformation in comparison with the natural human vessels, but also to provide information for the biomaterials expert to be able to select a suitable material as an implant for the aorta.

Fluid-Structure Interaction Analysis of Parachute Finite Mass Inflation

Parachute inflation is coupled with sophisticated fluid-structure interaction (FSI) and flight mechanic behaviors in a finite mass situation. During opening, the canopy often experiences the largest deformation and loading. To predict the opening phase of a parachute, a computational FSI model for the inflation of a parachute, with slots on its canopy fabric, is developed using the arbitrary Lagrangian-Euler coupling penalty method. In a finite mass situation, the fluid around the parachute typically has an unsteady flow; therefore, a more complex opening phase and FSI dynamics of a parachute are investigated. Navier-Stokes (N-S) equations for uncompressible flow are solved using an explicit central difference method. The three-dimensional visualization of canopy deformation as well as the evolution of dropping velocity and overload is obtained and compared with the experimental results. This technique could be further applied in the airdrop test of a parachute for true prediction of the inflation characteristics.

Quantifying the injury of the human eye components due to tennis ball impact using a computational fluid–structure interaction model

Although it might be believed that the eye only comprised a very small area of the face, its injury due to the ball impacts in different sports seems to be severe enough to entice many researchers to determine the level of injury and then attempt to minimize it. Sports-related eye injuries, especially tennis, pose a substantial and preventable problem to the eye due to the high speed of the tennis ball (69 m/s). This is why many ophthalmologists provide a wide range of information for their patients regarding the risks of eye injuries in tennis to prevent the injury to well over 100,000 eyes each year. However, so far although there are some general information regarding the injury to the human eye components due to the tennis ball impact, the details of the stresses and deformations have not been well determined. Therefore, the goal of this study was to determine the stresses and deformations of the eye components, including cornea, aqueous body, iris, ciliary body, lens, vitreous body, retina, sclera, optic nerve, extra and intraconal fats, and muscles, attributable to the tennis ball impact via a Lagrangian–Eulerian computational coupling model. Magnetic resonance imaging was employed to establish a finite element model of the human eye according to a normal human eye. The numerical results revealed the highest amount of stress in the iris (19.2 MPa), whereas the lowest one was observed in the vitreous body (1.77 Pa). The cornea also experienced the stress of 8.27 MPa which might be high enough to invoke rupture in this delicate material. In addition, the results exhibited a decreasing and increasing of the radius of curvature for the cornea and lens, respectively. Finally, the collision of the tennis ball to the eye triggered the resultant displacement of 0.045 µm in the optic nerve which may imply a non-significant injury to that. The findings of this study may have implications not only for understating the values of stresses and deformations in the human eye components but also for helping the ophthalmologists to have a more precise diagnosis about the injury position in the eye due to the tennis ball impact.

A computational fluid-structure interaction model of the blood flow in the healthy and varicose saphenous vein.

Varicose vein has become enlarged and twisted and, consequently, has lost its mechanical strength. As a result of the varicose saphenous vein (SV) mechanical alterations, the hemodynamic parameters of the blood flow, such as blood velocity as well as vein wall stress and strain, would change accordingly. However, little is known about stress and strain and there consequences under experimental conditions on blood flow and velocity within normal and varicose veins. In this study, a three-dimensional (3D) computational fluid-structure interaction (FSI) model of a human healthy and varicose SVs was established to determine the hemodynamic characterization of the blood flow as a function of vein wall mechanical properties, i.e. elastic and hyperelastic. The mechanical properties of the human healthy and varicose SVs were experimentally measured and implemented into the computational model. The fully coupled fluid and structure models were solved using the explicit dynamics finite element code LS-DYNA. The results revealed that, regardless of healthy and varicose, the elastic walls reach to the ultimate strength of the vein wall, whereas the hyperelastic wall can tolerate more stress. The highest von Mises stress compared to the healthy ones was seen in the elastic and hyperelastic varicose SVs with 1.412 and 1.535 MPa, respectively. In addition, analysis of the resultant displacement in the vein wall indicated that the varicose SVs experienced a higher displacement compared to the healthy ones irrespective of elastic and hyperelastic material models. The highest blood velocity was also observed for the healthy hyperelastic SV wall. The findings of this study may have implications not only for determining the role of the vein wall mechanical properties in the hemodynamic alterations of the blood, but also for employing as a null information in balloon-angioplasty and bypass surgeries.

Plaque and arterial vulnerability investigation in a three-layer atherosclerotic human coronary artery using computational fluid-structure interaction method

Coronary artery disease is the common form of cardiovascular diseases and known to be the main reason of deaths in the world. Fluid-Structure Interaction (FSI) simulations can be employed to assess the interactions of artery/plaque and blood to provide a more precise anticipation for rupture of arterial tissue layers and plaque tissues inside an atherosclerotic artery. To date, the arterial tissue in computational FSI simulations has been considered as a one-layer structure. However, a single layer assumption might have deeply bounded the results and, consequently, more computational simulation is needed by considering the arterial tissue as a three-layer structure. In this study, a three-dimensional computational FSI model of an atherosclerotic artery with a three-layer structure and different plaque types was established to perform a more accurate arterial wall/plaque tissue vulnerability assessment. The hyperelastic material coefficients of arterial layers were calculated and implemented in the computational model. The fully coupled fluid and structure models were solved using the explicit dynamics finite element code LS-DYNA. The results revealed the significant role of plaque types in the normal and shear stresses induced within the arterial tissue layers. The highest von Mises and shear stresses were observed on the stiffest calcified plaque with 3.59 and 3.27 MPa, while the lowest von Mises and shear stresses were seen on the hypocellular plaque with 1.15 and 0.63 MPa, respectively. Regardless of plaque types, the media and adventitia layers were played protective roles by displaying less stress on their wall, whilst the intima layer was at a high risk of rupture. The findings of this study have implications not only for determining the most vulnerable arterial layer/plaque tissue inside an atherosclerotic coronary artery but also for balloon-angioplasty, stenting, and bypass surgeries.

A computational fluid-structure interaction model for plaque vulnerability assessment in atherosclerotic human coronary arteries

Coronary artery disease is responsible for a third of global deaths worldwide. Computational simulations of blood flow can be used to understand the interactions of artery/plaque and blood in coronary artery disease and to better predict the rupture of atherosclerotic plaques. So far, the mechanical properties of animals' coronary artery have been mostly used for hemodynamic simulation of atherosclerotic arteries. The mechanical properties of animals' coronary arteries are often not accurate enough and can be only used for an approximate estimation and comparative assessment of the cognate parameters in human. In this study, a three-dimensional (3D) computational fluid-structure interactions model with three different plaque types is presented to perform a more accurate plaque vulnerability assessment for human atherosclerotic plaques. The coronary arteries of twenty-two male individuals were removed during autopsy and subjected to uniaxial tensile loading. The hyperelastic material coefficients of coronary arteries were calculated and implemented to the computational model. The fully coupled fluid and structure models were solved using the explicit dynamics finite element code LS-DYNA. The normal and shear stresses induced within the plaques were significantly affected by different plaque types. The highest von Mises (153 KPa) and shear (57 KPa) stresses were observed for hypocellular plaques, while the lowest von Mises (70 KPa) and shear (39 KPa) stresses were observed on the stiffer calcified plaques. The results suggest that the risk of plaque rupture due to blood flow is lower for cellular and hypocellular plaques, while higher for calcified plaques with low fracture stresses.

Fluid flow in the osteocyte mechanical environment: a fluid–structure interaction approach

Osteocytes are believed to be the primary sensor of mechanical stimuli in bone, which orchestrate osteoblasts and osteoclasts to adapt bone structure and composition to meet physiological loading demands. Experimental studies to quantify the mechanical environment surrounding bone cells are challenging, and as such, computational and theoretical approaches have modelled either the solid or fluid environment of osteocytes to predict how these cells are stimulated in vivo. Osteocytes are an elastic cellular structure that deforms in response to the external fluid flow imposed by mechanical loading. This represents a most challenging multi-physics problem in which fluid and solid domains interact, and as such, no previous study has accounted for this complex behaviour. The objective of this study is to employ fluid-structure interaction (FSI) modelling to investigate the complex mechanical environment of osteocytes in vivo. Fluorescent staining of osteocytes was performed in order to visualise their native environment and develop geometrically accurate models of the osteocyte in vivo. By simulating loading levels representative of vigorous physiological activity ([Formula: see text] compression and 300 Pa pressure gradient), we predict average interstitial fluid velocities [Formula: see text] and average maximum shear stresses [Formula: see text] surrounding osteocytes in vivo. Interestingly, these values occur in the canaliculi around the osteocyte cell processes and are within the range of stimuli known to stimulate osteogenic responses by osteoblastic cells in vitro. Significantly our results suggest that the greatest mechanical stimulation of the osteocyte occurs in the cell processes, which, cell culture studies have indicated, is the most mechanosensitive area of the cell. These are the first computational FSI models to simulate the complex multi-physics mechanical environment of osteocyte in vivo and provide a deeper understanding of bone mechanobiology.

Validation of a 3D computational fluid–structure interaction model simulating flow through an elastic aperture

This work presents a validation of a fluid–structure interaction computational model simulating the flow conditions in an in vitro mock heart chamber modeling mitral valve regurgitation during the ejection phase during which the trans-valvular pressure drop and valve displacement are not as large. The mock heart chamber was developed to study the use of 2D and 3D color Doppler techniques in imaging the clinically relevant complex intra-cardiac flow events associated with mitral regurgitation. Computational models are expected to play an important role in supporting, refining, and reinforcing the emerging 3D echocardiographic applications. We have developed a 3D computational fluid–structure interaction algorithm based on a semi-implicit, monolithic method, combined with an arbitrary Lagrangian–Eulerian approach to capture the fluid domain motion. The mock regurgitant mitral valve corresponding to an elastic plate with a geometric orifice, was modeled using 3D elasticity, while the blood flow was modeled using the 3D Navier–Stokes equations for an incompressible, viscous fluid. The two are coupled via the kinematic and dynamic conditions describing the two-way coupling. The pressure, the flow rate, and orifice plate displacement were measured and compared with numerical simulation results. In-line flow meter was used to measure the flow, pressure transducers were used to measure the pressure, and a Doppler method developed by one of the authors was used to measure the axial displacement of the orifice plate. The maximum recorded difference between experiment and numerical simulation for the flow rate was 4%, the pressure 3.6%, and for the orifice displacement 15%, showing excellent agreement between the two.