Practical implications of the erroneous treatment of exposure time in the Eulerian hemolysis power law model.

BACKGROUND: Eulerian and Lagrangian power-law formulations are both widely used for computational fluid dynamics (CFD) to predict flow-induced hemolysis in blood-contacting medical devices. Both are based on the same empirical power-law correlation between hemolysis and the shear stress and exposure time. In the Lagrangian approach, blood damage is predicted by tracking both the stress and exposure time along a finite number of pathlines in the domain. In the Eulerian approach, a scalar transport equation is solved for a time-linearized damage index within the entire domain. Previous analytical work has demonstrated that there is a fundamental problem with the treatment of exposure time in the Eulerian model formulation such that the only condition under which the model correctly represents the true exposure time is in a flow field with no streamwise velocity variation. However, the practical implications of this limitation have yet to be thoroughly investigated. METHODS: In this study, we demonstrate the inaccuracy of Eulerian hemolysis power-law model predictions due to the erroneous treatment of exposure time by systematically considering four benchmark test cases with increasing degrees of flow acceleration: Poiseuille flow through a straight tube, inclined Couette flow, and flow through a converging tube with two different convergence ratios. RESULTS: Compared with Lagrangian predictions, we show that, as flow acceleration becomes more pronounced, the resultant inaccuracy in the Eulerian predictions increases. For the inclined Couette flow case, there is a small degree of flow acceleration that yields a discrepancy in the range of 10% between Lagrangian and Eulerian predictions. For flows with a larger degree of acceleration, as occurs in the converging tube flow cases, the discrepancy is considerably larger (up to 257%). CONCLUSION: The inaccuracy of hemolysis predictions due to the erroneous treatment of exposure time in the Eulerian power-law model can be significant when there is streamwise velocity variation in the flow field. These results may partially explain the extremely large variability in CFD hemolysis predictions reported in the literature between Lagrangian and Eulerian models.

Nasal airflow in the pygmy slow loris (Nycticebus pygmaeus) based on a combined histological, computed tomographic and computational fluid dynamics methodology.

'Macrosmatic' mammals have dedicated olfactory regions within their nasal cavity and segregated airstreams for olfaction and respiratory air-conditioning. Here, we examined the 3D distribution of olfactory surface area (SA) and nasal airflow patterns in the pygmy slow loris (Nycticebus pygmaeus), a primate with primitive nasal cavities, except for enlarged eyes that converge upon the posterodorsal nasal region. Using the head of an adult loris cadaver, we co-registered micro-computed tomography (CT) slices and histology sections to create a 3D reconstruction of the olfactory mucosa distribution. Histological sections were used to measure olfactory surface area and to annotate CT reconstructions. The loris has a complex olfactory recess (∼19% of total nasal SA) with multiple olfactory turbinals. However, the first ethmoturbinal has a rostral projection that extends far anterior to the olfactory recess, lined by ∼90% non-olfactory epithelium. Only one (of three) frontoturbinals bears olfactory mucosa. Computational fluid dynamics simulations of nasal airflow and odorant deposition revealed that there is some segregation of respiratory and olfactory flow in the loris nose, but that it is not as distinct as in well-studied 'macrosmats' (e.g. the dog). In the loris, airflow is segregated medially and laterally to vertically elongated, plate-like first ethmoturbinals. Thus, lorises may be said to have certain macrosmatic anatomical characteristics (e.g. olfactory recess), but not segregated nasal airflow patterns that are optimized for olfaction, as in canids. These results imply that a binary 'microsmatic/macrosmatic' dichotomy does not exist. Rather, mammals appear to exhibit complex trends with respect to specialization of the turbinals and recesses.

Tests of the sorption and olfactory "fovea" hypotheses in the mouse.

The spatial distribution of receptors within sensory epithelia (e.g., retina and skin) is often markedly nonuniform to gain efficiency in information capture and neural processing. By contrast, odors, unlike visual and tactile stimuli, have no obvious spatial dimension. What need then could there be for either nearest-neighbor relationships or nonuniform distributions of receptor cells in the olfactory epithelium (OE)? Adrian (Adrian ED. J Physiol 100: 459-473, 1942; Adrian ED. Br Med Bull 6: 330-332, 1950) provided the only widely debated answer to this question when he posited that the physical properties of odors, such as volatility and water solubility, determine a spatial pattern of stimulation across the OE that could aid odor discrimination. Unfortunately, despite its longevity, few critical tests of the "sorption hypothesis" exist. Here we test the predictions of this hypothesis by mapping mouse OE responses using the electroolfactogram (EOG) and comparing these response "maps" to computational fluid dynamics (CFD) simulations of airflow and odorant sorption patterns in the nasal cavity. CFD simulations were performed for airflow rates corresponding to quiet breathing and sniffing. Consistent with predictions of the sorption hypothesis, water-soluble odorants tended to evoke larger EOG responses in the central portion of the OE than the peripheral portion. However, sorption simulation patterns along individual nasal turbinates for particular odorants did not correlate with their EOG response gradients. Indeed, the most consistent finding was a rostral-greater to caudal-lesser response gradient for all the odorants tested that is unexplained by sorption patterns. The viability of the sorption and related olfactory "fovea" hypotheses are discussed in light of these findings.NEW & NOTEWORTHY Two classical ideas concerning olfaction's receptor-surface two-dimensional organization-the sorption and olfactory fovea hypotheses-were found wanting in this study that afforded unprecedented comparisons between electrophysiological recordings in the mouse olfactory epithelium and computational fluid dynamic simulations of nasal airflow. Alternatively, it is proposed that the olfactory receptor layouts in macrosmatic mammals may be an evolutionary contingent state devoid of the functional significance found in other sensory epithelia like the cochlea and retina.

The Influence of Sniffing on Airflow and Odorant Deposition in the Canine Nasal Cavity.

Nasal airflow plays a critical role in olfaction by transporting odorant from the environment to the olfactory epithelium, where chemical detection occurs. Most studies of olfaction neglect the unsteadiness of sniffing and assume that nasal airflow and odorant transport are "quasi-steady," wherein reality most mammals "sniff." Here, we perform computational fluid dynamics simulations of airflow and odorant deposition in an anatomically accurate model of the coyote (Canis latrans) nasal cavity during quiet breathing, a notional quasi-steady sniff, and unsteady sniffing to: quantify the influence of unsteady sniffing, assess the validity of the quasi-steady assumption, and investigate the functional advantages of sniffing compared to breathing. Our results reveal that flow unsteadiness during sniffing does not appreciably influence qualitative (gross airflow and odorant deposition patterns) or quantitative (time-averaged olfactory flow rate and odorant uptake) measures of olfactory function. A quasi-steady approximation is, therefore, justified for simulating time-averaged olfactory function in the canine nose. Simulations of sniffing versus quiet breathing demonstrate that sniffing delivers about 2.5 times more air to the olfactory recess and results in 2.5-3 times more uptake of highly- and moderately-soluble odorants in the sensory region per unit time, suggesting one reason why dogs actively sniff. Simulations also reveal significantly different deposition patterns in the olfactory region during inspiration for different odorants, and that during expiration there is little retronasal odorant deposition in the sensory region. These results significantly improve our understanding of canine olfaction, and have several practical implications regarding computer simulation of olfactory function.

New insight into the evolution of the vertebrate respiratory system and the discovery of unidirectional airflow in iguana lungs.

The generally accepted framework for the evolution of a key feature of the avian respiratory system, unidirectional airflow, is that it is an adaptation for efficiency of gas exchange and expanded aerobic capacities, and therefore it has historically been viewed as important to the ability of birds to fly and to maintain an endothermic metabolism. This pattern of flow has been presumed to arise from specific features of the respiratory system, such as an enclosed intrapulmonary bronchus and parabronchi. Here we show unidirectional airflow in the green iguana, a lizard with a strikingly different natural history from that of birds and lacking these anatomical features. This discovery indicates a paradigm shift is needed. The selective drivers of the trait, its date of origin, and the fundamental aerodynamic mechanisms by which unidirectional flow arises must be reassessed to be congruent with the natural history of this lineage. Unidirectional flow may serve functions other than expanded aerobic capacity; it may have been present in the ancestral diapsid; and it can occur in structurally simple lungs.

The influence of nasal airflow on respiratory and olfactory epithelial distribution in felids.

The surface area of the maxilloturbinals and fronto-ethmoturbinals is commonly used as an osteological proxy for the respiratory and the olfactory epithelium, respectively. However, this assumption does not fully account for animals with short snouts in which these two turbinal structures significantly overlap, potentially placing fronto-ethmoturbinals in the path of respiratory airflow. In these species, it is possible that anterior fronto-ethmoturbinals are covered with non-sensory (respiratory) epithelium instead of olfactory epithelium. In this study, we analyzed the distribution of olfactory and non-sensory, respiratory epithelia on the turbinals of two domestic cats (Felis catus) and a bobcat (Lynx rufus). We also conducted a computational fluid dynamics simulation of nasal airflow in the bobcat to explore the relationship between epithelial distribution and airflow patterns. The results showed that a substantial amount of respiratory airflow passes over the anterior fronto-ethmoturbinals, and that contrary to what has been observed in caniform carnivorans, much of the anterior ethmoturbinals are covered by non-sensory epithelium. This confirms that in short-snouted felids, portions of the fronto-ethmoturbinals have been recruited for respiration, and that estimates of olfactory epithelial coverage based purely on fronto-ethmoturbinal surface area will be exaggerated. The correlation between the shape of the anterior fronto-ethmoturbinals and the direction of respiratory airflow suggests that in short-snouted species, CT data alone are useful in assessing airflow patterns and epithelium distribution on the turbinals.

The effects of naris occlusion on mouse nasal turbinate development.

Unilateral naris occlusion, a standard method for causing odor deprivation, also alters airflow on both sides of the nasal cavity. We reasoned that manipulating airflow by occlusion could affect nasal turbinate development given the ubiquitous role of environmental stimuli in ontogenesis. To test this hypothesis, newborn mice received unilateral occlusion or sham surgery and were allowed to reach adulthood. Morphological measurements were then made of paraffin sections of the whole nasal cavity. Occlusion significantly affected the size, shape and position of turbinates. In particular, the nasoturbinate, the focus of our quantitative analysis, had a more delicate appearance on the occluded side relative to the open side. Occlusion also caused an increase in the width of the dorsal meatus within the non-occluded and occluded nasal fossae, compared with controls, and the position of most turbinates was altered. These results suggest that a mechanical stimulus from respiratory airflow is necessary for the normal morphological development of turbinates. To explore this idea, we estimated the mechanical forces on turbinates caused by airflow during normal respiration that would be absent as a result of occlusion. Magnetic resonance imaging scans were used to construct a three-dimensional model of the mouse nasal cavity that provided the input for a computational fluid dynamics simulation of nasal airflow. The simulation revealed maximum shear stress values for the walls of turbinates in the 1 Pa range, a magnitude that causes remodeling in other biological tissues. These observations raise the intriguing possibility that nasal turbinates develop partly under the control of respiratory mechanical forces.

A computational method for predicting inferior vena cava filter performance on a patient-specific basis.

A computational methodology for simulating virtual inferior vena cava (IVC) filter placement and IVC hemodynamics was developed and demonstrated in two patient-specific IVC geometries: a left-sided IVC and an IVC with a retroaortic left renal vein. An inverse analysis was performed to obtain the approximate in vivo stress state for each patient vein using nonlinear finite element analysis (FEA). Contact modeling was then used to simulate IVC filter placement. Contact area, contact normal force, and maximum vein displacements were higher in the retroaortic IVC than in the left-sided IVC (144 mm(2), 0.47 N, and 1.49 mm versus 68 mm(2), 0.22 N, and 1.01 mm, respectively). Hemodynamics were simulated using computational fluid dynamics (CFD), with four cases for each patient-specific vein: (1) IVC only, (2) IVC with a placed filter, (3) IVC with a placed filter and model embolus, all at resting flow conditions, and (4) IVC with a placed filter and model embolus at exercise flow conditions. Significant hemodynamic differences were observed between the two patient IVCs, with the development of a right-sided jet, larger flow recirculation regions, and lower maximum flow velocities in the left-sided IVC. These results support further investigation of IVC filter placement and hemodynamics on a patient-specific basis.

In vitro quantification of time dependent thrombus size using magnetic resonance imaging and computational simulations of thrombus surface shear stresses.

Thrombosis and thromboembolization remain large obstacles in the design of cardiovascular devices. In this study, the temporal behavior of thrombus size within a backward-facing step (BFS) model is investigated, as this geometry can mimic the flow separation which has been found to contribute to thrombosis in cardiac devices. Magnetic resonance imaging (MRI) is used to quantify thrombus size and collect topographic data of thrombi formed by circulating bovine blood through a BFS model for times ranging between 10 and 90 min at a constant upstream Reynolds number of 490. Thrombus height, length, exposed surface area, and volume are measured, and asymptotic behavior is observed for each as the blood circulation time is increased. Velocity patterns near, and wall shear stress (WSS) distributions on, the exposed thrombus surfaces are calculated using computational fluid dynamics (CFD). Both the mean and maximum WSS on the exposed thrombus surfaces are much more dependent on thrombus topography than thrombus size, and the best predictors for asymptotic thrombus length and volume are the reattachment length and volume of reversed flow, respectively, from the region of separated flow downstream of the BFS.

Examining the universality of the hemolysis power law model from simulations of the FDA nozzle using calibrated model coefficients.

Computational fluid dynamics (CFD) is widely used to predict mechanical hemolysis in medical devices. The most popular hemolysis model is the stress-based power law model that is based on an empirical correlation between hemoglobin release from red blood cells (RBCs) and the magnitude of flow-induced stress and exposure time. Empirical coefficients are traditionally calibrated using data from experiments in simplified Couette-type blood-shearing devices with uniform-shear laminar flow and well-defined exposure times. Use of such idealized coefficients in simulations of real medical devices with complex hemodynamics is thought to be a primary reason for the historical inaccuracy of absolute hemolysis predictions using the power law model. Craven et al. (Biomech Model Mechanobiol 18:1005-1030, 2019) recently developed a CFD-based Kriging surrogate modeling approach for calibrating empirical coefficients in real devices that could potentially be used to more accurately predict absolute hemolysis. In this study, we use the FDA benchmark nozzle to investigate whether utilizing such calibrated coefficients improves the predictive accuracy of the standard Eulerian power law model. We first demonstrate the credibility of our CFD flow simulations by comparing with particle image velocimetry measurements. We then perform hemolysis simulations and compare the results with in vitro experiments. Importantly, the simulations use coefficients calibrated for the flow of a suspension of bovine RBCs through a small capillary tube, which is relatively comparable to the flow of bovine blood through the FDA nozzle. The results show that the CFD predictions of relative hemolysis in the FDA nozzle are reasonably accurate. The absolute predictions are, however, highly inaccurate with modified index of hemolysis values from CFD in error by roughly three orders of magnitude compared with the experiments, despite using calibrated model coefficients from a relatively similar geometry. We rigorously examine the reasons for the inaccuracy that include differences in the flow conditions in the hemolytic regions of each device and the lack of universality of the hemolysis power law model that is entirely empirical. Thus, while the capability to predict relative hemolysis is valuable for product development, further improvements are needed before the power law model can be relied upon to accurately predict the absolute hemolytic potential of a medical device.

Modeling Flow in an In Vitro Anatomical Cerebrovascular Model with Experimental Validation.

Acute ischemic stroke (AIS) is a leading cause of mortality that occurs when an embolus becomes lodged in the cerebral vasculature and obstructs blood flow in the brain. The severity of AIS is determined by the location and how extensively emboli become lodged, which are dictated in large part by the cerebral flow and the dynamics of embolus migration which are difficult to measure in vivo in AIS patients. Computational fluid dynamics (CFD) can be used to predict the patient-specific hemodynamics and embolus migration and lodging in the cerebral vasculature to better understand the underlying mechanics of AIS. To be relied upon, however, the computational simulations must be verified and validated. In this study, a realistic in vitro experimental model and a corresponding computational model of the cerebral vasculature are established that can be used to investigate flow and embolus migration and lodging in the brain. First, the in vitro anatomical model is described, including how the flow distribution in the model is tuned to match physiological measurements from the literature. Measurements of pressure and flow rate for both normal and stroke conditions were acquired and corresponding CFD simulations were performed and compared with the experiments to validate the flow predictions. Overall, the CFD simulations were in relatively close agreement with the experiments, to within ±7% of the mean experimental data with many of the CFD predictions within the uncertainty of the experimental measurement. This work provides an in vitro benchmark data set for flow in a realistic cerebrovascular model and is a first step towards validating a computational model of AIS.

Modeling flow in an in vitro anatomical cerebrovascular model with experimental validation.

Acute ischemic stroke (AIS) is a leading cause of mortality that occurs when an embolus becomes lodged in the cerebral vasculature and obstructs blood flow in the brain. The severity of AIS is determined by the location and how extensively emboli become lodged, which are dictated in large part by the cerebral flow and the dynamics of embolus migration which are difficult to measure in vivo in AIS patients. Computational fluid dynamics (CFD) can be used to predict the patient-specific hemodynamics and embolus migration and lodging in the cerebral vasculature to better understand the underlying mechanics of AIS. To be relied upon, however, the computational simulations must be verified and validated. In this study, a realistic in vitro experimental model and a corresponding computational model of the cerebral vasculature are established that can be used to investigate flow and embolus migration and lodging in the brain. First, the in vitro anatomical model is described, including how the flow distribution in the model is tuned to match physiological measurements from the literature. Measurements of pressure and flow rate for both normal and stroke conditions were acquired and corresponding CFD simulations were performed and compared with the experiments to validate the flow predictions. Overall, the CFD simulations were in relatively close agreement with the experiments, to within ±7% of the mean experimental data with many of the CFD predictions within the uncertainty of the experimental measurement. This work provides an in vitro benchmark data set for flow in a realistic cerebrovascular model and is a first step towards validating a computational model of AIS.

Results of the Interlaboratory Computational Fluid Dynamics Study of the FDA Benchmark Blood Pump.

Computational fluid dynamics (CFD) is widely used to simulate blood-contacting medical devices. To be relied upon to inform high-risk decision making, however, model credibility should be demonstrated through validation. To provide robust data sets for validation, researchers at the FDA and collaborators developed two benchmark medical device flow models: a nozzle and a centrifugal blood pump. Experimental measurements of the flow fields and hemolysis were acquired using each model. Concurrently, separate open interlaboratory CFD studies were performed in which participants from around the world, who were blinded to the measurements, submitted CFD predictions of each benchmark model. In this study, we report the results of the interlaboratory CFD study of the FDA benchmark blood pump. We analyze the results of 24 CFD submissions using a wide range of different flow solvers, methods, and modeling parameters. To assess the accuracy of the CFD predictions, we compare the results with experimental measurements of three quantities of interest (pressure head, velocity field, and hemolysis) at different pump operating conditions. We also investigate the influence of different CFD methods and modeling choices used by the participants. Our analyses reveal that, while a number of CFD submissions accurately predicted the pump performance for individual cases, no single participant was able to accurately predict all quantities of interest across all conditions. Several participants accurately predicted the pressure head at all conditions and the velocity field in all but one or two cases. Only one of the eight participants who submitted hemolysis results accurately predicted absolute plasma free hemoglobin levels at a majority of the conditions, though most participants were successful at predicting relative hemolysis levels between conditions. Overall, this study highlights the need to validate CFD modeling of rotary blood pumps across the entire range of operating conditions and for all quantities of interest, as some operating conditions and regions (e.g., the pump diffuser) are more challenging to accurately predict than others. All quantities of interest should be validated because, as shown here, it is possible to accurately predict hemolysis despite having relatively inaccurate predictions of the flow field.

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction.

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. We also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

Mechanistic modeling of generic orally inhaled drug products: A workshop summary report.

In silico mechanistic modeling approaches have been designed by various stakeholders with the goal of supporting development and approval of generic orally inhaled drug products in the United States. This review summarizes the presentations and panel discussion that comprised a workshop session concentrated on the use of in silico models to predict various outcomes following orally inhaled drug product administration, including the status of such models and how model credibility may be effectively established.

"Mucosal maps" of the canine nasal cavity: Micro-computed tomography and histology.

Nasal turbinals, delicate and complex bones of the nasal cavity that support respiratory or olfactory mucosa (OM), are now easily studied using high resolution micro-computed tomography (µ-CT). Standard µ-CT currently lacks the capacity to identify OM or other mucosa types without additional radio-opaque staining techniques. However, even unstained mucosa is more radio-opaque than air, and thus mucosal thickness can be discerned. Here, we assess mucosal thickness of the nasal fossa using the cranium of a cadaveric adult dog that was µ-CT scanned with an isotropic resolution of 30 µm, and subsequently histologically sectioned and stained. After co-alignment of µ-CT slice planes to that of histology, mucosal thickness was estimated at four locations. Results based on either µ-CT or histology indicate olfactory mucosa is thicker on average compared with non-olfactory mucosa (non-OM). In addition, olfactory mucosa has a lesser degree of variability than the non-OM. Variability in the latter appears to relate mostly to the varying degree of vascularity of the lamina propria. Because of this, in structures with both specialized vascular respiratory mucosa and OM, such as the first ethmoturbinal (ET I), the range of thickness of OM and non-OM may overlap. Future work should assess the utility of diffusible iodine-based contrast enhanced CT techniques, which can differentiate epithelium from the lamina propria, to enhance our ability to differentiate mucosa types on more rostral ethmoturbinals. This is especially critical for structures such as ET I, which have mixed functional roles in many mammals.

Full-field microscale strain measurements of a nitinol medical device using digital image correlation.

Computational modeling and simulation are commonly used during the development of cardiovascular implants to predict peak strains and strain amplitudes and to estimate the associated durability and fatigue life of these devices. However, simulation validation has historically relied on comparison with surrogate quantities like force and displacement due to barriers to direct strain measurement-most notably, the small spatial scale of these devices. We demonstrate the use of microscale two-dimensional digital image correlation (2D-DIC) to directly characterize full-field surface strains on a nitinol medical device coupon under emulated physiological and hyperphysiological loading. Experiments are performed using a digital optical microscope and a custom, temperature-controlled load frame. Following applicable recommendations from the International DIC Society, hardware and environmental heating studies, noise floor analyses, and in- and out-of-plane rigid body translation studies are first performed to characterize the microscale DIC setup. Uniaxial tension experiments are also performed using a polymeric test specimen to characterize the strain accuracy of the approach up to nominal stains of 5%. Sub-millimeter fields of view and sub-micron displacement accuracies (9nm mean error) are achieved, and systematic (mean) and random (standard deviation) errors in strain are each estimated to be approximately 1,000µÏµ. The system is then demonstrated by acquiring measurements at the root of a 300µm-wide nitinol medical device strut undergoing fixed-free cantilever bending motion. Lüders-like transformation bands are observed originating from the tensile side of the strut that spread toward the neutral axis at an angle of approximately 55°. Despite the inherent limitations of optical microscopy and 2D-DIC, simple and relatively economical setups like that demonstrated herein could provide a practical and accessible solution for characterizing cardiovascular implant micromechanics, validating computational model strain predictions, and guiding the development of next-generation material models for simulating superelastic nitinol.

An Immersed Interface Method for Discrete Surfaces.

Fluid-structure systems occur in a range of scientific and engineering applications. The immersed boundary (IB) method is a widely recognized and effective modeling paradigm for simulating fluid-structure interaction (FSI) in such systems, but a difficulty of the IB formulation of these problems is that the pressure and viscous stress are generally discontinuous at fluid-solid interfaces. The conventional IB method regularizes these discontinuities, which typically yields low-order accuracy at these interfaces. The immersed interface method (IIM) is an IB-like approach to FSI that sharply imposes stress jump conditions, enabling higher-order accuracy, but prior applications of the IIM have been largely restricted to numerical methods that rely on smooth representations of the interface geometry. This paper introduces an immersed interface formulation that uses only a C 0 representation of the immersed interface, such as those provided by standard nodal Lagrangian finite element methods. Verification examples for models with prescribed interface motion demonstrate that the method sharply resolves stress discontinuities along immersed boundaries while avoiding the need for analytic information about the interface geometry. Our results also demonstrate that only the lowest-order jump conditions for the pressure and velocity gradient are required to realize global second-order accuracy. Specifically, we demonstrate second-order global convergence rates along with nearly second-order local convergence in the Eulerian velocity field, and between first- and second-order global convergence rates along with approximately first-order local convergence for the Eulerian pressure field. We also demonstrate approximately second-order local convergence in the interfacial displacement and velocity along with first-order local convergence in the fluid traction along the interface. As a demonstration of the method's ability to tackle more complex geometries, the present approach is also used to simulate flow in a patient-averaged anatomical model of the inferior vena cava, which is the large vein that carries deoxygenated blood from the lower extremities back to the heart. Comparisons of the general hemodynamics and wall shear stress obtained by the present IIM and a body-fitted discretization approach show that the present method yields results that are in good agreement with those obtained by the body-fitted approach.

Fluid-Structure Interaction Models of Bioprosthetic Heart Valve Dynamics in an Experimental Pulse Duplicator.

Computer modeling and simulation is a powerful tool for assessing the performance of medical devices such as bioprosthetic heart valves (BHVs) that promises to accelerate device design and regulation. This study describes work to develop dynamic computer models of BHVs in the aortic test section of an experimental pulse-duplicator platform that is used in academia, industry, and regulatory agencies to assess BHV performance. These computational models are based on a hyperelastic finite element extension of the immersed boundary method for fluid-structure interaction (FSI). We focus on porcine tissue and bovine pericardial BHVs, which are commonly used in surgical valve replacement. We compare our numerical simulations to experimental data from two similar pulse duplicators, including a commercial ViVitro system and a custom platform related to the ViVitro pulse duplicator. Excellent agreement is demonstrated between the computational and experimental results for bulk flow rates, pressures, valve open areas, and the timing of valve opening and closure in conditions commonly used to assess BHV performance. In addition, reasonable agreement is demonstrated for quantitative measures of leaflet kinematics under these same conditions. This work represents a step towards the experimental validation of this FSI modeling platform for evaluating BHVs.

Development and verification of a high-fidelity computational fluid dynamics model of canine nasal airflow.

The canine nasal cavity contains a complex airway labyrinth, dedicated to respiratory air conditioning, filtering of inspired contaminants, and olfaction. The small and contorted anatomical structure of the nasal turbinates has, to date, precluded a proper study of nasal airflow in the dog. This study describes the development of a high-fidelity computational fluid dynamics (CFD) model of the canine nasal airway from a three-dimensional reconstruction of high-resolution magnetic resonance imaging scans of the canine anatomy. Unstructured hexahedral grids are generated, with large grid sizes ((10-100) x 10(6) computational cells) required to capture the details of the nasal airways. High-fidelity CFD solutions of the nasal airflow for steady inspiration and expiration are computed over a range of physiological airflow rates. A rigorous grid refinement study is performed, which also illustrates a methodology for verification of CFD calculations on complex unstructured grids in tortuous airways. In general, the qualitative characteristics of the computed solutions for the different grid resolutions are fairly well preserved. However, quantitative results such as the overall pressure drop and even the regional distribution of airflow in the nasal cavity are moderately grid dependent. These quantities tend to converge monotonically with grid refinement. Lastly, transient computations of canine sniffing were carried out as part of a time-step study, demonstrating that high temporal accuracy is achievable using small time steps consisting of 160 steps per sniff period. Here we demonstrate that acceptable numerical accuracy (between approximately 1% and 15%) is achievable with practical levels of grid resolution (approximately 100 x 10(6) computational cells). Given the popularity of CFD as a tool for studying flow in the upper airways of humans and animals, based on this work we recommend the necessity of a grid dependence study and quantification of numerical error when presenting CFD results in complicated airways.