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This study is part of a FDA-sponsored project to evaluate the use and limitations of computational fluid dynamics (CFD) in assessing blood flow parameters related to medical device safety. In an interlaboratory study, fluid velocities and pressures were measured in a nozzle model to provide experimental validation for a companion round-robin CFD study. The simple benchmark nozzle model, which mimicked the flow fields in several medical devices, consisted of a gradual flow constriction, a narrow throat region, and a sudden expansion region where a fluid jet exited the center of the nozzle with recirculation zones near the model walls. Measurements of mean velocity and turbulent flow quantities were made in the benchmark device at three independent laboratories using particle image velocimetry (PIV). Flow measurements were performed over a range of nozzle throat Reynolds numbers (Re(throat)) from 500 to 6500, covering the laminar, transitional, and turbulent flow regimes. A standard operating procedure was developed for performing experiments under controlled temperature and flow conditions and for minimizing systematic errors during PIV image acquisition and processing. For laminar (Re(throat)=500) and turbulent flow conditions (Re(throat)≥3500), the velocities measured by the three laboratories were similar with an interlaboratory uncertainty of ∼10% at most of the locations. However, for the transitional flow case (Re(throat)=2000), the uncertainty in the size and the velocity of the jet at the nozzle exit increased to ∼60% and was very sensitive to the flow conditions. An error analysis showed that by minimizing the variability in the experimental parameters such as flow rate and fluid viscosity to less than 5% and by matching the inlet turbulence level between the laboratories, the uncertainties in the velocities of the transitional flow case could be reduced to ∼15%. The experimental procedure and flow results from this interlaboratory study (available at http://fdacfd.nci.nih.gov) will be useful in validating CFD simulations of the benchmark nozzle model and in performing PIV studies on other medical device models.

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Organic-aqueous liquid (phenol) extraction is one of many standard techniques to efficiently purify DNA directly from cells. Effective mixing of the two fluid phases increases the surface area over which biological component partitioning may occur. In this work, two phase mixing has been demonstrated in a three inlet microfluidic device geometry. Mixing between the two phases has been achieved by producing an electrohydrodynamic instability at the liquid-liquid interface between the two phases. The initial instability is modeled by considering the small signal linearized analysis for interfacial stresses from both fluid and electrical stress tensors for both inviscid and viscous models. These models predict the onset of instability and the stability criteria over a range of unstable wavenumbers of the mixing process. These models may be applied to relevant microscale geometries, where the unstable wavenumbers and fastest growth wavenumber are determined. At an applied electric field of $8.0·10 5 V/m an instability is experimentally observed by labeling the organic phase with a fluorescent dye and visualizing interfacial perturbations by microscopy. Increasing the electric field increases the instability growth rate and results in an increase of the level of mixing. These results show an increase in conductive fluid entrainment into the nonconducting fluid core measured as a percentage of area of entrainment into the fluorescently labeled organic phase. The entrainment area is seen to increase from 1.9 to 28.6% as the applied field is increased from 8.0·10 5 to 9.0·10 5 V/m. The mixing images are converted into a power spectrum using a fast Hartley transform and the band of unstable wavenumbers of the mixing process are determined. From these results, the theoretical field strengths required to produce these unstable wavenumbers are calculated using the theoretical model, determining the maximum field strength required to excite the largest measured unstable wavenumber. At lower field strengths tested, the theoretically predicted maximum electric field and fastest growth wavenumber compare favorably with the initially applied field and measured fastest growth wavenumber whereas at higher field strengths the theoretical field is much larger than the initially applied field. This is attributed to the larger level of mixing and the ability of the instability to grow beyond the linear range and the field increases as the mixing process occurs due to entrainment of highly conductive fluid decreasing the effective dielectric spacing so that the linearized models underpredict the instability growth rates and interfacial perturbations.

Computational fluid dynamics (CFD) is used to asses the hydrodynamic performance of a positive displacement left ventricular assist device. The computational model uses implicit large eddy simulation direct resolution of the chamber compression and modeled valve closure to reproduce the in vitro results. The computations are validated through comparisons with experimental particle image velocimetry (PIV) data. Qualitative comparisons of flow patterns, velocity fields, and wall-shear rates demonstrate a high level of agreement between the computations and experiments. Quantitatively, the PIV and CFD show similar probed velocity histories, closely matching jet velocities and comparable wall-strain rates. Overall, it has been shown that CFD can provide detailed flow field and wall-strain rate data, which is important in evaluating blood pump performance.

Computational fluid dynamics (CFD) is used to asses the hydrodynamic performance of a positive displacement left ventricular assist device. The computational model uses implicit large eddy simulation direct resolution of the chamber compression and modeled valve closure to reproduce the in vitro results. The computations are validated through comparisons with experimental particle image velocimetry (PIV) data. Qualitative comparisons of flow patterns, velocity fields, and wall-shear rates demonstrate a high level of agreement between the computations and experiments. Quantitatively, the PIV and CFD show similar probed velocity histories, closely matching jet velocities and comparable wall-strain rates. Overall, it has been shown that CFD can provide detailed flow field and wall-strain rate data, which is important in evaluating blood pump performance.

Cavitation is known to cause blood element damage and may introduce gaseous emboli into the cerebral circulation, increasing the patient's risk of stroke. Discovering methods to reduce the intensity of cavitation induced by mechanical heart valves (MHVs) has long been an area of interest. A novel approach for analyzing MHV cavitation is presented. A wavelet denoising method is explored because currently used analytical techniques fail to suitably unmask the cavitation signal from other valve closing sounds and noise detected with a hydrophone. Wavelet functions are used to denoise the cavitation signal during MHV closure and rebound. The wavelet technique is applied to the signal produced by closure of a 29-mm Medtronic-Hall MHV in degassed water with a gas content of 5 ppm. Valve closing dynamics are investigated under loading conditions of 500, 2500, and 4500 mm Hg/s. The results display a marked improvement in the quantity and quality of information that can be extracted from acoustic cavitation signals using the wavelet technique compared to conventional analytical techniques. Time and frequency data indicate the likelihood and characteristics of cavitation formation under specified conditions. Using this wavelet technique we observe an improved signal-to-noise ratio, an enhanced time-dependent aspect, and the potential to minimize valve closing sounds, which disguise individual cavitation events. The overall goal of this work is to eventually link specific valves with characteristic waveforms or distinct types of cavitation, thus promoting improved valve designs.