Flow fields in rotary blood pumps (RBPs) have a significant influence on hemocompatibility. Because flow characteristics vary with flow rate, different operating conditions play a role. Furthermore, turbulence is crucial in the evaluation of blood damage potential, but the level of turbulence in implantable RBPs is still unknown. In this study, we addressed both research aspects and for the first time measured turbulent flow fields in the HeartMate 3 (HM3) at different operating flows. The averaged, three-dimensional velocity field including fluctuating velocity components in a HM3 with a transparent lower housing was measured using three-dimensional particle tracking velocimetry (3D-PTV). In vitro results were compared with computational fluid dynamic (CFD) simulations for two flow cases, representing the lower and upper physiologic flow range (2.7 and 5.7 L/min), using two different turbulence models that account for fluctuating velocity fields: the k-ω shear stress transport and the Reynolds stress model (RSM). The measurements revealed higher mean and turbulent kinetic energies (TKEs) for the low-flow condition especially within the gap beneath the impeller. Computed mean fields agree well with 3D-PTV for both models, but the RSM predicts the TKE levels better than the k-ω model. Computational fluid dynamic results further show wall shear stresses higher than 150 Pa, a commonly used damage threshold, in the bottom gap for the lower flow condition. In conclusion, the low-flow condition was found to be more prone to blood damage. Furthermore, CFD predictions for turbulence must be carefully experimentally validated.
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Sci Rep
January 2025
Department of Mechanical Engineering, College of Engineering and Computer Sciences, Jazan University, P.O Box 45124, Jazan, Saudi Arabia.
Fluid flow across a Riga Plate is a specialized phenomenon studied in boundary layer flow and magnetohydrodynamic (MHD) applications. The Riga Plate is a magnetized surface used to manipulate boundary layer characteristics and control fluid flow properties. Understanding the behavior of fluid flow over a Riga Plate is critical in many applications, including aerodynamics, industrial, and heat transfer operations.
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January 2025
College of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, 100083, China.
Uneven of filling aggregate gradation may cause transportation problems such as pipe blockage due to segregation and stratification of filling slurry. To study the influence of aggregate gradation on the conveying performance of filler slurry, aggregate gradation experiments were carried out, rheological tests on slurries with coal gangue/aeolian sand ratios (6:4, 5:5 and 4:6) showed that appropriately increasing the proportion of aeolian sand can improve particle gradation. Computational fluid dynamics (CFD) scheme was used to simulate the pipeline transportation characteristics of the slurry under the conditions of three sets each of coal gangue/aeolian sand ratios, slurry concentrations (72%,74% and 76%), and inlet velocities (1.
View Article and Find Full Text PDFCardiovasc Eng Technol
January 2025
Transonic Systems Inc., 34 Dutch Mill Road, Ithaca, New York, 14850, USA.
Purpose: Over time, transit time flow measurement (TTFM) has proven itself as a simple and effective tool for intra-operative evaluation of coronary artery bypass grafts (CABGs). However, metrics used to screen for possible technical error show considerable spread, preventing the definition of sharp cut-off values to distinguish between patent, questionable, and failed grafts. The simulation study presented in this paper aims to quantify this uncertainty for commonly used patency metrics, and to identify the most important physiological parameters influencing it.
View Article and Find Full Text PDFBioinspir Biomim
January 2025
Chongqing Jiaotong University, No. 66, Xuefu Avenue, Nanan District, Chongqing City, Chongqing, Chongqing, 400074, CHINA.
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fluid dynamics (CFD) has emerged and been applied to simulate the autonomous behavior of higher organisms like fish. However, the scale of this cross-disciplinary method is directly affected by the efficiency of the DRL model.
View Article and Find Full Text PDFSci Adv
January 2025
Yale Cardiovascular Research Center, Yale School of Medicine, New Haven, CT 06511, USA.
Fluid shear stress (FSS) from blood flow sensed by vascular endothelial cells (ECs) determines vessel behavior, but regulatory mechanisms are only partially understood. We used cell state transition assessment and regulation (cSTAR), a powerful computational method, to elucidate EC transcriptomic states under low shear stress (LSS), physiological shear stress (PSS), high shear stress (HSS), and oscillatory shear stress (OSS) that induce vessel inward remodeling, stabilization, outward remodeling, or disease susceptibility, respectively. Combined with a publicly available database on EC transcriptomic responses to drug treatments, this approach inferred a regulatory network controlling EC states and made several notable predictions.
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