In silico analyses of blood flow and oxygen transport in human micro-veins and valves

BACKGROUND: Almost 95% of the venous valves are micron scale found in veins smaller than 300μm diameter. The fluid dynamics of blood flow and transport through these micro venous valves and their contribution to thrombosis is not yet well understood or characterized due to difficulty in making direct measurements in murine models. OBJECTIVE: The unique flow patterns that may arise in physiological and pathological non-actuating micro venous valves are predicted. METHODS: Computational fluid and transport simulations are used to model blood flow and oxygen gradients in a microfluidic vein. RESULTS: The model successfully recreates the typical non-Newtonian vortical flow within the valve cusps seen in preclinical experimental models and in clinic. The analysis further reveals variation in the vortex strengths due to temporal changes in blood flow. The cusp oxygen is typically low from the main lumen, and it is regulated by systemic venous flow. CONCLUSIONS: The analysis leads to a clinically-relevant hypothesis that micro venous valves may not create a hypoxic environment needed for endothelial inflammation, which is one of the main causes of thrombosis. However, incompetent micro venous valves are still locations for complex fluid dynamics of blood leading to low shear regions that may contribute to thrombosis through other pathways.

Numerical Study of Unsteady Cavitating Flow in an Inducer with Omega Vortex Identification

To accurately capture the behaviors of cavitation and reveal the unsteady cavitating flow mechanism, a condensate pump inducer is numerically analyzed in a separate numerical experiment with LES at critical cavitation number sind,c under the design point. Based on the new Omega vortex identification method, the correction between the flow structures and cavities is clearly illustrated. Besides, the pressure fluctuations around the inducer are analyzed. Special emphasis is put on the analysis of the interactions between the cavities, turbulent fluctuations, and vortical flow structures. The Omega vortex identification method could give an overall picture of the whole cavitating flow structures to present a clear correlation between the vortices and cavities. The results show that the shear cavitation dominant the cavitation characteristics under the design point. The pure rigid rotation region mainly concentrates at the edge of the cavities while the other sheet-like cavities near the casing walls are characterized by strong turbulence fluctuations. Besides, based on the analysis of the correlation between the cavities and flow structures, the rotating cavitation under the design point may mainly attribute to the interaction between the tip leakage vortex cavitation and the next blade.

Identification of Sharp Edge Non-Slender Delta Wing Aerodynamic Coefficient Using Neural Network

Delta wing formed a vortical flow on its surface which produced higher lift compared to conventional wing. The vortical flow is complex and non-linear which requires more studies to understand its flow physics. However, conventional flow analysis (wind tunnel test and computational flow dynamic) comes with several significant drawbacks. In recent times, application of neural network as alternative to conventional flow analysis has increased. This study is about utilization of Multi-Layer Perceptron (MLP) neural network to predict the coefficient of pressure (Cp ) on a delta wing model. The physical model that was used is a sharp edge non-slender delta wing. The training data was taken from wind tunnel tests. 70% of data is used as training, 15% is used as validation and another 15% is used as test set. The wind tunnel test was done at angle of attack from 0°-18° with increment of 3°. The flow velocity was set at 25m/s which correspond to 800,000 Reynolds number. The inputs are angle of attack and location of pressure tube (y/cr) while the output is Cp . The MLP models were fitted with 3 different transfer functions (linear, sigmoid, and tanh) and trained with Lavenberg-Marquadt backpropagation algorithm. The results of the models were compared to determine the best performing model. Results show that large amount of data is required to produce accurate prediction model because the model suffer from condition called overfitting.

Learning efficient navigation in vortical flow fields

Efficient point-to-point navigation in the presence of a background flow field is important for robotic applications such as ocean surveying. In such applications, robots may only have knowledge of their immediate surroundings or be faced with time-varying currents, which limits the use of optimal control techniques. Here, we apply a recently introduced Reinforcement Learning algorithm to discover time-efficient navigation policies to steer a fixed-speed swimmer through unsteady two-dimensional flow fields. The algorithm entails inputting environmental cues into a deep neural network that determines the swimmer’s actions, and deploying Remember and Forget Experience Replay. We find that the resulting swimmers successfully exploit the background flow to reach the target, but that this success depends on the sensed environmental cue. Surprisingly, a velocity sensing approach significantly outperformed a bio-mimetic vorticity sensing approach, and achieved a near 100% success rate in reaching the target locations while approaching the time-efficiency of optimal navigation trajectories.

Predictions of Vortex Flow in a Diesel Multi-Hole Injector Using the RANS Modelling Approach

The occurrence of vortices in the sac volume of automotive multi-hole fuel injectors plays an important role in the development of vortex cavitation, which directly influences the flow structure and emerging sprays that, in turn, influence the engine performance and emissions. In this study, the RANS-based turbulence modelling approach was used to predict the internal flow in a vertical axis-symmetrical multi-hole (6) diesel fuel injector under non-cavitating conditions. The project aimed to predict the aforementioned vortical structures accurately at two different needle lifts in order to form a correct opinion about their occurrence. The accuracy of the simulations was assessed by comparing the predicted mean axial velocity and RMS velocity of LDV measurements, which showed good agreement. The flow field analysis predicted a complex, 3D, vortical flow structure with the presence of different types of vortices in the sac volume and the nozzle hole. Two main types of vortex were detected: the “hole-to-hole” connecting vortex, and double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. Different flow patterns in the rotational direction of the “hole-to-hole” vortices have been observed at the low needle lift (anticlockwise) and full needle lift (clockwise), due to their different flow passages in the sac, causing a much higher momentum inflow at the lower lift with its much narrower flow passage.

Examining the Kinematic Structures within which Lightning Flashes are Initiated using a Cloud-Resolving Model

Lightning is frequently initiated within the convective regions of thunderstorms, and so flash rates tend to follow trends in updraft speed and volume. It has been suggested that lightning production is linked to the turbulent flow generated by updrafts as turbulent eddies organize charged hydrometeors into complex charge structures. These complex charge structures consist of local regions of increased charge magnitudes between which flash initiating electric fields may be generated. How turbulent kinematics influences lightning production, however, remains unclear. In this study, lightning flashes produced in a multi-cell and two supercell storms simulated using The Collaborative Model for Multiscale Atmospheric Simulation (COMMAS) were examined to identify the kinematic flow structures within which they occurred. By relating the structures of updrafts to thermals, initiated lightning were expected to be located where the rate of strain and rotational flow are equal, or between updraft and eddy flow features. Results showed that the average lightning flash is initiated in kinematic flow structures dominated by vortical flow patterns, similar to those of thermals, and the structures’ kinematics are characterized by horizontal vorticity and vertical shearing. These kinematic features were common across all cases and demonstrated that where flash initiating electric fields are generated is along the periphery of updrafts where turbulent eddies are produced. Careful consideration of flow structures near initiated flashes is consistent with those of thermals rising through a storm.

Impact of Spatial and Temporal Stability of Aneurismal Flow Vortices on Vascular Endothelial Cells

Disturbed flow vortices are linked with altered vascular endothelial cell (EC) morphology and protein expression indicative of intracranial aneurysms (IA). Unfortunately, lesser known is the impact of vortex spatial and temporal stability on EC changes. In this study, the interplay between vortex stability and EC changes was investigated by a novel combination of parallel plate flow chamber (PPFC) design and computational analysis. ECs were exposed to laminar (7.5 dynes/cm wall shear stress) or low (<1 dynes/cm) stress vortical flow using PPFCs. Immunofluorescent imaging analyzed EC morphology, while ELISA tests quantified VE-cadherin (cell-cell adhesion), VCAM-1 (macrophage-EC adhesion), and cleaved caspase-3 (apoptotic signal) expression. PPFC flow was simulated, then vortex stability calculated via the temporally averaged degree of (volume) overlap (TA-DVO) of vortices within a given area. EC morphological changes were independent of vortex stability. Increased stability promoted VE-cadherin degradation (correlation coefficient r = -0.84) and 5-fold increased cleaved caspase-3 post 24-hrs in stable (TA-DVO 0.736+0.05) vs unstable (TA-DVO 0.606+0.2) vortices. ECs in stable vortices displayed a 4.5-fold increase in VCAM-1 than unstable counterparts after 12-hrs flow. Flow vortices of greater spatial and temporal stability impart greater degrees of EC changes related to inflammation, cell-cell adhesion, and apoptosis, than unstable vortices.

Assessment of intracardiac flow dynamics for the evaluation of patients with aortic stenosis

Background Assessment of intracardiac flows and turbulence has acquired rising significance in the past few years, due to the development and introduction of technologies for non-invasive cardiovascular imaging. Recent studies have shown that alterations in intracardiac fluid dynamics can be helpful to identify abnormalities in cardiac function. Purpose This study investigates the additional information provided by the quantitative assessment of intracardiac flow dynamics for the evaluation of patients with aortic stenosis (AS), by using an advanced echocardiography vortex-based approach. Methods Sixty-one patients with severe AS (33 females) and 38 healthy sex- and BSA-matched controls (CTRL) (15 females) were prospectively included and underwent echocardiographic assessment of intracardiac flow dynamics. Echocardiographic measurements were performed on apical three chamber views. The HyperDoppler software adapted to the echo-scanner without contrast injection was used to assess intracardiac vortex properties. The following parameters were obtained: vortex area (VA) (the ratio between the total vortex area and the left ventricular (LV) area); vortex length (VL) (the longitudinal length of the vortex relative to the total LV length; vortex depth (VD) (the distance of the vortex center from the LV base relative to the total LV long axis). Inter-rater variability was measured using intraclass correlation coefficients (ICCs) between two independent operators. Results Patients with severe AS (mean gradient: 47,5±13,9 mmHg; aortic valve area: 0.7±0.2 cm2; ejection fraction: 53±7%) had increased LV wall thickness (p&lt;0.001) and mass index (p&lt;0.001) compared with controls. Greater indexed left atrial volume (p&lt;0.001), E/e' (p&lt;0.001) and trans-tricuspid gradient (p&lt;0.001) were also observed in the AS group. The assessment of VA, VL and VD was feasible in the whole population. Their calculation was reliable, as ICCs were very good for VA (0.878, p=0.033), VL (0.960, p=0.004) and VD (0,905, p=0.021). Mean VA was significantly larger in patients with severe aortic stenosis compared with CTRL (p=0.033). VL and VD (p=0.026 and p&gt;0.001, respectively) were significantly higher in AS patients compared with CTRL. Among those who underwent TAVR, we observed a significant difference in the delta values of VA and VL pre-postTAVR in patients with and without significant paravalvular leak (p&lt;0.05). Conclusions The newly defined VA, VL and VD, quantitative indices of vortical flow, were significantly increased in the LV cavity of patients with severe AS compared to normal subjects. These indices, whose measurement was feasible and reliable, might provide complementary information to standard echocardiography, useful for the further diagnostic and prognostic characterization of the heterogeneous population of patients with severe AS. FUNDunding Acknowledgement Type of funding sources: None.