Simulation Of Blood Flow Research Articles

Modeling and simulation of blood flow under the influence of radioactive materials having slip with MHD and nonlinear mixed convection

Radioactive materials are widely in industry, nuclear plants and medical treatments. Scientists and workers in these fields are mostly exposed to such materials, and adverse effects on blood and temperature profiles are observed. In this regard, objective of the current study is to model and simulate blood based nanofluid with three very important radioactive materials, named as Uranium dioxide (UO2), Thorium dioxide (ThO2) and Radium (Rd). In this modeling blood based nanofluid is considered under the influence of magneto hydrodynamic effect, non-linear mixed convection and thermal radiation, Joule heating, along with velocity and temperature slip. A three-dimensional fluid model is considered in bounded domain to justify flow geometry in arteries. System of partial differential equations are converted to highly nonlinear coupled ordinary differential equations by using suitable transformations. The obtained system is solved numerically using Fehlberg Runge–Kutta algorithm. Validity and convergence of the obtained solutions are confirmed through residual errors, numerical uncertainties and comparison with experimental data. Moreover, effect of pertinent fluid parameters on the velocity (radial, axial, tangential) and temperature profiles of blood flow are analyzed graphically. Furthermore, Skin friction and Nusselt number are also analyzed graphically against volume fraction of involved radioactive materials for the case of UO2,ThO2 and Rd comparatively. Analysis reveals that increase in volume fraction of radioactive elements results in increased blood flow through walls in both radial and tangential directions. In case of slip at fluid solid-interface, the highest skin fraction is observed in case of Radium nanoparticles.

Temporal-spatial heterogeneity of hematocrit in microvascular networks

Hematocrit, defined as the volume percentage of red blood cells in blood, is an important indicator of human health status, which demonstrates the capability of blood to deliver oxygen. It has been studied over many decades using in vivo, in vitro, and in silico experiments, and recent studies have shown that its major feature in microvascular networks is the temporal-spatial heterogeneity. The present work is a numerical study of such temporal-spatial heterogeneity, based on direct simulations of cellular-scale blood flow in complex microvascular networks. The simulations take into account the cell deformation and aggregation and thus are able to capture both the three-dimensional dynamics of each individual cell and the temporal-spatial distribution of cell population. The results showed that the temporal-spatial heterogeneity is more pronounced in the network that has the vessels with smaller diameters or with more complex geometry. Such heterogeneity is largely attributed to the existence of bifurcations, where the positively correlated hypotactic (feeding-branch) and paratactic (branch-branch) relations are generally observed in both the time-averaged hematocrit and temporal hematocrit ranges. This suggests that the successive bifurcations have a substantial impact on the temporal-spatial heterogeneity of hematocrit. However, these positive correlations may be broken up if the diameter of the feeding vessel is small enough or the bifurcation is asymmetric extremely, due to the vessel blockage. The present study is of great clinical significance to help doctors make more accurate diagnosis and treatment, by providing more information about the temporal-spatial distribution of the hematocrit in microvascular networks.

Deep learning-based hemodynamic prediction of carotid artery stenosis before and after surgical treatments.

Hemodynamic prediction of carotid artery stenosis (CAS) is of great clinical significance in the diagnosis, prevention, and treatment prognosis of ischemic strokes. While computational fluid dynamics (CFD) is recognized as a useful tool, it shows a crucial issue that the high computational costs are usually required for real-time simulations of complex blood flows. Given the powerful feature-extraction capabilities, the deep learning (DL) methodology has a high potential to implement the mapping of anatomic geometries and CFD-driven flow fields, which enables accomplishing fast and accurate hemodynamic prediction for clinical applications. Based on a brain/neck CT angiography database of 280 subjects, image based three-dimensional CFD models of CAS were constructed through blood vessel extraction, computational domain meshing and setting of the pulsatile flow boundary conditions; a series of CFD simulations were undertaken. A DL strategy was proposed and accomplished in terms of point cloud datasets and a DL network with dual sampling-analysis channels. This enables multimode mapping to construct the image-based geometries of CAS while predicting CFD-based hemodynamics based on training and testing datasets. The CFD simulation was validated with the mass flow rates at two outlets reasonably agreed with the published results. Comprehensive analysis and error evaluation revealed that the DL strategy enables uncovering the association between transient blood flow characteristics and artery cavity geometric information before and after surgical treatments of CAS. Compared with other methods, our DL-based model trained with more clinical data can reduce the computational cost by 7,200 times, while still demonstrating good accuracy (error<12.5%) and flow visualization in predicting the two hemodynamic parameters. In addition, the DL-based predictions were in good agreement with CFD simulations in terms of mean velocity in the stenotic region for both the preoperative and postoperative datasets. This study points to the capability and significance of the DL-based fast and accurate hemodynamic prediction of preoperative and postoperative CAS. For accomplishing real-time monitoring of surgical treatments, further improvements in the prediction accuracy and flexibility may be conducted by utilizing larger datasets with specific real surgical events such as stent intervention, adopting personalized boundary conditions, and optimizing the DL network.

Impact of viscosity modeling on the simulation of aortic blood flow

Modeling issues for the simulation of blood flow in an aortic coarctation are studied in this paper. From the physical point of view, several viscosity models for non-Newtonian fluids as well as a Newtonian fluid model will be considered. From the numerical point of view, two different turbulence models are utilized in the simulations. The impact of both, the physical and the numerical modeling, on clinically relevant biomarkers is investigated and compared.

Evaluation of Different Cannulation Strategies for Aortic Arch Surgery Using a Cardiovascular Numerical Simulator.

Aortic disease has a significant impact on quality of life. The involvement of the aortic arch requires the preservation of blood supply to the brain during surgery. Deep hypothermic circulatory arrest is an established technique for this purpose, although neurological injury remains high. Additional techniques have been used to reduce risk, although controversy still remains. A three-way cannulation approach, including both carotid arteries and the femoral artery or the ascending aorta, has been used successfully for aortic arch replacement and redo procedures. We developed circuits of the circulation to simulate blood flow during this type of cannulation set up. The CARDIOSIM© cardiovascular simulation platform was used to analyse the effect on haemodynamic and energetic parameters and the benefit derived in terms of organ perfusion pressure and flow. Our simulation approach based on lumped-parameter modelling, pressure-volume analysis and modified time-varying elastance provides a theoretical background to a three-way cannulation strategy for aortic arch surgery with correlation to the observed clinical practice.

Implicit Finite-difference Schemes for Equations of One-dimensional Hemodynamics

The paper is devoted to the construction and analysis of implicit finite-difference schemes for a system of one-dimensional equations of hemodynamics. The schemes are based on the use of finite differences, which approximate spatial derivative with the fourth order. The schemes are based on the splitting on physical processes. According to this approach, at one time step, two mechanical processes are considered: the deformation of the vessel filled with fluid and the fluid flow in the deformed vessel. This approach makes it possible to separately consider finite-difference schemes, which approximate governing equations. In the practical implementation of the proposed schemes, they are reduced to systems of linear algebraic equations with pentadiagonal matrices. The stability analysis of constructed schemes is based on the von Neumann method and the principle of frozen coefficients. In the numerical solution of problems with known analytical solutions, it is demonstrated that the schemes lead to numerical solutions with a fourth-order convergence rate. In the computational experiments on simulation of blood flow in model vascular systems, it is demonstrated that the developed schemes make it possible to perform calculations in much less time than well-known explicit finite-difference and finite-volume schemes.

Validity and Diagnostic Performance of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images

Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images. A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. The correlation coefficient and Bland-Altman plots were used to assess the agreement between the calculated FFR and the aFFR. A total of 146 patients were included, with 95 men and 51 women, with a mean (SD) age of 61.1 (9.5) y. The mean (SD) aFFR was 0.847 (0.072), and 41 patients (27.0%) had an aFFR of 0.80 or less. There was a strong intraobserver correlation between the computational FFRs (r = 0.808; P < .001; κ = 0.806; P < .001). There was also a strong correlation between aFFR and computational FFR (r = 0.820; P < .001) and good agreement on the Bland-Altman plot. The computational FFR had a high sensitivity (95.1%) and specificity (90.1%) for detecting an aFFR of 0.80 or less. A novel software program provides a feasible method of calculating FFR from coronary angiography images without resorting to pharmacologically induced hyperemia.

Development of Surface Smoothing Method for Blood Flow Simulation

Development of Surface Smoothing Method for Blood Flow Simulation

Fabrication of a Gelatin-Based Microdevice for Vascular Cell Culture.

This study presents a novel technique for fabricating microfluidic devices with microbial transglutaminase-gelatin gels instead of polydimethylsiloxane (PDMS), in which flow culture simulates blood flow and a capillary network is incorporated for assays of vascular permeability or angiogenesis. We developed a gelatin-based device with a coverslip as the bottom, which allows the use of high-magnification lenses with short working distances, and we observed the differences in cell dynamics on gelatin, glass, and PDMS surfaces. The tubes of the gelatin microfluidic channel are designed to be difficult to pull out of the inlet hole, making sample introduction easy, and the gelatin channel can be manipulated from the cell introduction to the flow culture steps in a manner comparable to that of a typical PDMS channel. Human umbilical vein endothelial cells (HUVECs) and normal human dermal fibroblasts (NHDFs) were successfully co-cultured, resulting in structures that mimicked blood vessels with inner diameters ranging from 10 µm to 500 µm. Immunostaining and scanning electron microscopy results showed that the affinity of fibronectin for gelatin was stronger than that for glass or PDMS, making gelatin a suitable substrate for cell adhesion. The ability for microscopic observation at high magnification and the ease of sample introduction make this device easier to use than conventional gelatin microfluidics, and the above-mentioned small modifications in the device structure are important points that improve its convenience as a cell assay device.

Simulation of blood flow in human arteries as porous media

The porous flow model studies the blood flow in a curve shape. This study has addressed simulations of blood flow in a porous media through an elbow artery; two-dimensional (2D), have been investigated. The blood flow is supplied with diameters such as (300 and 500 µm). The outputs from numerical simulations have presented the details of blood flow patterns and the local distribution of blood flow along the artery. The effects of permeability concerning the variations in the Reynolds number (Re = 0.1, 1 and 5) and changing porosity levels have been discussed. Different vessel diameters were studied to show the velocity distribution inside the vessel. Results are presented in variations of velocity distributions and local variations of flow rates through the vessel dimensions. Outputs compare with the available data, and a good agreement find. The study potentially evaluates the role of porosity and flow conditions when the body is subject to diseases.

Applications of a novel reciprocating positive displacement pump in the simulation of pulsatile arterial blood flow.

Pulsatile arterial blood flow plays an important role in vascular system mechanobiology, especially in the study of mechanisms of pathology. Limitations in cost, time, sample size, and control across current in-vitro and in-vivo methods limit future exploration of novel treatments. Presented is the verification of a novel reciprocating positive displacement pump aimed at resolving these issues through the simulation of human ocular, human fingertip and skin surface, human cerebral, and rodent spleen organ systems. A range of pulsatile amplitudes, frequencies, and flow rates were simulated using pumps made of 3D printed parts incorporating a tubing system, check valve and proprietary software. Volumetric analysis of 430 total readings across a flow range of 0.025ml/min to 16ml/min determined that the pump had a mean absolute error and mean relative error of 0.041 ml/min and 1.385%, respectively. Linear regression analysis compared to expected flow rate across the full flow range yielded an R2 of 0.9996. Waveform analysis indicated that the pump could recreate accurate beat frequency for flow ranges above 0.06ml/min at 70BPM. The verification of accurate pump output opens avenues for the development of novel long-term in-vitro benchtop models capable of looking at fluid flow scenarios previously unfeasible, including low volume-high shear rate pulsatile flow.

Mitigation of the turbulence within an arteriovenous fistula with a stent implantation

The transitional flow which initiates within the junction (anastomosis) of an arteriovenous fistula (AVF) is known to be a contributing factor in the onset of vascular disease. A novel treatment method involving the implantation of a flexible stent across the anastomosis has enabled the retention of a large proportion of functioning AVFs, despite the propensity for stent malapposition to occur at the sharp inner curve of the anastomosis. Large Eddy Simulations (LES) of a patient-specific AVF with and without the presence of a stent captured oscillatory flow behaviour emanating from the interface of the two inlet flows in the stent-absent case, however, these oscillatory features were subdued in the stented case. The stent-absent case generally had higher Turbulent Kinetic Energy (TKE) in the anastomosis which led to larger cycle-to-cycle variations in wall shear stress (WSS). The significantly lower TKE generated at the heel of the stented AVF was contained within the malapposed stent, thereby resulting in lower WSS fluctuations. However, a slight increase in turbulence downstream of the malapposed stent edge was noted. This detailed study reveals a significant decrease in turbulence within the AVF in the presence of the stent, thereby, providing a level of understanding underpinning the success of the treatment strategy from a fluid dynamic perspective.

Blood flow but not cannula positioning influences the efficacy of Veno-Venous ECMO therapy

Despite being vital in treating intensive-care patients with lung failure, especially COVID-19 patients, Veno-Venous Extra-Corporeal Membrane Oxygenation does not exploit its full potential, leaving ample room for improvement. The objective of this study is to determine the effect of cannula positioning and blood flow on the efficacy of Veno-Venous Extra-Corporeal Membrane Oxygenation, in particular in relationship with blood recirculation. We performed 98 computer simulations of blood flow and oxygen diffusion in a computerized-tomography-segmented right atrium and venae cavae for different positions of the returning and draining cannulae and ECMO flows of 3 L/min and 5,hbox {L}/hbox {min}. For each configuration we measured how effective Veno-Venous Extra-Corporeal Membrane Oxygenation is at delivering oxygen to the right ventricle and thus to the systemic circulation. The main finding is that VV-ECMO efficacy is largely affected by the ECMO flow (global peak blood saturation: {92.8},%; average inter-group saturation gain: 9 percentage points) but only scarcely by the positioning of the cannulae (mean saturation ± standard deviation for the 3 L/min case: 83.12 pm 0.49; for the 5,hbox {L}/hbox {min} case: 92.21 pm 0.37). An important secondary outcome is that recirculation, more intense with a higher ECMO flow, is less detrimental to the procedure than previously thought. The efficacy of current ECMO procedures is intrinsically limited and fine-tuning the positions of the cannulae, risking infections, offers very little gain. Setting a higher ECMO flow offers the biggest benefit despite mildly increasing blood recirculation.

Numerical and Computational simulation of blood flow on hybrid nanofluid with heat transfer through a stenotic artery: Silver and gold nanoparticles

The proposed study aims to examine the numerical modeling of hybrid nanofluid with nanoparticles such as gold and silver across stenotic artery using Computational fluid dynamics (CFD) in COMSOL Multiphysics. Blood is employed as the base fluid in this research investigation. The flow is modeled as an unstable, incompressible, and laminar Newtonian fluid and blood's Newtonian character is suitable at high shear rates. The performance of blood flow was studied to receive pressure, heat, and velocity changes caused by the stenotic artery. Silver and gold nanomaterials were employed in this study. The Computational fluid dynamics (CFD) approach was used to develop an algorithm for mass, velocity, and energy. COMSOL Multiphysics was used to produce a fine element-size mesh. To the knowledge of the researchers, no one has previously tried to obtain medical processes and therapy implications by studying the flow via a deformed porous channel using blood as a base fluid and as nanostructure materials. Indeed, the findings of this study are unique, and the numerical findings have never been reported by any scholar.

Dissipative particle dynamics simulations for biological systems: From protein structures to cell mechanics

<p indent="0mm">Dissipative particle dynamics (DPD) is a mesoscopic coarse-grained simulation method developed in recent years, which is an important method for studying the dynamic behaviors of soft matter and complex fluids. In this method, each DPD particle represents a coarse-grained virtual cluster of a set of atoms or groups of matter. The position and momentum of the DPD particle are updated in a continuous phase but spaced at discrete time steps. The coarse-grained DPD particles are subject to simplified pairwise interacting conservative, dissipative, and random forces. Especially, the dissipative force and random force in the DPD method act as a heat sink and a source, respectively, and the combined effect of these two forces act as a thermostat, which conserves momentum and thus provides the correct description of hydrodynamic interactions for the model system. In addition, a common choice of the soft repulsion for the conservative force allows using larger integration time steps in DPD simulations than that usually allowed in classical molecular dynamics (MD) simulations. Hence, compared with the MD method, the computational cost of the DPD simulation is significantly reduced due to the smaller number of modeled particles and the larger computational time step, enabling the simulations of the static and dynamic behaviors of complex fluids and soft matter systems at physically attractive length scale and time scale. Moreover, the particle-based framework of the DPD method enables people to easily incorporate additional physical features into the model systems and extend its application to complex systems. For these reasons, the DPD method and its extension have been successfully applied to numerous soft matter and complex fluid systems such as oil/water/surfactant systems, chemical morphology, microscopic morphology, phase separation, as well as dynamics and rheological properties of polymer solutions and colloidal suspensions. In this paper, we first introduce the theoretical formulation and parameterization of the DPD method. Then, we review recent advances in DPD modeling of biological systems, focusing on its applications at the molecular and cellular scales. At the molecular scale, we highlight examples of successful simulations of the protein structures and their interactions, the structure and dynamics of amphiphilic lipid molecule membranes (e.g., the self-assembly of lipid molecules, the structure and properties of lipid membranes, the fusion of lipid membranes, and the budding and fission of lipid membranes), the interaction of lipid membranes with protein molecules, and the interaction of nanoparticles with lipid membranes; at the cellular scale, we focus on the DPD modeling of blood cell flow and blood rheological behaviors in the blood microcirculatory systems, including the shape deformation and flow dynamics of red blood cells, the margination and adhesion dynamics of white blood cells, the margination and aggregation behaviors of platelets, the hemorheological behavior of blood flow, as well as the separation of circulating tumor cells from blood flow using microfluidic devices. Additionally, we compare the advantages and disadvantages of the microscale blood flow simulations between the continuum-based methods and particle-based methods, including the DPD method. Finally, we briefly present the development trends and application prospects of DPD modeling in biological systems.

Abnormal jugular valves are not the sole explanation of an impaired outflow from the cranial cavity through the internal jugular veins: results of &lt;I&gt;in silico&lt;/I&gt; studies

Background. Currently, pathological jugular valves are thought to be the main cause of altered hemodynamics in the internal jugular veins, the so-called chronic cerebrospinal venous insufficiency. The alternative interpretation of flow disturbances in these veins is that the main source of abnormal outflow are nozzle-like strictures in their upper parts, at the level or just below the jugular foramen, for example, caused by an enlarged transverse process of the atlas and/or styloid process of the temporal bone.1 These in silico studies were aimed at validation of this hypothesis.&#x0D; Methods. With the use of computational fluid mechanics software: the Flowsquare+ and the COMSOL multiphysics, we simulated blood flow in the models of internal jugular veins that exhibited different morphologies (Figure 1). With the Flowsquare+ software, we performed 3-dimensional simulations for the assessment of relevance of the strictures at the level of jugular foramen, while the COMSOL multiphysics software, which was used in 2-dimensional mode, gave us more detailed insight into the behavior of the jugular valve. Results. There was a normal unidirectional flow, with the centrally positioned centerline velocity and no flow separation in modeled veins, which were not narrowed or presented with gradual narrowings. On the contrary, in a majority of models with nozzle-like strictures located at the beginning of the studied veins, abnormal flow patterns were revealed, with significant flow separation and regions with reversed flow. The most severe flow abnormalities were not seen in the models with nozzles of a small cross-sectional area, but rather in those positioned asymmetrically. Abnormal valves (with reversed or asymmetric leaflets) further impaired the flow in models with symmetrically positioned nozzles, but had no significant impact on the flow in a case of an already altered flow evoked by the asymmetric nozzles.1 Importantly, simulations performed with the COMSOL multiphysics revealed that flow disturbances evoked by significant stenosis in the upper part of the internal jugular vein distort leaflets of the jugular valve. This was not seen as a case of a minor stenosis.&#x0D; Conclusions. We demonstrated that our working hypothesis is credible and that impaired outflow from the brain through the internal jugular veins is likely to be primarily caused by pathological strictures in the upper parts of these veins, instead of pathological jugular valves that, as of yet, were the main target of clinical research. In addition, pathology of the jugular valves may be secondary to the strictures in the upper segments of the internal jugular veins.

Quasi-simultaneous coupling methods for partitioned problems in computational hemodynamics

The paper describes the numerical coupling challenges in multiphysics problems like the simulation of blood flow in compliant arteries. In addition to an iterative coupling between the fluid flow and elastic vessel walls, i.e. fluid-structure interaction, also the coupling between a detailed 3D local (arterial) flow model and a more global 0D model (representing a global circulation) is analyzed. Most of the coupling analysis is formulated in the more abstract setting of electrical-network models. Both, weak (segregated) and strong (monolithic) coupling approaches are studied, and their numerical stability limitations are discussed. Being a hybrid combination, the quasi-simultaneous coupling method, developed for partitioned problems in aerodynamics, is shown to be a robust and flexible approach for hemodynamic applications too.

Parametric analysis of an efficient boundary condition to control outlet flow rates in large arterial networks

Substantial effort is being invested in the creation of a virtual human—a model which will improve our understanding of human physiology and diseases and assist clinicians in the design of personalised medical treatments. A central challenge of achieving blood flow simulations at full-human scale is the development of an efficient and accurate approach to imposing boundary conditions on many outlets. A previous study proposed an efficient method for implementing the two-element Windkessel model to control the flow rate ratios at outlets. Here we clarify the general role of the resistance and capacitance in this approach and conduct a parametric sweep to examine how to choose their values for complex geometries. We show that the error of the flow rate ratios decreases exponentially as the resistance increases. The errors fall below 4% in a simple five-outlets model and 7% in a human artery model comprising ten outlets. Moreover, the flow rate ratios converge faster and suffer from weaker fluctuations as the capacitance decreases. Our findings also establish constraints on the parameters controlling the numerical stability of the simulations. The findings from this work are directly applicable to larger and more complex vascular domains encountered at full-human scale.

Hemodynamic simulation of aneurysmal aorta using a parallel algorithm and a flow-rate based resistance splitting method

Hemodynamic analysis of the aortic aneurysm can provide clinically useful information for the treatment and management of the disease. However, it is still a big challenge to accurately resolve the flow field within a clinically acceptable computing time. In this work, we adopt a two-level domain decomposition-based preconditioned parallel nonlinear solver to solve the unsteady Navier–Stokes equations with three-element Windkessel outlet boundary conditions, where model parameters are estimated by a novel method based on the blood flow rate ratio obtained from the ultrasound. The simulated results are verified by using clinically measured data. Several numerical experiments are performed to show the robustness of the proposed algorithm against different parameters. The proposed algorithm scales up to 2400 processor cores with 50% parallel efficiency and greatly reduces the computing time of the full-size aortic blood flow simulation.

On the Effects of Boundary Conditions in One-Dimensional Models of Hemodynamics

The paper is devoted to the theoretical analysis of the effects of boundary conditions on the solutions of the system of one-dimensional (1D) hemodynamics. The integral inequalities, which realize the energy inequalities for the solutions of initial-boundary-value problems, are obtained. It is demonstrated that the unphysical unbounded solutions can take place for the case of bounded functions from boundary conditions. For the periodic boundary conditions, the integral estimation illustrates the correct behavior of the solution. For this case of boundary conditions, the effective Fourier method for the analytical solution is proposed. The analytical solutions, obtained by this approach, can be used for the comparison of different 1D blood-flow models. The results obtained in the paper allow for an the alternatively view of the stated boundary conditions and can explain some problems, which can arise in numerical simulations. They expand the possibilities of the application of analytical methods in the field of blood-flow simulation. The results can be useful for the specialists on blood-flow modeling.