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Results for “Computational hemodynamics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Computational Hemodynamic Simulation of Human Circulatory System under Altered Gravity

A computational hemodynamics approach is presented to simulate the blood flow through the human circulatory system under altered gravity conditions. Numerical techniques relevant to hemodynamics issues are introduced to non-Newtonian modeling for flow characteristics governed by red blood cells, distensible wall motion due to the heart pulse, and capillary bed modeling for outflow boundary conditions. Gravitational body force terms are added to the Navier-Stokes equations to study the effects of gravity on internal flows. Six-type gravity benchmark problems are originally presented to provide the fundamental understanding of gravitational effects on the human circulatory system. For code validation, computed results are compared with steady and unsteady experimental data for non-Newtonian flows in a carotid bifurcation model and a curved circular tube, respectively. This computational approach is then applied to the blood circulation in the human brain as a target problem. A three-dimensional, idealized Circle of Willis configuration is developed with minor arteries truncated based on anatomical data. Demonstrated is not only the mechanism of the collateral circulation but also the effects of gravity on the distensible wall motion and resultant flow patterns.

Kim. Chang Sung↗
NASA NTRS2001

Computational Hemodynamics Involving Artificial Devices

This paper reports the progress being made towards developing complete blood flow simulation capability in human, especially, in the presence of artificial devices such as valves and ventricular assist devices. Devices modeling poses unique challenges different from computing the blood flow in natural hearts and arteries. There are many elements needed such as flow solvers, geometry modeling including flexible walls, moving boundary procedures and physiological characterization of blood. As a first step, computational technology developed for aerospace applications was extended in the recent past to the analysis and development of mechanical devices. The blood flow in these devices is practically incompressible and Newtonian, and thus various incompressible Navier-Stokes solution procedures can be selected depending on the choice of formulations, variables and numerical schemes. Two primitive variable formulations used are discussed as well as the overset grid approach to handle complex moving geometry. This procedure has been applied to several artificial devices. Among these, recent progress made in developing DeBakey axial flow blood pump will be presented from computational point of view. Computational and clinical issues will be discussed in detail as well as additional work needed.

Kwak, Dochan↗
DOE OSTI2019

Propagating uncertainties in large-scale hemodynamics models via network uncertainty quantification and reduced-order modeling

Numerical simulations of the cardiovascular system are affected by uncertainties arising from a substantial lack of data related to the boundary conditions and the physical parameters of the mathematical models. Quantifying the impact of this uncertainty on the numerical results along the circulatory network is challenged by the complexity of both the morphology of the domain and the local dynamics. Here, we propose to integrate (i) the Transverse Enriched Pipe Element Methods (TEPEM) as a reduced-order model for effectively computing the 3D local hemodynamics; and (ii) a combination of uncertainty quantification via Polynomial Chaos Expansion and classical relaxation methods – called network uncertainty quantification (NetUQ) – for effectively propagating random variables that encode uncertainties throughout the networks. The findings demonstrate the computational effectiveness of computing the propagation of uncertainties in networks with nontrivial topology, including portions of the cerebral and the coronary systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Model-based parameter estimation using cardiovascular response to orthostatic stress

This paper presents a cardiovascular model that is capable of simulating the short-term (< or approximately equal to 3 min) transient hemodynamic response to gravitational stress and a gradient-based optimization method that allows for the automated estimation of model parameters from simulated or experimental data. We perform a sensitivity analysis of the transient heart rate response to determine which parameters of the model impact the heart rate dynamics significantly. We subsequently include only those parameters in the estimation routine that impact the transient heart rate dynamics substantially. We apply the estimation algorithm to both simulated and real data and showed that restriction to the 20 most important parameters does not impair our ability to match the data.

Non-NASA Center↗
NASA NTRS2002

Numerical simulation of the influence of gravity and posture on cardiac performance

A numerical model of the cardiovascular system was used to quantify the influences on cardiac function of intrathoracic pressure and intravascular and intraventricular hydrostatic pressure, which are fundamental biomechanical stimuli for orthostatic response. The model included a detailed arterial circulation with lumped parameter models of the atria, ventricles, pulmonary circulation, and venous circulation. The venous circulation was divided into cranial, central, and caudal regions with nonlinear compliance. Changes in intrathoracic pressure and the effects of hydrostatic pressure were simulated in supine, launch, sitting, and standing postures for 0, 1, and 1.8 G. Increasing intrathoracic pressure experienced with increasing gravity caused 12% and 14% decreases in cardiac output for 1 and 1.8 G supine, respectively, compared to 0 G. Similar results were obtained for launch posture, in which the effects of changing intrathoracic pressure dominated those of hydrostatic pressure. Compared to 0 G, cardiac output decreased 0.9% for 1 G launch and 15% for 1.8 G launch. In sitting and standing, the position of the heart above the hydrostatic indifference level caused the effects of changing hydrostatic pressure to dominate those of intrathoracic pressure. Compared to 0 G, cardiac output decreased 13% for 1 G sitting and 23% for 1.8 G sitting, and decreased 17% for 1 G standing and 31% for 1.8 G standing. For a posture change from supine to standing in 1 G, cardiac output decreased, consistent with the trend necessary to explain orthostatic intolerance in some astronauts during postflight stand tests. Simulated lower body negative pressure (LBNP) in 0 G reduced cardiac output and mean aortic pressure similar to I G standing, suggesting that LBNP provides at least some cardiovascular stimuli that may be useful in preventing postflight orthostatic intolerance. A unifying concept, consistent with the Frank-Starling mechanism of the heart, was that cardiac output was proportional to cardiac diastolic transmural pressure for all postures and gravitational accelerations.

Non-NASA Center↗
DOE OSTI2021

A Poisson equation method for prescribing fully developed non-Newtonian inlet conditions for computational fluid dynamics simulations in models of arbitrary cross-section

Prescribing inlet boundary conditions for computational fluid dynamics (CFD) simulations of internal flow in complex geometries such as anatomical vascular models is challenging. In the absence of patient-specific inlet velocity data, a common approach for long blood vessels is to assume that the inlet flow is fully developed. In vessels of irregular cross section, however, prescribing fully developed conditions is complicated due to the lack of a general closed-form analytical solution. In this study, we develop a simple Poisson equation method for prescribing fully developed inlet conditions for the flow of either Newtonian or non-Newtonian fluids in CFD models of arbitrary cross-section. We first derive the generalized Poisson equation for fully developed flow of a non-Newtonian fluid and we then develop and verify a methodology for numerically computing the solution on any planar boundary domain. In addition, we develop a simple extension of the method for prescribing a non-orthogonal inlet velocity that represents fully developed flow from an upstream tube that is connected to the CFD inlet at a non-orthogonal angle. This may be used to investigate a common source of uncertainty in CFD simulations of internal flow that is due to a lack of information concerning the exact streamwise flow direction at the inlets. Comparison to several Newtonian and non-Newtonian benchmark verification solutions shows the method to be extremely accurate. As a practical demonstration case, we use the method to prescribe fully developed conditions on multiple non-circular inlets for the non-Newtonian flow of blood in a patient-specific model of the inferior vena cava (IVC). Finally, we further demonstrate the utility of the method by performing a sensitivity study using the patient-specific IVC model, wherein we investigate the influence of inlet velocity flow direction on the non-Newtonian IVC hemodynamics. Given its simplicity and computational efficiency, the method is shown to be far superior to alternative approaches for prescribing fully developed inlet conditions in such complicated geometries. In conclusion, to facilitate the adoption of our Poisson equation method, we have distributed our OpenFOAM source code and the associated test cases from this study as open-source software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders

Abstract Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices (PI and RI), the interpretation of such metrics for disease assessment relies on ad hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer parameters, such as vascular resistance, compliance, and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with branching carotid artery and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

Biophysics↗
DOE OSTI2020

Collagen Turnover in Relation to Risk Factors and Hemodynamics in Human Intracranial Aneurysms

Determinants for molecular and structural instability, that is, impending growth or rupture, of intracranial aneurysms (IAs) remain uncertain. To elucidate this, we endeavored to estimate the actual turnover rates of the main molecular constituent in human IA (collagen) on the basis of radiocarbon ( 14 C) birth dating in relation to IA hemodynamics. Collagen turnover rates in excised human IA samples were calculated using mathematical modeling of 14 C birth dating data of collagen in relation to risk factors and histological markers for collagen maturity/turnover in selected IA. Hemodynamics were simulated using image-based computational fluid dynamics. Correlation, logistic regression, and receiver operating characteristic analyses were performed. Collagen turnover rates were estimated in 46 IA (43 patients); computational fluid dynamics could be performed in 20 IA (20 patients). The mean collagen turnover rate (γ) constituted 126% (±1% error) per year. For patients with arterial hypertension, γ was greater than 2600% annually, whereas γ was distinctly lower with 32% (±1% error) per year for patients without risk factors, such as smoking and hypertension. There was a distinct association between histological presence of rather immature collagen in human IA and the presence of modifiable risk factors. Spatial-temporal averaged wall shear stress predicted rapid collagen turnover (odds ratio, 1.6 [95% CI, 1.0–2.7]). Receiver operating characteristic analysis demonstrated a good test accuracy (area under the curve, 0.798 [95% CI, 0.598–0.998]) for average wall shear stress with a threshold ≥4.9 Pa for rapid collagen turnover. Our data indicate that turnover rates and stability of collagen in human IA are strongly associated with the presence of modifiable risk factors and aneurysmal hemodynamics. Finally, these findings underline the importance of strict risk factor modification in patients with unruptured IA. Future should include more detailed risk factor data to establish a more causal understanding of hemodynamics and the rupture risk of individual IA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Multi-GPU immersed boundary method hemodynamics simulations

Large-scale simulations of blood flow that resolve the 3D deformation of each comprising cell are increasingly popular owing to algorithmic developments in conjunction with advances in compute capability. Among different approaches for modeling cell-resolved hemodynamics, fluid structure interaction (FSI) algorithms based on the immersed boundary method are frequently employed for coupling separate solvers for the background fluid and the cells within one framework. GPUs can accelerate these simulations; however, both current pre-exascale and future exascale CPU-GPU heterogeneous systems face communication challenges critical to performance and scalability. In this paper, we describe, to our knowledge, the largest distributed GPU-accelerated FSI simulations of high hematocrit cell-resolved flows with over 17 million red blood cells. We compare scaling on a fat node system with six GPUs per node and on a system with a single GPU per node. Through comparison between the CPU- and GPU-based implementations, we identify the costs of data movement in multiscale multi-grid FSI simulations on heterogeneous systems and show it to be the greatest performance bottleneck on the GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. Here, we propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reductions than diseased models. In all cases, our workflow coupling Dakota’s MLMF estimators with the SimVascular cardiovascular modeling framework makes uncertainty quantification feasible for constrained computational budgets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks

Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient’s hemodynamics and increase the severity of many cardiovascular diseases. Observing and quantifying associations between these factors and hemodynamics can be difficult due to the multitude of co-existing conditions and blood flow parameters in real patient data. Machine learning-driven, physics-based simulations provide a means to understand how potentially correlated conditions may affect a particular patient. Here, we use a combination of machine learning and massively parallel computing to predict the effects of physiological factors on hemodynamics in patients with coarctation of the aorta. We first validated blood flow simulations against in vitro measurements in 3D-printed phantoms representing the patient’s vasculature. We then investigated the effects of varying the degree of stenosis, blood flow rate, and viscosity on two diagnostic metrics – pressure gradient across the stenosis (ΔP) and wall shear stress (WSS) - by performing the largest simulation study to date of coarctation of the aorta (over 70 million compute hours). Using machine learning models trained on data from the simulations and validated on two independent datasets, we developed a framework to identify the minimal training set required to build a predictive model on a per-patient basis. We then used this model to accurately predict ΔP (mean absolute error within 1.18 mmHg) and WSS (mean absolute error within 0.99 Pa) for patients with this disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Determining the impacts of venoarterial extracorporeal membrane oxygenation on cerebral oxygenation using a one-dimensional blood flow simulator

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a mechanical system that provides rapid and short-term support for patients with cardiac failure. In many patients, pulmonary function is also impaired, resulting in poorly-oxygenated cardiac outflow competing against well-oxygenated VA-ECMO outflow, a condition known as North-South syndrome. North-South syndrome is a primary concern because of its potential to cause cerebral hypoxia, which has a critical influence on neurological complications often seen in this patient population. In order to reduce ischemic neurological complications, it is important to understand how clinical decisions regarding VA-ECMO parameters influence blood oxygenation. In our work, we studied the impacts of flow rate and cannulation site on oxygenation using a one-dimensional (1D) model to simulate blood flow. Our model was initially tested by comparing blood flow results to those observed from experimental work in VA-ECMO patients. The 1D model was combined with a two-phase flow model to simulate oxygenation. Additionally, the influence of various other clinician-tunable parameters on oxygenation in the common carotid arteries (CCAs) were tested, including, blood viscosity, cannula position within the insertion artery, heart rate, and systemic vascular resistance (SVR), as well as geometrical changes such as arterial radius and length. Our results indicated that blood oxygenation to the brain strongly depended on the cannula insertion site and the VA-ECMO flow rate with a weaker but potentially significant dependence on arterial radius. During femoral cannulation, VA-ECMO flow rates greater than ~4.9 L/min were needed to perfuse the CCAs. However, axillary and central cannulation began to perfuse the CCAs at significantly lower flow (~1 L/min). These results may help explain the incidence of cerebral hypoxia in this patient population and the common need to change cannulation strategies during treatment to address this clinical problem. While this work describes patient-averaged results, determining these relationships between VA-ECMO parameters and cerebral hypoxia is an important step towards future work to develop patient-specific models that clinicians can use to improve outcomes.

1D blood flow↗
NASA NTRS1994

Computer simulation of the effect of dDAVP with saline loading on fluid balance after 24-hour head-down tilt

Fluid loading (FL) before Shuttle reentry is a countermeasure currently in use by NASA to improve the orthostatic tolerance of astronauts during reentry and postflight. The fluid load consists of water and salt tablets equivalent to 32 oz (946 ml) of isotonic saline. However, the effectiveness of this countermeasure has been observed to decrease with the duration of spaceflight. The countermeasure's effectiveness may be improved by enhancing fluid retention using analogs of vasopressin such as lypressin (LVP) and desmopressin (dDAVP). In a computer simulation study reported previously, we attempted to assess the improvement in fluid retention obtained by the use of LVP administered before FL. The present study is concerned with the use of dDAVP. In a recent 24-hour, 6 degree head-down tilt (HDT) study involving seven men, dDAVP was found to improve orthostatic tolerance as assessed by both lower body negative pressure (LBNP) and stand tests. The treatment restored Luft's cumulative stress index (cumulative product of magnitude and duration of LBNP) to nearly pre-bedrest level. The heart rate was lower and stroke volume was marginally higher at the same LBNP levels with administration of dDAVP compared to placebo. Lower heart rates were also observed with dDAVP during stand test, despite the lower level of cardiovascular stress. These improvements were seen with only a small but significant increase in plasma volume of approximately 3 percent. This paper presents a computer simulation analysis of some of the results of this HDT study.

NASA Discipline Cardiopulmonary↗
NASA NTRS1995

Spectral indices of cardiovascular adaptations to short-term simulated microgravity exposure

We investigated the effects of exposure to microgravity on the baseline autonomic balance in cardiovascular regulation using spectral analysis of cardiovascular variables measured during supine rest. Heart rate, arterial pressure, radial flow, thoracic fluid impedance and central venous pressure were recorded from nine volunteers before and after simulated microgravity, produced by 20 hours of 6 degrees head down bedrest plus furosemide. Spectral powers increased after simulated microgravity in the low frequency region (centered at about 0.03 Hz) in arterial pressure, heart rate and radial flow, and decreased in the respiratory frequency region (centered at about 0.25 Hz) in heart rate. Reduced heart rate power in the respiratory frequency region indicates reduced parasympathetic influence on the heart. A concurrent increase in the low frequency power in arterial pressure, heart rate, and radial flow indicates increased sympathetic influence. These results suggest that the baseline autonomic balance in cardiovascular regulation is shifted towards increased sympathetic and decreased parasympathetic influence after exposure to short-term simulated microgravity.

NASA Discipline Cardiopulmonary↗
NASA NTRS2004

PIV Investigations of the Flow Field in the Volute of a Rotary Blood Pump

A full-size acrylic model of a rotary blood pump was developed in order to utilize Particle Image Velocimetry (PIV) to make measurements of the fluid velocities and turbulent stresses throughout the device. The development of an understanding of the hemodynamics within the blood pump is critical to the development and validation of computational models. A blood analog solution, consisting of sodium iodide solution and glycerin, was developed to match physiological kinematic viscosity. The refractive indecies of the fluid, the pump casing and the impeller were matched to facilitate the use of PIV to make velocity measurements. Velocity measurements made in the volute exit/diffuser region are presented for pumps speeds of 3000-3850 rpm. At each speed data were obtained at a physiological pressure of 90 mmHg and at a maximum flow condition. Four hundred data pairs were used for each resultant mean velocity vector value, representing greater than an order of magnitude more data pairs than reported previously in the literature on similar devices and resulting in velocity uncertainty levels of approximately 2.9%.

Sankovic, John M.↗