A unified method for estimating pressure losses at vascular junctions

Mynard, Jonathan P.; Valen‐Sendstad, Kristian

doi:10.1002/cnm.2717

Cited by 42 publications

(50 citation statements)

References 55 publications

(120 reference statements)

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“…[12][13][14][15] The FDA nozzle benchmark model remains highly relevant for biomedical problems and our aim was to further validate the open-source CFD solver Oasis 16 that we have extensively used to study turbulent-like cardiovascular flows. [17][18][19][20][21][22][23] We focus on the flow at Re = 3500, which is in the particularly challenging transitional flow regime, for which the in vitro experiments displayed the least variability.…”

mentioning

confidence: 99%

The FDA nozzle benchmark: “In theory there is no difference between theory and practice, but in practice there is”

Bergersen

Mortensen

Valen‐Sendstad

2018

Numer Methods Biomed Eng

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The utility of flow simulations relies on the robustness of computational fluid dynamics (CFD) solvers and reproducibility of results. The aim of this study was to validate the Oasis CFD solver against in vitro experimental measurements of jet breakdown location from the FDA nozzle benchmark at Reynolds number 3500, which is in the particularly challenging transitional regime. Simulations were performed on meshes consisting of 5, 10, 17, and 28 million (M) tetrahedra, with Δt = 10 seconds. The 5M and 10M simulation jets broke down in reasonable agreement with the experiments. However, the 17M and 28M simulation jets broke down further downstream. But which of our simulations are "correct"? From a theoretical point of view, they are all wrong because the jet should not break down in the absence of disturbances. The geometry is axisymmetric with no geometrical features that can generate angular velocities. A stable flow was supported by linear stability analysis. From a physical point of view, a finite amount of "noise" will always be present in experiments, which lowers transition point. To replicate noise numerically, we prescribed minor random angular velocities (approximately 0.31%), much smaller than the reported flow asymmetry (approximately 3%) and model accuracy (approximately 1%), at the inlet of the 17M simulation, which shifted the jet breakdown location closer to the measurements. Hence, the high-resolution simulations and "noise" experiment can potentially explain discrepancies in transition between sometimes "sterile" CFD and inherently noisy "ground truth" experiments. Thus, we have shown that numerical simulations can agree with experiments, but for the wrong reasons.

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mentioning

confidence: 99%

The FDA nozzle benchmark: “In theory there is no difference between theory and practice, but in practice there is”

Bergersen

Mortensen

Valen‐Sendstad

2018

Numer Methods Biomed Eng

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“…If we assume continuity of dP across the junction (i.e., dP1 ϭ dP2 ϭ dP 3), thereby ignoring the generally small pressure losses that occur at junctions (27), then dP 1 dQ 1 ϭ dP 2 dQ 2 ϩ dP 3 dQ 3 (11) This may be generalized to any multibranch junction as follows,…”

Section: Wave Power At Junctionsmentioning

confidence: 99%

Novel wave power analysis linking pressure-flow waves, wave potential, and the forward and backward components of hydraulic power

Mynard

Smolich

2016

American Journal of Physiology-Heart and Circulatory Physiology

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Wave intensity analysis provides detailed insights into factors influencing hemodynamics. However, wave intensity is not a conserved quantity, so it is sensitive to diameter variations and is not distributed among branches of a junction. Moreover, the fundamental relation between waves and hydraulic power is unclear. We, therefore, propose an alternative to wave intensity called "wave power," calculated via incremental changes in pressure and flow (dPdQ) and a novel time-domain separation of hydraulic pressure power and kinetic power into forward and backward wave-related components (ΠP±and ΠQ±). Wave power has several useful properties:1) it is obtained directly from flow measurements, without requiring further calculation of velocity;2) it is a quasi-conserved quantity that may be used to study the relative distribution of waves at junctions; and3) it has the units of power (Watts). We also uncover a simple relationship between wave power and changes in ΠP±and show that wave reflection reduces transmitted power. Absolute values of ΠP±represent wave potential, a recently introduced concept that unifies steady and pulsatile aspects of hemodynamics. We show that wave potential represents the hydraulic energy potential stored in a compliant pressurized vessel, with spatial gradients producing waves that transfer this energy. These techniques and principles are verified numerically and also experimentally with pressure/flow measurements in all branches of a central bifurcation in sheep, under a wide range of hemodynamic conditions. The proposed "wave power analysis," encompassing wave power, wave potential, and wave separation of hydraulic power provides a potent time-domain approach for analyzing hemodynamics.

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“…). However, more advanced coupling conditions have been proposed which are capable of modelling pressure losses at junctions (Mynard & Valen‐Sendstad, ).…”

Section: Review Of Recent 1d Circulation Modelsmentioning

confidence: 99%

Roadmap for cardiovascular circulation model

Safaei

Bradley

Suresh

et al. 2016

The Journal of Physiology

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Computational models of many aspects of the mammalian cardiovascular circulation have been developed. Indeed, along with orthopaedics, this area of physiology is one that has attracted much interest from engineers, presumably because the equations governing blood flow in the vascular system are well understood and can be solved with well-established numerical techniques. Unfortunately, there have been only a few attempts to create a comprehensive public domain resource for cardiovascular researchers. In this paper we propose a roadmap for developing an open source cardiovascular circulation model. The model should be registered to the musculo-skeletal system. The computational infrastructure for the cardiovascular model should provide for near real-time computation of blood flow and pressure in all parts of the body. The model should deal with vascular beds in all tissues, and the computational infrastructure for the model should provide links into CellML models of cell function and tissue function. In this work we review the literature associated with 1D blood flow modelling in the cardiovascular system, discuss model encoding standards, software and a model repository. We then describe the coordinate systems used to define the vascular geometry, derive the equations and discuss the implementation of these coupled equations in the open source computational software OpenCMISS. Finally, some preliminary results are presented and plans outlined for the next steps in the development of the model, the computational software and the graphical user interface for accessing the model.

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A unified method for estimating pressure losses at vascular junctions

Cited by 42 publications

References 55 publications

The FDA nozzle benchmark: “In theory there is no difference between theory and practice, but in practice there is”

The FDA nozzle benchmark: “In theory there is no difference between theory and practice, but in practice there is”

Novel wave power analysis linking pressure-flow waves, wave potential, and the forward and backward components of hydraulic power

Roadmap for cardiovascular circulation model

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