184 research outputs found

    Performance Evaluation of Parallel Haemodynamic Computations on Heterogeneous Clouds

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    The article presents performance evaluation of parallel haemodynamic flow computations on heterogeneous resources of the OpenStack cloud infrastructure. The main focus is on the parallel performance analysis, energy consumption and virtualization overhead of the developed software service based on ANSYS Fluent platform which runs on Docker containers of the private university cloud. The haemodynamic aortic valve flow described by incompressible Navier-Stokes equations is considered as a target application of the hosted cloud infrastructure. The parallel performance of the developed software service is assessed measuring the parallel speedup of computations carried out on virtualized heterogeneous resources. The performance measured on Docker containers is compared with that obtained by using the native hardware. The alternative solution algorithms are explored in terms of the parallel performance and power consumption. The investigation of a trade-off between the computing speed and the consumed energy is performed by using Pareto front analysis and a linear scalarization method

    On Efficiency of Parallel Solvers for the Blood Flow through Aortic Valve

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    Mathematical modelling of cardiac haemodynamics presents a great challenge to the computational scientists due to numerous numerical issues and required computational resources. In this paper, we study the parallel performance of 3D simulation software for the blood flow through the aortic valve. The fluid flow problem with the open aortic valve leaflets is formulated and solved in parallel. The choice between the segregated and coupled numerical schemes is discussed and investigated. We present and compare the parallel performance results of both types of parallel solvers. We investigate their strong and weak scalability

    The Development of a Patient-Specific, Open Source Computational Fluid Dynamics Tool to Comprehensively and Innovatively Study Coarctation of the Aorta in a Limited Resource Clinical Context

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    Congenital heart disease (CHD) has a global prevalence of 8 per 1000 births [1] and coarctation of the aorta (CoA) is one of the most common defects with a prevalence of 7% of all cases. The occurrence of CHD in Africa is estimated to be significantly lower, which is attributed to a lack of data [2]. This emphasises the restricted human resources, as well as diagnostic and intervention capacity of specialists in Africa which leads to delayed treatment, presentation with established severity and, consequently, a worse prognosis. Computational Fluid Dynamics (CFD) is seen as the tool that will lead to a better understanding of the haemodynamic effects caused by the malformations related to CoA and provide insights into post-repair morbidity. In addition, the development of a computational tool is envisaged to improve the clinical capacity for diagnosis as well as provide a tool to conduct in silico repair planning. In a low and lower-middle income country healthcare facility, the supplementary data that CFD can provide can add diagnostic value, plan interventions to be more effective and efficient, as well as provide data that may improve postrepair patient management. The aim of this project is to develop a patient-specific, open source, computational fluid dynamics toolchain that is able to study the haemodynamics relating to CoA. In order to do so, a protocol for the collection of doppler echocardiography (echo) and CTA data is proposed. The method for processing the echo data and manually segmenting the CTA data is presented and evaluated. The open source, OpenFOAM code is used to simulate a patient-specific CoA case as well as two in silico designs of coarctation repairs based on expanding the coarctation from the original dataset. The CFD toolchain was developed such that patient data collected from the hospital could be processed to present key haemodynamic metrics such as velocities in the field at the coarctation zone, the pressure gradient across the coarctation and volumetric flow rates through each supra-aortic branch. These results are obtained for each case's geometry, and the trends and impacts that increasing the coarctation ratio has on each of the haemodynamic metrics is presented. The results show that the coarctation pressure gradient and maximum coarctation velocity decrease while perfusion of the lower limbs recovers with expanding coarctation ratio. Following an analysis of the results, it is evident that the pipeline is capable of running patient-specific CFD simulations and can present clinically relevant results. It is noted that this work is a proof of concept and so several steps are discussed that will improve the pipeline

    From Benchtop to Beside: Patient-specific Outcomes Explained by Invitro Experiment

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    Study: Recent analyses show that females have higher early postoperative (PO) mortality and right ventricular failure (RVF) than males after left ventricular assist device (LVAD) implantation; and that this association is partially mediated by smaller LV size in females. Benchtop experiments allow us to investigate patient-specific (PS) characteristics in a reproducible way given the fact that the PS anatomy and physiology is mimicked accurately. With multiple heart models of varying LV size, we can directly study the individual effects of titrating the LVAD speed and the resulting bi-ventricular volumes, shedding light on the interplay between LV and RV as well as resulting inter-ventricular septum (IVS) positions, which may cause the different outcomes pertaining to sex. Methods: In vitro, we studied the impact of the heart size to IVS position using two smaller and two larger sized PS silicone heart phantoms derived from clinical CT images (Fig. 1A). With ultrasound crystals that were integrated on a placeholder inflow cannula, the IVS position was measured during LV and RV volume changes (dV) mimicking varying ventricular loading states (Fig. 1B). Figure 1 A Two small (blue) and two large PS heart phantoms (orange) on B benchtop. C Median septum curvature results. LVEDD/LVV/RVV: LV enddiastolic diameter/LV and RV volume. Results: Going from small to large dV, at zero curvature, the septum starts to shift towards the left; for smaller hearts at dV = -40 mL and for larger hearts at dV = -50 mL (Fig. 1C). This result indicates that smaller hearts are more prone to an IVS shift to the left than larger hearts. We conclude that smaller LV size may therefore mediate increased early PO LVAD mortality and RVF observed in females compared to males. Novel 3D silicone printing technology enables us to study accurate, PS heart models across a heterogeneous patient population. PS relationships can be studied simultaneously to clinical assessments and support the decision-making prior to LVAD implantation

    Vascular Hemodynamics CFD Modeling

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    Three dimensional pulsatile blood flow CFD simulations in geometrically genuine normal and non-normal (aneurysm) human neck-head vascular systems nominally spanning the aortic arch to the circle of Willis has been performed and studied. CT scans of the human aortic arch and the carotid arteries were interpreted to obtain geometric data defining the boundary for a vascular CFD simulation. This was accomplished by reconstructing the surface from the anatomical slices and by imposing pertinent boundary conditions at the various artery termini. Following automated formation of a non-conformal CFD mesh, steady and unsteady laminar and low turbulent simulations were performed both for the normal and aneurysm models. Atherosclerosis and atherosclerotic induced aneurysms can occur in the ascending aorta. The results showed marked differences in the flow dynamics for the two models. Secondary flow is induced in both of the models due to the curvature of the aortic arch which is distorted in three dimensions. Counter clockwise rotating vortex formation was seen at the aneurysm segment in the ascending aorta for the aneurysm model which was absent for the normal case. The effect of the aneurysm bulge was seen in regions proximal to it at peak reverse flow causing secondary flow. These secondary aortic blood flows are though to have an effect on the wall shear stress distribution. Maximum pressure regions for the aneurysm were observed at regions distal to it indicating the possible location for rupture. Wall shear force (WSF) values for the normal case at the aortic bend were low indicating the possible reason for the formation of the aneurysm in the first place. The WSF values at the aneurysm segment for the aneurysm case were also low supporting the low shear stress induced atherosclerotic aneurysms theory. These results may act as a precursor for a multiscale Large eddy simulation model (LES) for pulsatile blood flow eliminating the need for a priori definition of the flow as laminar or turbulent

    Maritime Computing Transportation, Environment, and Development: Trends of Data Visualization and Computational Methodologies

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    This research aims to characterize the field of maritime computing (MC) transportation, environment, and development. It is the first report to discover how MC domain configurations support management technologies. An aspect of this research is the creation of drivers of ocean-based businesses. Systematic search and meta-analysis are employed to classify and define the MC domain. MC developments were first identified in the 1990s, representing maritime development for designing sailboats, submarines, and ship hydrodynamics. The maritime environment is simulated to predict emission reductions, coastal waste particles, renewable energy, and engineer robots to observe the ocean ecosystem. Maritime transportation focuses on optimizing ship speed, maneuvering ships, and using liquefied natural gas and submarine pipelines. Data trends with machine learning can be obtained by collecting a big data of similar computational results for implementing artificial intelligence strategies. Research findings show that modeling is an essential skill set in the 21st century

    The Performance Analysis of the Thermal Discrete Element Method Computations on the GPU

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    The paper presents a GPU implementation of the thermal discrete element method (TDEM) and the comparative analysis of its performance. Several discrete element models for granular flows, the bonded particle model and the TDEM are considered for quantitative comparison of computational performance. The performance measured on NVIDIA(R) Tesla™ P100 GPU is compared with that attained by running the same OpenCL code on Intel(R) Xeon™ E5-2630 CPU with 20 cores. The presented GPU implementation of the TDEM increases the computing time of the bonded particle model only up to 30.6 % of the computing time of the simplest DEM model, which is an acceptable decrease in the performance required for solving coupled thermomechanical problems
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