Please use this identifier to cite or link to this item:
Title: Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: the ASME 2012 Summer Bioengineering Conference CFD Challenge
Authors: Steinman, David A. 
Hoi, Yiemeng 
Fahy, Paul 
Morris, Liam 
Walsh, Michael T 
Aristokleous, Nicolas 
Anayiotos, Andreas 
Papaharilaou, Yannis 
Arzani, Amirhossein 
Shadden, Shawn C 
Berg, Philipp 
Janiga, Gábor 
Bols, Joris 
Segers, Patrick 
Bressloff, Neil W. 
Cibis, Merih 
Gijsen, Frank H 
Cito, Salvatore 
Pallares, Jordi 
Browne, Leonard D 
Costelloe, Jennifer A 
Lynch, Adrian G 
Degroote, Joris 
Vierendeels, Jan 
Fu, Wenyu 
Qiao, Aike 
Hodis, Simona 
Kallmes, David F 
Kalsi, Hardeep 
Long, Quan 
Kheyfets, Vitaly O 
Finol, Ender A 
Kono, Kenichi 
Malek, Adel M 
Lauric, Alexandra 
Menon, Prahlad G. 
Pekkan, Kerem 
Esmaily Moghadam, Mahdi 
Marsden, Alison L 
Oshima, Marie 
Katagiri, Kengo 
Peiffer, Véronique 
Mohamied, Yumnah 
Sherwin, Spencer J 
Schaller, Jens 
Goubergrits, Leonid 
Usera, Gabriel 
Mendina, Mariana 
Valen-Sendstad, Kristian 
Habets, Damiaan F 
Xiang, Jianping 
Meng, Hui 
Yu, Yue 
Karniadakis, George E 
Shaffer, Nicholas 
Loth, Francis 
Major Field of Science: Engineering and Technology
Field Category: Mechanical Engineering
Keywords: Centerlines;Discretizations;Flow byes;Flow instabilities;Flow model;Fluid property;Future challenges;High temporal resolution;In-phase;Measured values;Micro CT;Microcomputed tomography;Phase I;Phase II;Physical model;Pressure patterns;Research groups;Solution strategy;Submillimeters;Systolic pressure
Issue Date: 2013
Source: Journal of Biomechanical Engineering, 2013, vol. 135, no. 2
Volume: 135
Issue: 2
Journal: Journal of Biomechanical Engineering 
Abstract: Stimulated by a recent controversy regarding pressure drops predicted in a giant aneurysm with a proximal stenosis, the present study sought to assess variability in the prediction of pressures and flow by a wide variety of research groups. In phase I, lumen geometry, flow rates, and fluid properties were specified, leaving each research group to choose their solver, discretization, and solution strategies. Variability was assessed by having each group interpolate their results onto a standardized mesh and centerline. For phase II, a physical model of the geometry was constructed, from which pressure and flow rates were measured. Groups repeated their simulations using a geometry reconstructed from a micro-computed tomography (CT) scan of the physical model with the measured flow rates and fluid properties. Phase I results from 25 groups demonstrated remarkable consistency in the pressure patterns, with the majority predicting peak systolic pressure drops within 8% of each other. Aneurysm sac flow patterns were more variable with only a few groups reporting peak systolic flow instabilities owing to their use of high temporal resolutions. Variability for phase II was comparable, and the median predicted pressure drops were within a few millimeters of mercury of the measured values but only after accounting for submillimeter errors in the reconstruction of the life-sized flow model from micro-CT. In summary, pressure can be predicted with consistency by CFD across a wide range of solvers and solution strategies, but this may not hold true for specific flow patterns or derived quantities. Future challenges are needed and should focus on hemodynamic quantities thought to be of clinical interest.
ISSN: 1528-8951
DOI: 10.1115/1.4023382
Rights: © American Society of Mechanical Engineers
Type: Article
Affiliation : Cyprus University of Technology 
University of Toronto 
Galway Mayo Institute of Technology 
University of Limerick 
Foundation for Research & Technology-Hellas (F.O.R.T.H.) 
Illinois Institute of Technology 
Otto von Guericke University of Magdeburg 
Ghent University 
University of Southampton 
Erasmus MC 
University Rovira i Virgili 
University of Limerick 
Beijing University of Technology 
Mayo Clinic 
Brunel University 
University of Texas at San Antonio 
Wakayama Rosai Hospital 
Tufts Medical Center 
Carnegie Mellon University 
University of California, San Diego 
Tokyo University of Science 
Shibaura Institute of Technology 
Imperial College London 
Charité-Universitätsmedizin Berlin 
Universidad de la República 
State University of New York at Buffalo 
Brown University, Providence 
University of Akron, Akron 
Appears in Collections:Άρθρα/Articles

CORE Recommender
Show full item record

Citations 5

checked on Aug 31, 2020


Last Week
Last month
checked on Oct 18, 2020

Page view(s)

Last Week
Last month
checked on Oct 23, 2020

Google ScholarTM



Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.