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research-article

Methodology for CFD Validation for Medical Use: Application to Intracranial Aneurysm

[+] Author and Article Information
Nikhil Paliwal

Department of Mechanical & Aerospace Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA; Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA
npaliwal@buffalo.edu

Robert Damiano

Department of Mechanical & Aerospace Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA; Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA
rjdamian@buffalo.edu

Nicole Varble

Department of Mechanical & Aerospace Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA; Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA
nvarble@buffalo.edu

Vincent Tutino

Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA; Department of Biomedical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
vincentt@buffalo.edu

Zhongwang Dou

Department of Mechanical & Aerospace Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
zhongwan@buffalo.edu

Adnan Siddiqui

Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA; Department of Neurosurgery, University at Buffalo, the State University of New York, Buffalo, NY, USA
asiddiqui@ubns.com

Hui Meng

Department of Mechanical & Aerospace Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA; Toshiba Stroke and Vascular Research Center, University at Buffalo, the State University of New York, Buffalo, NY, USA; Department of Biomedical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA; Department of Neurosurgery, University at Buffalo, the State University of New York, Buffalo, NY, USA
huimeng@buffalo.edu

1Corresponding author.

ASME doi:10.1115/1.4037792 History: Received January 20, 2017; Revised August 28, 2017

Abstract

Computational fluid dynamics (CFD) is a promising tool to aid in clinical diagnoses of cardiovascular diseases. However, it uses assumptions that simplify the complexities of the real cardiovascular flow. Due to high-stakes in the clinical setting, it is critical to calculate the effect of these assumptions in the CFD simulation results. However, existing CFD validation approaches do not quantify error in the simulation results due to the CFD solver's modeling assumptions. Instead, they directly compare CFD simulation results against validation data. Thus, to quantify the accuracy of a CFD solver, we developed a validation methodology that calculates the CFD model error (arising from modeling assumptions). Our methodology identifies independent error sources in CFD and validation experiments, and calculates the model error by parsing out other sources of error inherent in simulation and experiments. To demonstrate the method, we simulated the flow field of a patient-specific intracranial aneurysm in the commercial CFD software STAR-CCM+. Particle image velocimetry provided validation datasets for the flow field on 2 orthogonal planes. The average model error in the STAR-CCM+ solver was 5.63%±5.49% along the intersecting validation line of the orthogonal planes. Furthermore, we demonstrated that our validation method is superior to existing validation approaches by applying 3 representative existing validation techniques to our CFD and experimental dataset, and comparing the validation results. Our validation methodology offers a streamlined workflow to extract the "true" accuracy of a CFD solver.

Copyright (c) 2017 by ASME
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