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Hariharan P, D'Souza GA, Horner M, et al. Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations. PLoS One. 2017;12(6):e0178749doi: 10.1371/journal.pone.0178749.
Hariharan, P., D'Souza, G. A., Horner, M., Morrison, T. M., Malinauskas, R. A., & Myers, M. R. (2017). Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations. PloS one, 12(6), e0178749. https://doi.org/10.1371/journal.pone.0178749
Hariharan, Prasanna, et al. "Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations." PloS one vol. 12,6 (2017): e0178749. doi: https://doi.org/10.1371/journal.pone.0178749
Hariharan P, D'Souza GA, Horner M, Morrison TM, Malinauskas RA, Myers MR. Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations. PLoS One. 2017 Jun 08;12(6):e0178749. doi: 10.1371/journal.pone.0178749. eCollection 2017. PMID: 28594889; PMCID: PMC5464577.
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PLoS One. 2017 Jun 08;12(6):e0178749. doi: 10.1371/journal.pone.0178749. eCollection 2017.

Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations.

PloS one

Prasanna Hariharan, Gavin A D'Souza, Marc Horner, Tina M Morrison, Richard A Malinauskas, Matthew R Myers

Affiliations

  1. US Food and Drug Administration, Silver Spring, Maryland, United States of America.
  2. ANSYS, Inc., Evanston, Illinois, United States of America.

PMID: 28594889 PMCID: PMC5464577 DOI: 10.1371/journal.pone.0178749

Abstract

A "credible" computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing "model credibility" is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a "threshold-based" validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results ("S") of velocity and viscous shear stress were compared with inter-laboratory experimental measurements ("D"). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student's t-test. However, following the threshold-based approach, a Student's t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical devices.

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