Cerebral aneurysm blood flow simulations: There's solver settings and then there's solver settings.
Venue: Journal of biomechanics

http://dx.doi.org/10.1016/j.jbiomech.2017.04.039 0021-9290/ 2017  Thanks to Google Scholar, we were instantly alerted to the article from Dennis et al. (2017), entitled ‘‘Cerebral aneurysm blood flow simulations are sensitive to basic solver settings” which demonstrated the impact of time-step size and residual error tolerances on aneurysm CFD solutions. While we appreciate the attention that is being paid, finally, to robust verification of cardiovascular CFD models, we were surprised and disappointed that the authors appeared to be unaware of a study published in 2015, in which we looked at the compounding effects of mesh density, time-step size and solver numerics on aneurysm CFD (Khan et al., 2015). In particular, we demonstrated the clear benefits of using high-order numerical schemes allowing for coarser mesh and time-step resolutions vs. prevalent low-order, dissipative schemes with fine resolutions. While our study relied on open-source solvers, we did include in the Discussion a sanity check using Fluent. Specifically, for a single (steady inflow) model with fixed mesh density and time-step size, we gradually refined several Fluent solver settings from their default values, and showed that this had a non-negligible effect on the (suppression of) flow instabilities. Dennis et al. appeared to use expert choices for their fixed solver settings (e.g. solver order, pressure scheme, upwinding method). In our experience with aneurysm CFD Challenges, many groups are not using (and may not even be aware of) such expert options, but rather are relying on default solver settings, which often turn out to be low-order, dissipative schemes. We fear that Dennis et al.’s emphasis on residual error tolerances may draw attention away from those more basic and crucial solver settings. We also think the readership deserves more clarity from this Mayo Clinic group on the practical impact of what seem, at least from the single case shown in their Figs. 2–4, to be minor differences in peak systolic flow patterns due to the solver settings they chose to vary. Slight changes in the location or extent of an impingement jet or vortex core can lead to apparently large point-wise errors; however, one may question whether these are ‘‘large” relative to the uncertainties of aneurysm CFD and of clinical decision-making. For example, Dr. Kallmes has previously highlighted the problem of aneurysm neck overestimation by 3D angiography (Kallmes, 2011), which was subsequently shown to have a similar – or, depending upon one’s perspective, similarly minor – impact on intra-aneurysm flow and WSS (Schneiders et al., 2013). In this context, Dennis et al.’s paper might have the unintended and ironic effect of discouraging users from probing their basic solver settings if they perceive the reported differences to be, practically, negligible. Finally, Dennis et al. conclude that solution convergence ‘‘must be ensured individually and independently for each aneurysm simulation”, which echoes the conclusion of a previous grid refinement study from this group (Hodis et al., 2012). As we pointed out in Khan et al. (2015), such case-by-case verification is hardly pragmatic for large studies. (Or, to put it in clinical terms, it might well be efficacious, but it’s unlikely to be effective.) Instead, as argued in Khan et al. (2015), a more practicable approach would be to establish robust and rigorously calibrated CFD protocols, which aim to balance the trade-offs among CPU time, operator time, and the nominal accuracy required by the clinical or biological application. In summary, we regret that Dennis et al. missed this opportunity to reflect upon, and perhaps rebut, some of the issues raised in our 2015 study. In writing this letter, we hope to stimulate such dialog for the benefit of the aneurysm CFD community.