TACC: How Supercomputing Reveals Early Red Blood Cell Damage

Key Takeaways

• Stampede3 enabled high‑resolution RBC deformation simulations.
• Droplet model calibrated with data from twelve donors.
• OpenFOAM integration provided mechanistic flow predictions.
• Study paves way for safer mechanical circulatory support devices.
• ACCESS allocation offered free supercomputing core‑hours.

Summary

Researchers at Penn State used the Texas Advanced Computing Center's Stampede3 supercomputer, funded by NSF ACCESS, to run high‑resolution simulations of red blood cell deformation in mechanical circulatory support devices. By adapting a droplet deformation equation within OpenFOAM, the team calibrated a model against experimental data from twelve donors, achieving low prediction error. The study, published in the Annals of Biomedical Engineering, demonstrates how massive core‑hour allocations enable detailed biophysical insights that were impossible on standard workstations. These insights could inform safer blood‑pump designs and reduce hemolysis risk.

Pulse Analysis

Blood pumps are essential for heart‑failure patients, yet the shear forces they generate can rupture red blood cells, a phenomenon known as hemolysis. Traditional experimental approaches struggle to capture the rapid, three‑dimensional stresses that cells experience in these devices. By leveraging the massive parallelism of Stampede3, researchers can now simulate millions of cell interactions in realistic flow fields, revealing deformation patterns that were previously invisible. This computational depth bridges a critical gap between laboratory tests and clinical performance, offering a clearer picture of how device geometry influences cell trauma.

The core of the new methodology is a droplet‑based deformation framework implemented in the open‑source CFD platform OpenFOAM. Unlike earlier models that relied on simplified stress metrics, this approach treats each red blood cell as a fluid droplet whose shape evolves under complex, multidimensional flow conditions. Calibration against high‑speed microfluidic imaging from a dozen human donors yielded a mean absolute error well within biomedical tolerances, confirming the model’s predictive power. Stampede3’s allocation of tens of thousands of core‑hours reduced simulation runtimes from weeks on a laptop to days, making iterative design cycles feasible for engineering teams.

For device manufacturers and clinicians, the implications are immediate. Accurate, scalable simulations enable virtual testing of pump geometries before costly prototyping, accelerating the path to regulatory approval and market entry. Moreover, the digital‑twin capability opens avenues for patient‑specific optimization, where a pump’s operating parameters can be tuned to an individual’s blood rheology. As supercomputing resources become more accessible through programs like NSF ACCESS, the biomedical engineering field is poised to translate these high‑fidelity models into safer, more effective circulatory support technologies, ultimately saving lives and reducing treatment expenses.