Computational fluid dynamics can compute fractional flow reserve (FFR) accurately. However, existing models are limited by either the intravascular hemodynamic phenomarkers that can be captured or the fidelity of geometries that can be modeled. This study aimed to validate a new coronary angiography‐based FFR framework, FFRHARVEY, and examine intravascular hemodynamics to identify new biomarkers that…
Understanding the evolving nature of coronary hemodynamics is crucial for early disease detection and monitoring progression. We require digital twins that mimic a patient’s circulatory system by integrating continuous physiological data and computing hemodynamic patterns over months. Current models match clinical flow measurements but are limited to single heartbeats. To this end, we introduced the…
Tracking hemodynamic responses to treatment and stimuli over long periods remains a grand challenge. Moving from established single-heartbeat technology to longitudinal profiles would require continuous data describing how the patient’s state evolves, new methods to extend the temporal domain over which flow is sampled, and high-throughput computing resources. While personalized digital twins can accurately measure…
As biological research demands simulations with increasingly larger cell counts, optimizing these models for largescale deployment on heterogeneous supercomputing resources becomes crucial. This requires the redesign of fluid-structure interaction tasks written around distributed data structures built for CPU-based systems, where design flexibility and overall memory footprint are key considerations, to instead be performant on CPU-GPU…
Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with…
Cloud computing resources are becoming an increasingly attractive option for simulation workflows but require users to assess a wider variety of hardware options and associated costs than required by traditional in-house hardware or fixed allocations at leadership computing facilities. The pay-as-you-go model used by cloud providers gives users the opportunity to make more nuanced cost-benefit…
In this episode of Pratt School of Engineering’s Dean’s Minutes, Dean Lynch and Professor Amanda Randles talk about how digital twins — advanced, personalized computational models of a patient’s body — could help save lives.
Researchers at Duke are focused on understanding how 2-meter-long DNA is organized within a micron-size cell nucleus.