A growing disparity between supercomputer computation speeds and I/O rates makes it
increasingly infeasible for applications to save all results for offline analysis. Instead …

The computational work to perform particle advection‐based flow visualization techniques
varies based on many factors, including number of particles, duration, and mesh type. In …

Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential
ensemble data assimilation framework is challenging due to the exponential growth in the …

We propose an Eulerian approach to compute the expected finite time Lyapunov exponent
(FTLE) of uncertain flow fields. The definition extends the usual FTLE for deterministic …

Identifying marine pollutant sources is essential to assess, contain and minimize their risk.
We propose a Lagrangian Particle Tracking algorithm (LPT) to study the transport of passive …

We study uncertainty in the dynamics of time-dependent flows by identifying barriers and
enhancers to stochastic transport. This topological segmentation is closely related to the …

The large-scale motions in 3D turbulent channel flows, known as Turbulent Superstructures
(TSS), play an essential role in the dynamics of small-scale structures within the turbulent …

This study evaluates the benefit of using parallelism from GPUs or multi-core CPUs for
particle advection workloads. We perform 1000+ experiments, involving four generations of …

Flow fields are often partitioned into data blocks for massively parallel computation and
analysis based on blockwise relationships. However, most of the previous techniques only …

FTLE (Finite Time Lyapunov Exponent) computation is one of the standard approaches to
Lagrangian flow analysis. The main features of interest in FTLE fields are ridges that …