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Currently, it is challenging to investigate aneurismal hemodynamics based on current in vivo data such as Magnetic Resonance Imaging or Computed Tomography due to the limitations in both spatial and temporal resolutions. In this work, we investigate the use of modal analysis at various resolutions to examine its usefulness for analyzing blood flows in brain aneurysms. Two variants of Dynamic Mode Decomposition (DMD): (i) Hankel-DMD; and (ii) Optimized-DMD, are used to extract the time-dependent dynamics of blood flows during one cardiac cycle. First, high-resolution hemodynamic data in patient-specific aneurysms are obtained using Computational Fluid Dynamics. Second, the dynamics modes, along with their spatial amplitudes and temporal magnitudes are calculated using the DMD analysis. Third, an examination of DMD analyses using a range of spatial and temporal resolutions of hemodynamic data to validate the applicability of DMD for low-resolution data, similar to ones in clinical practices. Our results show that DMD is able to characterize the inflow jet dynamics by separating large-scale structures and flow instabilities even at low spatial and temporal resolutions. Its robustness in quantifying the flow dynamics using the energy spectrum is demonstrated across different resolutions in all aneurysms in our study population. Our work indicates that DMD can be used for analyzing blood flow patterns of brain aneurysms and is a promising tool to be explored in in vivo.
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This content will become publicly available on August 1, 2026
Dynamic Mode Decomposition of Geostrophically Balanced Motions From SWOT Cal/Val in the Separated Gulf Stream
Abstract The decomposition of oceanic flow into its geostrophically balanced and unbalanced motions carries theoretical and practical significance for the oceanographic community. These two motions have distinct dynamical characteristics and affect the transport of tracers differently from one another. The launch of the Surface Water and Ocean Topography (SWOT) satellite provides a prime opportunity to diagnose the surface balanced and unbalanced motions on a global scale at an unprecedented spatial resolution. Here, we apply dynamic‐mode decomposition (DMD), a linear‐algebraic data‐driven method, to tidally‐forced idealized and realistic numerical simulations at submesoscale‐permitting resolution and one‐day‐repeat SWOT observations of sea‐surface height (SSH) in the Gulf Stream downstream of Cape Hatteras, a region commonly referred to as the separated Gulf Stream. DMD is able to separate out the spatial modes associated with sub‐inertial periods from super‐inertial periods. The sub‐inertial modes of DMD can be used to extract geostrophically balanced motions from SSH fields, which have an imprint of internal gravity waves, so long as the data extends long enough in time. We utilize the statistical relation between relative vorticity and strain rate as the metric to gauge the extraction of geostrophy.
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- Award ID(s):
- 2123740
- PAR ID:
- 10636383
- Publisher / Repository:
- AGU
- Date Published:
- Journal Name:
- Earth and Space Science
- Volume:
- 12
- Issue:
- 8
- ISSN:
- 2333-5084
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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