Field Geometry Incompletely Reconstructs Realized Vortical Adjacency in Turbulent Dissipation Forecasting

We test whether the topological organization of the vorticity field carries predictive information about future local dissipation in turbulence, beyond low-order field-geometry features. Using a coarse-grained Eulerian-cell representation of forced isotropic turbulence (Johns Hopkins Turbulence Database, Re_lambda about 433), we construct a vortex skeleton graph and adapt the relational-advantage framework developed for granular force-network ensembles (FNE-I). Relational (graph) features add predictive value for future dissipation at every horizon tested, growing with prediction horizon, and surviving five robustness checks including a strengthened geometric baseline that explicitly includes vorticity and velocity-gradient-tensor invariants. The Contact Realization Underdetermination index CRU_turb is about 0.58, placing turbulence between glassy dynamics (CRU about 0) and granular force networks (CRU 0.94 to 0.99), interpreted as a hypothesis as an epistemic rather than ontic form of underdetermination. This is a companion study to FNE-I (granular force-network ensembles).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-18
DOI
https://doi.org/10.5281/zenodo.20745907
Primary Topic
Fluid Dynamics and Turbulent Flows
Type
preprint
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preprint

Field Geometry Incompletely Reconstructs Realized Vortical Adjacency in Turbulent Dissipation Forecasting

KyeongMin Kim
Zenodo (CERN European Organization for Nuclear Research)
Fluid Dynamics and Turbulent Flows
preprint

Field Geometry Incompletely Reconstructs Realized Vortical Adjacency in Turbulent Dissipation Forecasting

KyeongMin Kim
preprint en

Abstract

We test whether the topological organization of the vorticity field carries predictive information about future local dissipation in turbulence, beyond low-order field-geometry features. Using a coarse-grained Eulerian-cell representation of forced isotropic turbulence (Johns Hopkins Turbulence Database, Re_lambda about 433), we construct a vortex skeleton graph and adapt the relational-advantage framework developed for granular force-network ensembles (FNE-I). Relational (graph) features add predictive value for future dissipation at every horizon tested, growing with prediction horizon, and surviving five robustness checks including a strengthened geometric baseline that explicitly includes vorticity and velocity-gradient-tensor invariants. The Contact Realization Underdetermination index CRU_turb is about 0.58, placing turbulence between glassy dynamics (CRU about 0) and granular force networks (CRU 0.94 to 0.99), interpreted as a hypothesis as an epistemic rather than ontic form of underdetermination. This is a companion study to FNE-I (granular force-network ensembles).

Zenodo (CERN European Organization for Nuclear Research)
Fluid Dynamics and Turbulent Flows
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