Symbolic regression can produce parsimonious, interpretable closure models for reduced-order simulations that match or beat neural network and structural closures on under-resolved flow benchmarks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Symbolic Regression of Data-Driven Reduced Order Model Closures for Under-Resolved, Convection-Dominated Flows
Symbolic regression can produce parsimonious, interpretable closure models for reduced-order simulations that match or beat neural network and structural closures on under-resolved flow benchmarks.