2 citations · 3 across the 5 of their papers we have counts for
5 papers
Numerically Consistent Non-Boussinesq Subgrid-scale Stress Model with Enhanced Convergence
Yuenong Ling, Adrián Lozano-Durán
We extend the data-assimilation approach of Ling and Lozano-Durán (AIAA 2025-1280) to develop machine-learning-based subgrid-scale stress (SGS) models for large-eddy simulation (LE…
General-purpose Data-driven Wall Model for Low-speed Flows Part I: Baseline Model
Yuenong Ling, Imran Hayat, Konrad Goc +1
We present a general-purpose wall model for large-eddy simulation. The model builds on the building-block flow principle, leveraging essential physics from simple flows to train a…
Building-block flow model for computational fluids
Gonzalo Arranz, Yuenong Ling, Sam Costa +2
We introduce a closure model for wall-modeled large-eddy simulation (WMLES), referred to as the Building-block Flow Model (BFM). The foundation of the model rests on the premise th…
Information-theoretic causality and applications to turbulence: energy cascade and inner/outer layer interactions
Adrián Lozano-Durán, Gonzalo Arranz, Yuenong Ling
We introduce an information-theoretic method for quantifying causality in chaotic systems. The approach, referred to as IT-causality, quantifies causality by measuring the informat…
Wall-modeled large-eddy simulation based on building-block flows
Yuenong Ling, Gonzalo Arranz, Emily Williams +3
A unified subgrid-scale (SGS) and wall model for large-eddy simulation (LES) is proposed by devising the flow as a collection of building blocks that enables the prediction of the…