Investigating Turbulent Dynamics in the Nocturnal Boundary Layer: A Large Eddy Simulation Study of the South Fork Wind Farm

Abstract In this study, Large Eddy Simulations (LES) with realistic inflow conditions are conducted to investigate the dynamics of the nocturnal marine atmospheric boundary layer (MABL) (with approximately 8 m/s mean inflow speeds) around the South Fork Wind Farm, completed in March 2024 and located 35 miles offshore and east of Montauk Point, NY. The LES framework incorporates 12 turbines represented by actuator disk models. We analyze the turbulence and circulation dynamics in the wake regions, focusing on the effects of tilting and stretching on vorticity as they represent the biggest budget terms. Our findings reveal that these processes intensify circulation and induce convergent (upward) motions in the near wake, while acting as sinks of vorticity in the far wake, thereby weakening circulation and facilitating flow recovery mechanisms. Additionally, we identify shear production as the primary source of turbulent kinetic energy (TKE) downstream of the actuator discs, peaking above the hub height, particularly at the top tip. The summer nocturnal boundary layer typically has consistent upward buoyancy flux. Heating at the surface induces convection and produces TKE. Overall, TKE is primarily removed through dissipation and transport.

Authors

Institutions

Publication Details

Journal
Journal of Physics Conference Series
Published
2025-05-01
DOI
https://doi.org/10.1088/1742-6596/3016/1/012048
Citations
1
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
4.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating Turbulent Dynamics in the Nocturnal Boundary Layer: A Large Eddy Simulation Study of the South Fork Wind Farm

Adam Ayouche, Baylor Fox‐Kemper, Georgios Matheou, Yongjie Lu
1 citations
Journal of Physics Conference Series
Wind Energy Research and Development
4.99
article

Investigating Turbulent Dynamics in the Nocturnal Boundary Layer: A Large Eddy Simulation Study of the South Fork Wind Farm

Adam Ayouche, Baylor Fox‐Kemper, Georgios Matheou, Yongjie Lu
article en
1 citations

Abstract

Abstract In this study, Large Eddy Simulations (LES) with realistic inflow conditions are conducted to investigate the dynamics of the nocturnal marine atmospheric boundary layer (MABL) (with approximately 8 m/s mean inflow speeds) around the South Fork Wind Farm, completed in March 2024 and located 35 miles offshore and east of Montauk Point, NY. The LES framework incorporates 12 turbines represented by actuator disk models. We analyze the turbulence and circulation dynamics in the wake regions, focusing on the effects of tilting and stretching on vorticity as they represent the biggest budget terms. Our findings reveal that these processes intensify circulation and induce convergent (upward) motions in the near wake, while acting as sinks of vorticity in the far wake, thereby weakening circulation and facilitating flow recovery mechanisms. Additionally, we identify shear production as the primary source of turbulent kinetic energy (TKE) downstream of the actuator discs, peaking above the hub height, particularly at the top tip. The summer nocturnal boundary layer typically has consistent upward buoyancy flux. Heating at the surface induces convection and produces TKE. Overall, TKE is primarily removed through dissipation and transport.

Journal of Physics Conference SeriesVol. 3016(1)
University of Connecticut (US), Brown University (US)
Openalex Percentile: Top 6%
Wind Energy Research and Development
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.