Dr.ir. D.J.N. (Dries) Allaerts
Dr.ir. D.J.N. (Dries) Allaerts
Profile
Expertise
- Wind-farm flow dynamics
- Boundary-layer meteorology
- Atmospheric stability
- Atmospheric gravity waves
- Computational fluid dynamics
- High-performance computing
- Scientific programming
Current position
- Assistant Professor (Wind Energy), TU Delft (AE), 2020 -- current
Previous positions
- R&D engineer, Diabatix (BE), 2019 -- 2020
- Postdoctoral researcher, NREL (National Renewable Energy Laboratory; US), 2018 -- 2019
- Postdoctoral researcher, KU Leuven (BE), 2016 -- 2018
- PhD researcher, KU Leuven (BE), 2012 -- 2016
Education
- PhD in Mechanical Engineering, KU Leuven (BE), 2016
- MSc in Energy Engineering, KU Leuven (BE), 2012
- BSc in Mechanical Engineering, KU Leuven (BE), 2010
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Biography
Dries Allaerts is a Tenure Track Assistant Professor at the faculty of Aerospace Engineering in the Wind Energy Section. Previously, he was a postdoctoral researcher at the National Renewable Energy Laboratory (NREL) in Boulder, CO, US, and at KU Leuven in Belgium. He obtained his PhD at the same university in 2016.
His research interests cover the development of Computational Fluid Dynamics (CFD) techniques and their application to wind-farm flow dynamics in realistic atmospheric conditions. Two particular areas of interest are Mesoscale-to-Microscale Coupling (MMC) and regional-scale flow effects caused by wind farms, such as upstream flow blockage, extended downstream wake regions, and self-induced gravity waves.
Expertise
Publications
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2024
A shear stress parametrization for arbitrary wind farms in conventionally neutral boundary layers
S. Stipa / D.J.N. Allaerts / Joshua Brinkerhoff
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2024
TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows
S. Stipa / Arjun Ajay / D.J.N. Allaerts / Joshua Brinkerhoff
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2023
A Novel Framework for Spatiotemporal Analysis of Temperature Profiles Applied to Europe
S. Jamaer / D. Allaerts / J. Meyers / N. P.M. Van Lipzig
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2023
Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy
Sue Ellen Haupt / Branko Kosović / Larry K. Berg / Colleen M. Kaul / Matthew Churchfield / Jeffrey Mirocha / D.J.N. Allaerts / Thomas Brummet / Shannon Davis / More Authors
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2023
Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site
Dries Allaerts / Eliot Quon / Matt Churchfield
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Courses 2023
Courses 2022
Media
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2023-04-25
tudies from Delft University of Technology in the Area of Wind Energy Reported (Using Observational Mean-flow Data To Drive Large-eddy Simulations of a Diurnal Cycle At the Swift Site)
Appeared in: Energy Daily News
Ancillary activities
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2022-11-17 - 2024-11-16
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2022-11-17 - 2024-11-16