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Job Record #16606
TitleTwo funded PhD opportunities - wind farm LES
CategoryPhD Studentship
EmployerUniversity of British Columbia
LocationCanada, British Columbia, Kelowna
InternationalYes, international applications are welcome
Closure Date* None *
Two Funded PhD Positions Available 

Reduced-Order Modelling of Turbine Induction and Wake Blockage Effects in 
Large Wind Farms

Position description:

Dr. Joshua Brinkerhoff of the UBC School of Engineering and UBC Okanagan 
Computational Fluid Dynamics Laboratory is seeking applicants for a doctoral 
student (PhD) position in the area of Reduced-Order Modelling of Turbine 
Induction and Wake Blockage Effects in Large Wind Farms. The position is 
open to students who have completed a Masters degree in mechanical, wind 
energy, or aerospace engineering or a related discipline. Applicants with 
interests in fluid mechanics, computational fluid mechanics (CFD), numerical 
simulation, parallel computing, and wind turbine aerodynamics are encouraged 
to apply. Coding experience in Python/C/C++ and prior CFD experience is an 
asset, as is strong skills in CAD software and meshing tool for CFD. 
Students with experience in large-scale parallel computing, large eddy 
simulations (LES), programming in MPI, immersed boundary methods (IBM), and 
PETSc numerical libraries are particularly encouraged to apply, as are those 
with prior experience in wind energy systems.

There are two (2) open positions. The successful candidates will receive 
full financial support for their doctoral studies. This opportunity is 
available to Canadian citizens, permanent residents of Canada, and 
international applicants meeting the admission criteria for UBC Okanagan and 
School of Engineering. It is expected that successful candidates will 
commence graduate studies from January 1, 2021 or earlier. 

The project is a multi-disciplinary joint project involving industrial and 
academic collaborations. Dr. Joshua Brinkerhoff will supervise students in 
their computational research at UBC Okanagan. UL Renewables (https://aws- will provide industrial funding, support, and technology 
transfer. The computational research will be complemented by detailed field 
measurements conducted through the XWakes research project funded by the 
German Federal Ministry for Economic Affairs and Energy and conducted by 
Fraunhofer-Institut für Windenergiesysteme, Technical University of 
Braunschweig, Karlsruhe Institute of Technology (KIT), University of 
Oldenburg (Center for Wind Energy Research, ForWind), University of 
Tübingen, Helmholtz-Zentrum Geesthacht, and UL International GmbH. Direct 
partnership with these institutions promises candidates a unique, industry-
driven, and international research training opportunity yielding high-impact 
research outcomes.

Project description:

OpenWind® is an industry-leading software tool developed by UL LLC for 
determining the best layout of wind turbines in a wind farm. The software 
allows layout planning and resource estimation for proposed wind energy 
sites. Integral to the OpenWind® software are accurate, well-validated but 
simultaneously low-cost reduced-order models that capture the aeolian and 
aerodynamic processes within the wind farm. Two particularly important 
processes that are not presently well-captured are (1) the turbine induction 
effect upstream of the rotor and (2) the effect of interacting turbine wakes 
on the energy generation of neighbouring turbines. 

(1)	Induction effects: The induction effect produces a deceleration of 
the flow upstream of the turbine due to the elliptic influence of the 
momentum extracted from the flow at the turbine rotor disk. The result is an 
induction zone—a region of locally depressed wind velocity that propagates 
upstream from the turbine. Current reduced-order models of turbine induction 
do not account for several complicating factors known to influence wind farm 
performance: multiple rotors, the inter- and intra-row rotor spacing, wind 
shear affects, atmospheric stability conditions, complex terrain effects, 
and wind orientation with respect to a multirow wind farm. How these effects 
will impact the behaviour of the induction zone needs to be evaluated 
through large eddy simulations (LES), from which a reduced-order model can 
be developed and implemented into OpenWind®.

(2)	Wake-wake interactions: there is a persistent need for better models 
to parameterize the growth and interaction of turbine wakes. Turbine wakes 
have a significant impact on the power losses in a wind farm, as well as the 
turbine fatigue loading. Reducing crosswind spacing reduces costs in off-
shore installations due to the expense of subsea cabling, but may adversely 
impact wake-induced loads. A clearer picture of wake-wake interactions for a 
range of crosswind spacing needs to be developed, from which reduced-order 
models can be developed and implemented into OpenWind®. Moreover, large wind 
farms can create an upstream deceleration of the bulk flow entering the 
array due to the combined blockage effects of the individual turbine wakes, 
analogous to the induction around a single rotor. The existence of this 
effect, its sensitivity to the wind farm size, its dependence on the wind 
speed and direction, and the influence of turbine spacing needs to be 
investigated. Finally, so-called “deep array” effects—where a large wind 
farm acts like an increased surface roughness, generating an internal 
boundary layer of slower flow [6]—need to be parameterized within OpenWind® 
via a suitable reduced-order model that includes the impact of rotor thrust 
coefficient, terrain complexity, roughness, atmospheric stability, and wind 
speed profile.

The candidates will use an in-house, massively-parallel LES code to conduct 
the computational research, with the aim of (1) developing physics-based 
reduced-order models of turbine induction and wake effects in large wind 
turbine arrays, and (2) evaluating their fidelity via comparison to state-
of-the-art wind farm field measurements.

Training and professional development:

Candidates will receive high-quality formal and informal training in the 
following areas: (1) wind farm aerodynamics; (2) computational fluid 
dynamics; (3) turbulence; (4) high performance computing; (5) large eddy 
simulation; (6) reduced-order modelling. Candidates will have opportunities 
to author and participate in impactful peer-reviewed publications as well as 
present at national and international conferences. 

Application procedure:

Candidates are asked to submit:
• A cover letter describing their research interests, experience, and 
motivations for graduate study
• A detailed curriculum vitae highlighting their educational and 
professional achievements
• A list of three professional and/or academic references
• Unofficial transcripts from their Masters degree
• English test scores (if required). Applicants with degrees in a language 
other than English must have a minimum TOEFL score of 580 (PBT) or 92 (IBT) 
or IELTS minimum overall band of 6.5 (with nothing less than 6.0 per 
individual test)

Interested candidates should send the above documents and direct queries to 
Dr. Joshua Brinkerhoff ( Additional information 
of Dr. Brinkerhoff’s research is available from his research webpage: 

Equity and diversity are essential to academic excellence. An open and 
diverse research team fosters the inclusion of voices that have been 
underrepresented or discouraged. Equity and diversity not only lead to a 
more fair and open society, but also improves the quality of the science and 
increases the opportunities to learn and grow from each other. Dr. 
Brinkerhoff specifically encourages applications from members of groups that 
have been marginalized on any grounds enumerated under the B.C. Human Rights 
Code, including sex, sexual orientation, gender identity or expression, 
racialization, disability, political belief, religion, marital or family 
status, age, and/or status as a First Nation, Metis, Inuit, or Indigenous 

Contact Information:
Please mention the CFD Jobs Database, record #16606 when responding to this ad.
NameJoshua Brinkerhoff
Email ApplicationYes
AddressSchool Of Engineering
1137 Alumni Avenue
Record Data:
Last Modified19:33:03, Thursday, May 28, 2020

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