Background Computational Methodology Results Conclusions + future directions

Investigation of the influence ofturbine-to-turbine interaction

on their performance using OpenFOAM

Dr Gavin Tabor, Mulualem Gebreslassie, Prof Mike Belmont

CEMPS, University of Exeter

Background Computational Methodology Results Conclusions + future directions

Background: Lift/Drag Turbine

Novel design for tidal turbine based on cycloidal turbine involvingcomplex rotating airfoil blades

• Blades act in drag mode on one side; rotate (0.5Ω) to developlift on other side

• Unit operates as cross-flow turbine

• Energy extracted through volume – high efficiency (measuredefficiency of ∼ 50%

• High blockage factor; suitable for near-surface (eg. esturine)sites.

• Development backed by AquaScientific Ltd – someexperimental and esturine testing done

Background Computational Methodology Results Conclusions + future directions

Background Computational Methodology Results Conclusions + future directions

Project aims

Ultimate aim : to model large (100+) farms of units

Proximate aim : low-cost CFD model of multiple units to studyinteractions. However; detailed turbine blade motion too costly;simple actuator disk models insufficiently detailed.

• Developed new Immersed Body Force technique to treat blademotion

• LES turbulence formulation – need to examine large scaletransient motions

• VOF – free surface important for turbine behaviour

Computational code used : OpenFOAM

Background Computational Methodology Results Conclusions + future directions

LES and VOF

Filtered NSE including body force terms :

∇.u = 0,

∂tu +∇.(u ⊗u ) = ∇.(S − B) + F

S = −pI + 2νD

B is SGS Stress term : effect of SGS turbulence on GS flowrepresented by 1-equation eddy viscosity model.

F represents artificial body force term.

Background Computational Methodology Results Conclusions + future directions

VOF

FSF represented by indicator function α

∂α

∂t+∇.(αu ) +∇.(α(1− α)ur ) = 0

Final term is artificial compression term active only on interface.

Physical properties calculated as weighted average of individualcomponents;

µ = αµw + (1− α)µa

Background Computational Methodology Results Conclusions + future directions

Turbine modelling

Immersed body force method :

• Blades represented by bodyforces

F = FD + F L

• Compromise between accuracyand efficiency

• Capable of representing largescale vortexes

Background Computational Methodology Results Conclusions + future directions

What is OpenFOAM?

OpenFOAM is an Open Source CCM code/code library :

• Written in C++

• Based on FVM on arbitrary unstructured (polyhedral cell)meshes

• Originally developed by Henry Weller and others at IC (1990 –2000); Nabla Ltd (2000 – 2004) as FOAM

• Now released (2004 –) under Gnu GPL by OpenCFD Ltd.(http://www.opencfd.co.uk/)

• Extensive user community

• Extensions and variants released by 3rd parties (-dev, pyFoam)

• Academic and commercial usage.

Background Computational Methodology Results Conclusions + future directions

Strictly, OpenFOAM is not a CFD code – it is a C++ library ofclasses for writing CFD codes.

OpenFOAM uses the full range of the C++ language –inheritance, polymorphism, templating, operator overloading etc –where appropriate :

• Class mechanism – define new “types” for CFD

• Interface vs implementation : segregation of effort.

• Operator Overloading – provides standard mathematicalsyntax

• Inheritance, polymorphism etc – encodes relationshipsbetween conceptual entities in code

Effective result is a high level “language” for encoding CFD.

Background Computational Methodology Results Conclusions + future directions

Validation

Laboratory testing carried outin flow channel; flow rate andturbine rotation under a rangeof mechanical torqueconditions :

• Flow rate measured withrotormeter

• Torque output usingmechanical system

• Rotation rate recordedoptically.

Compared with functionallyequivalent CFD simulations.

Background Computational Methodology Results Conclusions + future directions

Single Turbine simulation

Background Computational Methodology Results Conclusions + future directions

Wake profiles

Background Computational Methodology Results Conclusions + future directions

Two turbine simulations

• Reduced efficiencyby 18% at 15Dturbine spacing

• Reduced efficiencyby at least 7% at20D spacing

Background Computational Methodology Results Conclusions + future directions

Three turbine simulations

• Performance of middleturbine improved due toblockage effect at 2Dlateral spacing

• As the lateral spacingincreased to 4D theblockage effect wasreduced

Background Computational Methodology Results Conclusions + future directions

Seven turbine simulations

• 3D spacing inflicted highenergy shadowing ondownstream row

• Increased lateral spacing(6D) reduces the wakeinteraction and theperformance of thedownstream row improved

• There was a blockageeffect on the performanceof the base turbine in themiddle row

Background Computational Methodology Results Conclusions + future directions

Seven turbine simulations

Background Computational Methodology Results Conclusions + future directions

Summary

• IBF model constructed and successfully validated – goodcomparison with experimental results

• Successfully generates large scale vortex behaviour – LES andfree surface simulation to capture other important effects

• Low cost method allows turbine/turbine interaction to besimulated. Wake decay also shown (single and multipleturbines)

• Able to examine other turbine issues (eg. effects of venturiplates)

Background Computational Methodology Results Conclusions + future directions

Future directions

Intention to take this work in two directions – higher detail andlarger scale.

Higher detail – PhD project (Matt Berry) to simulate detailedblade motion – MRF, GGI, overset meshing

Larger scale – EPSRC-funded project to develop farm modelling;ROM for individual turbines in linked array, poweroptimisation and flood risk modelling

Background Computational Methodology Results Conclusions + future directions

Any Questions?