A set of libraries and executables creating a workflow for performing
gradient-based optimisation loops. The main executable (adjointOptimisationFoam)
solves the flow (primal) equations, followed by the adjoint equations and,
eventually, the computation of sensitivity derivatives.
Current functionality supports the solution of the adjoint equations for
incompressible turbulent flows, including the adjoint to the Spalart-Allmaras
turbulence model and the adjoint to the nutUSpaldingWallFunction, [1], [2].
Sensitivity derivatives are computed with respect to the normal displacement of
boundary wall nodes/faces (the so-called sensitivity maps) following the
Enhanced Surface Integrals (E-SI) formulation, [3].
The software was developed by PCOpt/NTUA and FOSS GP, with contributions from
Dr. Evangelos Papoutsis-Kiachagias,
Konstantinos Gkaragounis,
Professor Kyriakos Giannakoglou,
Andy Heather
and contributions in earlier version from
Dr. Ioannis Kavvadias,
Dr. Alexandros Zymaris,
Dr. Dimitrios Papadimitriou
[1] A.S. Zymaris, D.I. Papadimitriou, K.C. Giannakoglou, and C. Othmer.
Continuous adjoint approach to the Spalart-Allmaras turbulence model for
incompressible flows. Computers & Fluids, 38(8):1528–1538, 2009.
[2] E.M. Papoutsis-Kiachagias and K.C. Giannakoglou. Continuous adjoint methods
for turbulent flows, applied to shape and topology optimization: Industrial
applications. 23(2):255–299, 2016.
[3] I.S. Kavvadias, E.M. Papoutsis-Kiachagias, and K.C. Giannakoglou. On the
proper treatment of grid sensitivities in continuous adjoint methods for shape
optimization. Journal of Computational Physics, 301:1–18, 2015.
Integration into the official OpenFOAM release by OpenCFD
- Don't remove the constant/polyMesh directory if it contains a
blockMeshDict or blockMeshDict.m4 file. Offer a reminder that
system/ is the normal place for it.
- include cleanup of other postProcessing directories:
* Ensight, EnSight, ensightWrite
- don't need to remove files that cleanSnappyFiles already removed:
* 0/cellLevel 0/pointLevel
- bundle removal of constant/ items together:
* constant/cellDecomposition constant/polyMesh constant/tetDualMesh
Provides efficient integration of complex laminar reaction chemistry,
combining the advantages of automatic dynamic specie and reaction
reduction with ISAT (in situ adaptive tabulation). The advantages grow
as the complexity of the chemistry increases.
References:
Contino, F., Jeanmart, H., Lucchini, T., & D’Errico, G. (2011).
Coupling of in situ adaptive tabulation and dynamic adaptive chemistry:
An effective method for solving combustion in engine simulations.
Proceedings of the Combustion Institute, 33(2), 3057-3064.
Contino, F., Lucchini, T., D'Errico, G., Duynslaegher, C.,
Dias, V., & Jeanmart, H. (2012).
Simulations of advanced combustion modes using detailed chemistry
combined with tabulation and mechanism reduction techniques.
SAE International Journal of Engines,
5(2012-01-0145), 185-196.
Contino, F., Foucher, F., Dagaut, P., Lucchini, T., D’Errico, G., &
Mounaïm-Rousselle, C. (2013).
Experimental and numerical analysis of nitric oxide effect on the
ignition of iso-octane in a single cylinder HCCI engine.
Combustion and Flame, 160(8), 1476-1483.
Contino, F., Masurier, J. B., Foucher, F., Lucchini, T., D’Errico, G., &
Dagaut, P. (2014).
CFD simulations using the TDAC method to model iso-octane combustion
for a large range of ozone seeding and temperature conditions
in a single cylinder HCCI engine.
Fuel, 137, 179-184.
Two tutorial cases are currently provided:
+ tutorials/combustion/chemFoam/ic8h18_TDAC
+ tutorials/combustion/reactingFoam/laminar/counterFlowFlame2D_GRI_TDAC
the first of which clearly demonstrates the advantage of dynamic
adaptive chemistry providing ~10x speedup,
the second demonstrates ISAT on the modest complex GRI mechanisms for
methane combustion, providing a speedup of ~4x.
More tutorials demonstrating TDAC on more complex mechanisms and cases
will be provided soon in addition to documentation for the operation and
settings of TDAC. Also further updates to the TDAC code to improve
consistency and integration with the rest of OpenFOAM and further
optimize operation can be expected.
Original code providing all algorithms for chemistry reduction and
tabulation contributed by Francesco Contino, Tommaso Lucchini, Gianluca
D’Errico, Hervé Jeanmart, Nicolas Bourgeois and Stéphane Backaert.
Implementation updated, optimized and integrated into OpenFOAM-dev by
Henry G. Weller, CFD Direct Ltd with the help of Francesco Contino.
- redistributePar to have almost (complete) functionality of decomposePar+reconstructPar
- low-level distributed Field mapping
- support for mapping surfaceFields (including flipping faces)
- support for decomposing/reconstructing refinement data
