TY - JOUR
T1 - In-Situ Adaptive Manifolds
T2 - Enabling computationally efficient simulations of complex turbulent reacting flows
AU - Lacey, Cristian E.
AU - Novoselov, Alex G.
AU - Mueller, Michael E.
N1 - Funding Information:
The authors gratefully acknowledge funding from the Army Research Office (ARO) Young Investigator Program (YIP) under grant W911NF-17-1-0391 and the National Aeronautics and Space Administration (NASA) under grant NNX16AP90A . C.E.L. gratefully acknowledges the Daniel and Florence Guggenheim Foundation Fellowship for additional funding support. The simulations presented in this article were performed on computational resources supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Office of Information Technology’s High Performance Computing Center and Visualization Laboratory at Princeton University.
Funding Information:
The authors gratefully acknowledge funding from the Army Research Office (ARO) Young Investigator Program (YIP) under grant W911NF-17-1-0391 and the National Aeronautics and Space Administration (NASA) under grant NNX16AP90A. C.E.L. gratefully acknowledges the Daniel and Florence Guggenheim Foundation Fellowship for additional funding support. The simulations presented in this article were performed on computational resources supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Office of Information Technology's High Performance Computing Center and Visualization Laboratory at Princeton University.
Publisher Copyright:
© 2020 The Combustion Institute
PY - 2021/1
Y1 - 2021/1
N2 - Reduced-order manifold approaches to turbulent combustion modeling traditionally involve precomputation of manifold solutions and pretabulation of the thermochemical database versus a small number of manifold variables. However, additional manifold variables are required as the complexity of turbulent combustion processes increases through consideration of, for example, multi-modal, non-adiabatic, or non-isobaric combustion, or combustion featuring multiple and/or inhomogeneous inlets. This increase in the number of manifold variables comes with an increase in the computational cost of precomputing a greater number of manifold solutions, most of which are never actually utilized in a CFD calculation. The memory required to store the pretabulated high-dimensional thermochemical database also increases, practically limiting the complexity of manifold-based combustion models. In this work, a new In-Situ Adaptive Manifolds (ISAM) approach is developed that overcomes this limitation by combining ‘on-the-fly’ calculation of manifold solutions with In-Situ Adaptive Tabulation (ISAT), enabling the use of more complex manifold-based turbulent combustion models. The performance of ISAM is evaluated via LES of turbulent nonpremixed jet flames with both hydrogen and hydrocarbon fuels. A performance assessment indicates that the computational overhead associated with ISAM compared to pretabulation ranges from negligible up to a factor of two, with most of this overhead associated with convolution of the thermochemical state against a presumed subfilter PDF. In addition, the memory requirements of ISAM are more than two orders of magnitude less than conventional tabulation. These results demonstrate the potential for ISAM to accommodate significantly more complex manifold-based combustion models.
AB - Reduced-order manifold approaches to turbulent combustion modeling traditionally involve precomputation of manifold solutions and pretabulation of the thermochemical database versus a small number of manifold variables. However, additional manifold variables are required as the complexity of turbulent combustion processes increases through consideration of, for example, multi-modal, non-adiabatic, or non-isobaric combustion, or combustion featuring multiple and/or inhomogeneous inlets. This increase in the number of manifold variables comes with an increase in the computational cost of precomputing a greater number of manifold solutions, most of which are never actually utilized in a CFD calculation. The memory required to store the pretabulated high-dimensional thermochemical database also increases, practically limiting the complexity of manifold-based combustion models. In this work, a new In-Situ Adaptive Manifolds (ISAM) approach is developed that overcomes this limitation by combining ‘on-the-fly’ calculation of manifold solutions with In-Situ Adaptive Tabulation (ISAT), enabling the use of more complex manifold-based turbulent combustion models. The performance of ISAM is evaluated via LES of turbulent nonpremixed jet flames with both hydrogen and hydrocarbon fuels. A performance assessment indicates that the computational overhead associated with ISAM compared to pretabulation ranges from negligible up to a factor of two, with most of this overhead associated with convolution of the thermochemical state against a presumed subfilter PDF. In addition, the memory requirements of ISAM are more than two orders of magnitude less than conventional tabulation. These results demonstrate the potential for ISAM to accommodate significantly more complex manifold-based combustion models.
KW - In-Situ Adaptive Tabulation (ISAT)
KW - Large Eddy Simulation (LES)
KW - Manifold-based modeling
KW - Turbulent nonpremixed combustion
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U2 - 10.1016/j.proci.2020.06.207
DO - 10.1016/j.proci.2020.06.207
M3 - Article
AN - SCOPUS:85090473844
SN - 1540-7489
VL - 38
SP - 2673
EP - 2680
JO - Proceedings of the Combustion Institute
JF - Proceedings of the Combustion Institute
IS - 2
ER -