On-demand generation of reduced mechanisms based on hierarchically extended intrinsic low-dimensional manifolds in generalized coordinates

König, Karin; Maas, Ulrich

doi:10.1016/j.proci.2008.05.039

Cited by 12 publications

(3 citation statements)

References 46 publications

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“…They obtained a combined speed up of over a factor of 10 for a propane mechanism with 117 species and 665 reactions in a laminar flame calculation. König and Mauss [124] have developed an on-demand, intrinsic low dimensional manifold (ILDM) method to reduce the computational requirements of detailed chemical kinetic mechanisms when calculating chemically reacting flows. Normally, the ILDM method requires the calculations of an ILDM table that covers the whole state space that is expected to be accessed by the computation.…”

Section: Reduction Of Detailed Chemical Kinetic Mechanismsmentioning

confidence: 99%

Recent progress in the development of diesel surrogate fuels

Pitz

Mueller

2011

Progress in Energy and Combustion Science

641

371

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There has been much recent progress in the area of surrogate fuels for diesel. In the last few years, experiments and modeling have been performed on higher molecular weight components of relevance to diesel fuel such as n-hexadecane (n-cetane) and 2,2,4,4,6,8,8-heptamethylnonane (iso-cetane). Chemical kinetic models have been developed for all the n-alkanes up to 16 carbon atoms. Also, there has been much experimental and modeling work on lower molecular weight surrogate components such as n-decane and n-dodecane that are most relevant to jet fuel surrogates, but are also relevant to diesel surrogates where simulation of the full boiling point range is desired. For two-ring compounds, experimental work on decalin and tetralin recently has been published. For multi-component surrogate fuel mixtures, recent work on modeling of these mixtures and comparisons to real diesel fuel is reviewed. Detailed chemical kinetic models for surrogate fuels are very large in size. Significant progress also has been made in improving the mechanism reduction tools that are needed to make these large models practicable in multidimensional reacting flow simulations of diesel combustion. Nevertheless, major research gaps remain. In the case of iso-alkanes, there are experiments and modeling work on only one of relevance to diesel: iso-cetane. Also, the iso-alkanes in diesel are lightly branched and no detailed chemical kinetic models or experimental investigations are available for such compounds. More components are needed to fill out the iso-alkane boiling point range. For the aromatic class of compounds, there has been no new work for compounds in the boiling point range of diesel. Most of the new work has been on alkyl aromatics that are of the range C7 to C8, below the C10 to C20 range that is needed. For the chemical class of cycloalkanes, experiments and modeling on higher molecular weight components are warranted. Finally for multi-component surrogates needed to treat real diesel, the inclusion of higher molecular weight components is needed in models and experimental investigations.

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Section: Reduction Of Detailed Chemical Kinetic Mechanismsmentioning

confidence: 99%

Recent progress in the development of diesel surrogate fuels

Pitz

Mueller

2011

Progress in Energy and Combustion Science

641

371

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“…The method was successfully applied for the development of reduced models describing the combustion of high-molecular-weight hydrocarbons, such as iso-octane and n-dodecane (Blasenbrey and Maas 2000). A further development of the ILDM algorithm applicable for slower processes was suggested by Maas and co-workers (Nafe and Maas 2002;Bykov and Maas 2007b;König and Maas 2009). Surovtsova and co-workers (2009) applied the ILDM method to several biochemical systems and implemented the method (together with a modified version) within the computer code COPASI .…”

Section: Intrinsic Low-dimensional Manifoldsmentioning

confidence: 99%

Analysis of Kinetic Reaction Mechanisms

Turányi¹,

Tomlin²

2014

199

172

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“…After that, for each group of similar points (cluster), a reduced kinetic mechanism is generated via Directed Relation Graph with Error Propagation (DRGEP; Pepiot-Desjardins and Pitsch, 2008). The chemical reduction step can also be accomplished using different kinetic reduction techniques such as Computational Singular Perturbation or Intrinsic Low-Dimensional Manifolds (Maas, 1998;Valorani et al, 2006Valorani et al, , 2007König and Maas, 2009). After this step, a library of reduced mechanisms, corresponding to different chemical conditions, is obtained.…”

Section: Introductionmentioning

confidence: 99%

Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations

D’Alessio

Cuoci

Parente

2021

DCE

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The integration of Artificial Neural Networks (ANNs) and Feature Extraction (FE) in the context of the Sample- Partitioning Adaptive Reduced Chemistry approach was investigated in this work, to increase the on-the-fly classification accuracy for very large thermochemical states. The proposed methodology was firstly compared with an on-the-fly classifier based on the Principal Component Analysis reconstruction error, as well as with a standard ANN (s-ANN) classifier, operating on the full thermochemical space, for the adaptive simulation of a steady laminar flame fed with a nitrogen-diluted stream of n-heptane in air. The numerical simulations were carried out with a kinetic mechanism accounting for 172 species and 6,067 reactions, which includes the chemistry of Polycyclic Aromatic Hydrocarbons (PAHs) up to C $ {}_{20} $ . Among all the aforementioned classifiers, the one exploiting the combination of an FE step with ANN proved to be more efficient for the classification of high-dimensional spaces, leading to a higher speed-up factor and a higher accuracy of the adaptive simulation in the description of the PAH and soot-precursor chemistry. Finally, the investigation of the classifier’s performances was also extended to flames with different boundary conditions with respect to the training one, obtained imposing a higher Reynolds number or time-dependent sinusoidal perturbations. Satisfying results were observed on all the test flames.

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On-demand generation of reduced mechanisms based on hierarchically extended intrinsic low-dimensional manifolds in generalized coordinates

Cited by 12 publications

References 46 publications

Recent progress in the development of diesel surrogate fuels

Recent progress in the development of diesel surrogate fuels

Analysis of Kinetic Reaction Mechanisms

Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations

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