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Abstract A novel methodology is developed to extract accurate skeletal reaction models for nuclear combustion. Local sensitivities of isotope mass fractions with respect to reaction rates are modeled based on the forced optimally time-dependent (f-OTD) scheme. These sensitivities are then analyzed temporally to generate skeletal models. The methodology is demonstrated by conducting skeletal reduction of constant density and temperature burning of carbon and oxygen relevant to Type Ia supernovae (SNe Ia). The 495-isotopes Torch model is chosen as the detailed reaction network. A map of maximum production of56Ni in SNe Ia is produced for different temperatures, densities, and proton-to-neutron ratios. The f-OTD simulations and the sensitivity analyses are then performed with initial conditions from this map. A series of skeletal models are derived and their performances are assessed by comparison against currently existing skeletal models. Previous models have been constructed intuitively by assuming the dominance ofα-chain reactions. The comparison of the newly generated skeletal models against previous models is based on the predicted energy release and44Ti and56Ni abundances by each model. The consequences ofye≠ 0.5 in the initial composition are also explored whereyeis the electron fraction. The simulated results show that56Ni production decreases by decreasingyeas expected, and that the43Sc is a key isotope in proton and neutron channels toward56Ni production. It is shown that an f-OTD skeletal model with 150 isotopes can accurately predict the56Ni abundance in SNe Ia forye≲ 0.5 initial conditions.
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Skeletal reaction models for methane combustion
A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). The sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.
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- Award ID(s):
- 2042918
- PAR ID:
- 10545913
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Fuel
- Volume:
- 357
- Issue:
- PA
- ISSN:
- 0016-2361
- Page Range / eLocation ID:
- 129581
- Subject(s) / Keyword(s):
- Methane-air combustion Skeletal model Local sensitivity analysis Forced optimally time dependent modes High-pressure
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.fuel.2023.129581
