Skip to main content Link Menu Expand (external link) Document Search Copy Copied

Application

Application of the optimized and uncertainty-minimized FFCM-2.

Table of contents

  1. Hybrid chemistry (HyChem) modeling
  2. List of FFCM-2 based HyChem models
  3. References

Hybrid chemistry (HyChem) modeling

The development of foundational fuel chemistry model is not only critical to small hydrocarbons, but relevant to the modeling of real, multicomponent fuel combustion.

Recently, a physics-based hybrid chemistry (HyChem) modeling approach was developed for modeling combustion chemistry of large hydrocarbons and real, distillate fuels1$^{,}$2$^{,}$3$^{,}$4$^{,}$5$^{,}$6$^{,}$7. The HyChem approach decouples the high-temperature combustion of large hydrocarbons and real, liquid fuels into two stages that are separable in temporal and spatial scales: the fuel first undergoes a rapid decomposition to produce a mixture of smaller intermediate species; these fragments, consisting primarily of foundational fuels, are oxidized to the final combustion products. The fuel decomposition is a fast process, and can be modeled with a few global, lumped reactions. The stoichiometric coefficients and rate constants of the lumped reactions can be determined by solving an inverse problem, using as targets the speciation data of thermal and oxidative pyrolysis experiments conducted in shock tube and flow reactor. The rate limiting step is the oxidation of the fragments, which must be treated with a detailed, foundational fuel chemistry model.

A major challenge in kinetic modeling of the real, multi-component fuels is to determine the chemical compositions precisely. The HyChem approach treats the real fuel as one single species to resolve this issue. Also, HyChem uses a few global, lumped reactions to decouple the fuel decomposition from the oxidation of foundational fuel mixtures. It avoids compiling a great many reaction pathways and rate constants that cannot be studied by first-principle or experiments. The number of chemical species and reactions in the HyChem models are significantly reduced to the level of foundational fuel chemistry. The model could be further reduced to 40 to 50 species to be applicable to CFD simulations. The HyChem approach has been successfully applied to modeling a series of conventional jet fuels1$^{,}$2, synthetic jet fuels3, rocket fuels2, gasoline fuels6, sustainable aviation fuels4 and formation of NOx from the Jet A fuel5.

An issue identified in the earlier HyChem work is that the uncertainties of HyChem models remain large, due to the uncertainties in the foundational fuel chemistry2$^{,}$4. Thus, an accurate and uncertainty-minimized foundational C0−4 combustion chemistry model is critical to modeling large hydrocarbons and real, distillate fuels.

List of FFCM-2 based HyChem models

Fuel POSF number Type & Applications Status
JP-8 A1, POSF 10264 Distillate jet fuel Working in progress
Jet A A2, POSF 10325 Distillate jet fuel Available8
JP-5 A3, POSF 10289 Distillate jet fuel Available
JP-10 N/A Synthetic jet fuel Available
RP2-1 POSF 7688 Distillate rocket fuel Available
RP2-2 POSF 5433 Distillate rocket fuel Available
Shell A N/A Gasoline fuel Working in progress
Shell D N/A Gasoline fuel Working in progress
Gevo ATJ C1, POSF 11498 Synthetic jet fuel Available8
Gevo ATJ POSF 12394 Synthetic jet fuel Available8
C5 POSF 12345 Synthetic jet fuel Working in progress
n-Dodecane N/A Pure species Available

References

  1. Wang, H., Xu, R., Wang, K., Bowman, C. T., Hanson, R. K., Davidson, D. F., Brezinsky, K. & Egolfopoulos, F. N. (2018). A physics-based approach to modeling real-fuel combustion chemistry-I. Evidence from experiments, and thermodynamic, chemical kinetic and statistical considerations. Combustion and Flame, 193, 502-519. ↩ ↩2

  2. Xu, R., Wang, K., Banerjee, S., Shao, J., Parise, T., Zhu, Y., Wang, S., Movaghar, A., Lee, D., Zhao, R., Han, X., Gao, Y., Lu, T., Brezinsky, K., Egolfopoulos, F., Davidson, D., Hanson, R., Bowman, C. T. & Wang, H. (2018). A physics-based approach to modeling real-fuel combustion chemistry–II. Reaction kinetic models of jet and rocket fuels. Combustion and Flame, 193, 520-537. ↩ ↩2 ↩3 ↩4

  3. Tao, Y., Xu, R., Wang, K., Shao, J., Johnson, S., Movaghar, A., Han, X., Park, J. W., Lu, T., Brezinsky, K., Egolfopoulos, F., Davidson, D., Hanson, R., Bowman, C. T. & Wang, H. (2018). A Physics-based approach to modeling real-fuel combustion chemistry–III. Reaction kinetic model of JP10. Combustion and Flame, 198, 466-476. ↩ ↩2

  4. Wang, K., Xu, R., Parise, T., Shao, J., Movaghar, A., Lee, D., Park, J. W., Gao, Y., Lu, T., Egolfopoulos, F., Davidson, D., Hanson, R., Bowman, C. T. & Wang, H. (2018). A physics-based approach to modeling real-fuel combustion chemistry–IV. HyChem modeling of combustion kinetics of a bio-derived jet fuel and its blends with a conventional Jet A. Combustion and Flame, 198, 477-489. ↩ ↩2 ↩3

  5. Saggese, C., Wan, K., Xu, R., Tao, Y., Bowman, C. T., Park, J. W., Lu, T. & Wang, H. (2020). A physics-based approach to modeling real-fuel combustion chemistry–V. NOx formation from a typical Jet A. Combustion and Flame, 212, 270-278. ↩ ↩2

  6. Xu, R., Saggese, C., Lawson, R., Movaghar, A., Parise, T., Shao, J., Choudhary, R., Park, J. W., Lu, T., Hanson, R. K., Davidson, D. F., Egolfopoulos, F. N., Aradi, A., Prakash, A., Mohan, V. R. R., Cracknell, R. & Wang, H. (2020). A physics-based approach to modeling real-fuel combustion chemistry–VI. Predictive kinetic models of gasoline fuels. Combustion and Flame, 220, 475-487. ↩ ↩2

  7. Xu, R., & Wang, H. (2021). A physics-based approach to modeling real-fuel combustion chemistry–VII. Relationship between speciation measurement and reaction model accuracy. Combustion and Flame, 224, 126-135. ↩

  8. Zhang, Y., Dong, W., Vandewalle, L. A., Xu, R., Smith, G. P. & Wang, H. (2023). Foundational Fuel Chemistry Model 2 - iso-Butene chemistry and application in modeling alcohol-to-jet fuel combustion. Combustion and Flame, submitted. ↩ ↩2 ↩3

Table of contents

Back to top

Copyright © 2023 Stanford Foundational Fuel Chemistry Model Initiative