Automatic Extension of a Semi-Detailed Synthetic Fuel Reaction Mechanism

Abstract

To identify promising sustainable fuels, e.g., to select novel synthetic fuels with the greatest impact on minimizing global warming, new methods for rapid and economical technical fuel assessment are urgently needed. Here, numerical models that are capable of predicting technical key data quickly and without experimental setup are necessary. One method is the use of chemical kinetic models, which are able to predict the technical key parameters related to combustion behavior. For a rapid technical fuel assessment, these chemical kinetic models need to be validated for new fuel components and for different temperature and pressure ranges. This work presents a new approach to extend the existing semi-detailed chemical kinetic models. For the application of the approach, the semi-detailed reaction mechanism DLR Concise was selected and extended for the low temperature combustion modeling of n-heptane and isooctane. The open-source software reaction mechanism generator (RMG) was used for this extension. Furthermore, an optimization of the merged chemical kinetic model with the linear transformation model (linTM) was conducted in order to improve the reproducibility of ignition delay times. The improvement of the predictive performance of ignition delay times at low temperatures for both species was successfully demonstrated. Therefore, this approach can be used to quickly add new species or reaction pathways to an existing semi-detailed reaction mechanism to enable a model-based technical fuel assessment for the early identification of promising fuels.

Keywords

• chemical kinetic mechanism
• automatic model generation
• synthetic fuels
• model optimization
• RMG
• semi-detailed