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conference cpote2026 logo
CPOTE2026 | 9th International Conference on
Contemporary Problems of Thermal Engineering
23-25 September 2026 | Kraków, Poland | In-person

Abstract CPOTE2026-3006-A

A stochastic reactor model with crevice flow and flame–wall quenching for ammonia–hydrogen engine emission prediction

Tim FRANKEN, Brandenburg University of Technology Cottbus-Senftenberg, Germany
Michał PASTERNAK, LOGE Polska Sp. z o.o., Poland
Reddy Babu SIDDAREDDY, LOGE Polska Sp z o.o., Poland
Christine MOUNAÏM-ROUSSELLE, University of Orléans, France
Fabian MAUSS, Brandenburg University of Technology Cottbus-Senftenberg, Germany

Ammonia-hydrogen engines have been introduced as a carbon-free technology for the future transport sector. However, their practical deployment is challenged by harmful emissions of NH3, NO, and N2O, with N2O being particularly concerning due to its strong greenhouse gas effect. Hence, it is of great importance to minimise emissions over the entire engine operating range. Zero-dimensional stochastic reactor model (SRM) accounts for finite-rate chemistry and is a powerful tool for the optimisation of engine operation. However, predicting emissions from ammonia-hydrogen engines remains challenging because crevice flow and flame-wall interaction effects have not been considered. To address this limitation, models for crevice flow and flame-wall quenching are implemented in SRM in this work. The new model is validated against engine experiments comprising a sweep of hydrogen fraction, equivalence ratio and engine speed. The results highlight that the crevice volume plays an important role in trapping NH3 during combustion. In combination with flame–wall quenching, this mechanism allows unburned NH3 to escape into the exhaust, with larger crevice volumes leading to higher NH3 emissions. In addition, NH3 released from the crevice back into the burned gas zone initiates the reaction sequence NH3 → NH2 → NH → N2O, thereby enhancing N2O formation.

Keywords: Ammonia-hydrogen combustion, Detailed chemistry, Stochastic reactor model, Emissions, Spark ignition engine