Abstract

Rotating detonation engines combine compact geometry with the potential for higher specific impulse compared to deflagration-based propulsion, enabled by pressure-gain combustion. However, their increased thermal loads present a major challenge. In the current literature, thermal characterisation of rotating detonation hardware relies either on experimental reconstructions or on high-fidelity simulations. A predictive and coolant-coupled low-order heat transfer model for rotating detonation rocket engines is not yet available in the open literature. This paper introduces such a reduced-order predictive tool for rotating detonation combustors, capable of estimating both cycle-averaged wall heat flux and coolant thermal behaviour. Implemented in Python, the tool supports any propellant available in NASA’s Chemical Equilibrium with Applications and CoolProp, handles single-phase thermodynamic regimes, and spans geometric and operating ranges from laboratory-scale test rigs to engine-relevant conditions. With computation times below one second, it enables rapid trade studies, model-based screening, and sensitivity analyses. Benchmarking was performed against experimental test cases covering H2/O2, CH4/O2 and C2H4/O2 mixtures, as well as multiple injector geometries and chamber configurations. The approach complements existing high-fidelity tools by offering a low-order alternative grounded in transparent assumptions and benchmarked against multiple datasets.

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