Reduced Order Modeling Framework for Combustor Instabilities Using Truncated Domain Training
This work addresses the high computational cost of simulating combustion instabilities in rocket engines, offering a more efficient ROM training approach for aerospace engineers.
The paper presents a multi-fidelity framework for predicting combustion instabilities in rocket engines, using projection-based reduced order models trained on truncated domains to reduce training costs. Numerical tests on a quasi-1D rocket combustor show enhanced predictive capabilities and robustness compared to traditional ROMs.
A multi-fidelity framework is established and demonstrated for prediction of combustion instabilities in rocket engines. The major idea is to adapt appropriate fidelity modeling approaches for different components in a rocket engine to ensure accurate and efficient predictions. Specifically, the proposed framework integrates projection-based Reduced Order Models (ROMs) that are developed using bases generated on truncated domain simulations. The ROM training is performed on truncated domains, and thus does not require full order model solutions on the full rocket geometry, thus demonstrating the potential to greatly reduce training cost. Geometry-specific training is replaced by the response generated by perturbing the characteristics at the boundary of the truncated domain. This training method is shown to enhance predictive capabilities and robustness of the resulting ROMs, including at conditions outside the training range. Numerical tests are conducted on a quasi-1D model of a single-element rocket combustor and the present framework is compared to traditional ROM development approaches.