Reduced-Order Modeling Framework for Combustor Instabilities Using Truncated Domain Training

Abstract

A multifidelity framework is established and demonstrated for the prediction of combustion instabilities in rocket engines. The main 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 costs. 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 the predictive capabilities and robustness of the resulting ROMs, including at conditions outside the training range. Numerical tests are conducted on a quasi-one-dimensional model of a single-element rocket combustor, and the present framework is compared to traditional ROM development approaches.