Super-resolution flow-field reconstruction in rotating detonation combustors

Abstract

The high-resolution flow field information is crucial for understanding the operational mechanisms of rotating detonation combustors (RDCs). However, due to limitations in sensor technology and observation techniques, the present experimental methods face great challenges in obtaining high-resolution data of RDCs. In the study, a novel physics-informed deep generative model is proposed for super-resolution flow-field reconstruction with low-resolution inputs. Compare to other methods, the application of physics-based constraints in this method enables accurate reconstruction of critical phenomena in RDCs while maintaining physics consistency. Additionally, the proposed super-resolution reconstruction method can be further employed for low sampling depth even binary input data, thereby evidently reducing the sampling depth per measurement point, which helps to overcome the challenges associated with high-frequency data acquisition and facility the implementation of larger-scale measurement arrays. As an extension to the measurement capabilities in reactive flow systems, the presented model possesses notable engineering significance.