Breakthrough method to tame combustion instability using complex networks

Engineers have long battled a problem that can cause loud, damaging oscillations inside gas turbines and aircraft engines: combustion instability. These unwanted pressure fluctuations create vibrations so intense that they can cause fatal structural damage to combustor walls, posing a serious threat in many applications. Combustion instability occurs when acoustic waves, heat release, and flow patterns interact in a strong feedback loop, amplifying each other until the entire system becomes unstable.

The complex interaction has made it difficult to predict when and where dangerous oscillations will emerge. This challenge has motivated researchers to seek new analytical frameworks that can capture the key driving regions of combustion instability.

Now, a research team led by Professors Hiroshi Gotoda from Tokyo University of Science and Ryoichi Kurose from Kyoto University, Japan, has developed an innovative approach using network science to understand and suppress combustion instability. Their paper, published in Volume 24, Issue 1 of the journal Physical Review Applied on July 1, 2025, applies complex network analysis to spray combustion instability in a backward-facing step combustor.

In the ‘turbulence network,’ each point in the flow field is represented as a node with connections representing the strength of vortex interactions. The study reveals that the network exhibits a scale-free topology, which is a pattern where a few highly connected hubs dominate the entire system’s behavior.

The team discovered that these network hubs appear and disappear in sync with the formation and collapse of large-scale organized vortices. When such organized vortex structures form, a scale-free network topology emerges; when they collapse, the network topology disappears. Most importantly, the researchers identified specific regions that they referred to as ‘connector communities’—areas where different parts of the network interact most strongly. By strategically placing small physical obstacles in these critical regions, they successfully suppressed combustion instability. The obstacles disrupt the vortex interactions that sustain the destructive feedback loop, significantly reducing both acoustic pressure fluctuations and the coupling between pressure and heat release oscillations.

This work reveals the dynamic appearance, disappearance, and reappearance of scale-free topologies during spray combustion instability. This discovery extends our understanding beyond earlier research on gaseous combustion systems. Notably, this approach provides engineers with a new tool for identifying where to intervene in combustion systems to prevent instability, potentially leading to more stable combustors across various industrial applications.

Overall, the network-based analysis used in this study represents a promising fusion of mathematical information science with combustion research, offering a new paradigm for understanding complex fluid dynamics. “Our work shows that turbulence networks not only characterize the structural organization of turbulent flows but also provide deeper insights into the temporal evolution of dominant flow structures," note Profs. Gotoda and Kurose. “These findings offer important insights into network-based strategies for suppressing combustion instability.” This approach could be valuable for designing new combustors for gas turbines used for power generation and aircraft engines, contributing to multiple sustainable development goals in the form of cleaner energy and higher industrial and transportation efficiency.

Further work in this field will help address critical needs in new combustor design. “In our next study, we will conduct numerical simulations with different geometries and sizes of the obstacle to gain a deeper understanding of the suppression mechanism of spray combustion instability,” comment Profs. Gotoda and Kurose, with eyes on the future.

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Reference                    

1. DOI: 10.1103/zhkg-c3kh
   Authors: Kenta Kato¹, Hiroshi Gotoda¹, Yusuke Nabae¹, Maho Kawai², and Ryoichi Kurose²
   Affiliations:         
   ¹Department of Mechanical Engineering, Tokyo University of Science, Japan
   ²Department of Mechanical Engineering and Science, Kyoto University, Japan

        2. DOI: 10.1103/PhysRevE.110.024204
           Authors: Kenta Kato¹, Hiroyuki Hashiba¹, Jun Nagao², Hiroshi Gotoda¹, Yusuke Nabae¹, and Ryoichi Kurose²
           Affiliations:         
             ¹Department of Mechanical Engineering, Tokyo University of Science, Japan
            ²Department of Mechanical Engineering and Science, Kyoto University, Japan