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News/A Reinforcement-Learning-Augmented Liquid-Fueled Reactor Network Model for Predicting Lean Blowout in Gas Turbine Combustors
arxiv
PublishedJuly 22, 2026 at 4:00 AM
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A Reinforcement-Learning-Augmented Liquid-Fueled Reactor Network Model for Predicting Lean Blowout in Gas Turbine Combustors

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2607.19281v1 Announce Type: new Abstract: This study introduces a reinforcement learning (RL) framework for generating optimal liquid-fueled reactors to improve lean blowout (LBO) predictions in gas turbine combustors. Existing approaches for determining cluster boundaries rely on manual heuri

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Mentioned models
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    k-means clustering
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    actor-critic RL agent
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#reinforcement-learning#clustering#gas-turbine#combustors

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Mentioned models
02
  • 01
    k-means clustering
  • 02
    actor-critic RL agent
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#reinforcement-learning#clustering#gas-turbine#combustors

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