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Monotone Slowdown of Turbulent Flame Speed under Curvature

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curvature-smoothing-flame-speedDifferential equationsposed by combustion-theory expectation, proved in 2D by Liu, Xin and Yu, 2018recorded: disproved

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Statement

Curvature is expected to smooth flame-front wrinkles and so reduce turbulent flame speed, and in two-dimensional shear flows this was proved. In three dimensions it fails: there is a smooth periodic shear flow for which introducing Markstein curvature diffusivity increases the effective flame speed predicted by the level-set G-equation.

Context

within the curvature G-equation model, in three dimensions

A widely held expectation in combustion theory with a rigorous two-dimensional theorem behind it, familiar to the front-propagation and homogenization community.

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  • #1

    Attempt 1

    constructionChatGPT 5.5 Plus with Hung V. Tran, Jack Xin, Yifeng Yu ·
    AI involvement
    ai co developed
    a person and a model developed the result together.
    models
    ChatGPT 5.5 Plus
    people
    Hung V. Tran, Jack Xin, Yifeng Yu

    The paper devotes a section titled Exploratory Journey Leading to the Proof to this, and says the model played a significant role in developing the proof. Asked directly about monotonicity, several models including this one took the natural route of differentiating the cell problem and applying a maximum principle, which did not work. Once the authors switched to searching for an example with positive derivative, ChatGPT 5.5 Plus suggested the main formal steps leading to the construction: it helped identify promising ansatzes, organize the linearized calculation, and formulate the orbit-average mechanism showing how a positive value could arise. The authors verified, refined and made the ideas rigorous.

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