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                <identifier>oai:data.mendeley.com/898c3r87pf.2</identifier>
                <datestamp>2026-10-08T07:53:11Z</datestamp>
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    <dc:creator>Mehdi, Ghazanfar</dc:creator>
    <dc:title>Plasma-Assisted Swirl Flame Dynamics: Imaging, Modal, and Acoustic Data</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>•	The dataset provides combined optical, modal, spectral, and acoustic measurements of plasma-assisted swirl flames, enabling a comprehensive assessment of how sinusoidal plasma discharges affect flame structure, stability, and combustion dynamics.
•	High-speed CH* chemiluminescence images document the evolution of flame lift-off, attachment, reaction-zone position, and heat-release fluctuations across equivalence ratios from Φ = 1.0 to Φ = 0.45, under plasma-off and plasma-on conditions.
•	The data demonstrate that plasma actuation extends the stable operating range of the combustor: at Φ = 0.45, a self-sustained flame is observed only when plasma is applied, providing direct experimental evidence of plasma-enhanced lean flame stabilization.
•	POD and SPOD results quantify the redistribution of fluctuation energy among coherent flame structures, showing that plasma reduces the dominance of low-order modes and suppresses energetic high-frequency oscillations.
•	The simultaneous analysis of microphone signals and POD mode coefficients links acoustic pressure fluctuations to flame-structure dynamics, supporting the interpretation of plasma-induced stabilization through reduced unsteady heat release and improved flame anchoring.
•	The dataset can be used to validate reduced-order and high-fidelity models of plasma–flame interaction, including models of plasma-enhanced ignition, radical production, mixing, heat release, and thermoacoustic response.
•	The paired plasma-off and plasma-on measurements, acquired under identical imaging settings, provide a consistent benchmark for future experimental, numerical, and machine-learning-based studies of plasma-assisted combustion.</dc:description>
    <dc:subject>Energy Engineering</dc:subject>
    <dc:subject>Mechanical Engineering</dc:subject>
    <dc:contributor>Bonuso, Sara</dc:contributor>
    <dc:contributor>Harth, Stefan Raphael</dc:contributor>
    <dc:contributor>Pescini, Elisa</dc:contributor>
    <dc:contributor>De Giorgi, Maria Grazia</dc:contributor>
    <dc:contributor>Kaario, Ossi</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/898c3r87pf.2</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/898c3r87pf.2</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:relation>https://data.mendeley.com/datasets/898c3r87pf</dc:relation>
    <dc:date>2026-10-08T07:53:11Z</dc:date>
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