Characterization of a high-pressure flame facility using high-speed chemiluminescence and OH LIF imaging

Independent technical summary

The study develops and characterizes a laboratory-scale, optically accessible high-pressure burner facility operating with premixed methane–air flames. The facility is intended as a controlled testbed for optical combustion diagnostics and for investigations of flame behaviour and species distributions at elevated pressure. The paper characterizes the diagnostic platform and selected flame conditions; it does not by itself validate soot or detailed chemical-kinetic models.

Flame behaviour was examined using kHz-rate hydroxyl and methylidyne chemiluminescence imaging, OH laser-induced fluorescence imaging and two-color OH-LIF thermometry. For the OH-LIF and thermometry measurements, a stainless-steel disk mounted above the burner surface stabilized the flames at pressures up to 10 bar.

Approximately 10 ns Nd:YAG laser pulses at 283.305 nm excited the Q₁(7) rotational line of the OH A²Σ⁺–X²Π (1,0) band. Fluorescence was detected from the A–X (1,1) and (0,0) bands.

The OH-LIF signal varied linearly with laser energy within the investigated range. Increasing pressure from 1 to 10 bar produced a nonlinear reduction in signal. Collisional-quenching corrections explained only part of that loss, indicating that laser-beam absorption, fluorescence trapping and other pressure-dependent spectroscopic effects must also be considered before absolute or quantitatively transferable OH information is inferred.

The measured OH excitation spectrum agreed well with LIFBASE predictions. Equivalence-ratio scans at different pressures were consistent with Cantera equilibrium calculations. Two-dimensional OH distributions and two-color OH-LIF temperature fields showed qualitative agreement with ANSYS Fluent flame simulations. These comparisons support diagnostic interpretation and model plausibility, but they are not equivalent to quantitative validation of the CFD, chemistry or absolute OH field.

Technical contribution

The work establishes a documented experimental platform that combines elevated-pressure operation, optical access, high-speed imaging, laser diagnostics and numerical comparison. It therefore supports diagnostic-method development and controlled studies of pressure-dependent flame structure and stability within the characterized operating domain.

A central contribution is the explicit identification of high-pressure limitations in OH-LIF signal quantification. The study shows that collisional quenching alone is insufficient to explain the observed pressure dependence and that optical attenuation, fluorescence trapping and related spectroscopic effects must be considered before quantitative OH interpretation.

Diagnostic and modelling framework

• laboratory-scale, optically accessible high-pressure burner;
• premixed methane–air flames;
• kHz-rate OH* and CH* chemiluminescence imaging;
• OH laser-induced fluorescence imaging;
• two-color OH-LIF thermometry;
• flame stabilization up to 10 bar using a stainless-steel disk;
• comparison of excitation spectra with LIFBASE;
• equilibrium comparisons using Cantera;
• qualitative comparison of OH and temperature fields with ANSYS Fluent simulations.

Scope and application boundary

The facility was characterized for the reported premixed methane–air configurations and demonstrated up to 10 bar for the OH-LIF and thermometry measurements. This operating range should not be presented as equivalent to the full 30–50 bar pressure range cited for modern gas-turbine combustors and turbine inlets.

The OH-distribution and temperature comparisons with ANSYS Fluent were qualitative. They do not constitute complete quantitative validation of the numerical model, combustion chemistry, heat-loss treatment or absolute OH concentration.

Quantitative OH-LIF at elevated pressure requires treatment of collisional quenching, spectral broadening, laser-sheet absorption, fluorescence trapping, detector response and spatially varying temperature and composition. Calibration, uncertainty propagation and the spatial and temporal resolution of the diagnostic must also be appropriate to the quantity being reported. Neglecting these effects can distort inferred concentration and temperature fields.

The stainless-steel stabilization disk is part of the experimental boundary condition. Its influence on heat loss, recirculation, flame shape and local transport should be considered when transferring the findings to another burner or interpreting comparisons with an unstabilized flame.

Evidence interpretation

The paper combines facility characterization, chemiluminescence, OH-LIF imaging, two-color thermometry and numerical comparison. These are complementary evidence types with different levels of quantitative content.

Chemiluminescence and planar LIF can characterize flame location, structure and relative signal behaviour, while absolute concentration or temperature interpretation requires the corresponding calibration, spectroscopic corrections and uncertainty analysis. Qualitative agreement with a simulation supports physical plausibility but does not by itself validate reaction kinetics, soot chemistry or all local transport fields.

Publisher access

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Citation

Swain, W., Wang, Y., Parajuli, P., Hay, M., Saylam, A., Dreier, T., Schulz, C., & Kulatilaka, W. (2023). Characterization of a high-pressure flame facility using high-speed chemiluminescence and OH LIF imaging. Experiments in Fluids, 64, Article 71. https://doi.org/10.1007/s00348-023-03611-0

Relation to burner CFD and kinetic-intelligence work

This publication characterizes the experimental facility and its optical-diagnostic behaviour. The separate high-pressure sooting-flame study addresses burner geometry, flow structure and soot-related CFD, while later kinetic-intelligence work addresses mechanism reduction, reaction-network analysis and adaptive chemistry. These are distinct evidence layers; facility characterization does not automatically validate the CFD or the later kinetic methods, and the reverse is also true.

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• Kinetic Intelligence — reduction, network analysis and adaptive chemistry