Particle-resolved optical diagnostics of solid fuel combustion for clean power generation: a review

Abstract

Chemical energy carriers are crucial for addressing challenges that arise from the time lag, large distances, and temporal fluctuations in renewable energy production, which lead to unbalanced energy production and demand. However, the thermochemical utilization of chemical energy carriers such as solid fuels must be widely decarbonized to achieve a climate-neutral circular economy, despite remaining important for reliable electricity generation and stable economics. To accomplish this, extensive fundamental research is required to understand the underlying chemical and physical processes that can potentially be realized on an industrial scale. This paper reviews optical diagnostics used for particle-level combustion studies for clean power generation applications. Specifically, we focus on particle-resolved optical experiments for oxy-fuel coal combustion, biomass combustion, and utilization of iron in a regenerative oxidation-reduction scheme. We summarize previous studies categorized by the type of fuels, used reactors, investigated parameters, and experimental methodology. To provide a shared understanding, phenomenological aspects of the multistage combustion process at the particle level are outlined using examples of bituminous coal and iron particle burning in hot gas, respectively. A selection of experimental studies is highlighted, with a particular methodological focus on the measurement of relevant quantities at the particle level. These representative examples address relevant parameters, including particle number density, particle size and shape, surface temperature, ignition and combustion time, gas flame structure, gas temperature and species, nanoparticle formation, gas velocity, and particle dynamics. Finally, open issues and unsolved problems that require further effort to improve diagnostics for solid fuel combustion studies are discussed.

Measurement Science and Technology’s second century underway

“…Looking back over the 2023 issues, review articles have remained prominent with articles covering smart optical coordinate and surface metrology [3], linear and nonlinear dimensionality reduction from fluid mechanics to machine learning [4], guided ultrasonic wave propagation imaging [5], mechanical ventilation based on machine learning [6], deep learning-based methods in structural reliability analysis [7], 3D optical measurement techniques [8], the application of Josephson voltage standards [9], combustion of metal particles [10], heterogeneous sensing for target tracking [11], quantitative gas property measurements by filtered Rayleigh scattering [12], optical fiber reflectometry detecting static and dynamic Rayleigh spectra [13], stimulated emission depletion microscopy [14], mechanical fault diagnosis based on deep transfer learning [15] and advanced combustion dynamics [16].…”