ABSTRACT
The detection of chemiluminescence from various radicals and molecules in a hydrocarbon flame can provide valuable information on the rate of local heat release, combustion stability, and combustion completeness. In this study, chemiluminescence from the combustion process is detected using a high-speed color camera within the broadband spectrum of visible light. Whereon, a novel hyperspectral reconstruction approach based on the physically plausible spectral reconstruction (PPSR) is employed to reconstruct the spectral chemiluminescence signals from 400 to 700 nm with a resolution of 10 nm to provide 31 different spectral channels. The reconstructed key chemiluminescence signals (e.g., CH*, CH2O*, C2*, and CO2*) from the color images are further analyzed to characterize the chemical kinetics and combustion processes under engine conditions. The spectral chemiluminescence evolution with engine crank angle is identified to comprehend the effect of H2 fraction on flame characteristics and combustion kinetics. Additionally, in this study, a detailed kinetic mechanism is adopted to deepen the theoretical understanding and describe the spectral chemiluminescence from H2/CH4 and H2/CH4/n-dodecane flames at relevant conditions for various species including OH*, CH*, C2*, and CO2*. The results indicate that the PPSR is an adequately reliable approach to reconstructing spectral wavelengths based on chemiluminescence signals from the color images, which can potentially provide qualitative information about the evolution of various species during combustion. Here, the reconstructed chemiluminescence images show less than 1% errors compared to the raw images in red, green, and blue channels. Furthermore, the reconstructed chemiluminescence trends of CH*, CH2O*, C2*, and CO2* show a good agreement with the detailed kinetics 0D simulation.
ABSTRACT
We provide research findings on the physics of aerosol and droplet dispersion relevant to the hypothesized aerosol transmission of SARS-CoV-2 during the current pandemic. We utilize physics-based modeling at different levels of complexity, along with previous literature on coronaviruses, to investigate the possibility of airborne transmission. The previous literature, our 0D-3D simulations by various physics-based models, and theoretical calculations, indicate that the typical size range of speech and cough originated droplets ( d ⩽ 20 µ m ) allows lingering in the air for O ( 1 h ) so that they could be inhaled. Consistent with the previous literature, numerical evidence on the rapid drying process of even large droplets, up to sizes O ( 100 µ m ) , into droplet nuclei/aerosols is provided. Based on the literature and the public media sources, we provide evidence that the individuals, who have been tested positive on COVID-19, could have been exposed to aerosols/droplet nuclei by inhaling them in significant numbers e.g. O ( 100 ) . By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols ( d ⩽ 20 µ m ) over distances O ( 10 m ) in generic environments. We study susceptible and infected individuals in generic public places by Monte-Carlo modelling. The developed model takes into account the locally varying aerosol concentration levels which the susceptible accumulate via inhalation. The introduced concept, 'exposure time' to virus containing aerosols is proposed to complement the traditional 'safety distance' thinking. We show that the exposure time to inhale O ( 100 ) aerosols could range from O ( 1 s ) to O ( 1 min ) or even to O ( 1 h ) depending on the situation. The Monte-Carlo simulations, along with the theory, provide clear quantitative insight to the exposure time in different public indoor environments.
