Comprehensive reevaluation of acetaldehyde chemistry - part I : assessment of important kinetic parameters and the underlying uncertainties

Abstract

Understanding the combustion chemistry of acetaldehyde is crucial to developing robust and accurate combustion chemistry models for practical fuels, especially for biofuels. This study aims to re-evaluate the important rate and thermodynamic parameters for acetaldehyde combustion chemistry and determine the physical uncertainties of these parameters. The rate parameters of 79 key reactions are reevaluated using > 100,000 direct experiments and quantum chemistry computations from > 900 studies, and the thermochemistry (Δhf(298 K), s0(298 K) and cp) of 24 key species are reevaluated based on the ATCT database, the NIST Chemistry WebBook, the TMTD database, and 35 published chemistry models. The updated parameters are incorporated into a recent acetaldehyde chemistry model, which is further assessed against available fundamental experiments measurements (10 RCM-IDT, 123 ST-IDT, 633 JSR-species concentrations, and 102 flow reactor-species concentrations) and existing chemistry models, with clearly better performance obtained in the high-temperature regime. Sensitivity and flux analyses further highlight the insufficiencies of previous models in representing the key pathways, particularly the branching ratios of acetaldehyde- and formaldehyde-consuming pathways. Meanwhile, temperature-dependent and temperature-independent uncertainties are statistically evaluated for kinetic and thermochemical parameters, respectively, where the large differences between the updated and the original model parameters reveal the necessity of reassessment of kinetic and thermochemical parameters completely based on direct experiments and theoretical calculations for rate and thermodynamic parameters. The application of the determined uncertainty domains of the key kinetic and thermodynamic parameters is further demonstrated through a case study, with the modelling uncertainty and its reliability highlighted. With the configured uncertainty domain of the updated acetaldehyde chemistry model, further uncertainty quantification and optimization can be conducted to improve the model performance, which is currently under progress in the authors’ group.