Congratulations to our PhD Candidate Giampaolo Maio! His paper with title “A virtual chemical mechanism for prediction of NO emissions from flames” has been recently published on Combustion Theory and Modelling.
G. Maio, M. Cailler, A. Cuoci, B. Fiorina, A virtual chemical mechanism for prediction of NO emissions from flames, (2020), Combustion Theory and Modelling, In Press, DOI: 10.1080/13647830.2020.1772509
A reduced order kinetic model for NO (nitric oxide) prediction, based on the virtual chemistry methodology [M. Cailler, N. Darabiha, and B. Fiorina, Development of a virtual optimized chemistry method. Application to hydrocarbon/air combustion, Combust. Flame 211 (2020), pp. 281–302], is developed and applied. Virtual chemistry aims to optimise thermochemical properties and kinetic rate parameters of a network of virtual species and reactions. A virtual main chemical mechanism is dedicated to temperature and heat release prediction and is coupled with the flow governing equations, whereas satellite sub-mechanisms are designed to predict pollutants formation. Two virtual chemistry mechanisms are here employed: a main mechanism for calculating the temperature and heat release rate and a second mechanism dedicated to NO prediction. To recover the chemical structure of multi-mode combustion, both premixed and non-premixed flamelets are included in the learning database used to optimise the virtual NO mechanism. A multi-zone optimisation procedure is developed to accurately capture both fast and slow NO chemistry that include prompt, thermal and reburning pathways. The proposed NO sub-mechanism and optimisation methodology are applied to CH (Formula presented.) /air combustion. Laminar 1-D premixed and non-premixed flamelet configurations are first tested. The approach is then further assessed in 2-D CFD laminar flame simulations, by providing a direct comparison against detailed chemistry. 2-D premixed, non-premixed and partially premixed flame configurations are numerically investigated. For all cases, the virtual mechanism fairly captures temperature and (Formula presented.) chemistry with only 12 virtual species and 8 virtual reactions with a drastic CPU time reduction compared to detailed chemistry.