An optimized, data-driven reaction mechanism for Dual-Fuel combustion of Ammonia and Diesel Primary Reference Fuels

Abstract

<div class="section abstract"><div class="htmlview paragraph">The possibility to operate current diesel engines in dual-fuel mode with the addition of an alternative fuel is fundamental to accelerate the energy transition to achieve carbon neutrality. The simulation of the dual- fuel combustion process with 0D/1D combustion models is fundamental for the performance prediction, but still particularly challenging, due to chemical interactions of the mixture.</div><div class="htmlview paragraph">The authors defined a novel data-driven workflow for the development of combustion reaction mechanisms and used it to generate a dual-fuel mechanism for Ammonia and Diesel Primary Reference Fuels (DPRF) suitable for efficient combustion simulations in heavy duty engines, with variable cetane number Diesel fuels.</div><div class="htmlview paragraph">A baseline reaction mechanism was created by merging the detailed ammonia mechanism by Glarborg et al. with reaction pathways for n- hexadecane and 2,2,4,4,6,8,8-heptamethylnonane from a well-established multi-component fuel mechanism. To define its target validity space, a standardized database of experimental measurements was developed which covers ignition delay times and species concentration profiles in shock tubes, rapid compression machines, and jet stirred reactors. Standardized experimental data served for both mechanism reduction, performance comparison of the optimized mechanism, and a source for simulation input. First, Element Flux (EF) Analysis was run to assess the activity coefficient of each species, and to define a set of reduced mechanisms; a 120-species, 1147 reactions was chosen as the target size and further optimized. During the genetic optimization, the reaction rates of the most relevant reactions were optimized, within uncertainty bounds gathered from the experimental literature. The merit function was evaluated as a multi-objective formulation that compared performance at all experiments.</div><div class="htmlview paragraph">The final mechanism showed noticeable accuracy improvements over the baseline “full” mechanism, with significantly smaller size. The generalized methodology also demonstrated successful mechanism development with little user input, and paved the way for further mechanism improvement and expansion to other target fuels.</div></div>