An automated target species selection method for dynamic adaptive chemistry simulations

Abstract

The relative importance index (RII) method for determining appropriate target species for dynamic adaptive chemistry (DAC) simulations using the directed relation graph with error propagation (DRGEP) method is developed. The adequacy and effectiveness of this RII method is validated for two fuels: n-heptane and isopentanol, representatives of a ground transportation fuel component and bio-alcohol, respectively.The conventional method of DRGEP target species selection involves picking an unchanging (static) set of target species based on the combustion processes of interest; however, these static target species may not remain important throughout the entire combustion simulation, adversely affecting the accuracy of the method. In particular, this behavior may significantly reduce the accuracy of the DRGEP-based DAC approach in complex multidimensional simulations where the encountered combustion conditions cannot be known a priori with high certainty. Moreover, testing multiple sets of static target species to ensure the accuracy of the method is generally computationally prohibitive. Instead, the RII method determines appropriate DRGEP target species solely from the local thermo-chemical state of the simulation, ensuring that accuracy will be maintained. Further, the RII method reduces the expertise required of users to select DRGEP target species sets appropriate to the combustion phenomena under consideration.Constant volume autoignition simulations run over a wide range of initial conditions using detailed reaction mechanisms for n-heptane and isopentanol show that the RII method is able to maintain accuracy even when traditional static target species sets fail, and are even more accurate than expert-selected target species sets. Additionally, the accuracy and efficiency of the RII method are compared to those of static target species sets in single-cell engine simulations under homogeneous charge compression ignition conditions. For simulations using more stringent DRGEP thresholds, the RII method performs similarly to that of the static target species sets. With a larger DRGEP threshold, the RII method is significantly more accurate than the static target species sets without imposing significant computational overhead.Furthermore, the applicability of the RII method to a DRG-based DAC scheme is discussed.

Reduced Chemistry for a Gasoline Surrogate Valid at Engine-Relevant Conditions

“…However, the skeletal and reduced mechanisms produced here may still be too large to use in high-fidelity reactive flow simulations, even considering the significant extent of reduction compared to the original detailed mechanism. Therefore, while incorporating reduced chemistry in multidimensional reactive-flow simulations is the focus of our future work, dynamic mechanism reduction techniques may be required and are also under investigation 49 .…”

Development of a reduced chemical mechanism targeted for a 5-component gasoline surrogate: A case study on the heat release nature in a GCI engine

“…Due to the efficient characteristics, the direct relation graph with error propagation (DRGEP) based approach using Dijkstra search algorithm, which has proved to be more accurate on species removal than the other search algorithms by Niemeyer and Sung [32], is used for the first-step reduction. From previous studies of other researchers [33,34], the DRGEP-based methods are very sensitive to the target species such as HO 2 , CO, CH 2 O, etc. near NTC regions for two-stage ignition fuels.…”

A pre-partitioned adaptive chemistry methodology for the efficient implementation of combustion chemistry in particle PDF methods

“…This methodology theoretically guarantees a maximal reduction in the time needed to integrate the chemistry equations, but is efficient only if the time taken by the reduction algorithm is comparatively small. Species elimination or dimension-reduction methods based on graph or element flux analysis methods have been shown to satisfy this requirements [27,29,[34][35][36][37][38]40]. In particular, the Dynamic Adaptive Chemistry, or DAC, technique [27] has been applied on a variety of configurations, including methane/air combustion in partially-stirred reactor [34], 1D premixed, unsteady, freely-propagating methane/air flame [35], homogeneous ignition [37], and compression-ignition engine simulations [36].…”