Reactive computational fluid dynamics modelling methane–hydrogen admixtures in internal combustion engines part II: Large eddy simulation

Abstract

Fuels based on admixtures of methane/natural gas and hydrogen are a promising way to reduce CO2 emissions of spark ignition engines and increase their efficiency. A lot of work was conducted experimentally, whereas only limited numerical work is available in the context of three-dimensional modelling of the full engine cycle. This work addresses this fact by proposing a reactive computational fluid dynamics modelling framework to consider the effects of hydrogen addition on the combustion process. Part I of this two-part study focuses on the modelling and crucial considerations in order to predict the mean cycle based on the G-equation combustion model using the Reynolds-averaged Navier–Stokes equations. There, the effect of increased burning speed was globally captured by increasing the flame speed coefficient A, appearing in the considered flame speed closure. The proposed simplified modelling of the early flame stage proved to be robust for the conducted hydrogen variation from 0 to 50 vol% H2 for stoichiometric and lean operation. Scope of this work, Part II, are cyclic fluctuations and the hydrogen influence thereon using large eddy simulation and the proposed modelling framework. The model is probed towards its capabilities to predict the fluctuation of the combustion process for 0 and 50 vol% H2 and correlations influencing the observed peak pressure of the individual cycle are presented. It is shown that the considered approach is capable to reproduce the cyclic fluctuations of the combustion process under the influence of hydrogen addition as well as lean operation. The importance of the early flame phase with respect to arising fluctuations is highlighted as well as the contribution of the resolved scales in terms of the flame front wrinkling.

Modelling Study of Cycle-To-Cycle Variations (CCV) in Spark Ignition (SI)-Controlled Auto-Ignition (CAI) Hybrid Combustion Engine by Using Reynolds-Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES)

“…The sub-grid k model [33,34] was used to model the flows and turbulence in the LES simulations. The model has been successfully applied in LES modelling of flow [35], spray [36] and combustion [37] in combustion engines. As recommended by Speziale [34], a transport equation is solved for the sub-grid scale (SGS) kinetic energy to derive an appropriate turbulence velocity scale, which is as follows:…”

“…∆ is the grid filter size and is defined as V cell 1/3 . The LES version of the three-zones extended coherent flame model (ECFM3Z) [37,38] was applied for the LES modelling of SI-CAI hybrid combustion, with the same modelling concept adopted for the RANS simulations of the SI-CAI hybrid, combustion as detailed in previous section. In the LES version of the ECFM-3Z model, a new equation for modelling the SGS flame surface density Σ (Σ = ρσ) is considered as the following [38]:…”

A method for determining hydrogen–methane–nitrogen mixtures for laboratory tests of syngas-fuelled internal combustion engines

“…The turbulent flames in spark-ignition engines resemble highly wrinkled laminar flames; 3 hence, the combustion process is governed by the (fast) chemical reaction rates, whereas the turbulent motion can only wrinkle or distort the thin laminar flame zone. 18–21…”

Enabling robust simulation of polyoxymethylene dimethyl ether 3 (PODE3) combustion in engines

“…Due to convenience and cost-efficiency, the modeling of engine combustion processes through computational fluid dynamics (CFD) has been progressively prevalent. [34][35][36][37][38][39] Many fuel chemical mechanisms have been studied and developed within the community to better predict combustion performance and emissions. 40 One of the first PODE 3 mechanisms was put forward by Sun et al 41 to model combustion at high temperature.…”