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Generating energy from combustion is prone to pollutant formation. In energy systems working under non-premixed combustion mode, rapid mixing is required to increase the heat release rates. However, local extinction and re-ignition may occur, resulting from strong turbulence–chemistry interaction, especially when rates of mixing exceed combustion rates, causing harmful emissions and flame instability. Since the physical mechanisms for such processes are not well understood, there are not yet combustion models in large eddy simulation (LES) context capable of accurately predicting them. In the present study, finite-rate scale similarity (SS) combustion models were applied to evaluate both heat release and combustion rates. The performance of three SS models was a priori assessed based on the direct numerical simulation of a temporally evolving syngas jet flame experiencing high level of local extinction and re-ignition. The results show that SS models following the Bardina’s “grid filtering” approach (A and B) have lower errors than the model based on the Germano’s “test filtering” approach (C), in terms of mean, root mean square (RMS), and local errors. In mean, both Bardina’s based models capture well the filtered combustion and heat release rates. Locally, Model A captures better major species, while Model B retrieves radicals more accurately.

In this work, the performances of two recently developed finite-rate dynamic scale similarity (SS) sub-grid scale (SGS) combustion models (named DB and DC) for non-premixed turbulent combustion are a priori assessed based on three Direct Numerical Simulation (DNS) databases. These numerical experiments feature temporally evolving syngas jet flames with different Reynolds (Re) numbers (2510, 4487 and 9079), experiencing a high level of local extinction. For comparison purposes, the predicting capability of these models is compared with three classical non-dynamic SS models, namely the scale similarity resolved reaction rate model (SSRRRM or A), the scale similarity filtered reaction rate model (SSFRRM or B), and a SS model derived by the "test filtering" approach (C), as well as an existing dynamic version of SSRRRM (DA). Improvements in the prediction of heat release rates using a new dynamic model DC are observed in high Re flame case. By decreasing Re, dynamic procedures produce results roughly similar to their non-dynamic counterparts. In the lowest Re, the dynamic methods lead to higher errors. Keywords Dynamic scale similarity combustion model • Finite-rate SGS combustion model • A priori DNS analysis • LES • Non-premixed jet flame • Extinction re-ignition Electronic supplementary material The online version of this article (

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A comprehensive Euler–Lagrange framework for pulverized coal combustion using detailed multi-step heterogeneous kinetics is presented. The heterogeneous kinetics employ the POLIMI model that involves 37 species (22 solid species and 15 gas species) and 49 reactions to describe detailed pyrolysis as well as char oxidation, gasification, and annealing for a wide range of coals. The porous structure of the coal particles is considered, and the heterogeneous reactions are assumed to occur throughout the entire particle in a volume-based approach. The ordinary differential equations of the heterogeneous kinetics are integrated on each Lagrangian coal particle and predict the conversion of the raw coal components to light volatile hydrocarbons, heavy tar species, and char off-gases. Hence, the composition of the solid fuel components and the released gas changes dynamically in space and time, providing high-fidelity predictions of solid fuel combustion. The chemical conversion of the released species in the gas phase is described by a homogeneous kinetic mechanism with 76 species and 973 reactions that was reduced from the comprehensive CRECK-G-1407 kinetic mechanism. The new modeling framework is employed within carrier-phase direct numerical simulations (CP-DNS) of pulverized coal combustion in a three-dimensional turbulent mixing layer. This configuration includes the additional physics of turbulence and particle group combustion by mixing solid fuel particles suspended in a primary oxidizer stream with the products from lean volatile combustion in a secondary stream. The CP-DNS results are analyzed with and without the available set of 14 char conversion reactions, and a low degree of char conversion indicated by an increased rate of CO production is captured for particles with temperatures higher than 1800 K. The CP-DNS results from the detailed POLIMI approach feature a distinct bimodal shape of the volatile release curve and multi-regime combustion. The POLIMI data are used to evaluate the predictive capability of simpler pyrolysis models. The original competing two-step model (C2SM) by Kobayashi is investigated and shown to predict heavily delayed ignition. A new competing two-step devolatilization approach is proposed as an alternative model reduction suitable for fitting bimodal volatile release rates, such as that predicted by POLIMI. The CP-DNS using the alternative pyrolysis model faithfully captures the onset of ignition and multi-regime flame branches. Differences arise in the local tar species compositions in the gas phase as a result of the time-varying (POLIMI) and fixed (new C2SM) volatile compositions for the respective models. The flame structure is further analyzed by chemical explosive mode analysis (CEMA), and the occurrence of premixed and non-premixed flames zones is confirmed, whereas a simpler flame index analysis fails to correctly indicate the multi-regime nature of the flame. This recognition of multi-regime combustion serves as a guidance for selecting suitable conditioning variables for...

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