NO emission prediction using virtual optimized chemistry

A reduced order kinetic model for NO (Nitric Oxide) prediction, based on the recently developed virtual chemistry methodology, is proposed in this article. Temperature and heat release are resolved through the optimization of a virtual main mechanism whereas NO emissions are reproduced through the optimization of a dedicated sub-mechanism. The proposed NO sub-mechanism is optimized over a learning database made of 1D-premixed and 1D opposed jet diusion flames. The approach is further assessed in a premixed 2D CFD laminar flame computation proposing a direct comparison against fully detailed chemistry

The effect of combustion sub-grid closures in LES of MILD combustion

info:eu-repo/semantics/nonPublishe

The role of thermophoretic effect in the formation of soot from liquid fuels

In order to rationalize soot formation in two-phase combustion, the related dynamics can be conveniently studied in simpler systems. In the latest twenty years, experimental activity in drop towers and in the outer space have allowed to investigate the combustion of isolated droplets in microgravity conditions, i.e. spherically symmetric systems where buoyancy effects and slip velocity are absent, yet still containing the major phenomena affecting real combustion (unsteady evolution, convection, gas and soot radiation, heterogeneous properties and so on). In such conditions, it had been speculated [1] that a key role in soot formation is played by thermophoretic effect, because of which solid particles are transported towards the droplet surface, thus increasing their residence times in the fuel-rich area, where soot growth is kinetically favoured. The spherical symmetry also allows to numerically study these systems with a relatively low computational weight. The importance of thermophoresis in the dynamics of soot formation can thus be investigated in a variety of operating conditions (droplet size, pressure, composition, etc.), which is the subject of this work. Starting from a description of the constitutive parts of the isolated-droplet model, the transient dynamics of soot formation in n-heptane droplets is analysed. The impact of the submodel describing thermophoresis is considered in detail, and indications about its possible refinements are provided

Predictive-Quality Surface Reaction Chemistry in Real Reactor Models: Integrating First-Principles Kinetic Monte Carlo Simulations into Computational Fluid Dynamics

We present a numerical framework to integrate first-principles kinetic Monte Carlo (1p-kMC) based microkinetic models into the powerful computational fluid dynamics (CFD) package CatalyticFoam. This allows for the simultaneous account of a predictive-quality surface reaction kinetics inside an explicitly described catalytic reactor geometry. Crucial means toward an efficient and stable implementation are the exploitation of the disparate time scales of surface chemistry and gas-phase transport, as well as the reliable interpolation of irregularly gridded 1p-kMC data by means of an error-based modified Shepard approach. We illustrate the capabilities of the framework using the CO oxidation at Pd(100) and RuO2(110) model catalysts in different reactor configurations and fluid dynamic conditions as showcases. These showcases underscore both the necessity and value of having reliable treatments of the surface chemistry and flow inside integrated multiscale catalysis simulations when aiming at an atomic-scale understanding of the catalytic function in near-ambient environments. Our examples highlight how intricately this function is affected by specifics of the reactor geometry and heat dissipation channels on the one end, and on the other end by characteristics of the intrinsic catalytic activity that are only captured by treatments beyond prevalent mean-field rate equations

New Dynamic Scale Similarity Based Finite-Rate Combustion Models for LES and a priori DNS Assessment in Non-premixed Jet Flames with High Level of Local Extinction

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

A comprehensive CFD model for the biomass pyrolysis

The present work addresses the study of the pyrolysis of biomass particle, with the aim to improve the comprehensive mathematical model of the thermochemical processes involving solids decomposition. A new CFD model for the biomass pyrolysis was developed at the particle scale in order to properly describe the relative role of reaction kinetics and transport phenomena. The model is able to solve the Navier-Stokes equations for both the gas and solid porous phase. The code employs the open-source OpenFOAM® framework to effectively manage the computational meshes and the discretization of fundamental governing equations. The mathematical algorithm is based on the PIMPLE method for transient solver and exploit the operator-splitting technique that allows the separation of the transport and the reactive term in order to handle complex computational geometries minimizing the computational effort. The model was tested with experimental data for both reactive and non-reactive conditions. The code is able to provide correct information about temperature distribution within the particle, gas, tar and char formation rates

Detailed kinetics of pyrolysis and combustion of catechol and guaiacol, as reference components of bio-Oil from biomass

Fast biomass pyrolysis is an effective process to produce bio-oils thus allowing to partially replace nonrenewable fossil fuels. Bio-oils are complex mixtures with a great amount of large oxygenated organic species, such as substituted phenolic components. Although experimental and kinetic modeling studies of phenol and anisole pyrolysis and combustion are available in the literature, only a minor attention has been devoted to kinetic mechanisms of substituted phenolic species, such as catechol and guaiacol. Multiple substitutions on aromatic ring can originate proximity effects and thus significantly modify bond energies, consequently affecting reaction pathways. Careful evaluations of bond dissociation energies and reference kinetic parameters, based on theoretical computations, are first performed. Guaiacol and catechol pyrolysis and combustion reactions are then compared with the corresponding phenol and anisole mechanisms. This kinetic study allows to identify some preliminary rate rules useful to validate a detailed kinetic mechanism of bio-oil pyrolysis and combustion