A computational study of the effects of multiphase dynamics in catalytic upgrading of biomass pyrolysis vapor

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145281/1/aic16184.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145281/2/aic16184_am.pd

A feasibility study on the use of low-dimensional simulations for database generation in adaptive chemistry approaches

LES/PDF approaches can be used for simulating challenging turbulent combustion configurations with strong turbulence chemistry interactions. Transported PDF methods are computationally expensive compared to flamelet-like turbulent combustion models. The pre-partitioned adaptive chemistry (PPAC) methodology was developed to address this cost differential. PPAC entails an offline preprocessing stage, where a set of reduced models are generated starting from an initial database of representative compositions. At runtime, this set of reduced models are dynamically utilized during the reaction fractional step leading to computational savings. We have recently combined PPAC with in-situ adaptive tabulation (ISAT) to further reduce the computational cost. We have shown that the combined method reduced the average wall-clock time per time step of large-scale LES/particle PDF simulations of turbulent combustion by 39\%. A key assumption in PPAC is that the initial database used in the offline stage is representative of the compositions encountered at runtime. In our previous study this assumption was trivially satisfied as the initial database consisted of compositions extracted from the turbulent combustion simulation itself. Consequently, a key open question remains as to whether such databases can be generated without having access to the turbulent combustion simulation. Towards answering this question, in the current work, we explore whether the compositions for forming such a database can be extracted from computationally-efficient low-dimensional simulations such as 1D counterflow flames and partially stirred reactors. We show that a database generated using compositions extracted from a partially stirred reactor configuration leads to performance comparable to the optimal case, wherein the database is comprised of compositions extracted directly from the LES/PDF simulation itself

A conceptual model of the flame stabilization mechanisms for a lifted Diesel-type flame based on direct numerical simulation and experiments

This work presents an analysis of the stabilization of diffusion flames created by the injection of fuel into hot air, as found in Diesel engines. It is based on experimental observations and uses a dedicated Direct Numerical Simulation (DNS) approach to construct a numerical setup, which reproduces the ignition features obtained experimentally. The resulting DNS data are then used to classify and analyze the events that allow the flame to stabilize at a certain Lift-Off Length (LOL) from the fuel injector. Both DNS and experiments reveal that this stabilization is intermittent: flame elements first auto-ignite before being convected downstream until another sudden auto-ignition event occurs closer to the fuel injector. The flame topologies associated to such events are discussed in detail using the DNS results, and a conceptual model summarizing the observation made is proposed. Results show that the main flame stabilization mechanism is auto-ignition. However, multiple reaction zone topologies, such as triple flames, are also observed at the periphery of the fuel jet helping the flame to stabilize by filling high-temperature burnt gases reservoirs localized at the periphery, which trigger auto-ignitions

On the Validation of a One-Dimensional Biomass Pyrolysis Model Using Uncertainty Quantification

Predictive modeling tools have the potential to accelerate the development and deployment of biomass thermochemical conversion. Considerable progress has been made in the modeling of biomass pyrolysis at the particle level, where chemical kinetics and transport processes are coupled. However, rigorous validation of the corresponding models is challenging because of the considerable uncertainty in the values of several biomass properties. Toward this end, we use the principles of uncertainty quantification (UQ) for a rigorous analysis of the validity of a commonly used one-dimensional wood pyrolysis model. Uncertainty in the modeling parameters of the transport processes is propagated to the simulation results of the pyrolysis model. The model predictions are compared with several detailed experimental measurements for pyrolysis of wood particles. The results show that the uncertainty in the model predictions account for some of the discrepancies with the experimental measurements, especially for the particle temperature profiles and the gas phase species production rates. Experimental targets are identified whose predictions cannot be improved by an accurate knowledge of the transport model parameters and require further improvements in the chemical kinetics model. The use of a systematic optimization technique is also demonstrated to choose the optimal values of uncertain model parameters

P-DRGEP: A novel methodology for the reduction of kinetics mechanisms for plasma-assisted combustion applications

Detailed kinetics mechanisms for plasma-assisted combustion contain numerous species and reactions that model the interplay between non-equilibrium plasma processes and hydrocarbon oxidation. While physically accurate and comprehensive, such detailed mechanisms are impractical for simulations of unsteady multi-dimensional plasma discharges and their effect on reactive mixtures in practical devices. In this work, we develop and apply a novel methodology for the reduction of large detailed plasma-assisted combustion mechanisms to smaller skeletal ones. The methodology extends the Directed Relation Graph with Error Propagation (DRGEP) approach in order to consider the energy branching characteristics of plasma discharges during the reduction. Ensuring tight error tolerances on the relative proportions of energy lost by the electrons to the various classes of impact processes (i.e. vibrational and electronic excitation, ionization, and impact dissociation) is key to preserving the correct discharge physics in the skeletal mechanism. To this end, new targets that include energy transfers are defined and incorporated in DRGEP. The performance of the novel framework, called P-DRGEP, is assessed for the simulation of ethylene-air ignition by nanosecond repetitive pulsed discharges at conditions relevant to supersonic combustion and flame holding in scramjet cavities, i.e. from 600 K to 1000 K, 0.5 atm, and equivalence ratios between 0.75 and 1.5. P-DRGEP is found to be greatly superior to the traditional reduction approach applied to plasma-assisted ignition in that it generates a smaller skeletal mechanism with significantly lower errors. For ethylene-air ignition at the target conditions, P-DRGEP generates a skeletal mechanism with 54 species and 236 reactions, resulting in a 84% computational speed-up for ignition simulations, while guaranteeing errors below 10% on the time required for ignition following the first pulse, 1% on the mean electron energy, between 4 and 35% on electron energy losses depending on the process, and 5% on the laminar flame speed.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Reduced Chemical Kinetics for the Modeling of TiO₂ Nanoparticle Synthesis in Flame Reactors

Flame synthesis represents a viable technique for large-scale production of titanium dioxide (TiO₂) nanoparticles. A key ingredient in the modeling of this process is the description of the chemical kinetics, which include Ti oxidation, hydrocarbon fuel combustion, and chlorination. While detailed chemical mechanisms have been developed for predicting TiO₂ nanoparticle properties by West et al. (e.g., <i>Combust. Flame</i> <b>2009</b>, <i>156</i>, 1764), their use in turbulent reacting flow simulations is limited to very simple configurations or requires significant modeling assumptions to bring their computational cost down to an acceptable level. In this work, a reduced kinetic scheme describing the oxidation of TiCl₄ in a methane flame is derived from and validated against the predictions of a detailed mechanism from the literature. The reduction procedure uses graph-based methods for unimportant kinetic pathways elimination and quasi-steady-state species selection. Reduction targets are chosen in accordance with previous modeling results that showed the importance of temperature and overall concentration of titanium-containing species in both nucleation and surface growth rates. The resulting reduced scheme is thoroughly evaluated over a wide range of conditions relevant to flame-based synthesis, and the capability of the reduced model to adequately capture the process dynamics at a much lower computational cost is demonstrated