Computational Study of Turbulent Combustion Systems and Global Reactor Networks
| dc.contributor.author | Chen, Lu | en |
| dc.contributor.committeechair | Battaglia, Francine | en |
| dc.contributor.committeemember | Karim, Ayman M. | en |
| dc.contributor.committeemember | Paul, Mark R. | en |
| dc.contributor.committeemember | Bayandor, Javid | en |
| dc.contributor.committeemember | Lattimer, Brian Y. | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2017-09-06T08:00:48Z | en |
| dc.date.available | 2017-09-06T08:00:48Z | en |
| dc.date.issued | 2017-09-05 | en |
| dc.description.abstract | A numerical study of turbulent combustion systems was pursued to examine different computational modeling techniques, namely computational fluid dynamics (CFD) and chemical reactor network (CRN) methods. Both methods have been studied and analyzed as individual techniques as well as a coupled approach to pursue better understandings of the mechanisms and interactions between turbulent flow and mixing, ignition behavior and pollutant formation. A thorough analysis and comparison of both turbulence models and chemistry representation methods was executed and simulations were compared and validated with experimental works. An extensive study of turbulence modeling methods, and the optimization of modeling techniques including turbulence intensity and computational domain size have been conducted. The final CFD model has demonstrated good predictive performance for different turbulent bluff-body flames. The NOx formation and the effects of fuel mixtures indicated that the addition of hydrogen to the fuel and non-flammable diluents like CO2 and H2O contribute to the reduction of NOx. The second part of the study focused on developing chemical models and methods that include the detailed gaseous reaction mechanism of GRI-Mech 3.0 but cost less computational time. A new chemical reactor network has been created based on the CFD results of combustion characteristics and flow fields. The proposed CRN has been validated with the temperature and species emission for different bluff-body flames and has shown the capability of being applied to general bluff-body systems. Specifically, the rate of production of NOx and the sensitivity analysis based on the CRN results helped to summarize the reduced reaction mechanism, which not only provided a promising method to generate representative reactions from hundreds of species and reactions in gaseous mechanism but also presented valuable information of the combustion mechanisms and NOx formation. Finally, the proposed reduced reaction mechanism from the sensitivity analysis was applied to the CFD simulations, which created a fully coupled process between CFD and CRN, and the results from the reduced reaction mechanism have shown good predictions compared with the probability density function method. | en |
| dc.description.abstractgeneral | Turbulent combustion has been regarded as one of the most typical occurrences with industrial burners, where turbulent flow is produced by large vortex eddies when fuel and oxidizer mixes. Due to increasing demands for energy and concerns for environmental pollution, it is important to have a comprehensive understanding of turbulent combustion processes. To help provide information related to turbulent combustion, computational modeling can be used to give physical insights of the combustion process. A numerical study of turbulent combustion systems was pursued to examine different computational modeling techniques and to understand the mechanisms in terms of fluid dynamics and chemical kinetics. Computational fluid dynamics (CFD) was used to predict the flow field, including gas velocities, temperatures and fuel characteristics. Another computational technique known as the chemical reactor network (CRN) was used to provide information related to the chemical reactions and pollutant production. A method was developed as part of the study to couple the computational methods to pursue better understandings of the mechanisms and interactions between turbulent flow and mixing, ignition behavior and pollutant formation. Results have been compared with experimental data to optimize the modeling techniques and validate the developed model. The CRN model with the detailed gaseous reaction mechanism from the Gas Research Institute GRI-Mech 3.0 created a reacting network across the combustor with flame chemistry details. By post-processing the CRN results using a sensitivity analysis, the reduced reaction mechanism was summarized, which provided a promising method to generate representative reactions of the system from hundreds of species and reactions that occur in the combustion process. The proposed reduced reaction mechanism was applied to the CFD simulations, which created a fully coupled process between CFD and CRN. The results from the reduced reaction mechanism have shown good predictions compared with the probability density function method, which is a simplified way to model combustion. Pollutant emission such as NOx has also been studied in both CFD and CRN models, in terms of the effects of fuel mixtures, the formation mechanisms and influential factors as well as reactions to the formation process. The work provides guidance for an integrated framework to model and study turbulence and chemical reactions for turbulent combustion systems. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:12539 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/78804 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Turbulent combustion | en |
| dc.subject | turbulence model | en |
| dc.subject | chemical reactor network | en |
| dc.subject | sensitivity analysis | en |
| dc.subject | reduced chemical mechanism | en |
| dc.title | Computational Study of Turbulent Combustion Systems and Global Reactor Networks | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |