A computational fluid dynamics simulation model for flare analysis and control
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Industrial flares are units designed to safely dispose of waste hydrocarbon gases from chemical and petrochemical plants by burning gases to carbon dioxide and steam, which are then released to the atmosphere. There is still great uncertainty about flare efficiency and the resultant gas emissions under different operating conditions. For this reason, environmental agencies have encouraged the development of predictive models for flare gas combustion systems, so effective control and mitigation strategies can be implemented. The principal focus of this dissertation is to develop mathematical models of industrial flares that predict the efficiency of these industrial combustion systems. For this purpose, a computational fluid dynamics (CFD) simulation model is implemented to analyze the effects of variables such as ambient wind velocity, gas heating value, and steam injection on flare combustion efficiency. Some advanced chemistry and turbulence submodels are also implemented to describe the complex flare flow phenomena. Simulation results show that flares may represent an important source of gas emissions due to inefficient operation at high crosswinds and large steam/fuel ratios. The predictive models presented in this work will allow for better estimation of the resulting gas emissions from industrial plants. Use of these simulation models will also yield economic savings for environmental studies compared to setting up expensive flare experiments. In addition, these predictive models allow for a detailed analysis of species concentration profiles and turbulent flow patterns within the flames, data which is not available experimentally. Furthermore, several instrumentation and control strategies for industrial flares are analyzed in this dissertation. A new approach for flare monitoring based on multivariate image analysis is proposed so that flare combustion efficiency can be measured in real-time.