استفاده از تجزیه و تحلیل حساسیت و الگوریتم ژنتیک برای مدیریت انتشار کاتالیزور از پالایشگاه های نفت
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|25856||2014||9 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Mathematical and Computer Modelling, Volume 44, Issues 5–6, September 2006, Pages 430–438
Excessive catalyst emissions from Fluidized Catalytic Cracking Units (FCCU) during start-up situations are common, and have been deemed ‘normal’, with little research conducted on determining their causes. A MATLAB model found to predict trends in emission rates under normal conditions has been expanded to better represent the actual processes inside a FCCU. First and second order sensitivity analysis techniques are used to assess the interactions between various operational parameters, with a genetic algorithm used to optimize the operating conditions to minimize air emissions. These ‘key’ parameters may then be altered to help manage both normal and start-up emissions through operational changes. It was also found that significant scale-up issues arise with the use of the attrition models found in the literature.
The petroleum industry currently employs Fluidizing Catalytic Cracking Units (FCCUs) as the major tool in producing gasoline from crude oil. FCCUs typically consist of a rising main where the chemical reactions between catalyst and hydrocarbons occur; a reactor to separate the product and catalyst; and a regenerator to re-charge the used catalyst. The regenerator is a fluidized bed used to combust coke from the used catalyst, with cyclones to remove particles from the flue gas stream before venting to the atmosphere. The recharged catalyst then re-circulates through the rising main and the process is repeated . Catalyst emissions from FCCUs have the potential to impact significantly on the environmental efficiency of the overall refining operation . Currently, FCCUs are designed and operated in such a way as to maximize output and profitability of the refinery . In recent years, fine particle emissions from industry have been identified as important contributors to poor environmental and health standards across the United States . With increasing demands for cleaner air, and the lack of literature dealing with FCCU emissions, there is a need for the relationships between current operational strategies and air pollution to be better understood. In an attempt to better understand emission modeling, an emission model was developed using MATLAB and tested on FCCU emissions  and . The model was based on the essential processes inside the FCCU including fluidization, elutriation, entrainment and attrition, with model equations sourced from the literature. Emission results were then compared with observations from an operating FCCU, where the FCCU particle emissions during a start-up period were identified. This allows the complete range of emissions to be compared with modelled results . The aim of this paper is to further develop the model into a more realistic package, for use in modelling industrial emissions. Genetic algorithms and sensitivity analysis are used to identify the key input parameters required to best predict emissions from an operating FCCU. This will provide a simulation package of the FCCU, where the simulated emission can be studied in terms of system parameters.
نتیجه گیری انگلیسی
The updated model has shown that fine particles, gas velocity and particle density are the most important operational parameters in terms of minimizing particle emissions from an FCCU. Overall the model was found to significantly overestimate the true nature of emissions from an FCCU. It was concluded that this error was due to scale-up issues arising from the attrition terms used. Optimization of the model supported the hypothesis that it is the attrition terms, and in particular the cyclone attrition coefficient, which is responsible of the overestimation of particle emissions. It appears that cyclone attrition is substantially less in larger systems than that found in smaller laboratory based cyclones. Optimization of the model with a more realistic attrition term showed that even at high gas velocities emission levels could be minimized. This work has supported earlier studies identifying particle size, density and gas velocity as the main parameters which should be controlled to minimize particle emissions from FCCUs. Further work is needed to develop better attrition models for use in large scale systems, so more accurate emission models can be developed.