عنوان :
كاربرد مدل كسر مخلوط چندگانه در مدلسازي احتراق شعلههاي ديفيوژن
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
تبديل انرژي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك
صفحه شمار :
پانزده، ۱۲۲ص.: مصور، جدول، نمودار
استاد راهنما :
محسن دوازدهامامي
استاد مشاور :
احمد صابونچي
توصيفگر ها :
احتراق , مدل فليملت آرام , شبكههاي عصبي مصنوعي , كسرمخلوط چندگانه
استاد داور :
علي اكبر عالم رجبي، محمود اشرفي زاده
تاريخ ورود اطلاعات :
1397/04/30
چكيده انگليسي :
123 Application of Multi mixture Fraction model in Diffusion Flames Combustion Modeling Ahmad Nazari ahmad nazari@me iut ac ir Date of Submission 2018 06 24 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Mohsen Davazdah Emami Mohsen@cc iut ac ir Abstract The limitations of fossil fuel resources and environmental issues have provided extensive research on combustion science over the past decades and the reduction of combustion pollutants in industrial burners has been one of the fundamental challenges for researchers To monitor and control pollutants proper prediction of the temperature field and combustion products is essential On the other hand most of the combustion processes occur in a totally turbulent environment which is complicated by the interaction between chemical reactions and turbulence Therefore the simulation of these flows requires the selection of a suitable combustion model In the present study the laminar flamelet model is used for combustion modeling because of its high accuracy in predictions and computational economy and the k model is used for turbulence modeling This study is concerned with numerical solution of multi fuel combustion To this end a new program called multi mixture fraction model has been developed for the modeling of multi fuel burners and its applications in using flamelet model and flame sheet model have been investigated In order to ensure the correct predictions of the modeling the bluff body flame is simulated with one fuel stream and piloted methane air flame with two fuel streams Simulation of flamelet model requires generation of a flamelet library which is produced as preprocessing both in the physical space and in the mixture fraction space In this thesis the opposed flow flame in physical space has been used for flamelet library generation In the next step the mean of these quantities was obtained by numerical integration for different mean mixture fractions their variance and scalar dissipation rate and then by training an artificial neural network and inserting its weight and bias coefficients in the solution code for conservation equations the average mass fraction of species is foreseen The simulation results of the bluff body flame showed that the prediction of temperature and mass fraction of species by the neural network in the flamelet code yields good agreement with experimental data The flame sheet model does not offer a good prediction of species especially pollutants so that the mass fraction of CO is much less than its real value Another result of the simulation of this flame is the reduction of computational time with the help of neural networks in which the application of this network in the flamelet code reduced the computational time to about 40 percent over the implementation of flamelet fluent The simulation results of piloted methane air flame using the multi mixture fraction model were compared with experimental data as well as predictions of the flamelet fluent model The flamelet model based on a single mixture fraction predicts the mass fraction of CO and OH species more than real value in most situations But the use of two mixture fraction model reduced the prediction error for this species by about 5 and 8 percent respectively Also the use of two mixture fraction model reduced the temperature prediction error by about 11 percent compared to the single mixture fraction model The results of this simulation showed that the standard mixture fraction framework is not suitable for the modeling of multi fuel burners and the development of mixture fraction based on this study has the ability to solve combustion problems with more than one fuel input Keywords Combustion Laminar flamelet model Artificial neural network Multi mixture fraction
استاد راهنما :
محسن دوازدهامامي
استاد مشاور :
احمد صابونچي
استاد داور :
علي اكبر عالم رجبي، محمود اشرفي زاده