توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱CFD Simulation and Optimization of TiO2 Nanoparticles Synthesis by MOCVD Process
نویسنده(ها): ، ،
اطلاعات انتشار: چهاردهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۶
The Titanium dioxide nanoparticles’ (TiO2) deposition rate through metalorganic chemical vapor deposition (MOCVD) process was studied by means of computational fluid dynamics(CFD). Titanium tetraisopropoxide (TTIP) was used as a precursor and nitrogen as a carrier gas in this assay. Three–dimensional numerical simulation was utilized to gain a more complete andaccurate understanding of the deposition process. Influences of substrate temperature, precursor concentration and gas flow rate on deposition rate of TiO2 nanoparticles have been investigated. Results reflect that deposition rate was reduced by increasing substrate temperature and gas flow rate. In contrast it would be grown when concentration of TTIP at inlet gas flow rises. Furthermore, response surface methodology (RSM) was employed to assess individual and interactive effects of the three main independent parameters (substrate temperature, inlet gasvelocity and precursor concentration) on deposition rate and usage percent of TTIP. To achieve optimum point, both deposition rate and TTIP usage percent were defined as maximize . The optimum substrate temperature, inlet gas velocity and precursor concentration were found to be 744.0543 K, 0.0318 m\s and 0.0008 mol\m3, respectively.<\div>

۲Mathematical modeling and steady–state simulation of catalytic naphtha reforming using artificial neural networks
نویسنده(ها): ، ،
اطلاعات انتشار: هفتمین کنگره ملی مهندسی شیمی، سال
تعداد صفحات: ۱۲
In this study a mathematical steady–state model for catalytic reforming of naphtha was developed. The model was applied to predict reformate composition and temperature profiles in the reforming unit consisting of three fixed bed reactors in series. The process consists of dehydrogenation, dehydrocyclization, ring expansion, paraffins and iso–paraffins cracking, naphthenes cracking, paraffins isomerization and hydrodealkylation of aromatics. Steady–state simulation of catalytic naphtha reforming process was carried out using mathematical model and then the results used forthe simulation by artificial neural networks (ANNs). Finally, the results of simulation with ANNs were compared with model results, and the best performance of ANN was validated<\div>
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