مدل‌سازی اثر نانولوله‌های کربن اضافه شده به مخلوط سوخت دیزل-بیودیزل بر عملکرد و آلایندگی یک موتور دیزل با استفاده از شبکه عصبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه علوم کشاورزی و منابع طبیعی گرگان

2 استاد، مهندسی مکانیک بیوسیستم، دانشگاه تربیت مدرس تهران،

چکیده

بیودیزل و همچنین برخی نانوکاتالیست‌ها به عنوان افزودنی به سوخت دیزل می‌تواند باعث بهبود عملکرد و کاهش آلاینده-های موتور شود. در تحقیق حاضر، بیودیزل با نسبت 5 و 10 درصد ( B5 و B10) در مخلوط با سوخت دیزل استفاده شد. سپس نانولوله‌های کربن با غلظت 30، 60 و ppm90 به مخلوط سوخت برای ارزیابی عملکرد، آلایندگی و ارتعاش موتور دیزل استفاده گردید. از شبکه‌ عصبی چندلایه با قاعده یادگیری پس انتشار خطا رو به‌ جلو برای مدل‌سازی استفاده گردید. نوع سوخت، دور موتور، چگالی، ویسکوزیته و ارزش حرارتی سوخت، فشار مانیفولد ورودی، مصرف سوخت، دمای گازهای خروجی، اکسیژن موجود در گازهای خروجی، دمای روغن، رطوبت و فشار نسبی هوای محیط به‌عنوان پارامترهای لایه ورودی یا مستقل در نظر گرفته شدند. عملکرد، آلایندگی و ارتعاش موتور به‌عنوان پارامترهای لایه خروجی درنظر گرفته شدند. نتایج نشان داد که مصرف سوخت ویژه موتور و آلایندگی‌های CO و UHC کاهش یافته، در حالی که آلاینده NOx افزایشی بوده است. همچنین، مدل شبکه عصبی با الگوی آموزش پس انتشار خطا با 20-20 نرون در لایه‌های مخفی سیگموئیدی-سیگموئیدی توانایی پیش‌بینی پارامترهای مختلف را با عملکرد و دقت خوبی دارد. مقادیر عددی ضریب رگرسیونی (R) آموزش، ارزیابی و آزمون مدل بهینه شبکه به ترتیب 9999/0، 9985/0 و 9994/0 به‌دست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Modeling the effects of Carbon nanotubes added to diesel-biodiesel fuel blends on performance and emissions of a diesel engine using artificial neural network

نویسندگان [English]

  • ُSeyyed Hassan Hosseini 1
  • Ahmad Taghizadeh-Alisaraei 1
  • Barat Ghobadian 2
  • ahmad Abbaszadeh 1
2 Department of Mechanical Biosystems, Faculty of Agriculture, Tarbiat Modares University, P. O. Box Tehran, Iran,
چکیده [English]

Biodiesel and some nano-catalysts are an important additive to diesel fuel and can improve the engine performance and reduce emissions. In this study, biodiesel was added to pure diesel with ratios of 5 and 10 percent. Then, the carbon nanotubes were mixed as additive with these blends with concentrations of 30, 60, and 90 ppm to evaluate the performance, emissions, and vibration levels in a diesel engine. An ANN model, based on standard back-propagation learning algorithm for the engine, was developed. Multi-layer perception network (MLP) was used. The input or independent parameters were fuel blend, engine speed, fuel density, fuel viscosity, LHV, intake manifold pressure, fuel consumption, exhaust gas temperature, oxygen contained in exhaust gases, oil temperature, relative humidity and ambient air pressure. The target parameters were performance, emissions and RMS and Kurtosis of engine vibrations. The results showed that the specific fuel consumption and CO and UHC emissions decreased, while NOx emission increased. Also, the ANN model showed the training algorithm of back-propagation with 20-20 neurons in hidden layers (logsig-logsig) is able to predict different parameters with good performance and accuracy. The corresponding R-values for training, validation and testing were 0.9999, 0.9985 and 0.9994, respectively.
 

کلیدواژه‌ها [English]

  • Biodiesel with Carbon nanotubes
  • emissions
  • vibration
  • Neural Network
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