طراحی مجدد رادیاتور موتور بر اساس تعداد فین های بهینه به کمک الگوریتم ژنتیک

نوع مقاله : مقاله پژوهشی (کاربردی)

نویسندگان

1 دانشجوی دکتری، گروه مهندسی مکانیک بیوسیستم، واحد بناب، دانشگاه آزاد اسلامی، بناب،ایران.

2 استادیار، گروه مهندسی مکانیک بیوسیستم، واحد بناب، دانشگاه آزاد اسلامی، بناب، ایران.

چکیده

در این تحقیق، عملکرد حرارتی یک رادیاتور نمونه در شرایط محیطی تعریف‌شده، مطالعه شد. روابط حاکم بر انتقال حرارت برای جریان هوا و سیال خنک‌کننده آب و اتیلن گلیکول (%50-%50) در رادیاتور نوشته شد و سپس مشخصات رادیاتور، تغییر داده شدند و روابط، مجدد بررسی شد. مشاهده شد عملکرد حرارتی یک رادیاتور که طول آن 25 درصد کاهش داده شده ولی تعداد فین‌های آن از 385 به 437 افزایش داده شده است با عملکرد حرارتی رادیاتور اولیه، برابر است. برای بررسی این موضوع، از روش ϵ-NTU استفاده گردید. مقدار بهینه آن توسط الگوریتم ژنتیک طراحی‌شده 436 فین تعیین گردید. همچنین فاصله بین دو فین از  mm92/3 به mm94/2 کاهش یافت که مقدار بهینه آن توسط الگوریتم ژنتیک mm 867/2 تعیین گردید. کاهش طول رادیاتور، باعث سبک‌تر شدن رادیاتور و کاهش هزینه‌های ساخت می‌شود اما کاهش بیش‌ازحد آن می‌تواند باعث نزدیک شدن فین‌های خنک‌کننده به هم شود و مشکل در دفع حرارت را به وجود آورد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Redesign of engine radiator based on number of optimal fans using a genetic algorithm.

نویسندگان [English]

  • Bahman Rahmatinejad 1
  • Mahdi Abbasgholipour 2
  • Behzad Mohammadi Alasti 2
1 PhD student, Department of Biosystem Mechanical engineering, Bonab Branch, Islamic Azad University, Bonab, Iran.
2 Assistant Professor, Department of Biosystem Mechanical engineering, Bonab Branch, Islamic Azad University, Bonab, Iran.
چکیده [English]

In this study, the thermal performance of a sample radiator under defined environmental conditions was studied. The relations governing the heat transfer for the air flow and the cooling fluid of water and ethylene glycol (50% -50%) were written in the radiator and then the characteristics of the radiator were changed and the relations re-examined. It was observed that the thermal performance of a radiator whose length was reduced by 25% but number of fins increased from 385 to 437 was equal to the thermal performance of the original radiator. The ϵ-NTU method was used to investigate this matter. Its optimal value was determined by the designed genetic algorithm 436. In addition, the distance between the two fins was reduced from 3.92 mm to 2.94 mm, the optimal value of which was determined by a genetic algorithm of 2.867 mm. Reducing the length of the radiator makes the radiator lighter and reduces construction costs, but reducing it too much can cause the cooling fans to come closer together and create a problem with heat dissipation.

کلیدواژه‌ها [English]

  • Genetic Algorithm
  • Radiator function
  • cooling system
  • Engine
  • redesign
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