پیش‌بینی ضریب زبری مانینگ در کانال‌های روباز با فرم بستر تلماسه با استفاده از روش الگوریتم تکاملی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار گروه آب دانشکده عمران دانشگاه تبریز

2 استاد گروه آب دانشکده عمران دانشگاه تبریز

3 دانشجوی دکتری عمران سازه های هیدرولیکی دانشگاه تبریز و گروه عمران، واحد اهر، دانشگاه آزاد اسلامی، اهر – ایران

چکیده

پیش­بینی دقیق ضریب زبری در کانال­های روباز با شکل بستر تاثیر بسزایی در برنامه­ریزی، طراحی و بهره­برداری پروژه­های منابع آبی شامل انتقالآب و سیستم­های رودخانه­ای دارد. شکل­های مختلف بستر مانند تلماسه­ها اثراتبارزی بر روی مقاومت جریان دارند. با این وجود، به دلیل تاثیر پارامترهای مختلف بر ضریب زبری جریان تخمین دقیق این پارامتر مشکل می­باشد. در این مقاله کارایی روش برنامه‌ریزی بیان ژن (GEP) در تخمین ضریب زبری مانینگ درکانال­های روباز با شکل بستر تلماسه مورد ارزیابی قرارگرفته است. بدین منظور مدل‌های مختلفی بر اساس مشخصات جریان، فرم بستر و ذرات رسوبی تعریف‌ شد و با استفاده از چهار سری داده آزمایشگاهی مورد آزمون قرار گرفت. نتایج حاصله ضمن تائید قابلیت روش به‌کاررفته در تحقیق، برتری این روش را نسبت به روابط کلاسیک در تخمین ضریب زبری مانینگ به اثبات رساند. همچنین مشخص گردید که مدل با پارامترهای ورودی مربوط به هر دو مشخصات جریان و ذرات رسوبی در تخمین ضریب زبری مانینگ موفق­تر می­باشد. مطابق با نتایج آنالیز حساسیت پارامتر عدد رینولدز  بیشترین تاثیر را در پیش­بینی ضریب زبری دارا است.

کلیدواژه‌ها


عنوان مقاله [English]

Prediction of Manning roughness coefficient in open channels with dune bedforms using evolutionary algorithm method

نویسندگان [English]

  • Kiyoumars Roushangar 1
  • mohammad taghi Alami 2
  • SEYEDMAHDI SAGHEBIAN 3
1 Associate Professor, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
2 Professor, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
3 PhD student, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
چکیده [English]

An accurate prediction of the roughness coefficient in open channels with bedforms has a significant impact on the planning, design and operation of water resources projects, including water transport and river systems. Different bedforms such as dunes have obvious effects on flow resistance. However, due to the impact of various parameters on the roughness coefficient, accurate estimation of this parameter is difficult. In this paper, the efficiency of Gene Expression Programming (GEP) method in estimating manning roughness coefficient in open-channel channels with dune bedforms has been evaluated. In this regard, various models were defined based on flow, bedform, and sediment particles characteristics and were tested using four laboratory data series. The results proved capability of GEP in predicting Manning roughness coefficient and it was observed that the applied method is more accurate than semi-theoretical relationships.  It was also found that the model with input parameters related to both flow and sediment particles characteristics is more successful in estimating Manning roughness coefficient. According to the results of the sensitivity analysis, the Reynolds number parameter has the most significant impact in predicting the roughness coefficient.

کلیدواژه‌ها [English]

  • Dune
  • Gene expression programming
  • Manning Roughness coefficient
  • open channel
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