تعیین پارامترتنش موثردرشاخه خشک اندازی به روش برنامه نویسی ژنتیکی چندژنی

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی، دانشگاه شیراز، شیراز، ایران

چکیده

رفتار هیدرومکانیکی خاکهای غیراشباع تحت تاثیر وضعیت تنش قرار دارد. در سال های اخیر استفاده از تنش موثر به عنوان متغیر بنیادین که یک محیط چند فازی را به یک محیط پیوسته معادل تبدیل می کند بیش از پیش در بین محققان گسترش یافته است.  محاسبه تنش موثر نیازمند تخمین پارامتر تنش موثر است که خود تابعی از سایر متغیرهای فیزیکی تاثیرگذار و پارامترهای اساسی همانند خصوصیات منحنی نگهداشت آب-خاک می باشد. در این تحقیق از برنامه‌نویسی ژنتیکی چند ژنی (MGGP)  برای پیش‌بینی رابطه تنش مؤثر براساس پارامترها و متغیرهای فیزیکی تاثیرگذار استفاده شده است. مزیت اصلی رویکرد MGGP توانایی آن در پیش بینی معادلات بین متغیرهای یک سیستم پیچیده فیزیکی بدون هیچگونه فرض قبلی در مورد شکل احتمالی رابطه عملکردی است. مجموعه داده های ورودی شامل تنش خالص، مکش، شیب منحنی نگهداشت آب خاک (SWRC) ، فشار ورود هوا، مقدار آب حجمی باقیمانده و اشباع است. مقایسه پیش‌بینی مدل با داده‌های آزمایشگاهی و همچنین روابط سایر محققین نشان‌ داد عملکرد مدل در تخمین پارامتر تنش موثر قابل قبول و از دقت بالایی برخوردار است. دقت بالای معادله پیشنهادی، توسط ضریب تعیین94% بدست آمده برای 101 داده پارامتر تنش موثر گردآوری شده از ادبیات تحقیق، تایید گردید.  مطالعه پارامتری نشان داد که افرایش نسبت تنش خالص به مکش ورود هوا، به افزایش پارامتر تنش موثر در مکشهای یکسان می انجامد. درحالی که افزایش شیب منحنی نگهداشت آب-خاک و یا کاهش نسبت آب باقیمانده به آب اشباع به کاهش پارامتر تنش موثر در مکشهای یکسان می انجامد.

کلیدواژه‌ها

عنوان مقاله [English]

Determining the effective stress parameter in drying path by MGGP method

نویسندگان [English]

  • Ehsan Nikooee
  • Kasra Kamran Nejad
Civil and Environmental Engineering Department, Shiraz University
چکیده [English]

The hydromechanical behavior of unsaturated soils depends on their state of stress. In recent years, the use of effective stress as a fundamental variable converting a multiphase medium to a continuum has appealed to researchers’ attention. The determination of effective stress needs estimation of the so-called effective stress parameter, which is a function of other physical variables and essential parameters such as those of the soil water retention curve (SWRC). In the current study, multigene genetic programming (MGGP) has been employed to predict a relationship between the effective stress parameter of soils. The input variables are the net stress, suction, slope of the soil water retention curve, air entry value, and residual and saturated water contents. The comparison of the performance and accuracy of the obtained equation with the available equations as well as the values of effective stress parameters obtained from experimental tests indicate the reasonable adequacy and accuracy of the proposed equation.  For this purpose, 101 data points of effective stress parameters from the literature were gathered and used. The high coefficient of determination obtained for the proposed equation, namely, 0.94, confirmed its reasonable accuracy. The parametric study revealed that an increase in the ratio of net stress to the air entry value will lead to an increase in the effective stress parameter for the same suction levels. However, a decrease in the effective stress parameter values was observed with the increase in the SWRC slope, and with the decrease in the ratio of residual to saturated water content.

کلیدواژه‌ها [English]

  • Effective stress parameter
  • Artificial intelligence
  • Multi-gene genetic programming
  • Soil-water retention curve
  • Unsaturated soil

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نشریه مهندسی عمران امیرکبیر
دوره 55، شماره 5
مرداد 1402
صفحه 1039-1056

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