بهینه‌سازی ضرایب مدل‌های تخمین مقاومت فشاری ستون‌های بتنی محصورشده با FRP با استفاده از الگوریتم نهنگ

نوع مقاله : مقاله پژوهشی (نظری)

نویسنده

عضو هیئت علمی، گروه مهندسی عمران، دانشگاه فنی و حرفه‌ای، تهران، ایران.

چکیده

محصور کردن ستون‌های بتن مسلح، یکی از رایج‌ترین روش‌های مقاوم‌سازی ستون‌ها می‌باشد. آزمایش‌های متعددی بر روی بتن­های محصورشده با ورقه­های پلیمری مسلح الیافی (FRP) انجام شده است. همچنین، مدل­های متعددی برای تعیین مقاومت فشاری نمونه­های استوانه­ای بتنی محصورشده با FRP ارائه شده است. اما در مطالعات گذشته مدل­های کمتری برای تعیین مقاومت فشاری بتن­های محصورشده با FRP دارای مقطع مربع و مستطیل ارائه گردیده است. مدل­های ارائه شده در مطالعات گذشته با تعداد محدود نمونه بوده است. بنابراین استفاده از این مدل­ها برای تخمین مقاومت فشاری انواع بتن­های محصورشده با انواع FRP ممکن است دارای دقت کافی نباشد. بنابراین ارائه مدلی که بتواند مقاومت فشاری این نمونه­ها را با دقت کافی تخمین بزند، یکی از نیازهای اساسی مهندسان طراح مقاوم­سازی سازه­های بتنی می­باشد. در این مطالعه ابتدا، پایگاه اطلاعات 485 نمونه آزمایشگاهی بتن محصورشده با انواع FRP دارای مقطع مربعی و مستطیلی، از مطالعات گذشته گردآوری گردید. با بررسی اولیه 44 نمونه پرت از این پایگاه حذف گردید. سپس، با استفاده از 70 درصد نمونه­های این پایگاه و الگوریتم نهنگ، ضرایب ثابت مدل­های مطالعات گذشته طوری بهینه شد که اختلاف بین مقاومت فشاری آزمایشگاهی و مدل­ها به حداقل برسد. بنابراین این مدل­های بهبود یافته می­تواند برای تخمین مقاومت فشاری انواع بتن­های محصورشده با FRP استفاده شود. با مقایسه شاخص­های آماری نمونه­هایی که در فرآیند آموزش دخیل نبوده­اند نتایج نشان می­دهد که خطای کلی به طور میانگین 27 درصد کاهش و ضریب همبستگی (R2) 3 درصد افزایش می­یابد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Optimization of Coefficients of FRP-Confined Concrete Columns Compressive Strength Estimation Models using Whale Algorithm

نویسنده [English]

  • Gholamreza Ahani
Assistant faculty member, Department of Civil Engineering, Technical and Vocational University (TVU), Tehran, Iran.
چکیده [English]

Confining reinforced concrete columns is one of the most conventional methods of column retrofit. Many tests have been conducted on fiber-reinforced polymer (FRP) confined concrete. Additionally, numerous models for determining the compressive strength of FRP-confined concrete cylindrical samples have been proposed. However, in earlier research, fewer models have been presented for determining the compressive strength of FRP-confined concrete with square and rectangular sections. Previous studies have offered models with a limited number of samples. As a result, using these models to estimate the compressive strength of various types of FRP-confined concrete might not be sufficiently precise. Therefore, one of the fundamental requirements for design engineers in retrofitting concrete structures is the presentation of a model capable of reliably estimating the compressive strength of these samples. Initially, the database for the present research was built using 485 laboratory samples of concrete confined with various types of FRP with square and rectangular sections from prior studies. Forty-four outlier samples were deleted from the database during the initial assessment. The constant coefficients of previous research models were then adjusted so as to minimize the discrepancy between laboratory compressive strength and models using 70% of the samples and the whale optimization algorithm. Therefore, these improved models might be used to estimate the compressive strength of several types of FRP-confined concrete. By comparing the statistical indices of samples that were not engaged in the training process, the results demonstrated that the total error decreased by 27 percent on average, and the correlation coefficient (R2) increased by 3 percent.

کلیدواژه‌ها [English]

  • Retrofit Confining Fiber
  • reinforced polymer (FRP) Square and rectangular columns Compressive strength Whale optimization algorithm

مراجع

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فصلنامه علمی کارافن
دوره 19، شماره 3 - شماره پیاپی 59
فنی و مهندسی
آذر 1401
صفحه 433-460

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  • تاریخ دریافت: 03 اسفند 1400
  • تاریخ بازنگری: 22 مرداد 1401
  • تاریخ پذیرش: 02 مهر 1401

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