تخمین مقاومت برشی تیرهای بتن آرمه مسلح به الیاف پلیمری؛ مقایسه شبکه عصبی مصنوعی و روابط آیین نامه ای

نوع مقاله: علمی - پژوهشی

نویسندگان

1 استادیار، دانشکده مهندسی، دانشگاه کاشان، کاشان، ایران

2 دانشجوی کارشناسی ارشد مهندسی سازه، دانشکده مهندسی، دانشگاه کاشان، کاشان، ایران

3 کارشناس ارشد مهندسی سازه، دانشکده مهندسی، دانشگاه کاشان، کاشان، ایران

چکیده

در سال‌های اخیر آزمایشات تجربی متعددی در خصوص  تقویت برشی تیرهای بتن آرمه مسلح به الیاف پلیمری صورت گرفته است. در این راستا روابطی نیز برای تخمین مقاومت برشی تیرهای مسلح به الیاف پلیمری ارائه شده است. هدف از این مطالعه بررسی تخمین مقاومت برشی تیرهای مسلح به الیاف پلیمری بوسیله مدل شبکه عصبی مصنوعی پیش خور است. برای این منظور یک پایگاه داده متشکل از 304 تیر بتن­آرمه مسلح به الیاف پلیمری جهت ارزیابی رفتار برشی، از نتایج‌ تجزیه‌ و تحلیل‌ مقالات موجود گردآوری شده است. متغیرهای ورودی مدل شبکه عصبی شامل 11 متغیر دربرگیرنده مشخصات هندسی مقطع، میزان آرماتور، میزان الیاف پلیمری و مشخصات مصالح بتن و فولاد و الیاف پلیمری است و متغیر خروجی مقاومت برشی تیر است. بمنظور ارزیابی کارایی مدل شبکه عصبی در تخمین میزان ظرفیت برشی تیرهای تقویت شده، نتایج کسب شده از مدل شبکه عصبی با مقادیر روابط آیین نامه بتن ایران (نشریه 345) و آیین نامه بتن امریکا (ACI440)  مقایسه می‌شود. مقایسه نتایج نشان می دهد که در مجموع دقت مدل شبکه عصبی نسبت به دقت هر دو  آیین­نامه­ بیشتر است. بطور مشخص برای داده های مورد بررسی، درصد میانگین نسبی مطلق خطای برآورد در مدل شبکه عصبی 13 درصد، آیین نامه امریکا 34 درصد و آیین نامه ایران 39 درصد است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Shear strength estimation of the concrete beams reinforced with FRP; comparison of artificial neural network and equations of regulations

نویسندگان [English]

  • Mahmood Akbari 1
  • Vahid Jafari Deligani 2
  • Hamid Nezaminia 3
1 Assistant Professor, Department of Civil Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
2 MSc student, Department of Civil Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
3 MSc of Structure Engineering, Department of Civil Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
چکیده [English]

In recent years, numerous experimental tests were done on the concrete beams reinforced with the fiber-reinforced polymer (FRP). In this way, some equations were proposed to estimate the shear strength of the beams reinforced with FRP. The aim of this study is to explore the feasibility of using a feed-forward artificial neural network (ANN) model to predict the ultimate shear strength of the beams strengthened with FRP composites. For this purpose, a database consists of 304 reinforced FRP concrete beams have been collected from the available articles on the analysis of shear behavior of these beams. The inputs to the ANN model consists of the 11 variables including the geometric dimensions of the section, steel reinforcement amount, FRP amount and the properties of the concrete, steel reinforcement and FRP materials while the output variable is the shear strength of the FRP beam. To assess the performance of the ANN model for estimating the shear strength of the reinforced beams, the outputs of the ANN are compared to those of equations of the Iranian code (Publication No. 345) and the American code (ACI 440). The comparisons between the outputs of Iran and American regulations with those of the proposed model indicates that the predictive power of this model is much better than the experimental codes. Specifically, for under study data, mean absolute relative error (MARE) criteria is 13%, 34% and 39% for the ANN model, the American and the Iranian codes, respectively.

کلیدواژه‌ها [English]

  • concrete beam
  • Fiber reinforced composite
  • Shear strength
  • Artificial Neural Network
  • Publication No. 345
  • ACI 440

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