تخمین مقاومت فشاری بتن دارای الیاف لاستیک ضایعاتی با استفاده از شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی (کاربردی)

نویسنده

دکتری، گروه مهندسی عمران، دانشکده امام محمد باقر (ع)، دانشگاه فنی و حرفه‌ای استان مازندران، ایران.

چکیده

یکی از مواردی که به‌عنوان مواد غیرقابل بازیافت وارد محیط‌زیست می‌شود، لاستیک‌های مستعمل خودرو است. تحقیقات انجام‌شده نشان می‌دهد لاستیک‌های مستعمل از موادی تشکیل‌شده‌اند که به دلیل تجزیه نشدن آن‌ها در شرایط معمول، سبب ایجاد آلودگی‌ و آسیب به محیط‌زیست شده است. بر اساس تحقیقات صورت گرفته، یکی از راه‌های حذف این مواد، استفاده از ضایعات لاستیکی در بتن است. لذا در این تحقیق، با جایگزینی ذرات لاستیکی ضایعاتی به‌جای سنگ‌دانه‌ها و تخمین مقاومت فشاری بتن توسط شبکه عصبی مصنوعی با استفاده از پارامترهای ورودی (نسبت آب به سیمان، ماده افزودنی فوق‌روان‌کننده و ترکیب وزنی دانه‌بندی) پرداخته ‌شده است. نتایج حاصل از این پژوهش با پژوهش‌های مرتبط محققان مورد مقایسه قرار گرفت که حاکی از برتری و دقت بالای شبکه عصبی مصنوعی حاصله در این پژوهش است. شاخص مهندسی a-20 برای شبکه عصبی برابر یک به‌دست‌آمده و خطای 99 درصد از داده‌ها، کمتر از 15 درصد به‌دست‌آمده که نشان از تقریب مناسب مقاومت فشاری بتن حاوی ذرات لاستیکی ضایعاتی توسط شبکه عصبی مصنوعی است. همچنین نتایج آنالیز حساسیت با استفاده از روش میلن حاکی از تأثیر 40 درصدی مقدار وزنی ماده افزودنی فوق‌روان‌کننده به‌عنوان پارامتر حساس در این نوع از بتن است.

کلیدواژه‌ها


عنوان مقاله [English]

Prediction of compressive strength of concrete with rubber fibers using artificial neural networks

نویسنده [English]

  • Seyed Reza Salimbahrami
PhD, Department of Civil Engineering, Faculty of Imam Mohammad Baqer, Mazandaran Branch, Technical and Vocational University (TVU), Sari, Iran.
چکیده [English]

A non-recyclable material that enters the environment is used car tires. Research shows that used tires are made of materials that, due to their non-decomposition under normal conditions, cause pollution and damage to the environment. According to research, one method of removing these materials is to use rubber waste in concrete. Therefore, in this study, aggregate composites were replaced by waste rubber particles the compressive strength of concrete was estimated by artificial neural network using the input parameters water to cement ratio, superplasticizer additive and granulation weight composition. The results of this study were compared with other related research studies and confirmed the superiority and high accuracy of the artificial neural network obtained in this study. The a-20 engineering index of the neural network was determined to be one and the error of 99% of the data was less than 15%, indicating the appropriate approximation of the compressive strength of concrete containing waste rubber particles by the artificial neural network. In addition, the results of the sensitivity analysis using the Millen method indicated a 40% effect of the weight of the superplasticizer additive as a sensitive parameter in this type of concrete.

کلیدواژه‌ها [English]

  • Artificial neural network
  • recycling
  • environment
  • concrete
  • waste rubber particles
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