IJE TRANSACTIONS C: Aspects Vol. 31, No. 6 (June 2018) 903-909   

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A. Heidari and M. Hashempour
( Received: November 05, 2017 – Accepted in Revised Form: February 07, 2018 )

Abstract    Acrylic polymer that is highly stable against chemicals and is a good choice when concrete is subject to chemical attack. In this study, self-compacting concrete (SCC) made using acrylic polymer, nanosilica and microsilica has been investigated. The results of experimental testing showed that the addition of microsilica and acrylic polymer decreased the tensile, compressive and bending strength of the concrete. The addition of nanosilica and an increase in polymer content increased the bending strength of concrete and decreased the tensile and compressive strengths. Because, in the laboratory, the number of samples were limited and the amount of variation was small, comprehensive results cannot be achieved. With the help of neural networks, estimating any amount within the range of the input data is possible. In this paper, in addition to the experimental results, a backpropagation neural network (BNN) was used to simulate the testing on the strength of self-compacting polymeric concrete. The results showed that the use of the normalized mean squared error, resilient backpropagation training, tangent-sigmoid and log sigmoid transfer functions and five neurons in each hidden layers in a two-layer BNN produced good results with a regression value of 0.95 and error of 0.17.


Keywords    Backpropagation Neural Network, Polymeric Concrete, Self-compacting Concrete, Acrylic Polymer


چکیده    پلیمر اکریلیک بهدلیل مقاومت بالا در برابر مواد شیمیایی گزینه مناسبی در ساخت بتنهای مقاوم در برابر حملات شیمیایی است. در این مطالعه به بررسی بتن پلیمری خودمتراکم ساخته شده با پلیمر اکریلیک، نانوسیلیس و میکروسیلیس پرداخته شدهاست. نتایج حاصل از آزمایش نمونهها نشان داده که افزودن میکروسیلیس و افزایش میزان پلیمر، مقاومت کششی، فشاری و خمشی را کاهش میدهد. افزودن نانوسیلیس مقاومت خمشی بتن را افزایش و مقاومت کششی و فشاری با افزایش پلیمر کاهش یافته است. این مقدار کاهش به نسبت سایر طرحها کمتر است. بهعلت آنکه در آزمایشگاه ساخت نمونهها محدود و میزان تغییرات مقادیر اندک است نمیتوان به نتیجه مناسبی دست یافت. به کمک شبکههای عصبی هر مقداری را که در محدوده دادههای ورودی باشد را میتوان تخمین زد. در این مقاله علاوه بر نتایج آزمایشگاهی، عملکرد شبکه عصبی انتشار برگشتی بر تخمین مقاومت بتن خودمتراکم پلیمری پرداخته شدهاست. نتایج شبکه عصبی نشان داده که یک شبکه عصبی انتشار برگشتی دو لایه که در آن از تابع خطای استاندارد میانگین، تابع آموزش انعطافپذیر، تابع تحریک لوگ سیگموئید و تانژانت سیگموئید، و 5 نرون در هر یک از لایههای پنهان استفاده شود، نتایج مناسبی حاصل شده که در آن رگرسیون 95/0 و مقدار خطا 17/0 است.


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