مدلسازی جریان اسلامپ بتن خودتراکم حاوی متاکائولن با استفاده از روش‌های محاسبات نرم

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی و مدیریت ساخت موسسه آموزش عالی طبری بابل

2 دانشجوی دکترای دانشگاه صنعتی نوشیروانی بابل، بابل، ایران

3 استادیار دانشگاه صنعتی نوشیروانی بابل

چکیده

میزان حساسیت جریان اسلامپ بتن خود تراکم حاوی متاکائولن به مواد تشکیل دهنده آن و نسبت‌های طرح اختلاط،لزوم استفاده از مدل‌هایی با دقت بالا برای تضمین ویژگی‌های تخمین درست و تعمیم آن را ضرورت بخشیده است.ازاین رو، در این مقاله به بررسی قابلیت روش‌های اسپلاین رگرسیونی چندمتغیره تطبیقی و مدل درختی در مدلسازی و پیش‌بینی جریان اسلامپ بتن خودتراکم می-پردازد.برای این منظور،تعداد 117 داده مختلف از مقالات معتبر به چاپ رسیده جمع آوری و در این پژوهش مورد استفاده قرار گرفت.اطلاعات مورد استفاده در مدل های پیش‌نهادی در قالب هشت ورودی شامل سیمان،درشت دانه،ریزدانه،آب،متاکائولن،فوق روان کننده،چسباننده و اندازه بزرگترین دانه شرکت کننده در طرح اختلاط (Dmax) و یک خروجی جریان اسلامپ دسته بندی شد.برای ارزیابی دقت مدل‌های پیشنهادی، مطالعه ای مقایسه ای در قالب شاخص های آماری RMSE، R ، MAE انجام شد.نتایج بدست آمده از مجموعه داده ها در مراحل آموزش و آزمون مدل های پیش‌نهادی و مقایسه آنها با نتایج آزمایشگاهی پتانسیل بالای دو روش مارس و مدل درخت را در پیش‌بینی خواص بتن با دقت نشان می‌ دهد.آنالیز حساسیت انجام شده برای مشخص کردن تاثیرگزار ترین پارامتر در جریان اسلامپ بتن خودتراکم نشان داد ریزدانه و متاکائولن موثرترین متغیر‌ها درمدلسازی و پیش‌بینی جریان اسلامپ این نوع بتن خودتراکم در قالب روش‌ پیشنهادی مدل درخت در این پژوهش بوده است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Modeling the Slump Flow of Self-Compacting Concrete Incorporating Metakaolin Using Soft Computing Techniques

نویسندگان [English]

  • Ali Ashrafian 1
  • Mohammad Javad Taheri Amiri 2
  • farshidreza haghighi 3
1 MSc student, Tababri University of Babol
2 PhD student, Babol University of Technology, Babol, Iran
3 Assistant Professor, faculty of civil engineering, Babol University of technology
چکیده [English]

The sensitivity of slump flow of self-compacting concrete containing metakaolin to its ingredient materials and mixture proportions, necessitate the use of high accuracy models to guarantee both estimation and generalization features. Therefore this paper investigates the potential of multivariate adaptive regression splines (MARS) and model tree (MT) approaches in prediction of slump flow of self-compacting concrete. Total of 117 data collected from the several published literature were used in present work. The data used in proposed models are arranged in a format of eight input parameters including cement, coarse aggregate, fine aggregate, water, metakaolin, super plasticizer, binder and maximum size of aggregates (Dmax) and one output as slump flow. To evaluate the precision of the models, a comparative study has been performed in terms of RMSE, R and MAE indices. The results of training and testing datasets of the techniques are compared with experimental results and their comparisons demonstrate that the MARS and MT models have potential to predict concrete properties with great precision. Performed sensitivity analysis to assign effective parameters on slump flow was indicating fine aggregate and metakaolin is most effective variable for modeling and prediction in this type of the self-compacting concrete using MT technique in this study

کلیدواژه‌ها [English]

  • Self-Compacting Concrete
  • Slum flow
  • Metakaolin
  • MARS
  • Model tree
  • Modeling
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