PREDICTION OF ENERGY ABSORPTION CAPABILITY IN FIBER REINFORCED SELF-COMPACTING CONCRETE CONTAINING NANO-SILICA PARTICLES USING ARTIFICIAL NEURAL NETWORK

Authors

  • HAMIDREZA TAVAKOLI BABOL UNIVERSITY OF TECHNOLOGY
  • OMID LOTFIOMRAN BABOL UNIVERSITY OF TECHNOLOGY
  • SAMAN SOLEIMANI KUTANAEI QAEMSHAHR BRANCH, ISLAMIC AZAD UNIVERSITY
  • MASUOD FALLAHTABARSHIADE BABOL UNIVERSITY OF TECHNOLOGY

Keywords:

FIBER, SELF-COMPACTING CONCRETE, NANO-SILICA, MECHANICAL PROPERTIES, ARTIFICIAL NEURAL NETWORK.

Abstract

THE MAIN OBJECTIVE OF THE PRESENT WORK IS TO UTILIZE FEED FORWARD MULTI-LAYER PERCEPTRON TYPE OF ARTIFICIAL NEURAL NETWORKS TO FIND THE COMBINED EFFECT OF NANO-SILICA AND DIFFERENT FIBERS (STEEL, POLYPROPYLENE, GLASS) ON THE TOUGHNESS, FLEXURAL STRENGTH AND FRACTURE ENERGY OF CONCRETE IS EVALUATED. FOR THIS PURPOSE, 40 MIX PLOT INCLUDING 4 SERIES A AND B AND C AND D, WHICH CONTAIN, RESPECTIVELY, 0, 2, 4 AND 6% WEIGHT OF CEMENT, NANO-SILICA PARTICLES WERE USED AS A SUBSTITUTE FOR CEMENT. EACH OF SERIES INCLUDES THREE TYPES OF FIBERS (METAL: 0.2, 0.3 AND 0.5% VOLUME AND POLYPROPYLENE: 0.1, 0.15 AND 0.2 % VOLUME AND GLASS 0.15 AND 0.2 AND 0.3% BY VOLUME) WERE TESTED.

THE OBTAINED RESULTS FROM THE EXPERIMENTAL DATA ARE USED TO TRAIN THE MLP TYPE ARTIFICIAL NEURAL NETWORK. THE RESULTS OF THIS STUDY SHOW THAT FIBERS CONJUGATE PRESENCE AND OPTIMAL PERCENT OF NANO-SILICA IMPROVED TOUGHNESS, FLEXURAL STRENGTH AND FRACTURE ENERGY OF CONCRETE OF SELF-COMPACTING CONCRETE.

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Published

2014-01-20

Issue

Vol. 11 No. 6 (2014)

Section

Articles

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