Evaluating mechanical properties and impact resistance of modified concrete containing ground Blast Furnace slag and discarded rubber tire crumbs

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作者
Mhaya, Akram M. [1 ]
Fahim Huseien, Ghasan [2 ]
Faridmehr, Iman [3 ]
Razin Zainal Abidin, Ahmad [1 ]
Alyousef, Rayed [4 ]
Ismail, Mohammad [1 ]
机构
[1] School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai,Johor,81310, Malaysia
[2] Institute for Smart Infrastructure and Innovative Construction, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor Bahru,Johor,81310, Malaysia
[3] Institute of Architecture and Construction, South Ural State University, Lenin Prospect 76, Chelyabinsk,454080, Russia
[4] Department of Civil Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Alkharj,16273, Saudi Arabia
关键词
Neural networks - Tires - Compressive strength - Ductility - Genetic algorithms - Blast furnaces - Construction industry - Light weight concrete - Slags - Concrete aggregates;
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摘要
Lately, sustainable concretes with enhanced strength performance and ductility became demanding for the construction sector. Various industrial by-products as environmental friendly wastes were shown to be promising to achieve such concretes. Meanwhile, due to the rapid industrial developments and modernized lifestyle, the tire wastes became a serious environmental concern. Inclusion of these tire wastes into the concretes was demonstrated to be beneficial to design the rubber-modified sustainable concretes. Based on this factor, we prepared several rubberized concrete mixes by integrating the Ground Blast Furnace Slag (GBFS) with different contents of Discarded Rubber Tire Crumbs (DRTCs). All the designed rubber-modified mixes were characterized using diverse analytical techniques to determine their mechanical properties and impact resistance (IR). In addition, depending on each binder mass percentage, the mechanical properties of the produced concretes were evaluated by developing an optimized artificial neural network (ANN) combined with the genetic algorithm (GA) and compared with the available experimental test database. The mixes obtained using the DRTCs contents of 5–30% as fine or/and coarse aggregates substitution revealed satisfactory compressive strength suitable for practical applications. It is established that the incorporation of DRTCs as substitute component to the natural river sand or/and crushed gravel aggregates can largely improve the IR and ductility of the proposed concretes. © 2021 Elsevier Ltd
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