RETRACTED: Strength and dynamic elasticity modulus of rubberized concrete designed with ANFIS modeling and ultrasonic technique-Reference-Cited by-同舟云学术

RETRACTED: Strength and dynamic elasticity modulus of rubberized concrete designed with ANFIS modeling and ultrasonic technique

Published:2020-04 Issue: Volume:240 Page:117920
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Jalal Mostafa,Grasley Zachary,Nassir Navid,Jalal Hamid

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference69 articles.

1. Effects of waste steel fibers on strength and stress-strain behavior of concrete incorporating silica nanopowder;Sotoudeh;Indian J. Sci. Technol.,2013

2. Compressive strength enhancement of concrete reinforced by waste steel fibers utilizing nano SiO2;Jalal;Middle East J. Sci. Res.,2012

3. A comprehensive review on the applications of waste tire rubber in cement concrete;Thomas;Renew. Sustain. Energy Rev.,2016

4. ETRMA. ETRMA, annual report 2013/2014, ETRMA 2014 Brussels, Belgium.

5. Rubber Manufacturers Association. US scrap tire management summary. Washington DC, USA; 2014.

Cited by 35 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-driven predictive models for compressive strength of steel fiber reinforced concrete subjected to high temperatures;Case Studies in Construction Materials;2023-12

2. Application of hybrid intelligent algorithm for multi-objective optimization of high performance concrete in complex alpine environment highway;Construction and Building Materials;2023-11

3. Machine learning interpretable-prediction models to evaluate the slump and strength of fly ash-based geopolymer;Journal of Materials Research and Technology;2023-05

4. Use of operational research techniques for concrete mix design: A systematic review;Heliyon;2023-04

5. An adaptive neuro-fuzzy inference system (ANFIS) model to predict the pozzolanic activity of natural pozzolans;COMPUT CONCRETE;2023