A unified model for predicting the compressive strength of recycled aggregate concrete containing supplementary cementitious materials-Reference-Cited by-同舟云学术

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A unified model for predicting the compressive strength of recycled aggregate concrete containing supplementary cementitious materials

Published:2020-04 Issue: Volume:251 Page:119752
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Xie Tianyu,Yang Guosong,Zhao Xinyu,Xu Jinjun,Fang Chengfeng

Funder

China’s National Natural Science Foundation of China

Guangdong’s Provincial Science and Technology Innovation

Fundamental Research Funds for the Central Universities, China

State Key Laboratory of Subtropical Building Science

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment

Reference113 articles.

1. Properties of concrete containing construction and demolition wastes and fly ash;Ahmed;J. Mater. Civ. Eng.,2012

2. Acceptability of demolished concrete waste aggregate in making high strength self-compacting concrete;Alam;Int. J. Civ. Eng.,2013

3. Evaluation of industrial by-products as sustainable pozzolanic materials in recycled aggregate concrete;Alnahhal;Sustainability,2017

4. Durability of recycled aggregate concrete using pozzolanic materials;Ann;Waste Manag.,2008

5. Supplementary cementitious materials origin from agricultural wastes–A review;Aprianti;Constr. Build. Mater.,2015

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1. Experimental and simulation analysis of RCA and para-wood ash as partial substitutes for NCA and cement in recycled aggregate concrete;Case Studies in Construction Materials;2024-12

2. Intelligent prediction of comprehensive mechanical properties of recycled aggregate concrete with supplementary cementitious materials using hybrid machine learning algorithms;Case Studies in Construction Materials;2024-12

3. Prediction of compressive strength of recycled concrete using gradient boosting models;Ain Shams Engineering Journal;2024-09

4. Determination of Fracture Mechanic Parameters of Concretes Based on Cement Matrix Enhanced by Fly Ash and Nano-Silica;Materials;2024-08-27

5. Interpretable Machine Learning Models for Prediction of UHPC Creep Behavior;Buildings;2024-07-07

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