Machine learning study of the mechanical properties of concretes containing waste foundry sand
Author:
Publisher
Elsevier BV
Subject
General Materials Science,Building and Construction,Civil and Structural Engineering
Reference63 articles.
1. F. Tittarelli, 4 – Waste foundry sand, in: Woodhead Publishing Series in Civil and Structural Engineering, Woodhead Publishing, 2018: pp. 121–147.
2. Strength, durability, and micro-structural properties of concrete made with used-foundry sand (UFS);Siddique;Constr. Build. Mater.,2011
3. Effect of two different sources and washing treatment on the properties of UFS by-products for mortar and concrete production;Monosi;Constr. Build. Mater.,2013
4. The effect of waste foundry sand (WFS) as partial replacement of sand on the mechanical, leaching and micro-structural characteristics of ready-mixed concrete;Basar;Constr. Build. Mater.,2012
5. Recycle option for metallurgical by-product (Spent Foundry Sand) in green concrete for sustainable construction;Siddique;J. Cleaner Prod.,2018
Cited by 150 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. Prediction of time-dependent concrete mechanical properties based on advanced deep learning models considering complex variables;Case Studies in Construction Materials;2024-12
2. Machine and deep learning methods for concrete strength Prediction: A bibliometric and content analysis review of research trends and future directions;Applied Soft Computing;2024-10
3. Predictive performance assessment of recycled coarse aggregate concrete using artificial intelligence: A review;Cleaner Materials;2024-09
4. Using ensemble machine learning and metaheuristic optimization for modelling the elastic modulus of geopolymer concrete;Cleaner Materials;2024-09
5. Drying shrinkage and crack width prediction using machine learning in mortars containing different types of industrial by-product fine aggregates;Journal of Building Engineering;2024-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3