Strength prediction and optimization for ultrahigh-performance concrete with low-carbon cementitious materials – XG boost model and experimental validation-Reference-Cited by-同舟云学术

Strength prediction and optimization for ultrahigh-performance concrete with low-carbon cementitious materials – XG boost model and experimental validation

Published:2023-07 Issue: Volume:387 Page:131606
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Khan Mohammad Iqbal,Abbas Yassir M.,Fares Galal,Alqahtani Fahad K.

Funder

Ministry of Education – Kingdom of Saudi Arabi

King Saud University

Publisher

Elsevier BV

Subject

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

Reference109 articles.

1. Cost-performance balance and new image analysis technique for ultra-high performance hybrid nano-based fiber-reinforced concrete;Khan;Constr. Build. Mater.,2022

2. Pedestrian Bridge over Las Vegas Avenue in Medellín;Abellán-García,2021

3. Factorial design of reactive concrete powder containing electric arc slag furnace and recycled glass powder;Abellán-García;Dyna,2020

4. Field testing of an ultra-high performance concrete overlay, United States;Haber,2017

5. Development of Ultra-High Performance concrete jointed precast decks and concrete piles in integral abutment bridges;Shaaban;The First International Symposium on Jointless & Sustainable Bridges,2016

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