Frost resistance and improvement techniques of recycled concrete: a comprehensive review DOI Creative Commons

Quan Ma,

Zhenhua Duan, Jun Wang

et al.

Frontiers in Materials, Journal Year: 2024, Volume and Issue: 11

Published: Oct. 28, 2024

In the pursuit of sustainable construction practices, utilization recycled concrete has emerged as a pivotal strategy, distinguished by its commitment to resource conservation and environmental stewardship. Nevertheless, inherent micro-porosity micro-cracking within old mortar may lead weak bonding performance at interfacial transition zone, culminating in diminished strength, reduced density, elevated water absorption rates compared conventional concrete, which critically impairs cold climates subjected freeze-thaw cycles. Consequently, this paper provides structured examination frost resistance properties cycling. Initially, study delineates mechanisms frost-induced damage synthesizing degradation pathways observed both during exposure. Subsequently, detailed analysis is conducted identify factors affecting resistance, encompassing proportion moisture affinity aggregates, addition silica fume fly ash, water-to-cement ratio, degree saturation. final segment, compiles reviews strategies for bolstering including incorporation air-entraining admixtures, fiber reinforcement, aggregate modification approaches. The objective research offer thorough comprehension with concentration on damage, critical determinants interventions augment resilience against freezing conditions. On basis, present paper, conjunction characteristics current status proposes recommendations application regions. This review anticipated facilitate researchers gaining comprehensive understanding measures enhance resistance. Furthermore, it aims assist engineering technical personnel selecting appropriate treatment methods improve regions, thereby promoting practical such areas.

Language: Английский

A review on properties and multi-objective performance predictions of concrete based on machine learning models DOI

Bowen Ni,

Md Zillur Rahman, Shuaicheng Guo

et al.

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112017 - 112017

Published: Feb. 1, 2025

Language: Английский

Citations

2
Comprehensive Review of Fatigue Life Prediction of Plain Concrete Using Machine Learning and Finite Element Methods DOI

Haikhal Faeez Hairuddin,

Mohamad Shazwan Ahmad Shah, Norhazilan Md Noor

et al.

Mechanisms and machine science, Journal Year: 2025, Volume and Issue: unknown, P. 440 - 459

Published: Jan. 1, 2025

Language: Английский

Citations

0
Machine Learning Models for Predicting Compressive Strength of Eco-Friendly Concrete with Copper Slag Aggregates DOI
Yaser Moodi, Naser Safaeian Hamzehkolaei, Iman Afshoon

et al.

Materials Today Communications, Journal Year: 2025, Volume and Issue: unknown, P. 112572 - 112572

Published: April 1, 2025

Language: Английский

Citations

0
Machine learning-driven modeling and interpretative analysis of drying shrinkage behavior in magnesium silicate hydrate cement DOI
Xiao Luo, Yue Li, Hui Lin

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112721 - 112721

Published: April 1, 2025

Language: Английский

Citations

0
Artificial intelligence in the design, optimization, and performance prediction of concrete materials: a comprehensive review DOI Creative Commons
Dayou Luo,

Kejin Wang,

Dongming Wang

et al.

npj Materials Sustainability, Journal Year: 2025, Volume and Issue: 3(1)

Published: May 17, 2025

Language: Английский

Citations

0
Data-intelligence driven methods for durability, damage diagnosis and performance prediction of concrete structures DOI Creative Commons
Fan Li, Daming Luo, Ditao Niu

et al.

Communications Engineering, Journal Year: 2025, Volume and Issue: 4(1)

Published: June 3, 2025

A large number of in-service reinforced concrete structures are now entering the mid-to-late stages their service life. Efficient detection damage characteristics and accurate prediction material performance degradation have become essential for ensuring safety these structures. Traditional methods, which primarily rely on manual inspections sensor monitoring, inefficient lack accuracy. Similarly, models materials, often based limited experimental data polynomial fitting, oversimplify influencing factors. In contrast, partial differential equation that account mechanisms computationally intensive difficult to solve. Recent advancements in deep learning machine learning, as part artificial intelligence, introduced innovative approaches both This paper provides a comprehensive overview theories models, reviews current research application durability structures, focusing two main areas: intelligent predictive modeling durability. Finally, article discusses future trends offers insights into innovation structure

Language: Английский

Citations

0
Investigation on compressive strength and splitting tensile strength of manufactured sand concrete: machine learning prediction and experimental verification DOI

Kaikai Jin,

Yue Li, Jiale Shen

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 110852 - 110852

Published: Sept. 1, 2024

Language: Английский

Citations

3
Frost resistance and improvement techniques of recycled concrete: a comprehensive review DOI Creative Commons

Quan Ma,

Zhenhua Duan, Jun Wang

et al.

Frontiers in Materials, Journal Year: 2024, Volume and Issue: 11

Published: Oct. 28, 2024

In the pursuit of sustainable construction practices, utilization recycled concrete has emerged as a pivotal strategy, distinguished by its commitment to resource conservation and environmental stewardship. Nevertheless, inherent micro-porosity micro-cracking within old mortar may lead weak bonding performance at interfacial transition zone, culminating in diminished strength, reduced density, elevated water absorption rates compared conventional concrete, which critically impairs cold climates subjected freeze-thaw cycles. Consequently, this paper provides structured examination frost resistance properties cycling. Initially, study delineates mechanisms frost-induced damage synthesizing degradation pathways observed both during exposure. Subsequently, detailed analysis is conducted identify factors affecting resistance, encompassing proportion moisture affinity aggregates, addition silica fume fly ash, water-to-cement ratio, degree saturation. final segment, compiles reviews strategies for bolstering including incorporation air-entraining admixtures, fiber reinforcement, aggregate modification approaches. The objective research offer thorough comprehension with concentration on damage, critical determinants interventions augment resilience against freezing conditions. On basis, present paper, conjunction characteristics current status proposes recommendations application regions. This review anticipated facilitate researchers gaining comprehensive understanding measures enhance resistance. Furthermore, it aims assist engineering technical personnel selecting appropriate treatment methods improve regions, thereby promoting practical such areas.

Language: Английский

Citations

1