Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives

NF Alkayem, L Shen, A Mayya, PG Asteris, R Fu… - Journal of Building …, 2024 - Elsevier
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …

Machine learning in concrete science: applications, challenges, and best practices

Z Li, J Yoon, R Zhang, F Rajabipour… - npj computational …, 2022 - nature.com
Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …

Fire-induced spalling of ultra-high performance concrete: A systematic critical review

M Amran, G Murali, N Makul, M Kurpińska… - … and Building Materials, 2023 - Elsevier
Ultra-high performance concrete (UHPC) is a novel concrete class characterized by a
compressive strength of more than 150 MPa. One of the most significant drawbacks of …

Strategy for preventing explosive spalling and enhancing material efficiency of lightweight ultra high-performance concrete

JX Lu, P Shen, Y Sun, CS Poon - Cement and Concrete Research, 2022 - Elsevier
The highly dense structure which causes the risk of explosive spalling is one of the major
limitations of using ultra high-performance concrete (UHPC). This study developed a …

Verifying domain knowledge and theories on Fire-induced spalling of concrete through eXplainable artificial intelligence

MK al-Bashiti, MZ Naser - Construction and Building Materials, 2022 - Elsevier
This paper adopts eXplainable Artificial Intelligence (XAI) to identify the key factors
influencing fire-induced spalling of concrete and to extract new insights into the …

[HTML][HTML] Machine learning for all! Benchmarking automated, explainable, and coding-free platforms on civil and environmental engineering problems

MZ Naser - Journal of Infrastructure Intelligence and Resilience, 2023 - Elsevier
One of the key challenges in fully embracing machine learning (ML) in civil and
environmental engineering revolves around the need for coding (or programming) …

[HTML][HTML] Intelligent predicting and monitoring of ultra-high-performance fiber reinforced concrete composites− A review

D Fan, Z Chen, Y Cao, K Liu, T Yin, XS Lv, JX Lu… - Composites Part A …, 2024 - Elsevier
Ultra-high-performance fiber reinforced concrete (UHPFRC) is an advanced composite
known for its exceptional mechanical properties and durability, playing a vital role in modern …

[BOOK][B] Machine learning for civil and environmental engineers: A practical approach to data-driven analysis, explainability, and causality

MZ Naser - 2023 - books.google.com
Accessible and practical framework for machine learning applications and solutions for civil
and environmental engineers This textbook introduces engineers and engineering students …

Can domain knowledge benefit machine learning for concrete property prediction?

Z Li, T Pei, W Ying, WV Srubar III… - Journal of the …, 2024 - Wiley Online Library
Understanding and predicting process–structure–property–performance relationships for
concrete materials is key to designing resilient and sustainable infrastructure. While …

Assessment of corrosion probability of steel in mortars using machine learning

H Ji, Y Lyu, Z Tian, H Ye - Reliability Engineering & System Safety, 2025 - Elsevier
Corrosion assessment enables engineers to quickly discern the corrosion status of steel in
concrete structures. However, existing assessment methods mainly rely on a single-factor …