Machine learning-based methods in structural reliability analysis: A review

SS Afshari, F Enayatollahi, X Xu, X Liang - Reliability Engineering & System …, 2022 - Elsevier
Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

[HTML][HTML] Adaptive approaches in metamodel-based reliability analysis: A review

R Teixeira, M Nogal, A O'Connor - Structural Safety, 2021 - Elsevier
The present work reviews the implementation of adaptive metamodeling for reliability
analysis with emphasis in four main types of metamodels: response surfaces, polynomial …

The role of artificial intelligence and digital technologies in dam engineering: Narrative review and outlook

MA Hariri-Ardebili, G Mahdavi, LK Nuss… - Engineering Applications of …, 2023 - Elsevier
This narrative review paper explores the diverse applications of artificial intelligence (AI) in
the field of dam engineering. Authored by research engineers specializing in civil …

A surrogate-assisted stochastic optimization inversion algorithm: Parameter identification of dams

YF Li, MA Hariri-Ardebili, TF Deng, QY Wei… - Advanced Engineering …, 2023 - Elsevier
Dynamic monitoring data plays an essential role in the structural health monitoring of dams.
This study presents a surrogate-assisted stochastic optimization inversion (SASOI) …

A unified analysis framework of static and dynamic structural reliabilities based on direct probability integral method

G Chen, D Yang - Mechanical Systems and Signal Processing, 2021 - Elsevier
Generally, the static and dynamic reliabilities of structures are addressed separately in the
existing methods except the computationally expensive stochastic sampling-based …

A comparative investigation using machine learning methods for concrete compressive strength estimation

K Güçlüer, A Özbeyaz, S Göymen… - Materials Today …, 2021 - Elsevier
Concrete compressive strength plays an important role in determining the mechanical
properties of concrete. The determination of concrete compressive strength requires lengthy …

The prediction of fire performance of concrete-filled steel tubes (CFST) using artificial neural network

MJ Moradi, K Daneshvar, D Ghazi-Nader… - Thin-Walled Structures, 2021 - Elsevier
Search for enhancing the efficiency has led to composite structures such as concrete-filled
steel tubes (CFST) with increasing applications across the world. The fire performance of …

Data-driven modeling of mechanical properties of fiber-reinforced concrete: a critical review

F Kazemi, T Shafighfard, DY Yoo - Archives of Computational Methods in …, 2024 - Springer
Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering
applications, and its mechanical properties are crucial for designing and evaluating its …

Structural dynamic reliability analysis: review and prospects

D Teng, YW Feng, JY Chen, C Lu - International Journal of Structural …, 2022 - emerald.com
Purpose The purpose of this paper is to briefly summarize and review the theories and
methods of complex structures' dynamic reliability. Complex structures are usually …

[HTML][HTML] Effect of inclusion of natural pozzolan and silica fume in cement-based mortars on the compressive strength utilizing artificial neural networks and support …

HA Dahish, MS Alfawzan, BA Tayeh… - Case Studies in …, 2023 - Elsevier
This study illustrates the effect of incorporating natural pozzolan (NP) and silica fume (SF) in
cement-based mortars on the compressive strength. Up to 40% of the weight of cement in …