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 …

Machine-learning methods for estimating performance of structural concrete members reinforced with fiber-reinforced polymers

F Kazemi, N Asgarkhani, T Shafighfard… - … Methods in Engineering, 2024 - Springer
In recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have
gained significant attention due to their exceptional properties, including lightweight …

Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures

F Kazemi, N Asgarkhani, R Jankowski - Soil Dynamics and Earthquake …, 2023 - Elsevier
Many studies have been performed to put quantifying uncertainties into the seismic risk
assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment …

Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete

T Shafighfard, F Kazemi, N Asgarkhani… - Engineering Applications of …, 2024 - Elsevier
High-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless
and environmentally friendly material. It has recently received a substantial amount of …

Machine learning-based seismic response and performance assessment of reinforced concrete buildings

F Kazemi, N Asgarkhani, R Jankowski - Archives of Civil and Mechanical …, 2023 - Springer
Complexity and unpredictability nature of earthquakes makes them unique external loads
that there is no unique formula used for the prediction of seismic responses. Hence, this …

[HTML][HTML] Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods

N Asgarkhani, F Kazemi… - … Applications of Artificial …, 2024 - Elsevier
Abstract Nowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral
force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of …

Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls

F Kazemi, N Asgarkhani, R Jankowski - Expert Systems with Applications, 2024 - Elsevier
Efficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation
plans, providing insights into building performance and retrofitting costs. The complexity of …

Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams

T Shafighfard, F Kazemi, F Bagherzadeh… - … ‐Aided Civil and …, 2024 - Wiley Online Library
One of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the
ability to anticipate their flexural response. With a comprehensive grid search, several …

Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction

N Asgarkhani, F Kazemi, R Jankowski - Computers & Structures, 2023 - Elsevier
Nowadays, due to improvements in seismic codes and computational devices, retrofitting
buildings is an important topic, in which, permanent deformation of buildings, known as …

Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various machine learning techniques

A Dehestani, F Kazemi, R Abdi, M Nitka - Engineering Fracture Mechanics, 2022 - Elsevier
Abstract Machine Learning (ML) method is widely used in engineering applications such as
fracture mechanics. In this study, twenty different ML algorithms were employed and …