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 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 …

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 …

[HTML][HTML] Integrating machine learning and remote sensing in disaster management: A decadal review of post-disaster building damage assessment

S Al Shafian, D Hu - Buildings, 2024 - mdpi.com
Natural disasters pose significant threats to human life and property, exacerbated by their
sudden onset and increasing frequency. This paper conducts a comprehensive bibliometric …

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 …

[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 …

Spatiotemporal heterogeneity of ecosystem service interactions and their drivers at different spatial scales in the Yellow River Basin

Q Liu, J Qiao, M Li, M Huang - Science of The Total Environment, 2024 - Elsevier
Accurately understanding ecosystem service (ES) interactions and an analysis of the
complex, multiscale driving mechanisms are foundational prerequisites for implementing …

Improved seismic intensity measures and regional structural risk estimation models

SQ Li - Soil Dynamics and Earthquake Engineering, 2024 - Elsevier
Seismic intensity measures are essential quantitative parameters for evaluating and
predicting engineering structures' seismic risk and vulnerability. Various regional …

Machine learning-based prediction of preplaced aggregate concrete characteristics

FO Moaf, F Kazemi, HS Abdelgader… - … Applications of Artificial …, 2023 - Elsevier
Abstract Preplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse
aggregate is placed in the mold and a Portland cement-sand grout with admixtures is …

Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete

F Kazemi, T Shafighfard, R Jankowski… - Archives of Civil and …, 2024 - Springer
Conventional ultra-high performance concrete (UHPC) has excellent development potential.
However, a significant quantity of CO2 is produced throughout the cement-making process …