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 …
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 …
plans, providing insights into building performance and retrofitting costs. The complexity of …
Comprehensive review of AI and ML tools for earthquake damage assessment and retrofitting strategies
PKS Bhadauria - Earth Science Informatics, 2024 - Springer
This comprehensive review paper examines the integration of Artificial Intelligence (AI) and
Machine Learning (ML) tools in earthquake engineering, specifically focusing on damage …
Machine Learning (ML) tools in earthquake engineering, specifically focusing on damage …
Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
Conventional ultra-high performance concrete (UHPC) has excellent development potential.
However, a significant quantity of CO2 is produced throughout the cement-making process …
However, a significant quantity of CO2 is produced throughout the cement-making process …
Enhancing seismic performance of steel buildings having semi-rigid connection with infill masonry walls considering soil type effects
F Kazemi, N Asgarkhani, R Jankowski - Soil Dynamics and Earthquake …, 2024 - Elsevier
Unpreventable constructional defects are the main issues in the case of steel Moment-
Resisting Frames (MRFs) that mostly occur in the rigidities of beam-to-column connections …
Resisting Frames (MRFs) that mostly occur in the rigidities of beam-to-column connections …
Developing machine learning models for identifying the failure potential of fire-exposed FRP-strengthened concrete beams
The resilience of fiber-reinforced polymer (FRP)-strengthened concrete beams under fire
exposure is a critical aspect of structural engineering, with significant implications for safety …
exposure is a critical aspect of structural engineering, with significant implications for safety …
Development and experimental validation of a novel double-stage yield steel slit damper-buckling restrained brace
F Kazemi, N Asgarkhani, N Lasowicz… - Engineering Structures, 2024 - Elsevier
This research is focused on the development and experimental validation of a novel double-
stage yield steel slit damper-buckling restrained brace (SSD-DYB) system designed for …
stage yield steel slit damper-buckling restrained brace (SSD-DYB) system designed for …
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 …
gained significant attention due to their exceptional properties, including lightweight …
Machine learning-driven feature importance appraisal of seismic parameters on tunnel damage and seismic fragility prediction
Q Wang, P Geng, L Wang, D He, H Shen - Engineering Applications of …, 2024 - Elsevier
This study proposes a machine learning-driven approach for the analysis of the feature
importance of seismic parameters on tunnel damage and seismic fragility prediction. The …
importance of seismic parameters on tunnel damage and seismic fragility prediction. The …
Probabilistic post-earthquake loss measurement for RC framed buildings using crack image analysis
Robust post-earthquake loss measurement is essential in community level for policy makers
and an area of interest for insurance companies at the building level. The seismic loss …
and an area of interest for insurance companies at the building level. The seismic loss …