Application of artificial intelligence in predicting the residual mechanical properties of fiber reinforced concrete (FRC) after high temperatures

V Farhangi, MJ Moradi, K Daneshvar… - Construction and Building …, 2024 - Elsevier
The practical application of Artificial Intelligence (AI) approaches in estimating the
mechanical properties of fiber-reinforced concrete (FRC) subjected to high temperatures …

Nonmodel rapid seismic assessment of eccentrically braced frames incorporating masonry infills using machine learning techniques

R Chalabi, O Yazdanpanah, KM Dolatshahi - Journal of Building …, 2023 - Elsevier
This study investigates the seismic behavior of eccentrically braced frames (EBFs) taking
into account the influence of masonry infill walls using a nonmodel scenario-based machine …

Experimental investigation and calculation method of the interfacial bonding performance of stone masonry reinforced with UHPC

Z Wang, L Li, J Zhou, R Chen, J Leng, H Zhang… - Journal of Building …, 2024 - Elsevier
Ultra-high performance concrete (UHPC) is a kind of excellent repair material for
strengthening existing concrete structures. However, the bonding properties between UHPC …

Machine learning models to predict the residual tensile strength of glass fiber reinforced polymer bars in strong alkaline environments: A comparative study

K Zhang, K Zhang, R Bao - Journal of Building Engineering, 2023 - Elsevier
The long-term durability of glass fiber reinforced polymers (GFRPs) in strong alkaline
environments is of utmost importance in marine infrastructure construction. The residual …

[HTML][HTML] A data-driven approach for fault diagnosis in multi-zone HVAC systems: Deep neural bilinear Koopman parity

FN Irani, M Bakhtiaridoust, M Yadegar… - Journal of Building …, 2023 - Elsevier
Sensor faults in heating, ventilation, and air conditioning (HVAC) systems are inevitable and
result in significant energy waste. This paper presents an innovative data-driven approach …

Modelling strategies for the updating of infilled RC building FEMs considering the construction phases

V Nicoletti, F Gara - Buildings, 2023 - mdpi.com
This paper deals with modelling strategies for the updating of Finite Element Models (FEMs)
of infilled Reinforced Concrete (RC) frame buildings. As is known, this building typology is …

INSPECT-SPSW: INelastic seismic performance evaluation computational tool for steel plate shear wall modeling in OpenSees

M AlHamaydeh, AM Maky, M Elkafrawy - Buildings, 2023 - mdpi.com
Modeling Steel Plate Shear Wall (SPSW) behavior can be computationally demanding. This
is especially true when high-fidelity modeling is carried out via shell or 3D solid elements. It …

A simplified homogeneous approach for non-linear analysis of masonry infill panels under in-plane loads

Z Fang, R Wang, P Wu, H Sun, MJ Moradi - Heliyon, 2024 - cell.com
This paper aims to create a unified model that effectively combines continuous 2-
dimensional elements and discrete components to capture the nonlinear characteristics and …

Machine learning-based models for predicting the progressive collapse resistance of truss string structures

W Liu, B Zeng, Z Zhou, J Yao, Y Lu - Engineering Structures, 2024 - Elsevier
Evaluating the progressive collapse resistance of truss string structures (TSSs) in the context
of key member failure presents a significant challenge, particularly when this indicator is …

Prediction and analysis of axial stress of piles for piled raft due to adjacent tunneling using explainable AI

DW Oh, SM Kong, SB Kim, YJ Lee - Applied Sciences, 2023 - mdpi.com
Tunneling, especially in urban areas, affects many structures on the ground, which directly
influences the usability and stability of the structures. The settlement of and axial stress on …