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CONTENTS
Volume 37, Number 2, February 2026
 

Abstract
This study introduces a data-intensive framework designed for the prediction of compressive strength and dry density of lightweight foamed concrete (LFC) by deploying five advanced machine learning (ML) models: CatBoost, NGBoost, PySR, TabNet, and XGBoost. A specially assembled database of 191 different mix designs was employed, and the models' performance was assessed through rigorous statistical metrics (R2, MAE, RMSE, MPAR) combined with k-fold cross-validation for robustness purposes. Among the tested models, XGBoost achieved the highest overall predictive accuracy (R2=0.994 and RMSE=26.09 kg/m3 for dry density), while NGBoost offered nearly comparable performance for compressive strength (R2=0.983, RMSE=1.82 MPa) and uniquely provided predictive distributions enabling uncertainty-aware design and reliability analysis. In order to maximize explainability, SHAP (Shapley Additive Explanations) analysis revealed cement content and foam volume as the top drivers of strength and density, verifying compliance with known engineering rules of thumb. Symbolic regression (PySR) yielded interpretable equations that approximate the structure-property relationships. As an application example, NGBoost was embedded into a minimalistic graphical user interface (GUI), and engineers can simply feed mix parameters for probabilistic predictions instantly. The proposed framework combines accuracy, interpretability, and usability and highlights the ability of ML surrogates for the acceleration of experimental mechanics and support for stochastic simulation, reliability analysis, and auto-mix design. Although limited by the relatively small and heterogeneous dataset, this research advances the computational simulation of sustainable concretes and complements ongoing efforts for the integration of the field of structural materials engineering with artificial intelligence.

Key Words
compressive strength; dry density; foamed concrete; machine learning; uncertainty

Address
Derya Bakbak: Grand National Assembly of Türkiye (TBMM), Ankara, Türkiye
Ahmet E. Kurtoğlu: Department of Civil Engineering, Iğdir University, Iğdir, Türkiye

Abstract
The crack trajectory in concrete specimens is a critical factor in characterizing structural failure. Due to the heterogeneous nature of concrete, the presence of asymmetric holes can disrupt uniformity within structural members. Asymmetry, non-uniformity, and variable loading further complicate the behavior of concrete components. This study involved the fabrication of 144 standard 150 mm cubic specimens with four different mix designs, containing fiber content at fractions of 0%, 8%, 16%, and 24%. The specimens had square, rectangular, and triangular holes, to evaluate the effects of holes geometry and asymmetry on concrete behavior. A numerical model was developed using VariCAD and analyzed with SimSolid. The specimens were subjected to five cycles of cyclic loading. Results showed that internal displacement was lower than external displacement under cyclic loading. Symmetric holes positioned at the center of the concrete had no significant effect on external displacement, whereas asymmetric holes increased maximum displacement at the corners. The length, width, and depth of the specimens influenced the areas of maximum displacement. The addition of fibers had a pronounced effect on internal displacement, shifting the maximum displacement and crack trajectory towards the corners in specimens with holes. Cyclic loading of specimens with different hole shapes revealed that crack initiation depended on the positions and conditions of holes. This finding was further supported by modeling of maximum displacement. Specimens with holes exhibited larger ultimate strain compared to those without holes.

Key Words
concrete hole; cyclic loading; fiber concrete; heterogeneous shape; maximum displacement

Address
Hamoon Fathi, Mohammad Hemen Jannaty: Department of Civil Engineering, Sa.C., Islamic Azad University, Sanandaj, Iran
Hassan Karampour: School of Engineering and Built Environment, Griffith University, Gold Coast Campus, QLD, 4222, Australia

Abstract
This research investigates the performance of fibre-reinforced lightweight hollow core slabs under varying flexure-to-shear ratios using numerical simulations. A three-dimensional finite element model is developed to replicate the response of the HCS having dimensions of 3400 mm length, 600 mm width, and 150 mm depth subjected to four-point bending tested at shear span to depth (a/d) ratios of 3.5, 7 and 10. The nonlinear FE analysis is conducted using ABAQUS software and validated against experimental results from previously tested fibre-reinforced lightweight hollow core slabs available in the literature. The numerical model accurately predicts load-deflection behavior and failure modes demonstrating good agreement with experimental findings. Additionally, the FE analysis provides insights into crack patterns and failure modes of hollow core slabs. Moreover, the validated numerical model is used to investigate the impact of various factors such as the effects of change in the reinforcement ratio, depth of the HCS, size of the hollow core, shape of the hollow core and a/d ratio on the load capacity of the fibre-reinforced lightweight hollow core slabs. Increasing the reinforcement ratio and slab depth substantially enhanced both cracking and ultimate load capacities. The core diameter had a significant influence on strength only in shear-dominant specimens (a/d<=3.5), while it was negligible in flexure-dominant cases. These findings demonstrate that the developed FE model can serve as a reliable tool for optimizing the design of FRLWHCS systems.

Key Words
fibre reinforced concrete; finite element analysis; hollow core slab; lightweight aggregate; the concrete damage plasticity model

Address
Sumit Sahoo, Rami A. Hawileh, Jamal A. Abdalla: Department of Civil Engineering, American University of Sharjah, Sharjah, United Arab Emirates
Adeeb Rahman: Department of Civil and Environmental Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, United States

Abstract
This study examines the effects of corrosion on prestressing strands, a critical factor influencing the durability and structural safety of aging prestressed concrete structures. Considering that the repair or rehabilitation of corroded prestressing strands is difficult and expensive, early detection of signs of corrosion in prestressing strands is crucial for the effective maintenance of these structures. Corrosion-induced reductions in elongation compromise the deformation capacity and seismic performance of these structures due to the mechanical property changes caused by corrosion. Using Faraday's law, the corrosion levels of prestressing strand specimens were estimated by calculating the charges passed through a defined circuit over a specific time period. The proposed quantification technique demonstrated high effectiveness in predicting the corrosion characteristics of the strands. Monotonic tensile tests conducted on 64 accelerated corroded prestressing strand specimens provided data to develop a reduction formula for elongation, a vital mechanical property. This formula facilitated the creation of an analytical model and numerical tools capable of simulating both local and overall behavior of corroded prestressing strands.

Key Words
corrosion on prestressing strands; deformation capacity; elongation; reduction formula; seismic performance

Address
Tae-Hoon Kim: Track & Civil Infrastructure Division, Korea Railroad Research Institute, 176, Cheoldobangmulgwan-ro, Uiwang-si, Gyeonggi-do, 16105, Republic of Korea
Chang-Ho Sun, Ick-Hyun Kim: Department of Civil and Environmental Engineering, University of Ulsan, 93, Daehak-ro, Nam-gu, Ulsan-si, 44610, Republic of Korea

Abstract
This paper proposes a new flexural design framework for stainless-steel RC beams based on an equivalent stress approach as well as simplified analytical approach that compromise the simplicity and practicality of design and incorporates the strain hardening of stainless-steel reinforcement. A comprehensive assessment of the proposed method and the current design procedures adopted for stainless-steel RC beam is presented using the collected data. The assessment includes a comparison with Eurocode 2 and ACI 318-19 as well as the Continuous Strength Method (CSM) for RC beams. The sensitivity of parameters on both ultimate and cracking moments is evaluated through a parametric study. In addition, a reliability analysis is performed to suggest a new partial safety factor for designing stainless-steel RC beams. The proposed simplified analytical approach demonstrated clear superiority over all other evaluated design methods, including Eurocode 2 (EC2), ACI 318-19, the Continuous Strength Method (CSM), and the proposed equivalent stress approach. The mean values of predicted-to-tested ratio and RMSE are 0.99 and 27.8. In addition to its accuracy, the simplified approach offered a straightforward, noniterative procedure, making it highly practical for both manual calculations and software-assisted design.

Key Words
CSM; flexural behaviour; new design method; RC beam; reliability analysis; stainless-steel reinforcement

Address
Musab Rabi: Department of Civil Engineering, Jerash University, 26150, Jordan
Felipe Piana Vendramell Ferreira: Department of Civil Engineering, State University of Maringá, Maringá, Paraná, Brazil
Ahmad N. Tarawneh: Civil Engineering Department, Faculty of Engineering, The Hashemite University, P.O. box 330127, Zarqa 13133, Jordan
Ikram Abarkan: Department of Physics, Faculty of Sciences, Abdelmalek Essaâdi University, 93002, Tetouan, Morocco
Rabee Shamass: Department of Civil and Environmental Engineering, Brunel University London, London, UK
Mazen J. Al-Kheetan: Civil and Environmental Engineering Department, College of Engineering, Mutah University, P.O. Box 7, Mutah 61710, Jordan
Yazan Momani: Civil Engineering Department, University of Petra, Amman, Jordan

Abstract
The study aims to investigate the structural behavior of Concrete-Filled FRP Tube (CFFT) columns internally reinforced with GFRP/CFRP bars, focusing on enhancing axial load capacity and deformation resistance. The research addresses the challenge of accurately predicting the axial performance of FRP-wrapped compressive members, which is crucial for designing durable and reliable CFFT columns. To address this problem, a comprehensive dataset of 650 FRP-wrapped compressive members was compiled from existing literature. Several previously developed strength prediction models were evaluated using key statistical indicators, including the root mean square error (RMSE) and coefficient of determination (R2), to assess predictive accuracy. Subsequently, a new analytical model was formulated to estimate the axial load capacity of CFFT columns, which was validated using finite element analysis (FEA) in ABAQUS. The FEA incorporated refined constitutive relationships for the concrete core, FRP tube, and longitudinal FRP reinforcement based on experimental data. Results showed that the proposed model outperformed previous models, achieving an R2 of 0.95 and an RMSE of 0.20, demonstrating its high accuracy. FEA results were in good correlation with experimental findings, with discrepancies of only 1.3% in axial deformation and 3.0% in ultimate axial load. The parametric study showed that increasing the FRP bars ratio from 1.2% to 2.2% enhanced axial strength by 179.01% and deflection by 15.75%. Similarly, increasing the GFRP tube thickness from 0.5 mm to 3 mm improved axial load by 64.02% and deformation by 34.74%. Moreover, raising the unwrapped concrete strength from 15 MPa to 65 MPa increased axial strength by 222.23% and deflection by 27.49%. Notably, increasing the column diameter from 100 mm to 350 mm led to a 2157.44% rise in axial strength and a 30.69% increase in deformation.

Key Words
axial capacity; finite element model (FEM); FRP-tube; numerical parametric study; strength model

Address
Wafeek Mohamed Ibrahim: Department of Architecture, College of Architecture & Planning, King Khalid University, Abha 61421, Saudi Arabia
Nejib Ghazouani: Mining Research Center, Northern Border University, Arar 73213, Arar, Saudi Arabia
Zeeshan Ahmad: Department of Civil Engineering, University of Engineering and Technology Taxila, 47050, Pakistan

Abstract
Most of the past studies about fire resistance of CFST column have dealt with the behavior of this column against uniform fires, while in truth interior columns of the building are actually placed within the walls; therefore, the columns subjected to non-uniform fire which causes the column surfaces exposed to fire with delay. It's important to investigate the effect of fire exposure's time delay on varied column surfaces. In this study, a numerical model was developed to investigate the effect of time delay on fire resistance, residual resistance, and heat distribution of CFST column's cross section. Results show that as the time delay has increased, the samples' fire resistance duration rises too. It also demonstrates that as the number of the sides, exposed to fire becomes more, the impact of time delay on fire resistance as well as the residual resistance of the column drops. Additionally, it has been observed that the ratio of fire resistance in the column, exposed to non-uniform fire with a time delay, to the column under a comprehensive fire is directly related to the reverse ratio of column sides, exposed to fire, to all column sides.

Key Words
concrete filled steel tube (CFST); finite element analysis; nonuniform fire; structural analysis; time delay

Address
Department of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran

Abstract
This study presents a data-driven approach for predicting the axial load-carrying strength (ALCS) of fiber-reinforced polymer (FRP) confined concrete columns using artificial neural networks (ANN). A comprehensive experimental database of 265 FRP-confined columns with varying geometries, material properties, and confinement characteristics was developed. Initially, 14 existing empirical models were evaluated, and a modified version of the Teng et al. model was proposed, achieving an R2 of 0.9219. To enhance predictive accuracy, a multilayer feedforward backpropagation ANN model was trained and validated using 66% and 33% of the dataset, respectively. The optimal ANN architecture, consisting of 9 neurons in the first hidden layer and 5 in the second, yielded superior prediction performance with a correlation coefficient R2=0.9956, a mean absolute error (MAE) of 1.43%, and a predicted average ALCS of 4383.82 kN compared to the experimental mean of 4309.60 kN. These results demonstrate that the proposed ANN model offers a highly reliable and practical tool for estimating the axial strength of FRP-confined concrete columns, outperforming traditional analytical models and supporting the advancement of intelligent structural design methods.

Key Words
ANN models; columns; experimental database; FRP confined concrete; MAE; parametric study

Address
Umara Nasir, Aqeel Ur Rehman: Department of Civil Engineering, University of Engineering and Technology Taxila, 47050, Pakistan
Nejib Ghazouani: Mining Research Center, Northern Border university, Arar 73213, Arar, Saudi Arabia
Nabil Ben Kahla: 1) Department of Civil Engineering, College of Engineering, King Khalid University, PO Box 394, Abha 61411, Saudi Arabia, 2) Center for Engineering and Technology Innovations, King Khalid University, Abha 61421, Saudi Arabia

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