Abstract
Transverse interlayer gaps in CRTS III slab tracks impair performance and pose significant risks to train safety. It is therefore essential that a reliable evaluation method be established and that targeted maintenance strategies be developed based on defect severity. However, existing classification criteria are often empirical and inconsistent. Numerous and non-uniform evaluation indicators are used, leading to inconsistent grade assessments that hinder effective maintenance decisions. To address this issue, twenty-one potential indicators and their respective limit values were first selected from existing standards for vehicle and track dynamic performance. Subsequently, a dynamic finite element model of the coupled vehicle-track-subgrade system was developed. Through a sensitivity analysis conducted with this model, three indicators—vertical rail displacement, vertical track slab displacement, and tensile stress of the track slab—were identified as the most suitable for damage classification. The effects of gap size and train speed on these key indicators were then systematically analyzed. Based on this analysis, quantitative size limits were established in accordance with a proposed three-grade damage classification principle. To precisely define the control boundaries for each classification grade, fitted function expressions were also developed. Ultimately, this study provides a framework for the maintenance of high-speed railway infrastructure, contributing to improved decision-making and long-term track stability.
Abstract
The hanger connectors are crucial components that connect the hangers to the stiffening girders. During operation, the back-twist effect of the hangers can lead to wear between the fork-ear plates of the connectors and the ear plates of the stiffening girder. To quantitatively identify the wear depth of fork-ear plates, the axial forces and the back-twist torque of the hanger are firstly calculated. Then, the longitudinal relative angle of the hanger connector is analyzed. Finally, the wear depth of the fork-ear plates is obtained by the Archard model. The results indicate that: when the design twist angle of the hanger is (3+-0.5)o, the wear depth of the fork-ear plate within the first month is 0.0246-0.0267 mm and the average wear depth is 0.0256 mm. After 120 months, the wear depth is 0.2308-0.2931 mm and the average wear depth is 0.2630 mm. The thickness loss is about 0.6%, and the bearing capacity loss is about 2.09%. The wear depth increases with the increase of the twist angle and axial force of the hanger, but the rate of increase continuously decreases. As the wear depth increases, the effect of wear on its bearing capacity should be fully considered.
Address
Xiaopeng Wang: School of Highway, Chang'an University, Xi'an 710064, China; Shaanxi Railway Institute, Weinan 714000, China
Song Xing: Bay Area Super Major Bridge Maintenance Technology Center of Guangdong, Highway Construction Co. Ltd., Guangzhou 510635, China
Yongjun Zhou: School of Highway, Chang'an University, Xi'an 710064, China
Peiyuan Hou: School of Highway, Chang'an University, Xi'an 710064, China; Tianjin
Abstract
Punching shear failure in reinforced concrete (RC) slabs is a brittle and critical phenomenon; therefore, reliable prediction of punching shear strength (PSS) is essential for safe design. Conventional design code equations (e.g., ACI and EC2) often involve simplified assumptions that may not fully capture the nonlinear interactions among geometric, material, and reinforcement parameters, especially in complex loading scenarios. To address this limitation, this study develops a novel hybrid machine-learning paradigm for accurate PSS estimation. The approach integrates the Random Forest (RF) algorithm with three advanced meta-heuristic optimization techniques: the dragonfly algorithm (DA), sparrow search algorithm (SSA), and whale optimization algorithm (WOA), to enhance RF hyperparameter tuning and predictive accuracy. A comprehensive dataset containing eight influential parameters was used to construct two modelling cases that account for variations in slab cross-sectional characteristics. The hybrid RF-DA and RF-SSA models achieved the highest predictive performance, reaching a correlation coefficient of 0.98 during the testing phase, outperforming conventional RF, SVR, ELM, and code-based predictions. Sensitivity analysis revealed that slab and column geometry, as well as concrete strength, exert the strongest influence on PSS. This study introduces a novel integration of Random Forest with DA, SSA, and WOA for PSS prediction, enabling the superior modeling of complex, nonlinear structural behavior. The hybrid framework provides a reliable, datadriven alternative to traditional code equations, with the RF-DA model demonstrating exceptional potential for broader application in concrete strength prediction and structural design optimization.
Key Words
hybrid intelligence modelling; metaheuristic optimization; punching shear strength; random forest; RC-slab
Address
Mosbeh R. Kaloop: Department of Civil and Environmental Engineering, Incheon National University, Incheon, Korea; Incheon Disaster Prevention Research Center, Incheon National University, Incheon, Korea; Public Works Engineering Department, Mansoura University, Mansoura, Egypt
Furquan Ahmad: Department of Civil Engineering, National Institute of Technology Patna, Patna, India
Pijush Samui: Department of Civil Engineering, National Institute of Technology Patna, Patna, India
Jong Wan Hu: Department of Civil and Environmental Engineering, Incheon National University, Incheon, Korea; Incheon Disaster Prevention Research Center, Incheon National University, Incheon, Korea
Mohamed Rezaik: Appout ITs, Tanta, Egypt
Basem S. Abdelwahed: Structural Engineering Department, Mansoura University, Mansoura, Egypt
Abstract
This study investigates the synergistic effect of bacterial strains, paper sludge ash (PSA), and coconut fibres (CF) on the mechanical performance, durability, and self-healing capacity of lightweight aggregate concrete. A novel bacterial-grouted system was developed by partially replacing cement with 15% PSA, reinforcing the matrix
with 0.5% CF, and incorporating Bacillus subtilis to induce microbial-induced calcium carbonate precipitation (MICP). The results demonstrated that the combined mix (CC+PSA+CF+BS) exhibited superior strength development, achieving up to 21.6% higher compressive strength and 35% greater impact energy than control concrete at 90 days. Enhanced UPV values confirmed the densification of the microstructure, while Cantabro loss reductions indicated improved abrasion resistance. The findings highlight that microbial precipitation, pozzolanic reactivity, and fibre bridging collectively improve crack resistance and long-term durability. This hybrid approach establishes an environmentally sustainable, high-performance concrete composite suitable for structural applications exposed to dynamic and abrasive environments.
Key Words
bacteria strain; coconut fiber; fiber-reinforced concrete; sustainable concrete
Address
Vadivel Jayanthi: Department of Civil Engineering, Alagappa Chettiar Government College of Engineering and Technology,
Karaikudi 630003, India
Sundaresan Srividhya: Department of Civil Engineering, Kangeyam Institute of Technology, Kangeyam, Tirupur 638108, India
Pitchaipillai Neelamegam: Department of Civil Engineering, SRM Valliammai Engineering College, Chennai 603203, India
Ramaiah Prakash: Department of Civil Engineering, Alagappa Chettiar Government College of Engineering and Technology,
Karaikudi 630003, India
Abstract
This study investigates the dynamic and static stability of a sinusoidal enclosed sandwich beam with a pre-twist, resting on a Pasternak foundation, under axial harmonic loads with minor initial curvature and a temperature gradient. The beam is also analyzed with an attached mass and viscoelastic end supports. To improve the static and dynamic buckling loads and stability regions, a viscoelastic layer is incorporated as the core and as an additional shear layer atop the Pasternak foundation, with elastic layers enveloping the viscoelastic core for enhanced system stability. The equations of motion are derived using Hamilton's energy principle and Galerkin's method. A parametric study is conducted to evaluate the influence of various factors, including beam geometry, foundation
stiffness, pre-twist angle, curvature, tip mass and position, and the loss factor of end supports, on critical dynamic loads and stability zones. The impact of these parameters on static critical loads is also examined. The study finds that proper tuning of the pre-twist angle, foundation stiffness, additional elastic layers, and end supports can significantly reduce unstable regions and increase both static and dynamic critical loads, thereby making the beam less susceptible to axial harmonic loading. The results are illustrated with detailed graphical representations. The objective of this work is to model and analyze the stability of an enclosed sinusoidal pre-twisted sandwich beam on a Pasternak foundation under combined thermal and mechanical loading. The novelty lies in simultaneously incorporating the enclosure effect, sinusoidal geometry, viscoelastic layers, Pasternak foundation and temperature gradient in a single analytical framework not previously reported.
Key Words
attached mass; curvature; enclosed sandwich beam; Pasternak foundation; pre-twisted beam; sinusoidal beam; temperature gradient; viscoelastic support
Address
Niraj Kumar Singh, Kumar Pradhan, Madhusmita Pradhan, Prasanta Kumar Pradhan, Pusparaj Dash: Department of Mechanical Engineering, VSSUT, Burla, Odisha 768018, India
Rashmita Parida: Department of Mechanical Engineering, OUTR, Bhubaneswar, Odisha 751029, India
Abstract
This article presents a comprehensive numerical study to determine the seismic performance of the Kirazliyali Çenesuyu Bridge, currently in service in Kocaeli, Türkiye, under both seismically isolated and non-isolated conditions, considering different soil types. The study holds great importance due to Kocaeli's status as one of Türkiye's most developed industrial regions, its location in a high-seismic-risk area, and its complex geological structure. The Kirazliyali Çenesuyu Bridge is a structure consisting of simply supported prestressed girders, commonly used in highway transportation networks. Designed as a twin bridge, the structure is 134 meters in length and 20 meters in width. Currently, the bridge is not equipped with seismic isolators; instead, its superstructure rests on elastomeric bearings over abutments and piers. Within the scope of this study, the bridge was retrofitted with Single Curved Friction Pendulum (SCFP) seismic isolators. These SCFP isolators were specifically designed in accordance with the Turkey Building Earthquake Code (TBEC-2019) standards for two distinct soil classes: ZA (hard rock) and ZC (very dense sand and gravel). The soil-pile interaction was simulated using single-parameter Winkler spring models in both horizontal and vertical directions. The Finite Element Model (FEM) of the bridge was developed in SAP2000 software, and analyses were conducted on this platform. The seismic performance of the bridge was assessed through nonlinear dynamic time history analyses using real earthquake ground motion records from the Imperial Valley, Kocaeli, and Kahramanmaraş (Pazarcik) earthquakes under various scenarios. The seismic responses of the bridge were examined in terms of base shear forces, lateral displacements of the pile, shear forces at the pier, bending moments at the pier, deck accelerations, and the hysteresis curves of the isolator. The study results demonstrate significant improvements in the seismic behavior of the bridge when equipped with the seismic isolation system. Furthermore, these improvements are shown to be directly influenced by the interaction of the structure-pile-soil system, as well as the compatibility between the frequency characteristics of this system and the frequency content of the imposed earthquake. The numerical data supporting these results are presented in the relevant sections through tables and graphs.
Address
Erdal Öner, Ayşe N. Aydoğan, Mustafa Ergün, Musa Artar: Department of Civil Engineering, Bayburt University, Bayburt 69010, Turkey
Muhammet Yurdakul: Department of Civil Engineering, Karadeniz Technical University, Trabzon 61830, Turkey
