Tao Yuan¹, Qin Tang², Zhiwen Zhu^2,*, Jin Jiang², Lin Zhang¹, Gangqiao Wang¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072805 - 31 March 2026

Abstract Using field monitoring data, this study directly compares the stress responses of fatigue-prone orthotropic steel deck (OSD) details with an epoxy asphalt concrete (EAC) overlay during in-service winter and summer seasons. This study was conducted on the E’dong Yangtze River Bridge in China, a cable-stayed bridge featuring a main span of 936 m and an EAC-paved deck pavement. The findings reveal that across all OSD details, stress levels and loading cycles are generally higher in summer than in winter. The most pronounced increase occurs at the rib-to-deck (RD) detail, particularly on the deck plate side.… More >

Yi Wang^1,2,*, Yansong Li², Bingxu Cai², Yukai Zhu¹, Hairong Wu¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072553 - 31 March 2026

Abstract Prefabricated buildings have developed rapidly due to their advantages in energy efficiency, environmental protection, and high construction efficiency, which have greatly promoted the advancements of connection technology and the mechanical properties of prefabricated hollow panels. This study proposes a new optimization scheme for prefabricated wall structures using transversely arranged prefabricated hollow plates and develops a new joint connection. First, the constitutive relations are experimentally validated to establish an accurate finite element analysis model; Then the equal-size specimens are compared with the control specimens without node connections; Finally, the effects of axial compression ratio, aspect ratio, More >

Yaguan Wang¹, Linlin Kou², Yang Gao^3,*, Qiang Sun¹, Yong Qin³, Genwang Peng³

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072538 - 31 March 2026

Abstract The fasteners employed in the railway tracks are susceptible to defects arising from their intricate composition. Foreign objects are frequently observed on the track bed in an open environment. These two types of defects pose potential threats to high-speed trains, thus necessitating timely and accurate track inspection. The majority of extant automatic inspection methods are predicated on the utilization of single visible light data, and the efficacy of the algorithmic processes is influenced by complex environments. Furthermore, due to the single information dimension, the detection accuracy of defects in similar, occluded, and small object categories… More >

Yajuan Lu^*, Yongtao Hu, Jie Li, Jinping Zhang, Jingjing Si

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.071110 - 31 March 2026

Abstract To address challenges in wind turbine blade defect detection models, primarily due to insufficient feature extraction capabilities and the difficulty of deploying models on drone-type edge devices, this study proposes a wind turbine blade defect detection model, WtCS-YOLO11, that incorporates multiscale feature extraction and an attention mechanism. Firstly, the cross-stage partial with two kernels and a wavelet convolution module (C3k2_WTConv) is proposed by introducing wavelet convolution into the module. The cross-stage partial with two kernels (C3k2) module in the necking network is replaced with the C3k2_WTConv module to increase the model’s receptive field, enable multiscale… More >

Trinh Thi Nhu Quynh¹, Hoa-Cuc. Nguyen², Bich-Ngoc. Mach², Thanh Q. Nguyen^3,4,*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.070202 - 31 March 2026

Abstract This study introduces a method for processing various types of random real-world signals from bridges in both experimental models and real-world scenarios using a wireless sensor system. By analyzing and processing signals collected during actual traffic on bridges, the study identifies and provides parameters that meet current quality inspection requirements to ensure the safety of bridge users. The parameters investigated in this study include deformation, natural frequency, amplitude, impact factor, and damping coefficient. Research has determined and highlighted key parameters to assess the quality of bridge spans to meet quality inspection standards. Using actual traffic More >

Niken Chatarina^*, Suyadi Suyadi, Noorhidana Vera Agustriana, Chairani Zilia, Mariyanto Mariyanto

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2026.067525 - 31 March 2026

Abstract In strong aggressive areas, Indonesian standards specify a maximum penetration of 30 mm. Concrete utilizes sulfate-resistant Portland Pozzolan Cement (PPC) for a target strength of 30 MPa, with and without silica fume and plastic fiber (SR-SFF-sea and SR-N-SFF). Some samples of SR-N-SFF are immersed in the sea (SR-N-SFF-sea), while others are protected (SR-N-SFF-protected). Additionally, concrete using non-sulfate-resistant cement (NSR-sea) with a strength of 20.75 MPa was also evaluated. All samples were subjected to penetration depth testing according to the DIN EN 12390-8 standard, demonstrating that they met the penetration requirements for intense aggression. The study… More > Graphic Abstract

Jie Li¹, Nan An^2,3, Youliang Ding^2,3,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072361 - 08 January 2026

Abstract Vehicle-induced response separation is a crucial issue in structural health monitoring (SHM). This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data. To extend the separation target from a fixed dataset to a continuously updating data stream, a block-wise sliding framework is first developed. This framework is further optimized considering the characteristics of real-time data streams, and its advantage in computational efficiency is theoretically demonstrated. During the decomposition and reconstruction processes, information from neighboring data blocks is fully utilized to reduce algorithmic complexity. In addition, a… More >

Longqi Liao¹, Jing Li², Yuhua Li³, Yuemin Wang³, Jinhua Li^1,*, Liyuan Cao^4,*, Chunxiang Li^4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072237 - 08 January 2026

Abstract Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing. This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis. It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters. First, this study made samples with gradient defects for two types of grouting sleeves, G18 and G20. These included four cases: 2D, 4D, 6D defects (where D is the diameter of the grouting sleeve), and no-defect. Then, an ultrasonic input/output data acquisition system was established. Three-dimensional sound field distribution data were obtained through an orthogonal… More >

Wu Feng^1,2,*, Tengku Anita Raja Hussin¹, Xu Yang³

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071664 - 08 January 2026

Abstract This study investigates the thermo–mechanical behavior of C40 concrete and reinforced concrete subjected to elevated temperatures up to 700°C by integrating experimental testing and advanced numerical modeling. A temperature-indexed Concrete Damage Plasticity (CDP) framework incorporating bond–slip effects was developed in Abaqus to capture both global stress–strain responses and localized damage evolution. Uniaxial compression tests on thermally exposed cylinders provided residual strength data and failure observations for model calibration and validation. Results demonstrated a distinct two-stage degradation regime: moderate stiffness and strength reduction up to ~400°C, followed by sharp deterioration beyond 500°C–600°C, with residual capacity at… More >

Pengwei Guo¹, Xiao Tan^2,3,*, Yiming Liu⁴

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071317 - 08 January 2026

Abstract Crack detection accuracy in computer vision is often constrained by limited annotated datasets. Although Generative Adversarial Networks (GANs) have been applied for data augmentation, they frequently introduce blurs and artifacts. To address this challenge, this study leverages Denoising Diffusion Probabilistic Models (DDPMs) to generate high-quality synthetic crack images, enriching the training set with diverse and structurally consistent samples that enhance the crack segmentation. The proposed framework involves a two-stage pipeline: first, DDPMs are used to synthesize high-fidelity crack images that capture fine structural details. Second, these generated samples are combined with real data to train… More >