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  • Open Access

    ARTICLE

    Dynamic Response Research of Dangerous Rockfall Impact Protection Structures

    Huaiqin Liu1, Meng Li1, Jianwen Shao2, Weishen Zhang1, Qifan Yang1, Yutong Li1, Tian Su1,3,*, Xuefeng Mei4

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1563-1588, 2025, DOI:10.32604/sdhm.2025.073009 - 17 November 2025

    Abstract Rock collapse is a significant geological disaster that poses a serious threat to life and property in mountainous regions worldwide. Investigating the response of protective structures to rockfall impacts can provide valuable references for the design and placement of such structures. In this study, RocPro3D and ABAQUS were employed to comprehensively analyze rockfall movement trajectories and the structural response upon impact. The results indicate that when the impact velocity of rockfall at the protective structure reaches 20–30 m/sec, the corresponding bounce height ranges from 5 to 8 m, and most rockfall accumulates at the slope More > Graphic Abstract

    Dynamic Response Research of Dangerous Rockfall Impact Protection Structures

  • Open Access

    REVIEW

    State-of-Art on Workability and Strength of Ultra-High-Performance Fiber-Reinforced Concrete: Influence of Fiber Geometry, Material Type, and Hybridization

    Qi Feng1,2, Weijie Hu1, Lu Liu3,*, Junhui Luo4

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1589-1605, 2025, DOI:10.32604/sdhm.2025.072955 - 17 November 2025

    Abstract Ultra-high performance fiber-reinforced concrete (UHPFRC) has received extensive attention from scholars and engineers due to its excellent mechanical properties and durability. However, there is a mutually restrictive relationship between the workability and mechanical properties of UHPFRC. Specifically, the addition of fibers will affect the workability of fresh UHPFRC, and the workability of fresh UHPFRC will also affect the dispersion and arrangement of fibers, thus significantly influencing the mechanical properties of hardened UHPFRC. This paper first analyzes the research status of UHPFRC and the relationship between its workability and mechanical properties. Subsequently, it outlines the test… More >

  • Open Access

    ARTICLE

    STPEIC: A Swin Transformer-Based Framework for Interpretable Post-Earthquake Structural Classification

    Xinrui Ma, Shizhi Chen*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148 - 17 November 2025

    Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

  • Open Access

    ARTICLE

    Experimental Study on Abrasion Resistance of Self-Compacting Concrete

    Weixi Zhu1,2,3, Yongdong Meng1,3,*, Jindong Xie2, Zhenglong Cai1,3, Yu Lyu2, Xiaowei Xu1,3

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1733-1744, 2025, DOI:10.32604/sdhm.2025.070098 - 17 November 2025

    Abstract To mitigate the severe abrasion damage caused by high-velocity water flow in hydraulic engineering applications in Xizang, China, this study systematically optimized key mix design parameters, including aggregate gradation, sand ratio, fly ash content, and superplasticizer dosage. Based on the optimized mix, the combined effects of an abrasion-resistance enhancement admixture (AEA) and silica fume (SF) on the abrasion resistance of self-compacting concrete (SCC) were examined. The results demonstrated that the appropriate incorporation of AEA and SF significantly improved the abrasion resistance of SCC without compromising its workability. The proposed mix design not only achieves superior… More >

  • Open Access

    ARTICLE

    Influence Mechanism of Liquid Level on Oil Tank Structures and Damage Risk Prevention Based on Shell Theory

    Si-Kai Wang1, Ti-Cai Wang1, Di-Fei Yi2, Jia Rui3, Peng-Fei Cao4, Hua-Ping Wang1,5,*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1411-1432, 2025, DOI:10.32604/sdhm.2025.070034 - 17 November 2025

    Abstract As a key storage facility, the structural safety of large oil tanks is directly related to the stable operation of the energy system. The static pressure caused by the change of liquid level is one of the main loads in the service process of storage tanks, which determines the structural deformation and damage risk. To explore the structural deformation properties under the change of liquid levels and provide a theoretical basis for the prevention and control of damage risk, this paper systematically analyzes the mechanical response of storage tanks under the pressures induced by different… More > Graphic Abstract

    Influence Mechanism of Liquid Level on Oil Tank Structures and Damage Risk Prevention Based on Shell Theory

  • Open Access

    ARTICLE

    Hybrid Attention-Driven Transfer Learning with DSCNN for Cross-Domain Bearing Fault Diagnosis under Variable Operating Conditions

    Qiang Ma1,2,3,4, Zepeng Li1,2, Kai Yang1,2,*, Shaofeng Zhang1,2, Zhuopei Wei1,2

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1607-1634, 2025, DOI:10.32604/sdhm.2025.069876 - 17 November 2025

    Abstract Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variable service conditions, and their diagnostic environments are complex and dynamic. In the process of bearing diagnosis, fault datasets are relatively scarce compared with datasets representing normal operating conditions. These challenges frequently cause the practicality of fault detection to decline, the extraction of fault features to be incomplete, and the diagnostic accuracy of many existing models to decrease. In this work, a transfer-learning framework, designated DSCNN-HA-TL,… More >

  • Open Access

    REVIEW

    Benefits of Artificial Intelligence for Achieving Durable and Sustainable Building Design

    Abdullah Alariyan1, Rawand A. Mohammed Amin2, Ameen Mokhles Youns3, Mahmoud Alhashash4, Favzi Ghreivati5, Ahed Habib6,*, Maan Habib7

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1387-1410, 2025, DOI:10.32604/sdhm.2025.069821 - 17 November 2025

    Abstract Artificial intelligence (AI) is transforming the building and construction sector, enabling enhanced design strategies for achieving durable and sustainable structures. Traditional methods of design and construction often struggle to adequately predict building longevity, optimize material use, and maintain sustainability throughout a building’s lifecycle. AI technologies, including machine learning, deep learning, and digital twins, present advanced capabilities to overcome these limitations by providing precise predictive analytics, real-time monitoring, and proactive maintenance solutions. This study explores the benefits of integrating AI into building design and construction processes, highlighting key advantages such as improved durability, optimized resource efficiency,… More >

  • Open Access

    ARTICLE

    Memory-Fused Dual-Stream Fault Diagnosis Network Based on Transformer Vibration Signals

    Mingxing Wu1, Chengzhen Li1, Xinyan Feng1, Fei Chen2, Yingchun Feng1, Huihui Song1, Wenyu Wang3, Faye Zhang3,*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1473-1487, 2025, DOI:10.32604/sdhm.2025.069811 - 17 November 2025

    Abstract As a core component of power systems, the operational status of transformers directly affects grid stability. To address the problem of “domain shift” in cross-domain fault diagnosis, this paper proposes a memory-enhanced dual-stream network (MemFuse-DSN). The method reconstructs the feature space by selecting and enhancing multi-source domain samples based on similarity metrics. An adaptive weighted dual-stream architecture is designed, integrating gradient reversal and orthogonality constraints to achieve efficient feature alignment. In addition, a novel dual dynamic memory module is introduced: the task memory bank is used to store high-confidence class prototype information, and adopts an More >

  • Open Access

    ARTICLE

    Experimental Study on Axial Compressive Behavior and Constitutive Model of Restored Mortar Masonry

    Dongyu Teng1,2,*, Hao Tang1,3,*, Peng He1,2, Zhen Hao1,2

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1717-1731, 2025, DOI:10.32604/sdhm.2025.069751 - 17 November 2025

    Abstract In order to study the axial compression characteristics of brick masonry historical buildings, and to better protect and repair traditional mortar-brick masonry historical buildings, axial compression tests were carried out on three kinds of restored mortar (pure mud mortar, pure mortar, and mud mortar) brick masonry with restored mortar brick masonry as the object of study. The damage modes, axial compression chemical indexes (compressive strength and elastic modulus), load-displacement curves and stress-strain curves of the three kinds of restored mortar brick masonry were obtained. The experimental results show that the compressive strength of mud mortar… More >

  • Open Access

    ARTICLE

    Automatic Potential Safety Hazard Detection for High-Speed Railroad Surrounding Environment Using Lightweight Hybrid Dual Tasks Architecture

    Zheda Zhao, Tao Xu, Tong Yang, Yunpeng Wu*, Fengxiang Guo*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1457-1472, 2025, DOI:10.32604/sdhm.2025.069611 - 17 November 2025

    Abstract Utilizing unmanned aerial vehicle (UAV) photography to timely detect and evaluate potential safety hazards (PSHs) around high-speed rail has great potential to complement and reform the existing manual inspections by providing better overhead views and mitigating safety issues. However, UAV inspections based on manual interpretation, which heavily rely on the experience, attention, and judgment of human inspectors, still inevitably suffer from subjectivity and inaccuracy. To address this issue, this study proposes a lightweight hybrid learning algorithm named HDTA (hybrid dual tasks architecture) to automatically and efficiently detect the PSHs of UAV imagery. First, this HDTA… More >

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