Open Access
ISSN:1930-2983 (print)
ISSN:1930-2991 (online)
Publication Frequency:Bi-monthly
Structural Durability & Health Monitoring (SDHM) is an interdisciplinary journal that serves as a platform for publishing high-quality research on the performance, safety, durability, and sustainability of structural systems across their full lifecycle. While continuing to emphasize structural durability, fatigue, damage mechanics, and health monitoring techniques, the journal also welcomes original studies in the broader fields of structural engineering.
This journal is a member of the Committee on Publication Ethics (COPE).
Scopus Citescore (Impact per Publication 2024): 2.5; SNIP (Source Normalized Impact per Paper 2024): 0.604; RG Journal Impact (average over last three years); Engineering Index (Compendex); Applied Mechanics Reviews; Cambridge Scientific Abstracts: Aerospace and High Technology, Materials Sciences & Engineering, and Computer & Information Systems Abstracts Database; INSPEC Databases; Mechanics; Science Navigator; Portico, etc...
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075676 - 18 May 2026
（This article belongs to the Special Issue: Smart Sensors and Smart CFRP Components for Structural Health Monitoring of Aerospace, Energy and Transportation Structures)
Abstract Carbon fiber reinforced polymer (CFRP) laminates are widely used in aerospace, new energy, and transportation engineering due to their high specific strength and stiffness. However, interlaminar delamination damage can lead to sudden structural failure, and the occurrence and prediction of such hidden defects are difficult to identify and evaluate using conventional inspection methods. To address this, smart CFRP laminates integrated with fiber Bragg grating (FBG) sensors offer a new approach for real-time structural health monitoring (SHM). Nevertheless, the influence mechanisms of the two integration methods—embedded and surface-bonded FBG sensors—on the static strength and impact resistance… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.076141 - 18 May 2026
（This article belongs to the Special Issue: Innovative and Sustainable Materials for Reinforced Concrete Structures)
Abstract This study investigates the contribution of fibers to the durability of reinforced concrete tunnel linings. Two cast-in-situ tunnels are herein analyzed after twenty years of service. Tunnel #1, made with plain concrete and steel rebar, has shown significant spalling at joints between two consecutive tunnel panels, caused by poor workmanship and construction details. Conversely, in Tunnel #2, close to Tunnel #1 on the same motorway, fiber-reinforced concrete (FRC) was used in combination with steel rebar. During the service life, the amount of FRC spalled from the cold joints of this lining has been significantly lower than More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.079074 - 18 May 2026
（This article belongs to the Special Issue: Smart Sensors and Smart CFRP Components for Structural Health Monitoring of Aerospace, Energy and Transportation Structures)
Abstract In response to the dynamic changes in fatigue damage location of crane welding structures under lifting loads and the difficulty in accurately obtaining the stress concentration factor of welds, which results in limited effetiveness of traditional health monitoring sensor placement. This paper proposes aa sensor placement optimization method that integrates damage prediction and risk assessment. Firstly, the influence of weld geometry on fatigue performance is analyzed, and a rapid estimation model for the stress concentration factor is established using a radial basis function support vector machine. Furthermore, a fatigue damage prediction model for the welded… More >
Open Access
REVIEW
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.076012 - 18 May 2026
Abstract Unsupervised machine learning has recently gained attention in structural health monitoring as engineers seek methods that can interpret large and complex data sets without prior labeling. Traditional diagnostic approaches often rely on predefined models or manual analysis, which limits their adaptability and efficiency when dealing with evolving structural behaviors or unforeseen conditions. Despite the growing interest in this domain, the literature remains fragmented, with limited systematic and bibliometric reviews that consolidate progress, identify prevailing trends, and clarify methodological limitations. This study addresses this gap through a comprehensive systematic and bibliometric review of research on unsupervised More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077081 - 18 May 2026
（This article belongs to the Special Issue: Innovative and Sustainable Materials for Reinforced Concrete Structures)
Abstract Many tests have been conducted over the years in Milan on moderately-thick concrete slabs—with diameter-to-thickness ratios of 5 and 5.5—either reinforced or unreinforced, all subjected to punching, with different mixes, reinforcement technologies, and loading procedures. Their results are revisited systematically in this paper, starting from a thorough review of the literature on moderately thick concrete slabs. The specimens were either square (but fastened to a circular support) or circular. In three experimental campaigns, 99 specimens were tested: 50 under quasi-static loading (including 16 exposed to high temperatures) and 49 under impulsive loading. The first campaign… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2025.075535 - 18 May 2026
（This article belongs to the Special Issue: Vibration Control, Dampers and Structural Health Monitoring)
Abstract The study proposes a low-cost friction damper designed to enhance the seismic performance of buildings, particularly in regions where existing structures lack adequate seismic resistance and conventional friction dampers are cost-prohibitive or require specialized fabrication. Friction dampers are displacement-controlled devices that dissipate energy through constant slip-force action and relative displacement between attachment points, typically ensuring elastic structural behavior under Design Basis Earthquake (DBE) demands and controlled yielding under Maximum Considered Earthquake (MCE) conditions. To address limitations in current practice, the proposed device integrates the damping mechanism of vehicle leaf-spring suspension systems with rotational plate friction… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075421 - 18 May 2026
（This article belongs to the Special Issue: Big Data and Machine Learning for Health Monitoring and Maintenance of Transportation Infrastructure)
Abstract Rutting is a serious issue in asphalt pavement, which may reduce the pavement driving quality and safety. Accurately predicting rutting depth is a crucial task in pavement engineering, providing crucial decision support for asphalt pavement design and maintenance. However, accurate prediction of pavement rutting still remains a significant challenge for pavement engineers. This research first selects the loading number, temperature, dynamic modulus, asphalt layer thickness, and base layer type and thickness as candidate features. Data preprocessing, including outlier handling and feature selection, is then performed. Finally, based on the stacking algorithm, a multi-model fusion approach… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077120 - 18 May 2026
（This article belongs to the Special Issue: Infrastructure Resilience Enhancement Empowered by Intelligent Perception and Advanced Algorithms)
Abstract This study experimentally investigates the Hybrid Effect of Steel Fiber (SF) and Recycled Rubber Powder (RRP) on Freeze-Thaw (F-T) Resistance and Pore Structure of Concrete. With respect to the mechanical properties of Steel Reinforced Concrete (SRC) before and after F-T cycles, the mixture incorporating 1.5% SF and 10% RRP achieves the optimal performance, exhibiting a distinct positive hybrid effect with the γ of the tensile-to-compressive strength ratio of 1.427. The synergistic interaction between SF and RRP preserves the compressive strength and significantly enhances the tensile performance of SRC. Meanwhile, it alleviates the degradation of mechanical More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.074828 - 18 May 2026
Abstract The structural integrity and longevity of wind turbine blades are critical determinants of the efficiency and reliability of wind energy systems. As the primary components responsible for converting kinetic wind energy into mechanical torque and subsequently electrical power, the aerodynamic, structural, and material characteristics of rotor blades directly influence turbine performance and operational lifespan. This research addresses the limitations of conventional blade designs, often characterized by stress concentration, fatigue damage, and dynamic instability by introducing a novel diamond-lattice internal support structure aimed at improving mechanical strength, fatigue resistance, and dynamic stability. Finite element simulations performed… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2025.076570 - 18 May 2026
（This article belongs to the Special Issue: Durability Assessment of Engineering Structures and Advanced Construction Technologies)
Abstract This study presents a comprehensive investigation into the deformation mechanisms of existing metro stations subjected to the simultaneous construction of adjacent foundation pits and underground tunnels. A refined three-dimensional numerical modeling framework is developed to simulate the entire construction process, capturing the complex interactions between excavation activities and station structures. The modeling encompasses deep excavation, side-crossing, and overcrossing passage construction, and the staged installation of support systems. Six construction schemes, varying in excavation sequence, interlayer thickness (clear distance), and passageway layout, are systematically analyzed. Field monitoring data are incorporated to validate the numerical models, enhancing… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.078140 - 18 May 2026
（This article belongs to the Special Issue: Infrastructure Resilience Enhancement Empowered by Intelligent Perception and Advanced Algorithms)
Abstract Accurate assessment of the failure stage of rail rolling contact fatigue (RCF) is critical for guiding timely maintenance by track personnel, ensuring safe rail operations, and reducing maintenance costs. Although various methods have been developed to detect rail damage and classify surface defects, the rolling contact fatigue failure state of rails has not yet been comprehensively and objectively evaluated. This paper introduces the application of image processing and improved deep-learning network algorithms in rail failure evaluation and judgment. Based on Swin Transformer, a deep learning network is developed. By dividing the rail rolling contact fatigue More >
Open Access
REVIEW
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.074644 - 18 May 2026
Abstract Composite structures have become integral to modern construction owing to their efficiency, strength, and economic benefits, with steel-headed studs serving as critical shear connectors between concrete slabs and steel beams. Existing research has investigated these connectors through push-out and pull-out experiments, fatigue and cyclic protocols, durability and temperature-extreme studies, and a wide range of analytical, numerical, and data-driven models. This study addresses the lack of a consolidated and critical review by combining a systematic review with a bibliometric assessment of 385 Scopus-indexed publications from 2000 to 2025, which shows sustained growth of research output and… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075835 - 18 May 2026
Abstract A composite bridge deck system consisting of an orthotropic steel deck and a normal-temperature-cured reactive powder concrete (RPC) layer is proposed to address the problems of pavement damage and fatigue cracks in steel bridge decks. In this study, a local finite element model of a bridge segment was established using ANSYS to calculate and compare the stress states of four deck systems: normal-temperature-cured RPC composite box girders, high-temperature-cured RPC composite box girders, pure steel box girders, and ordinary concrete composite box girders. Additionally, static load tests were conducted on a scaled local model to validate… More >
Graphic Abstract
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077736 - 18 May 2026
（This article belongs to the Special Issue: AI-Enhanced Low-Altitude Technology Applications in Structural Integrity Evaluation and Safety Management of Transportation Infrastructure Systems)
Abstract Key components of rail transit systems, such as tracks and vehicle bodies, are prone to developing various types and manifestations of defects during long-term operation. These defects not only accelerate component aging and failure but also pose serious threats to train operational safety. Among existing intelligent detection methods, they mostly rely solely on visible light images demonstrate limited robustness in complex scenarios. This limitation stems from their high dependence on ambient lighting conditions, rendering them insufficient to meet practical railway inspection requirements. While mainstream multimodal detection methods incorporate the complementary strengths of heterogeneous data sources,… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077137 - 18 May 2026
（This article belongs to the Special Issue: AI-Driven and Computer-Vision-Based Sensing Technology for Real-Time, Non-Destructive Applications)
Abstract Accurate characterization of live load histories remains critical for structural safety and efficient design; however, traditional codes often overestimate in-service loads. This study introduced an AI-driven framework integrating YOLOv8 object detection and DeepFace gender classification with continuous video surveillance to monitor live loads in academic buildings. Gender classification used local anthropometric data (77 kg males, 61 kg females) for precise load estimation, with privacy ensured via local processing and anonymized metadata only. Observed peaks were substantially below Eurocode and IBC provisions, confirming code conservatism. Uncertainty propagation from detector errors (recall 0.57, ±0.02 Kn/m2) minimally impacted projections. More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077878 - 18 May 2026
（This article belongs to the Special Issue: AI-Enhanced Low-Altitude Technology Applications in Structural Integrity Evaluation and Safety Management of Transportation Infrastructure Systems)
Abstract To enhance traffic infrastructure health monitoring via computer vision (CV) in adverse weather conditions, image dehazing has emerged as a critical processing step. However, current supervised dehazing models, typically trained on synthetic hazy-clean image pairs, often demonstrate limited generalization ability when deployed in real-world haze scenarios. This study proposes a novel unsupervised dehazing framework named the unpaired dual-domain dehazing network (UD3Net). Initially, a novel dual-domain convolutional mixer (DCM) is developed, which can extract local features in the spatial domain and global features in the frequency domain to achieve thorough information fusion, aiming to facilitate accurate estimation… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077926 - 18 May 2026
（This article belongs to the Special Issue: Advanced Detection Technologies and Interpretable Machine Learning Methods in Energy Infrastructure)
Abstract The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China. However, accurate measurement is challenging because these columns typically exhibit natural tapering, with diameters decreasing from the base to the top, and surface irregularities such as artificial cuts, cracks, and knots. Both the intrinsic geometric characteristics and surface defects reduce the precision of coordinate acquisition and the reliability of inclination estimation. To overcome these limitations, this study proposes a novel inclination measurement method for wooden columns in traditional timber buildings based on multi-section measurement and… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077643 - 18 May 2026
（This article belongs to the Special Issue: Greening the Pipes: Achieving Sustainability in Pipeline Engineering)
Abstract Accurate assessment of gas explosion risks in urban underground culverts is often hindered by the decoupling of leakage diffusion and explosion mechanics. This study develops a high-fidelity numerical framework by implementing a one-way coupling strategy, where the steady-state methane concentration field simulated in FLUENT is mapped into ANSYS/LS-DYNA as the initial material status. Unlike traditional models assuming uniform gas distribution, this approach captures the realistic impact of complex culvert geometries on explosion precursors. A multi-material coupled model involving the confined space, road surface, and surrounding air was established to investigate shock-wave propagation and structural response. The More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075587 - 18 May 2026
（This article belongs to the Special Issue: AI-driven Monitoring, Condition Assessment, and Data Analytics for Enhancing Infrastructure Resilience)
Abstract Conventional fiber Bragg grating (FBG) sensors used for tensile monitoring have a limited measurement range and therefore cannot cover the entire service stage of prestressed carbon-fiber-reinforced polymer (CFRP)–strengthened members. In this study, a smart CFRP plate is developed by embedding a wide-range FBG sensor in a prestressed CFRP plate. Based on strain-transfer theory for the grating region, an analytical expression for the average strain-transfer rate is derived and then used to inversely design the groove geometry and bonding parameters; the resulting groove size is 0.5 mm × 0.5 mm. During bonding, a tensile force of… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.076697 - 18 May 2026
Abstract Polyethylene (PE) pipes are widely used in various gas transmission applications due to their excellent flexibility and other advantages. As high-molecular-weight non-metallic polymeric materials, they inevitably undergo degradation and aging during service under the action of environmental factors such as temperature and ultraviolet (UV) radiation, which impairs their service performance. To investigate the effects of environmental factors on the aging and degradation of PE pipes, a reliable method for predicting their service life was developed in this study. Taking PE80 DN110 pipes as the research subject, an accelerated aging method was adopted to simulate the… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077489 - 18 May 2026
（This article belongs to the Special Issue: Greening the Pipes: Achieving Sustainability in Pipeline Engineering)
Abstract This paper proposes a novel approach for predicting the residual strength of corroded pipelines by combining the Kernel Extreme Learning Machine (KELM) with Sparrow Search Algorithm (SSA) optimization. The proposed SSA-KELM model addresses the limitations of traditional evaluation methods and single machine learning models in residual strength prediction. A dataset comprising 80 samples from burst tests and finite element simulations was used to validate the model. Results demonstrate that the SSA-KELM model achieves superior prediction accuracy with a maximum relative error of 13.54% and minimum relative error of 0.20%. The model’s mean absolute error (MAE), More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077108 - 18 May 2026
（This article belongs to the Special Issue: Durability Assessment of Engineering Structures and Advanced Construction Technologies)
Abstract With the increasing environmental pressure caused by waste plastic (WP), incorporating recycled plastics into asphalt concrete has become a promising strategy for sustainable pavement construction. In this study, waste polyethylene terephthalate (PET) was utilized to replace mineral aggregates through a dry process, and the effects of particle size and replacement level on the mechanical performance of asphalt concrete were systematically evaluated. High-temperature deformation resistance was assessed using wheel-tracking tests, followed by dynamic modulus measurements to examine the viscoelastic behavior and structural stiffness. Low-temperature cracking resistance was studied through fracture toughness and fracture energy tests, and… More >
Open Access
ARTICLE
Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.072074 - 18 May 2026
Abstract Under soft soil geological conditions, tunnel engineering disturbances can induce changes in ground surface surcharges and lead to stress redistribution in the surrounding soils. As relatively unfavorable loads during engineering disturbances, ground surface surcharges significantly influence both transverse and longitudinal deformations of shield tunnel structures, resulting in increased ellipticity, segment dislocations, joint openings, and tunnel settlement. This study investigates the effect of two different steel plate reinforcement methods—annular steel plates and cross-joint steel plates—on tunnel structures under surface surcharge loading. Using the Mohr–Coulomb elastoplastic constitutive model, the influence of surface surcharges on shield tunnel segment… More >
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