SDHMOpen Access

Structural Durability & Health Monitoring

ISSN:1930-2983(print)
ISSN:1930-2991(online)
Publication Frequency:Bi-monthly

  • Online
    Articles

    309

  • on board
    editors

    88

Special lssues


About the Journal

In order to maintain a reasonable cost for large scale structures such as airframes, offshore structures, nuclear plants etc., it is generally accepted that improved methods for structural integrity and durability assessment are required. Structural Health Monitoring (SDHM) had emerged as an active area of research for fatigue life and damage accumulation prognostics.

This journal is a member of the Committee on PublicationEthics (COPE).

Indexing and Abstracting

Scopus Citescore (Impact per Publication 2022): 3.0; SNIP (Source Normalized Impact per Paper 2022): 0.630; 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...

Structural Durability & Health Monitoring will be migrating from old submission system(https://www.tspsubmission.com) to new submission system(https://ijs.tspsubmission.com) on 27 March 2023.
Manuscripts submitted to old submission system before 27 March 2023 will continue to undergo normal review process in old submission system. New submissions after 27 March 2023 must be made through new submission system.
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  • Open Access

    REVIEW

    Emerging Trends in Damage Tolerance Assessment: A Review of Smart Materials and Self-Repairable Structures

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573
    (This article belongs to this Special Issue: Health Monitoring and Rapid Evaluation of Infrastructures)
    Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification… More >

  • Open Access

    ARTICLE

    Numerical Simulations of the Flow Field around a Cylindrical Lightning Rod

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 19-35, 2024, DOI:10.32604/sdhm.2023.042944
    Abstract As an important lightning protection device in substations, lightning rods are susceptible to vibration and potential structural damage under wind loads. In order to understand their vibration mechanism, it is necessary to conduct flow analysis. In this study, numerical simulations of the flow field around a 330 kV cylindrical lightning rod with different diameters were performed using the SST k-ω model. The flow patterns in different segments of the lightning rod at the same reference wind speed (wind speed at a height of 10 m) and the flow patterns in the same segment at different reference wind speeds were investigated. The variations… More >

  • Open Access

    ARTICLE

    Fault Diagnosis Method of Rolling Bearing Based on ESGMD-CC and AFSA-ELM

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 37-54, 2024, DOI:10.32604/sdhm.2023.029428
    Abstract Incomplete fault signal characteristics and ease of noise contamination are issues with the current rolling bearing early fault diagnostic methods, making it challenging to ensure the fault diagnosis accuracy and reliability. A novel approach integrating enhanced Symplectic geometry mode decomposition with cosine difference limitation and calculus operator (ESGMD-CC) and artificial fish swarm algorithm (AFSA) optimized extreme learning machine (ELM) is proposed in this paper to enhance the extraction capability of fault features and thus improve the accuracy of fault diagnosis. Firstly, SGMD decomposes the raw vibration signal into multiple Symplectic geometry components (SGCs). Secondly, the iterations are reset by the… More >

  • Open Access

    ARTICLE

    Assessment of the Influence of Tunnel Settlement on Operational Performance of Subway Vehicles

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 55-71, 2024, DOI:10.32604/sdhm.2023.044832
    (This article belongs to this Special Issue: Health Monitoring and Rapid Evaluation of Infrastructures)
    Abstract In the realm of subway shield tunnel operations, the impact of tunnel settlement on the operational performance of subway vehicles is a crucial concern. This study introduces an advanced analytical model to investigate rail geometric deformations caused by settlement within a vehicle-track-tunnel coupled system. The model integrates the geometric deformations of the track, attributed to settlement, as track irregularities. A novel “cyclic model” algorithm was employed to enhance computational efficiency without compromising on precision, a claim that was rigorously validated. The model’s capability extends to analyzing the time-history responses of vehicles traversing settlement-affected areas. The research primarily focuses on how… More >

  • Open Access

    ARTICLE

    A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 73-90, 2024, DOI:10.32604/sdhm.2023.044023
    Abstract The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains. However, in real-world scenarios, accurate predictions are challenging due to various interferences. This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter (KF). The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments. By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect of metals, it becomes possible… More >

    Graphic Abstract

    A Novel Method for Aging Prediction of Railway Catenary Based on Improved Kalman Filter

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