Journals / SDHM / Vol.13, No.4

  • Research Article

    BEST PAPER 2021

    Nonlinear Micromechanical Modelling of Transverse Tensile Damage Behavior in Fiber-Reinforced Polymer Composites

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 331-346, 2019, DOI:10.32604/sdhm.2019.07521
    Abstract The investigation focusing on the mechanical behaviors at the microstructural level in composite materials can provide valuable insight into the failure mechanisms at larger scales. A micromechanics damage model which comprises the coupling of the matrix constitutive model and the cohesive zone (CZM) model at fiber-matrix interfaces is presented to evaluate the transverse tensile damage behaviors of unidirectional (UD) fiber-reinforced polymer (FRP) composites. For the polymeric matrix that exhibits highly non-linear mechanical responses, special focus is paid on the formulation of the constitutive model, which characterizes a mixture of elasticity, plasticity as well as damage. The proposed constitutive model includes… More >

  • Research Article

    BEST PAPER 2021

    Fiber Grating-Based Strain Sensor Array for Health Monitoring of Pipelines

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 347-359, 2019, DOI:10.32604/sdhm.2019.05139
    Abstract Pipelines are one of the most important modern energy transportation methods, used especially for the transportation of certain dangerous energy media materials such as crude oil, natural gas, and chemical raw materials. New requirements have been put forward for the health monitoring and early security warning of pipelines because of the large-scale and complicated development trend of the pipe network system. To achieve an accurate assessment of the health conditions of pipeline infrastructure, obtaining as many precise operating parameters as possible, particularly at some critical parts of the pipeline, is necessary. Therefore, a novel type of fiber grating strain sensor… More >

  • Research Article

    BEST PAPER 2021

    Seismic Reliability Assessment of Inelastic SDOF Systems Subjected to Near-Fault Ground Motions Considering Pulse Occurrence

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 361-378, 2019, DOI:10.32604/sdhm.2019.05171
    Abstract The ground motions in the orientation corresponding to the strongest pulse energy impose more serious demand on structures than that of ordinary ground motions. Moreover, not all near-fault ground motion records present distinct pulses in the velocity time histories. In this paper, the parameterized stochastic model of near-fault ground motion with the strongest energy and pulse occurrence probability is suggested, and the Monte Carlo simulation (MSC) and subset simulation are utilized to calculate the first excursion probability of inelastic single-degree-of-freedom (SDOF) systems subjected to these types of near-fault ground motion models, respectively. Firstly, the influences of variation of stochastic pulse… More >

  • Research Article

    BEST PAPER 2021

    Kinematic Analysis and Rock Mass Classifications for Rock Slope Failure at USAID Highways

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 379-398, 2019, DOI:10.32604/sdhm.2019.08192
    Abstract Rock slope kinematic analysis and rock mass classifications has been conducted at the 17th km to 26th km of USAID (United States Agency for International Development) highway in Indonesia. This research aimed to examine the type of rock slope failures and the quality of rock mass as well. The scan-line method was performed in six slopes by using a geological compass to determine rock mass structure on the rock slope, and the condition of joints such as persistence, aperture, roughness, infilling material, weathering and groundwater conditions. Slope kinematic analysis was performed employing a stereographic projection. The rock slope quality and… More >

  • Research Article

    BEST PAPER 2021

    Comparative Study on Tree Classifiers for Application to Condition Monitoring of Wind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

    Structural Durability & Health Monitoring, Vol.13, No.4, pp. 399-416, 2019, DOI:10.32604/sdhm.2019.03014
    Abstract Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources. The wind turbine is an essential system used to change kinetic energy into electrical energy. Wind turbine blades, in particular, require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost. The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features. In this… More >

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