Home / Journals / SDHM / Vol.15, No.2, 2021
  • Open Access

    ARTICLE

    Inverse Load Identification in Stiffened Plate Structure Based on in situ Strain Measurement

    Yihua Wang1, Zhenhuan Zhou1, Hao Xu1,*, Shuai Li2, Zhanjun Wu1
    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 85-101, 2021, DOI:10.32604/sdhm.2021.014256
    Abstract For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition method. With demonstrated high accuracy,… More >

  • Open Access

    ARTICLE

    Experimental and Numerical Assessment on Seismic Performance of Earth Adobe Walls

    Zele Li1, Mohammad Noori2, Wael A. Altabey1,3,*
    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 103-123, 2021, DOI:10.32604/sdhm.2021.011193
    Abstract Earth buildings are common types of structures in most rural areas in all developing countries. Catastrophic failure and destruction of these structures under seismic loads always result in loss of human lives and economic losses. Wall is an important load-bearing component of raw soil buildings. In this paper, a novel approach is proposed to improve the strength and ductility of adobe walls. Three types of analyses, material properties, mechanical properties, and dynamic properties, are carried out for the seismic performance assessment of the adobe walls. These performed studies include that, material properties of the earth cylinder block, mechanical properties of… More >

  • Open Access

    ARTICLE

    Artificial Neural Network (ANN) Approach for Predicting Concrete Compressive Strength by SonReb

    Mario Bonagura, Lucio Nobile*
    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 125-137, 2021, DOI:10.32604/sdhm.2021.015644
    Abstract The compressive strength of concrete is one of most important mechanical parameters in the performance assessment of existing reinforced concrete structures. According to various international codes, core samples are drilled and tested to obtain the concrete compressive strengths. Non-destructive testing is an important alternative when destructive testing is not feasible without damaging the structure. The commonly used non-destructive testing (NDT) methods to estimate the in-situ values include the Rebound hammer test and the Ultrasonic Pulse Velocity test. The poor reliability of these tests due to different aspects could be partially contrasted by using both methods together, as proposed.in the SonReb… More >

  • Open Access

    ARTICLE

    Condition Evaluation in Steel Truss Bridge with Fused Hilbert Transform, Spectral Kurtosis, and Bandpass Filter

    Anshul Sharma1,*, Pardeep Kumar1, Hemant Kumar Vinayak2, Suresh Kumar Walia3
    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 139-165, 2021, DOI:10.32604/sdhm.2021.012316
    Abstract This study is concerned with the diagnosis of discrepancies in a steel truss bridge by identifying dynamic properties from the vibration response signals of the bridges. The vibration response signals collected at bridges under three different vehicular speeds of 10 km/hr, 20 km/hr, and 30 km/hr are analyzed using statistical features such as kurtosis, magnitude of peak-to-peak, root mean square, crest factor as well as impulse factor in time domain, and Stockwell transform in the time-frequency domain. The considered statistical features except for kurtosis show uncertain behavior. The Stockwell transform showed low-resolution outcomes when the presence of noise in the… More >

  • Open Access

    ARTICLE

    Characterization and Prediction of Nonlinear Stress-Strain Relation of Geostructures for Seismic Monitoring

    Abdoullah Namdar1,2,3,*
    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 167-182, 2021, DOI:10.32604/sdhm.2021.011127
    Abstract The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely. The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods. In this study, a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method (NFEM), and linear regression method which is a soft computing technique (SC) was applied for evaluating the results of NFEM, and it supports engineering judgment because the design of the geostructures is usually… More >

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