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Applied Sciences
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Advanced Devices and Data Analysis in Vibration Control and Structural...
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Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 October 2024 | Viewed by 2101

Special Issue Editors

Dr. Yinghao Zhao

E-Mail Website
Guest Editor
School of Civil Engineering, Guangzhou Maritime University, Guangzhou 510725, China
Interests: structural health monitoring; seismic fragility analysis; structural damage detection; deep learning; computer vision
Dr. Zeyu Wang

E-Mail Website
Guest Editor
School of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: machine learning; structural reliability; uncertainty quantification; Bayesian updating; surrogate modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Xijun Ye

E-Mail Website
Guest Editor
School of Civil Engineering, Guangzhou University, Guangzhou 510006, China
Interests: structural health monitoring; modal analysis; structural damage diagnosis; deep learning

Special Issue Information

Dear Colleagues,

Introduction

Structural health monitoring (SHM) is a vital function of modern large-scale structures and infrastructure systems. This technology, along with data-driven simulation and analysis, can ensure the safety, reliability and durability of infrastructures. As sensor technology has matured, there has been a surging increase in the number of studies performed in the field of SHM to enrich more functionalities for health monitoring. Many efficient methods such as image recognition for cracks, pattern recognition for structural vibration, etc., can be computationally efficient. However, the problems of SHM are still challenging, and therefore still need to be addressed with more advanced devices and data analysis techniques. In line with the practical purpose of SHM, methods that can simultaneously investigate state-of-the-practice engineering models and data-driven analysis methods should be investigated and devised. This Special Issue aims to provide a platform for researchers, practitioners, and engineers to share their latest findings, innovations, and developments in advanced devices, new data analysis strategies, artificial intelligence, deep learning, uncertainty quantification and engineering optimization for SHM.

Scope

This Special Issue focuses on the latest advances in advanced devices, innovative data analysis strategies, optimization methods, uncertainty quantification, Bayesian methods and artificial intelligence techniques for SHM. It covers research works related to sensors, data acquisition systems, wireless sensor networks, data analysis techniques, signal processing algorithms and optimization strategies for SHM and applications. This issue also covers the application of advanced devices, innovative data analysis strategies, artificial intelligence and deep learning in practical scenarios.

Topics of Interest

The topics of interest for this Special Issue include, but are not limited to, the following:

  1. Advanced sensors and data acquisition systems for SHM and engineering optimization;
  2. Wireless sensor networks for SHM;
  3. Innovative data analysis strategies for SHM and engineering optimization;
  4. Signal processing and machine learning techniques for SHM and engineering optimization;
  5. Non-destructive testing and evaluation for SHM;
  6. Experimental and numerical studies on SHM and engineering optimization;
  7. Applications of advanced devices, innovative data analysis strategies, artificial intelligence and deep learning in real-world scenarios;
  8. Health monitoring of large-scale structures such as bridges, wind turbines and buildings;
  9. Uncertainty quantification with advanced numerical methods and simulations;
  10. Risk-informed decision-making for SHM of infrastructure systems.

Dr. Yinghao Zhao
Dr. Zeyu Wang
Dr. Xijun Ye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural health monitoring
  • structural damage detection
  • risk-informed decision making
  • advanced devices
  • data analysis strategies
  • structural reliability
  • control system
  • Bayesian updating
  • deep learning
  • computer vision

Published Papers (2 papers)

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Research

14 pages, 2784 KiB  
Article
Laboratory Study of Effective Stress Coefficient for Saturated Claystone
by Fanfan Li, Weizhong Chen, Zhigang Wu, Hongdan Yu, Ming Li, Zhifeng Zhang and Fusheng Zha
Appl. Sci. 2023, 13(19), 10592; https://doi.org/10.3390/app131910592 - 22 Sep 2023
Cited by 1 | Viewed by 630
Abstract
Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a [...] Read more.
Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a stability analysis of waste disposal facilities. Consolidated drained (CD) tests were carried out on claystone samples to study their effective stress principle in this paper. Firstly, two samples were saturated under a specified confining pressure and pore pressure for about one month. Secondly, the confining pressure and pore pressure were increased to a specified value simultaneously and then reverted to the previous stress state (the deformations of the samples were recorded during the whole process). Different incremental combinations of the confining pressure and pore pressure were tried at this step. Finally, the effective stress coefficients of the samples were obtained through a back analysis. Furthermore, some potential influencing factors (the neutral stress and loading rate) of the effective stress coefficient were also studied through additional tests. Some interesting results are worth mentioning: (1) the effective stress coefficient of claystone is close to one; (2) the neutral stress and loading rate may have little effect on the effective stress coefficient of claystone. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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0 pages, 7505 KiB  
Article
Evaluation of Mechanical Performance of a New Disc Spring-Cable Counter Pressure Shock Absorber
by Yanfeng Wang, Xiaohui Wu, Shaofeng Ji, Faping Xiao and Dayang Wang
Appl. Sci. 2023, 13(15), 8718; https://doi.org/10.3390/app13158718 - 28 Jul 2023
Viewed by 973
Abstract
Mechanical performance evaluation of a new disc spring-cable counter pressure shock absorber is focused on in this study. The proposed shock absorber is always in a compressive working state with energy dissipation capacity under both tension and compression loadings. The design formulas of [...] Read more.
Mechanical performance evaluation of a new disc spring-cable counter pressure shock absorber is focused on in this study. The proposed shock absorber is always in a compressive working state with energy dissipation capacity under both tension and compression loadings. The design formulas of its axial bearing capacity, vertical stiffness, deformation energy of the shock absorber were derived, and the corresponding specific design process was provided in detail. Experimental and numerical investigations of the mechanical performance were conducted under static and dynamic loadings. The parameters influencing the laws of the mechanical performance of the shock absorber, including loading frequency, pre-compression deformation and loading amplitude, were investigated. The rationality of the proposed shock absorber was firstly verified through comparative analysis using experimental, numerical and theoretical calculations. The shock absorber with a friction coefficient of 0.005 between disc springs, and a friction coefficient of 0.3 between the disc spring and cover plate has the smallest error between experiment and theory for the flattening force. The bearing capacity of the shock absorber exhibits a linear relationship with the loading displacement in static loading. In dynamic loading, however, the bearing capacity shows a trend of slow growth followed by rapid growth. The energy dissipation capacity of the shock absorber shows an increase with the increase of loading displacement. The minimum equivalent damping ratio of all of the dynamic test cases is 7%, with a maximum up to 15.3%. Under the same loading frequency, the equivalent stiffness and equivalent damping ratio have a linear amplification trend with the increase of pre-compression deformation, and the maximum increase of equivalent stiffness is equal to 41.37%. Under the same loading frequency and pre-compression deformation, the energy consumption capacity can be improved by increasing the loading amplitude. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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