{"title":"A Random Field Model of Multipoint Bouncing Loads and Its Applications","authors":"Jiecheng Xiong, Jun Chen","doi":"10.1155/2024/2715182","DOIUrl":null,"url":null,"abstract":"<div>\n <p>In existing load models, the crowd bouncing load is often simplified as a single-point excitation; moreover, these models lack data support from crowd bouncing experiments. Inspired by the random field models widely adopted in seismic ground motion fields, a random field model for crowd bouncing loads was established in this research. The bouncing frequency, time lag, and amplitude of the coherence function were modeled to quantify the crowd synchronization; an auto-power spectral density (PSD) model from the author’s previous study was adopted for an individual bouncing load. The values of these parameters were obtained based on data from a crowd bouncing experiment involving 48 test subjects on the first day and 42 test subjects on the second day, in which the trajectories of reflective markers fixed at the clavicle of every test subjects were simultaneously recorded using three-dimensional motion capture system. Based on the PSD matrix of the crowd bouncing loads as simulated by the proposed random field model, the structural acceleration can be analyzed using random vibration analysis in the frequency domain. The established random field model and spectral analysis framework can be adopted to evaluate the vibrating performances of lightweight and high-strength structures. Moreover, the established load model is also the basis of structural vibration control.</p>\n </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2024 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/2715182","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Control & Health Monitoring","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/2715182","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In existing load models, the crowd bouncing load is often simplified as a single-point excitation; moreover, these models lack data support from crowd bouncing experiments. Inspired by the random field models widely adopted in seismic ground motion fields, a random field model for crowd bouncing loads was established in this research. The bouncing frequency, time lag, and amplitude of the coherence function were modeled to quantify the crowd synchronization; an auto-power spectral density (PSD) model from the author’s previous study was adopted for an individual bouncing load. The values of these parameters were obtained based on data from a crowd bouncing experiment involving 48 test subjects on the first day and 42 test subjects on the second day, in which the trajectories of reflective markers fixed at the clavicle of every test subjects were simultaneously recorded using three-dimensional motion capture system. Based on the PSD matrix of the crowd bouncing loads as simulated by the proposed random field model, the structural acceleration can be analyzed using random vibration analysis in the frequency domain. The established random field model and spectral analysis framework can be adopted to evaluate the vibrating performances of lightweight and high-strength structures. Moreover, the established load model is also the basis of structural vibration control.
期刊介绍:
The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications.
Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics.
Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.