Ahmed, M.A. and Chakrabarti, S.D. (2018) Scenario of Existing Solid Waste Management Practices and Integrated Solid Waste Management Model for Developing Country with Reference to Jhenaidah Municipality, Bangladesh. 4th International Conference on Civil Engineering for Sustainable Development (ICCESD 2018), Khulna, 9-10 February 2018.
https://iccesd.com/proc_2018/Papers/r_p4230.pdf

has been cited by the following article:

• TITLE: Vehicle-Bridge Interaction Simulation and Damage Identification of a Bridge Using Responses Measured in a Passing Vehicle by Empirical Mode Decomposition Method

  AUTHORS: Shohel Rana, Md. Rifat Zaman, Md. Ibrahim Islam Ifty, Seyedali Mirmotalebi, Tahsin Tareque

  KEYWORDS: Structural Health Monitoring, Vibration-Based Damage Identification, Vehicle-Bridge Interaction, Finite Element Model, Empirical Mode Decomposition

  JOURNAL NAME: Open Journal of Civil Engineering, Vol.13 No.4, December 28, 2023

  ABSTRACT: To prevent early bridge failures, effective Structural Health Monitoring (SHM) is vital. Vibration-based damage assessment is a powerful tool in this regard, as it relies on changes in a structure’s dynamic characteristics as it degrades. By measuring the vibration response of a bridge due to passing vehicles, this approach can identify potential structural damage. This dissertation introduces a novel technique grounded in Vehicle-Bridge Interaction (VBI) to evaluate bridge health. It aims to detect damage by analyzing the response of passing vehicles, taking into account VBI. The theoretical foundation of this method begins with representing the bridge’s superstructure using a Finite Element Model and employing a half-car dynamic model to simulate the vehicle with suspension. Two sets of motion equations, one for the bridge and one for the vehicle are generated using the Finite Element Method, mode superposition, and D’Alembert’s principle. The combined dynamics are solved using the Newmark-beta method, accounting for road surface roughness. A new approach for damage identification based on the response of passing vehicles is proposed. The response is theoretically composed of vehicle frequency, bridge natural frequency, and a pseudo-frequency component related to vehicle speed. The Empirical Mode Decomposition (EMD) method is applied to decompose the signal into its constituent parts, and damage detection relies on the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component. This technique effectively identifies various damage scenarios considered in the study.