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1. Theoretical vehicle bridge interaction model for bridges with non-simply supported boundary conditions

   https://doi.org/https://doi.org/10.1016/j.engstruct.2020.111839  

   Zhenhua Shi, Nasim Uddin (May 2021, Engineering structures)

   null (Ed.)

   Theoretical vehicle bridge interaction (VBI) models have been widely studied for decades for the simply supported boundary condition but not for the other boundary conditions. This paper presents the mathematical models for several non-simply supported boundary conditions including both ends fixed, fixed simply supported, and one end fixed the other end free (cantilever) boundary condition. The closed-form solutions can be found under the assumption that the vehicle acceleration magnitude is far lower than the gravitational acceleration constant. The analytical solutions are then illustrated on a specific bridge example to compare the responses due to different bridge boundary conditions, and to study different vehicle parameter effects on extracting multiple bridge frequencies (five) from the vehicle responses. A signal drift phenomenon can be observed on the acceleration response of both the bridge and the vehicle, while a camel hump phenomenon can be observed on the Fast Fourier analysis of the vehicle acceleration signal. The parameter study shows that the vehicle frequency is preferred to be high due to the attenuation effect on the bridge frequencies that are higher than the vehicle frequency. The vehicle speed parameter is preferred to be low to reduce both the camel hump phenomenon and the vehicle acceleration magnitude, while both the vehicle mass and damping parameter have little effect on the multiple bridge frequencies extraction from the vehicle. Besides presenting the explicit solutions for calibrating other numerical models, this study also demonstrates the feasibility of the vehicle-based bridge health monitoring approach, as any bridge anomaly due to deterioration may be sensitively reflected on the bridge frequency list extracted from the vehicle response. 

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2. Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

   https://doi.org/10.3390/s18124207  

   Elhattab, Ahmed; Uddin, Nasim; OBrien, Eugene (December 2018, Sensors)

   Recently, drive-by bridge inspection has attracted increasing attention in the bridge monitoring field. A number of studies have given confidence in the feasibility of the approach to detect, quantify, and localize damages. However, the speed of the inspection truck represents a major obstacle to the success of this method. High speeds are essential to induce a significant amount of kinetic energy to stimulate the bridge modes of vibration. On the other hand, low speeds are necessary to collect more data and to attenuate the vibration of the vehicle due to the roughness of the road and, hence, magnify the bridge influence on the vehicle responses. This article introduces Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR) as a new technique, which possesses the ability to extract bridge dynamic properties from the responses of a vehicle that passes over the bridge at high speed. Stochastic Resonance (SR) is a phenomenon where feeble information such as weak signals can be amplified through the assistance of background noise. In this study, bridge vibrations that are present in the vehicle responses when it passes over the bridge are the feeble information while the noise counts for the effect of the road roughness on the vehicle vibration. UPSR is one of the SR models that has been chosen in this study for its suitability to extract the bridge vibration. The main contributions of this article are: (1) introducing a Frequency Independent-Stochastic Resonance model known as the FI-UPSR and (2) implementing this model to extract the bridge vibration from the responses of a fast passing vehicle. 

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3. Vibration-Theoretic Approach to Vulnerability Analysis of Nonlinear Vehicle Platoons

   https://doi.org/10.1109/TITS.2023.3278574  

   Wang, Pengcheng; Wu, Xinkai; He, Xiaozheng (October 2023, IEEE Transactions on Intelligent Transportation Systems)

   This research explores the inherent vulnerability of nonlinear vehicle platoons characterized by the oscillatory behavior triggered by external perturbations. The perturbation exerted on the vehicle platoon is regarded as an external force on an object. Following the mechanical vibration analysis in mechanics, this research proposes a vibration-theoretic approach that advances our understanding of platoon vulnerability from two aspects. First, the proposed approach introduces damping intensity to characterize vehicular platoon vulnerability, which divides platoon oscillations into two types, i.e., underdamped and overdamped. The damping intensity measures the platoon’s recovery strength in responding to perturbations. Second, the proposed approach can obtain the resonance frequency of a nonlinear vehicle platoon, where resonance amplifies platoon oscillation magnitude when the external perturbation frequency equals the platoon’s damping oscillation frequency. The main contribution of this research lies in the analytical derivation of the closed-form formulas of damping intensity and resonance frequency. In particular, the proposed approach formulates platoon dynamics under perturbation as a second-order non-homogeneous ordinary differential equation, enabling rigorous derivations and analyses for platoons with complicated nonlinear car-following behaviors. Through simulations built on real-world data, this paper demonstrates that an overdamped vehicle platoon is more robust against perturbations, and an underdamped platoon can be destabilized easily by exerting a perturbation at the platoon’s resonance frequency. The theoretical derivations and simulation results shed light on the design of reliable platooning control, either for human-driven or automated vehicles, to suppress the adverse effects of oscillations. 

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4. Bridge Monitoring Utilizing Smart Portable Sensing System

   https://doi.org/10.32548/RS.2018.004  

   Elhattab, Ahmed; Uddin, Nasim; OBrien, Eugene (October 2018, 27th ASNT Research Symposium)

   Natural Frequencies of structures is an elegant intrinsic property that is essential for many Civil Structural applications, as Structural Health Monitoring and Simulation Modeling. The physically tangible relation between the frequency of the structures and its dynamic characteristics was the impetus for using different time/frequency based methods to quantify this fundamental property. Unfortunately, the disruption effect of noise requires incorporating advanced sensors, that provide signals with a low noise-intensity, to accurately identify the fundamental frequencies of the structure. This article solves this bottleneck via exploiting the Stochastic Resonance (SR) phenomena to extract the fundamental frequencies of a bridge using an acceleration recorded by a conventional portable sensor as the sensor implemented in small portable accelerometer. The portable accelerometer device has an M9 motion coprocessor designed mainly for tracking human activities. Human activities have an exaggerated amplitude when it is compared to the structural responses. Therefore, if an iPhone device is used to record the response of the structure (for example a bridge) the structure response will be swamped by severe surrounding noise because of its small amplitude. Therefore, in this vein, the SR phenomena has been employed to use rather than suppress the noise to magnify the feeble bridge response in the recorded acceleration and hence identify the corresponding frequency. The fidelity of the proposed approach has been verified using the data of a field experiment. The bridge frequencies are identified first using conventional vibration analysis, thereafter, the portable accelerometer has been attached to the bridge rail to record the bridge vibration under the passing traffic. The recorded data has been processed using a new Developed Underdamped Pinning Stochastic Resonance (DUPSR) technique to quantify the bridge frequency. 

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5. Extraction of Bridge Fundamental Frequencies Utilizing a Smartphone MEMS Accelerometer

   https://doi.org/10.3390/s19143143  

   Elhattab, Ahmed; Uddin, Nasim; OBrien, Eugene (July 2019, Sensors)

   Smartphone MEMS (Micro Electrical Mechanical System) accelerometers have relatively low sensitivity and high output noise density. Therefore, it cannot be directly used to track feeble vibrations such as structural vibrations. This article proposes an effective increase in the sensitivity of the smartphone accelerometer utilizing the stochastic resonance (SR) phenomenon. SR is an approach where, counter-intuitively, feeble signals are amplified rather than overwhelmed by the addition of noise. This study introduces the 2D-frequency independent underdamped pinning stochastic resonance (2D-FI-UPSR) technique, which is a customized SR filter that enables identifying the frequencies of weak signals. To validate the feasibility of the proposed SR filter, an iPhone device is used to collect bridge acceleration data during normal traffic operation and the proposed 2D-FI-UPSR filter is used to process these data. The first four fundamental bridge frequencies are successfully identified from the iPhone data. In parallel to the iPhone, a highly sensitive wireless sensing network consists of 15 accelerometers (Silicon Designs accelerometers SDI-2012) is installed to validate the accuracy of the extracted frequencies. The measurement fidelity of the iPhone device is shown to be consistent with the wireless sensing network data with approximately 1% error in the first three bridge frequencies and 3% error in the fourth frequency. 

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