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  • Open Access

    ARTICLE

    Dynamic Response Impact of Vehicle Braking on Simply Supported Beam Bridges with Corrugated Steel Webs Based on Vehicle-Bridge Coupled Vibration Analysis

    Yan Wang*, Siwen Li, Na Wei

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3467-3493, 2024, DOI:10.32604/cmes.2024.046454

    Abstract A novel approach for analyzing coupled vibrations between vehicles and bridges is presented, taking into account spatiotemporal effects and mechanical phenomena resulting from vehicle braking. Efficient modeling and solution of bridge vibrations induced by vehicle deceleration are realized using this method. The method’s validity and reliability are substantiated through numerical examples. A simply supported beam bridge with a corrugated steel web is taken as an example and the effects of parameters such as the initial vehicle speed, braking acceleration, braking location, and road surface roughness on the mid-span displacement and impact factor of the bridge are analyzed. The results show… More >

  • Open Access

    ARTICLE

    Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

    Yifan Huang1, Zikang Zhou1,2, Mingyu Li1, Xuedong Luo1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947

    Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of determination (R2), root mean square… More >

  • Open Access

    REVIEW

    A Review of the Tuned Mass Damper Inerter (TMDI) in Energy Harvesting and Vibration Control: Designs, Analysis and Applications

    Xiaofang Kang1,2,*, Qiwen Huang1, Zongqin Wu1, Jianjun Tang1, Xueqin Jiang1, Shancheng Lei3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2361-2398, 2024, DOI:10.32604/cmes.2023.043936

    Abstract Tuned mass damper inerter (TMDI) is a device that couples traditional tuned mass dampers (TMD) with an inertial device. The inertial device produces resistance proportional to the relative acceleration at its two ends through its “inertial” constant. Due to its unique mechanical properties, TMDI has received widespread attention and application in the past twenty years. As different configurations are required in different practical situations, TMDI is still active in the research on vibration control and energy harvesting in structures. This paper provides a comprehensive review of the research status of TMDI. This work first examines the generation and important vibration… More >

  • Open Access

    ARTICLE

    Prediction of Sound Transmission Loss of Vehicle Floor System Based on 1D-Convolutional Neural Networks

    Cheng Peng1, Siwei Cheng2, Min Sun1, Chao Ren1, Jun Song1, Haibo Huang2,*

    Sound & Vibration, Vol.58, pp. 25-46, 2024, DOI:10.32604/sv.2024.046940

    Abstract The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package… More >

  • Open Access

    ARTICLE

    Nonlinear Flap-Wise Vibration Characteristics of Wind Turbine Blades Based on Multi-Scale Analysis Method

    Qifa Lang, Yuqiao Zheng*, Tiancai Cui, Chenglong Shi, Heyu Zhang

    Energy Engineering, Vol.121, No.2, pp. 483-498, 2024, DOI:10.32604/ee.2023.042437

    Abstract This work presents a novel approach to achieve nonlinear vibration response based on the Hamilton principle. We chose the 5-MW reference wind turbine which was established by the National Renewable Energy Laboratory (NREL), to research the effects of the nonlinear flap-wise vibration characteristics. The turbine wheel is simplified by treating the blade of a wind turbine as an Euler-Bernoulli beam, and the nonlinear flap-wise vibration characteristics of the wind turbine blades are discussed based on the simplification first. Then, the blade’s large-deflection flap-wise vibration governing equation is established by considering the nonlinear term involving the centrifugal force. Lastly, it is… More >

  • Open Access

    ARTICLE

    Ice-Induced Vibrational Response of Single-Pile Offshore Wind-Turbine Foundations

    Zhoujie Zhu1, Gang Wang1, Qingquan Liu1, Guojun Wang2, Rui Dong2, Dayong Zhang2,3,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 625-639, 2024, DOI:10.32604/fdmp.2023.042128

    Abstract Important challenges must be addressed to make wind turbines sustainable renewable energy sources. A typical problem concerns the design of the foundation. If the pile diameter is larger than that of the jacket platform, traditional mechanical models cannot be used. In this study, relying on the seabed soil data of an offshore wind farm, the m-method and the equivalent embedded method are used to address the single-pile wind turbine foundation problem for different pile diameters. An approach to determine the equivalent pile length is also proposed accordingly. The results provide evidence for the effectiveness and reliability of the model based… More >

  • Open Access

    ARTICLE

    Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

    Longteng Liang1,2,3, Zhouquan Feng2,4,*, Hongyi Zhang2,4, Zhengqing Chen2,4, Changzhao Qian1,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2403-2419, 2024, DOI:10.32604/cmes.2023.031260

    Abstract Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to their exceptional damping performance and durability. However, the existing constitutive models present challenges to the widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA) software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing a new constitutive model that is both easily understandable and user-friendly for FEA software. By utilizing numerical results obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture the nonlinear behavior of ECDs. The effectiveness… More >

  • Open Access

    ARTICLE

    Fault Identification for Shear-Type Structures Using Low-Frequency Vibration Modes

    Cuihong Li1, Qiuwei Yang2,3,*, Xi Peng2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2769-2791, 2024, DOI:10.32604/cmes.2023.030908

    Abstract Shear-type structures are common structural forms in industrial and civil buildings, such as concrete and steel frame structures. Fault diagnosis of shear-type structures is an important topic to ensure the normal use of structures. The main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage assessment. However, for many shear-type structures, it is difficult to obtain accurate FEM. In order to avoid finite element modeling, a model-free method for diagnosing shear structure defects is developed in this paper. This method only needs to measure a few low-order vibration modes of the structure.… More >

  • Open Access

    ARTICLE

    Prediction of Damping Capacity Demand in Seismic Base Isolators via Machine Learning

    Ayla Ocak1, Ümit Işıkdağ2, Gebrail Bekdaş1,*, Sinan Melih Nigdeli1, Sanghun Kim3, Zong Woo Geem4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2899-2924, 2024, DOI:10.32604/cmes.2023.030418

    Abstract Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures. The base isolators may lose their damping capacity over time due to environmental or dynamic effects. This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-term isolator life. In this study, an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time. With the developed model, the required damping capacity of the isolator structure was estimated and compared… More >

  • Open Access

    ARTICLE

    Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

    Qixin Lan1, Binqiang Chen1,*, Bin Yao1, Wangpeng He2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2825-2844, 2024, DOI:10.32604/cmes.2023.030378

    Abstract The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the tool will generate significant noise and vibration, negatively impacting the accuracy of the forming and the surface integrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wear state and promptly replace any heavily worn tools to guarantee the quality of the cutting. The conventional tool wear monitoring models, which are based on machine learning, are specifically built for the intended cutting conditions. However, these models require retraining when the cutting conditions undergo any… More >

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