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  • Open Access

    ARTICLE

    Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

    Sabrina Meddah1,2,*, Sid Ahmed Tadjer3, Abdelhakim Idir4, Kong Fah Tee5,6,*, Mohamed Zinelabidine Doghmane1, Madjid Kidouche1

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 77-103, 2025, DOI:10.32604/sdhm.2024.053541 - 15 November 2024

    Abstract Maintaining the integrity and longevity of structures is essential in many industries, such as aerospace, nuclear, and petroleum. To achieve the cost-effectiveness of large-scale systems in petroleum drilling, a strong emphasis on structural durability and monitoring is required. This study focuses on the mechanical vibrations that occur in rotary drilling systems, which have a substantial impact on the structural integrity of drilling equipment. The study specifically investigates axial, torsional, and lateral vibrations, which might lead to negative consequences such as bit-bounce, chaotic whirling, and high-frequency stick-slip. These events not only hinder the efficiency of drilling… More >

  • Open Access

    ARTICLE

    Predominant Leptadenia pyrotechnica Alkali-Treated Fiber Composites: Characteristics Analysis

    Aruna M. Pugalenthi*, Khaoula Khlie

    Journal of Renewable Materials, Vol.12, No.11, pp. 1879-1893, 2024, DOI:10.32604/jrm.2024.055747 - 22 November 2024

    Abstract With growing environmental concerns and the depletion of oil reserves, the need to replace synthetic fibres with sustainable alternatives in composite materials has become increasingly urgent. This study investigates the potential of Leptadenia pyrotechnica fibre as a sustainable reinforcement material in hybrid composites alongside E-glass fibres. The primary objectives are to assess these hybrid composites’ mechanical properties, structural integrity, and performance. To achieve this, Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) were employed to analyze the microstructure and chemical composition of the composites. At the same time, mechanical testing focused on properties such… More >

  • Open Access

    ARTICLE

    Combined Wind-Storage Frequency Modulation Control Strategy Based on Fuzzy Prediction and Dynamic Control

    Weiru Wang1, Yulong Cao1,*, Yanxu Wang1, Jiale You1, Guangnan Zhang1, Yu Xiao2

    Energy Engineering, Vol.121, No.12, pp. 3801-3823, 2024, DOI:10.32604/ee.2024.055398 - 22 November 2024

    Abstract To ensure frequency stability in power systems with high wind penetration, the doubly-fed induction generator (DFIG) is often used with the frequency fast response control (FFRC) to participate in frequency response. However, a certain output power suppression amount (OPSA) is generated during frequency support, resulting in the frequency modulation (FM) capability of DFIG not being fully utilised, and the system’s unbalanced power will be increased during speed recovery, resulting in a second frequency drop (SFD) in the system. Firstly, the frequency response characteristics of the power system with DFIG containing FFRC are analysed. Then, based… More >

  • Open Access

    ARTICLE

    Modeling, Simulation, and Risk Analysis of Battery Energy Storage Systems in New Energy Grid Integration Scenarios

    Xiaohui Ye1,*, Fucheng Tan1, Xinli Song2, Hanyang Dai2, Xia Li2, Shixia Mu2, Shaohang Hao2

    Energy Engineering, Vol.121, No.12, pp. 3689-3710, 2024, DOI:10.32604/ee.2024.055200 - 22 November 2024

    Abstract Energy storage batteries can smooth the volatility of renewable energy sources. The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system (BESS). However, the current modeling of grid-connected BESS is overly simplistic, typically only considering state of charge (SOC) and power constraints. Detailed lithium (Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions. Additionally, there is a lack of real-time batteries risk assessment frameworks. To address these issues, in this… More >

  • Open Access

    ARTICLE

    Heuristic-Based Optimal Load Frequency Control with Offsite Backup Controllers in Interconnected Microgrids

    Aijia Ding, Tingzhang Liu*

    Energy Engineering, Vol.121, No.12, pp. 3735-3759, 2024, DOI:10.32604/ee.2024.054687 - 22 November 2024

    Abstract The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources. This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative (FOPID) controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration. To improve load frequency control, the proposed controllers are applied to a two-area interconnected microgrid system incorporating diverse energy sources, such as wind turbines, photovoltaic cells, diesel generators, and various storage technologies. A novel meta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers. The efficacy… More >

  • Open Access

    ARTICLE

    Software Cost Estimation Using Social Group Optimization

    Sagiraju Srinadhraju*, Samaresh Mishra, Suresh Chandra Satapathy

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1641-1668, 2024, DOI:10.32604/csse.2024.055612 - 22 November 2024

    Abstract This paper introduces the integration of the Social Group Optimization (SGO) algorithm to enhance the accuracy of software cost estimation using the Constructive Cost Model (COCOMO). COCOMO’s fixed coefficients often limit its adaptability, as they don’t account for variations across organizations. By fine-tuning these parameters with SGO, we aim to improve estimation accuracy. We train and validate our SGO-enhanced model using historical project data, evaluating its performance with metrics like the mean magnitude of relative error (MMRE) and Manhattan distance (MD). Experimental results show that SGO optimization significantly improves the predictive accuracy of software cost More >

  • Open Access

    REVIEW

    A Systematic Literature Review on Blockchain Consensus Mechanisms’ Security: Applications and Open Challenges

    Muhammad Muntasir Yakubu1,2,*, Mohd Fadzil B Hassan1,3, Kamaluddeen Usman Danyaro1, Aisha Zahid Junejo4, Muhammed Siraj5, Saidu Yahaya1, Shamsuddeen Adamu1, Kamal Abdulsalam6

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1437-1481, 2024, DOI:10.32604/csse.2024.054556 - 22 November 2024

    Abstract This study conducts a systematic literature review (SLR) of blockchain consensus mechanisms, an essential protocols that maintain the integrity, reliability, and decentralization of distributed ledger networks. The aim is to comprehensively investigate prominent mechanisms’ security features and vulnerabilities, emphasizing their security considerations, applications, challenges, and future directions. The existing literature offers valuable insights into various consensus mechanisms’ strengths, limitations, and security vulnerabilities and their real-world applications. However, there remains a gap in synthesizing and analyzing this knowledge systematically. Addressing this gap would facilitate a structured approach to understanding consensus mechanisms’ security and vulnerabilities comprehensively. The… More >

  • Open Access

    ARTICLE

    DAUNet: Detail-Aware U-Shaped Network for 2D Human Pose Estimation

    Xi Li1,2, Yuxin Li2, Zhenhua Xiao3,*, Zhenghua Huang1, Lianying Zou1

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3325-3349, 2024, DOI:10.32604/cmc.2024.056464 - 18 November 2024

    Abstract Human pose estimation is a critical research area in the field of computer vision, playing a significant role in applications such as human-computer interaction, behavior analysis, and action recognition. In this paper, we propose a U-shaped keypoint detection network (DAUNet) based on an improved ResNet subsampling structure and spatial grouping mechanism. This network addresses key challenges in traditional methods, such as information loss, large network redundancy, and insufficient sensitivity to low-resolution features. DAUNet is composed of three main components. First, we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce… More >

  • Open Access

    ARTICLE

    Adaptive Video Dual Domain Watermarking Scheme Based on PHT Moment and Optimized Spread Transform Dither Modulation

    Yucheng Liang1,2,*, Ke Niu1,2,*, Yingnan Zhang1,2, Yifei Meng1,2, Fangmeng Hu1,2

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2457-2492, 2024, DOI:10.32604/cmc.2024.056438 - 18 November 2024

    Abstract To address the challenges of video copyright protection and ensure the perfect recovery of original video, we propose a dual-domain watermarking scheme for digital video, inspired by Robust Reversible Watermarking (RRW) technology used in digital images. Our approach introduces a parameter optimization strategy that incrementally adjusts scheme parameters through attack simulation fitting, allowing for adaptive tuning of experimental parameters. In this scheme, the low-frequency Polar Harmonic Transform (PHT) moment is utilized as the embedding domain for robust watermarking, enhancing stability against simulation attacks while implementing the parameter optimization strategy. Through extensive attack simulations across various… More >

  • Open Access

    ARTICLE

    TLERAD: Transfer Learning for Enhanced Ransomware Attack Detection

    Isha Sood*, Varsha Sharma

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2791-2818, 2024, DOI:10.32604/cmc.2024.055463 - 18 November 2024

    Abstract Ransomware has emerged as a critical cybersecurity threat, characterized by its ability to encrypt user data or lock devices, demanding ransom for their release. Traditional ransomware detection methods face limitations due to their assumption of similar data distributions between training and testing phases, rendering them less effective against evolving ransomware families. This paper introduces TLERAD (Transfer Learning for Enhanced Ransomware Attack Detection), a novel approach that leverages unsupervised transfer learning and co-clustering techniques to bridge the gap between source and target domains, enabling robust detection of both known and unknown ransomware variants. The proposed method More >

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