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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

    Malfunction Diagnosis of the GTCC System under All Operating Conditions Based on Exergy Analysis

    Xinwei Wang1,2,*, Ming Li1, Hankun Bing1, Dongxing Zhang1, Yuanshu Zhang1

    Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

    Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

  • Open Access

    ARTICLE

    Thermodynamic, Economic, and Environmental Analyses and Multi-Objective Optimization of Dual-Pressure Organic Rankine Cycle System with Dual-Stage Ejector

    Guowei Li1,*, Shujuan Bu2, Xinle Yang2, Kaijie Liang1, Zhengri Shao1, Xiaobei Song1, Yitian Tang3, Dejing Zong4

    Energy Engineering, Vol.121, No.12, pp. 3843-3874, 2024, DOI:10.32604/ee.2024.056195 - 22 November 2024

    Abstract A novel dual-pressure organic Rankine cycle system (DPORC) with a dual-stage ejector (DE-DPORC) is proposed. The system incorporates a dual-stage ejector that utilizes a small amount of extraction steam from the high-pressure expander to pressurize a large quantity of exhaust gas to perform work for the low-pressure expander. This innovative approach addresses condensing pressure limitations, reduces power consumption during pressurization, minimizes heat loss, and enhances the utilization efficiency of waste heat steam. A thermodynamic model is developed with net output work, thermal efficiency, and exergy efficiency (Wnet, ηt, ηex) as evaluation criteria, an economic model is established… More >

  • Open Access

    ARTICLE

    Rapid Parameter-Optimizing Strategy for Plug-and-Play Devices in DC Distribution Systems under the Background of Digital Transformation

    Zhi Li1, Yufei Zhao2, Yueming Ji2, Hanwen Gu2, Zaibin Jiao2,*

    Energy Engineering, Vol.121, No.12, pp. 3899-3927, 2024, DOI:10.32604/ee.2024.055899 - 22 November 2024

    Abstract By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement, information communication, and other fields, the digital DC distribution network can efficiently and reliably access Distributed Generator (DG) and Energy Storage Systems (ESS), exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play (PnP) operations. However, during device plug-in and -out processes, improper system parameters may lead to small-signal stability issues. Therefore, before executing PnP operations, conducting stability analysis and adjusting parameters swiftly is crucial. This study introduces a four-stage strategy for parameter optimization to enhance… 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

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

    Inna Bilous1, Dmytro Biriukov1, Dmytro Karpenko2, Tatiana Eutukhova2, Oleksandr Novoseltsev2,*, Volodymyr Voloshchuk1

    Energy Engineering, Vol.121, No.12, pp. 3617-3634, 2024, DOI:10.32604/ee.2024.051684 - 22 November 2024

    Abstract This article focuses on the challenges of modeling energy supply systems for buildings, encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings. Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material, such as for thermal upgrades, which consequently incurs additional economic costs. It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions, considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in… More > Graphic Abstract

    Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

  • Open Access

    ARTICLE

    Performance Analysis of Machine Learning-Based Intrusion Detection with Hybrid Feature Selection

    Mohammad Al-Omari1, Qasem Abu Al-Haija2,*

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1537-1555, 2024, DOI:10.32604/csse.2024.056257 - 22 November 2024

    Abstract More businesses are deploying powerful Intrusion Detection Systems (IDS) to secure their data and physical assets. Improved cyber-attack detection and prevention in these systems requires machine learning (ML) approaches. This paper examines a cyber-attack prediction system combining feature selection (FS) and ML. Our technique’s foundation was based on Correlation Analysis (CA), Mutual Information (MI), and recursive feature reduction with cross-validation. To optimize the IDS performance, the security features must be carefully selected from multiple-dimensional datasets, and our hybrid FS technique must be extended to validate our methodology using the improved UNSW-NB 15 and TON_IoT datasets. More >

  • Open Access

    ARTICLE

    An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

    Saad M. Darwish1,*, Abdul Rahman M. Sabri2, Dhafar Hamed Abd2, Adel A. Elzoghabi1

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1595-1624, 2024, DOI:10.32604/csse.2024.054615 - 22 November 2024

    Abstract The number of blogs and other forms of opinionated online content has increased dramatically in recent years. Many fields, including academia and national security, place an emphasis on automated political article orientation detection. Political articles (especially in the Arab world) are different from other articles due to their subjectivity, in which the author’s beliefs and political affiliation might have a significant influence on a political article. With categories representing the main political ideologies, this problem may be thought of as a subset of the text categorization (classification). In general, the performance of machine learning models… 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

    REVIEW

    A Systematic Review of Automated Classification for Simple and Complex Query SQL on NoSQL Database

    Nurhadi, Rabiah Abdul Kadir*, Ely Salwana Mat Surin, Mahidur R. Sarker*

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1405-1435, 2024, DOI:10.32604/csse.2024.051851 - 22 November 2024

    Abstract A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of data. It accumulates substantial volumes of data and employs advanced analytics to correlate data from diverse origins containing various forms of semi-structured, structured, and unstructured information. These systems use a flat architecture and run different types of data analytics. NoSQL databases are nontabular and store data in a different manner than the relational table. NoSQL databases come in various forms, including key-value pairs, documents, wide columns, and graphs, each based on its data model. They offer simpler scalability and generally outperform… More >

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