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  • Open Access

    ARTICLE

    Life-Cycle Bearing Capacity for Pre-Stressed T-beams Based on Full-Scale Destructive Test

    Yushan Ye1, Tao Gao1, Liankun Wang2, Junjie Ma2, Yingchun Cai2, Heng Liu2,*, Xiaoge Liu2

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 145-166, 2025, DOI:10.32604/sdhm.2024.053756 - 15 November 2024

    Abstract To investigate the evolution of load-bearing characteristics of pre-stressed beams throughout their service life and to provide a basis for accurately assessing the actual working state of damaged pre-stressed concrete T-beams, destructive tests were conducted on full-scale pre-stressed concrete beams. Based on the measurement and analysis of beam deflection, strain, and crack development under various loading levels during the research tests, combined with the verification coefficient indicators specified in the codes, the verification coefficients of bridges at different stages of damage can be examined. The results indicate that the T-beams experience complete, incomplete linear, and… More >

  • Open Access

    REVIEW

    Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

    Chao Zhang1, Shang-Xi Lai1, Hua-Ping Wang1,2,*

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 25-54, 2025, DOI:10.32604/sdhm.2024.053662 - 15 November 2024

    Abstract Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring (SHM) system, so as to provide a scientific basis for structural damage identification and dynamic model modification. In view of this, this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters. The paper primarily introduces data-driven modal parameter recognition methods… More >

  • Open Access

    ARTICLE

    Novel Methodologies for Preventing Crack Propagation in Steel Gas Pipelines Considering the Temperature Effect

    Nurlan Zhangabay1,*, Ulzhan Ibraimova2, Marco Bonopera3,*, Ulanbator Suleimenov1, Konstantin Avramov4, Maryna Chernobryvko4, Aigerim Yessengali1

    Structural Durability & Health Monitoring, Vol.19, No.1, pp. 1-23, 2025, DOI:10.32604/sdhm.2024.053391 - 15 November 2024

    Abstract Using the software ANSYS-19.2/Explicit Dynamics, this study performed finite-element modeling of the large-diameter steel pipeline cross-section for the Beineu-Bozoy-Shymkent gas pipeline with a non-through straight crack, strengthened by steel wire wrapping. The effects of the thread tensile force of the steel winding in the form of single rings at the crack edges and the wires with different winding diameters and pitches were also studied. The results showed that the strengthening was preferably executed at a minimum value of the thread tensile force, which was 6.4% more effective than that at its maximum value. The analysis… More >

  • Open Access

    ARTICLE

    Optimization of Phosphate Adsorption Using Activated Carbon Derived from Pangium edule Shell

    Rachmannu Ilham1, Fataty Kurnia Rahmah1, Nurul Faradilah Said2, Mohamad Buang Budiono2, Suprapto Suprapto1,*

    Journal of Renewable Materials, Vol.12, No.11, pp. 1895-1909, 2024, DOI:10.32604/jrm.2024.055602 - 22 November 2024

    Abstract This study investigated the efficiency of activated carbon from Pangium edule shells for removing phosphate from aqueous solution. The adsorption capacity of the synthesized activated carbon was determined to be 19.8392 mg g−1. Various isotherm models were used to analyze the adsorption process, Henry, Freundlich, SIP, and Halsey isotherm fitting showed r2 values close to 1.0. These isotherms indicated a combination of physisorption and chemisorption mechanisms, with heterogeneity and multilayer formation playing important roles. A pseudo-second-order model described the adsorption kinetics well, suggesting chemisorption as the dominant mechanism with an r2 value of 1.0 and a rate constant… More >

  • Open Access

    ARTICLE

    Energy-Efficient and Cost-Effective Approaches through Energy Modeling for Hotel Building

    Alya Penta Agharid1, Indra Permana2, Nitesh Singh1, Fujen Wang2,*, Susan Gustiyana2

    Energy Engineering, Vol.121, No.12, pp. 3549-3571, 2024, DOI:10.32604/ee.2024.056398 - 22 November 2024

    Abstract Hotel buildings are currently among the largest energy consumers in the world. Heating, ventilation, and air conditioning are the most energy-intensive building systems, accounting for more than half of total energy consumption. An energy audit is used to predict the weak points of a building’s energy use system. Various factors influence building energy consumption, which can be modified to achieve more energy-efficient strategies. In this study, an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year. Energy modeling is conducted by using Autodesk Revit 2025. It… More >

  • Open Access

    REVIEW

    Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods

    Daixuan Zhou1, Yujin Liu1, Xu Wang2, Fuxing Wang1, Yan Jia2,*

    Energy Engineering, Vol.121, No.12, pp. 3573-3616, 2024, DOI:10.32604/ee.2024.055853 - 22 November 2024

    Abstract With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. More > Graphic Abstract

    Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods

  • Open Access

    ARTICLE

    Impact of Different Rooftop Coverings on Photovoltaic Panel Temperature

    Aws Al-Akam1,*, Ahmed A. Abduljabbar2, Ali Jaber Abdulhamed1

    Energy Engineering, Vol.121, No.12, pp. 3761-3777, 2024, DOI:10.32604/ee.2024.055198 - 22 November 2024

    Abstract Photovoltaic (PV) panels are essential to the global transition towards sustainable energy, offering a clean, renewable source that reduces reliance on fossil fuels and mitigates climate change. High temperatures can significantly affect the performance of photovoltaic (PV) panels by reducing their efficiency and power output. This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic (PV) panels. It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels, considering the thermal performance and its implications for enhancing their overall performance and sustainability. The… More >

  • Open Access

    ARTICLE

    Photovoltaic Power Generation Power Prediction under Major Extreme Weather Based on VMD-KELM

    Yuxuan Zhao1,2,*, Bo Wang1, Shu Wang1, Wenjun Xu2, Gang Ma2

    Energy Engineering, Vol.121, No.12, pp. 3711-3733, 2024, DOI:10.32604/ee.2024.054032 - 22 November 2024

    Abstract The output of photovoltaic power stations is significantly affected by environmental factors, leading to intermittent and fluctuating power generation. With the increasing frequency of extreme weather events due to global warming, photovoltaic power stations may experience drastic reductions in power generation or even complete shutdowns during such conditions. The integration of these stations on a large scale into the power grid could potentially pose challenges to system stability. To address this issue, in this study, we propose a network architecture based on VMD-KELM for predicting the power output of photovoltaic power plants during severe weather… More >

  • Open Access

    REVIEW

    A Comprehensive Overview and Comparative Analysis on Deep Learning Models

    Farhad Mortezapour Shiri*, Thinagaran Perumal, Norwati Mustapha, Raihani Mohamed

    Journal on Artificial Intelligence, Vol.6, pp. 301-360, 2024, DOI:10.32604/jai.2024.054314 - 20 November 2024

    Abstract Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and artificial intelligence (AI), outperforming traditional ML methods, especially in handling unstructured and large datasets. Its impact spans across various domains, including speech recognition, healthcare, autonomous vehicles, cybersecurity, predictive analytics, and more. However, the complexity and dynamic nature of real-world problems present challenges in designing effective deep learning models. Consequently, several deep learning models have been developed to address different problems and applications. In this article, we conduct a comprehensive survey of various deep learning models, including Convolutional Neural Network (CNN), Recurrent… More >

  • Open Access

    ARTICLE

    Improving Smart Home Security via MQTT: Maximizing Data Privacy and Device Authentication Using Elliptic Curve Cryptography

    Zainatul Yushaniza Mohamed Yusoff1, Mohamad Khairi Ishak2,*, Lukman A. B. Rahim3, Mohd Shahrimie Mohd Asaari1

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1669-1697, 2024, DOI:10.32604/csse.2024.056741 - 22 November 2024

    Abstract The rapid adoption of Internet of Things (IoT) technologies has introduced significant security challenges across the physical, network, and application layers, particularly with the widespread use of the Message Queue Telemetry Transport (MQTT) protocol, which, while efficient in bandwidth consumption, lacks inherent security features, making it vulnerable to various cyber threats. This research addresses these challenges by presenting a secure, lightweight communication proxy that enhances the scalability and security of MQTT-based Internet of Things (IoT) networks. The proposed solution builds upon the Dang-Scheme, a mutual authentication protocol designed explicitly for resource-constrained environments and enhances it… More >

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