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  • Open Access

    ARTICLE

    Two-Hop Delay-Aware Energy Efficiency Resource Allocation in Space-Air-Ground Integrated Smart Grid Network

    Qinghai Ou1, Min Yang1, Jingcai Kong1, Yang Yang2,*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2429-2447, 2025, DOI:10.32604/cmc.2025.062067 - 16 April 2025

    Abstract The lack of communication infrastructure in remote regions presents significant obstacles to gathering data from smart power sensors (SPSs) in smart grid networks. In such cases, a space-air-ground integrated network serves as an effective emergency solution. This study addresses the challenge of optimizing the energy efficiency of data transmission from SPSs to low Earth orbit (LEO) satellites through unmanned aerial vehicles (UAVs), considering both effective capacity and fronthaul link capacity constraints. Due to the non-convex nature of the problem, the objective function is reformulated, and a delay-aware energy-efficient power allocation and UAV trajectory design (DEPATD)… More >

  • Open Access

    ARTICLE

    Prediction and Comparative Analysis of Rooftop PV Solar Energy Efficiency Considering Indoor and Outdoor Parameters under Real Climate Conditions Factors with Machine Learning Model

    Gökhan Şahin1,*, Ihsan Levent2, Gültekin Işık2, Wilfried van Sark1, Sabir Rustemli3

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1215-1248, 2025, DOI:10.32604/cmes.2025.063193 - 11 April 2025

    Abstract This research investigates the influence of indoor and outdoor factors on photovoltaic (PV) power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and improving renewable energy efficiency. To predict plant efficiency, nineteen variables are analyzed, consisting of nine indoor photovoltaic panel characteristics (Open Circuit Voltage (Voc), Short Circuit Current (Isc), Maximum Power (Pmpp), Maximum Voltage (Umpp), Maximum Current (Impp), Filling Factor (FF), Parallel Resistance (Rp), Series Resistance (Rs), Module Temperature) and ten environmental factors (Air Temperature, Air Humidity, Dew Point, Air Pressure, Irradiation, Irradiation Propagation, Wind Speed, Wind… More >

  • Open Access

    REVIEW

    Progress in the Understanding and Modeling of Cavitation and Related Applications

    Jianying Li1,2,*, Donglai Li1,2, Tiefeng Li1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.3, pp. 445-470, 2025, DOI:10.32604/fdmp.2025.062337 - 01 April 2025

    Abstract Hydrodynamic cavitation, as an efficient technique applied in many physical and chemical treatment methods, has been widely used by various industries and in several technological fields. Relevant generators, designed with specific structures and parameters, can produce cavitation effects, thereby enabling effective treatment and reasonable transformation of substances. This paper reviews the design principles, performance, and practical applications associated with different types of cavitation generators, aiming to provide theoretical support for the optimization of these systems. It systematically analyzes the underpinning mechanisms and the various factors influencing the cavitation phenomena, also conducting a comparative analysis of More > Graphic Abstract

    Progress in the Understanding and Modeling of Cavitation and Related Applications

  • Open Access

    ARTICLE

    Enhancing LoRaWAN Sensor Networks: A Deep Learning Approach for Performance Optimizing and Energy Efficiency

    Maram Alkhayyal*, Almetwally M. Mostafa

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1079-1100, 2025, DOI:10.32604/cmc.2025.061836 - 26 March 2025

    Abstract The rapid expansion of the Internet of Things (IoT) has led to the widespread adoption of sensor networks, with Long-Range Wide-Area Networks (LoRaWANs) emerging as a key technology due to their ability to support long-range communication while minimizing power consumption. However, optimizing network performance and energy efficiency in dynamic, large-scale IoT environments remains a significant challenge. Traditional methods, such as the Adaptive Data Rate (ADR) algorithm, often fail to adapt effectively to rapidly changing network conditions and environmental factors. This study introduces a hybrid approach that leverages Deep Learning (DL) techniques, namely Long Short-Term Memory… More >

  • Open Access

    ARTICLE

    Innovative Mechanical Ventilation Control for Enhanced Indoor Air Quality and Energy Efficiency

    Giovanni Miracco1,*, Francesco Nicoletti1, Vittorio Ferraro2, Dimitrios Kaliakatsos1

    Energy Engineering, Vol.122, No.3, pp. 861-883, 2025, DOI:10.32604/ee.2025.060750 - 07 March 2025

    Abstract Indoor air quality (IAQ) is often overlooked, yet a poorly maintained environment can lead to significant health issues and reduced concentration and productivity in work or educational settings. This study presents an innovative control system for mechanical ventilation specifically designed for university classrooms, with the dual goal of enhancing IAQ and increasing energy efficiency. Two classrooms with distinct construction characteristics were analyzed: one with exterior walls and windows, and the other completely underground. For each classroom, a model was developed using DesignBuilder software, which was calibrated with experimental data regarding CO₂ concentration, temperature, and relative… More >

  • Open Access

    ARTICLE

    Evaluation Model for Energy Efficiency of Factory Workshop Based on DSR and Fuzzy Borda

    Shengjie Yang1,2, Zijian Zhu1,*, Xu Ouyang3

    Energy Engineering, Vol.122, No.3, pp. 1073-1092, 2025, DOI:10.32604/ee.2025.060293 - 07 March 2025

    Abstract In the context of advancing towards dual carbon goals, numerous factories are actively engaging in energy efficiency upgrades and transformations. To accurately pinpoint energy efficiency bottlenecks within factories and prioritize renovation sequences, it is crucial to conduct comprehensive evaluations of the energy performance across various workshops. Therefore, this paper proposes an evaluation model for workshop energy efficiency based on the drive-state-response (DSR) framework combined with the fuzzy BORDA method. Firstly, an in-depth analysis of the relationships between different energy efficiency indicators was conducted. Based on the DSR model, evaluation criteria were selected from three dimensions—drive… More >

  • Open Access

    ARTICLE

    Industrial Untapped Rotational Kinetic Energy Assessment for Sustainable Energy Recycling

    See Wei Jing, Md Tanjil Sarker*, Gobbi Ramasamy*, Siva Priya Thiagarajah, Fazlul Aman

    Energy Engineering, Vol.122, No.3, pp. 905-927, 2025, DOI:10.32604/ee.2025.058916 - 07 March 2025

    Abstract Electrical energy can be harvested from the rotational kinetic energy of moving bodies, consisting of both mechanical and kinetic energy as a potential power source through electromagnetic induction, similar to wind energy applications. In industries, rotational bodies are commonly present in operations, yet this kinetic energy remains untapped. This research explores the energy generation characteristics of two rotational body types, disk-shaped and cylinder-shaped under specific experimental setups. The hardware setup included a direct current (DC) motor driver, power supply, DC generator, mechanical support, and load resistance, while the software setup involved automation testing tools and… More >

  • Open Access

    ARTICLE

    Quantum Inspired Adaptive Resource Management Algorithm for Scalable and Energy Efficient Fog Computing in Internet of Things (IoT)

    Sonia Khan1, Naqash Younas2, Musaed Alhussein3, Wahib Jamal Khan2, Muhammad Shahid Anwar4,*, Khursheed Aurangzeb3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2641-2660, 2025, DOI:10.32604/cmes.2025.060973 - 03 March 2025

    Abstract Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks. However, existing methods often fail in dynamic and high-demand environments, leading to resource bottlenecks and increased energy consumption. This study aims to address these limitations by proposing the Quantum Inspired Adaptive Resource Management (QIARM) model, which introduces novel algorithms inspired by quantum principles for enhanced resource allocation. QIARM employs a quantum superposition-inspired technique for multi-state resource representation and an adaptive learning component to adjust resources in real time dynamically. In addition, an energy-aware scheduling module minimizes power More >

  • Open Access

    ARTICLE

    Energy Efficiency of a Solar Green Building Using Bio-Sourced Materials for Indoor Temperature and Humidity Optimization

    Soumia Mounir1,2,3,*, Youssef Maaloufa1,2,3, Abdelhamid Khabbazi2, Elina Mohd Husini4, Nurul Syala Abdul Latip4, Yakubu Aminu Dodo5,6, Rime EL Harrouni2,7, Mina Amazal3, Asma Souidi3, Malika Atigui3, Ahmed Aharoune3

    Energy Engineering, Vol.122, No.1, pp. 41-62, 2025, DOI:10.32604/ee.2024.057125 - 27 December 2024

    Abstract A clean environment with low carbon emissions is the goal of research on the development of green and sustainable buildings that use bio-sourced materials in conjunction with solar energy to create more sustainable cities. This is particularly true in Africa, where there aren’t many studies on the topic. The current study suggests a 90 m2 model of a sustainable building in a dry climate that is movable to address the issue of housing in remote areas, ensures comfort in harsh weather conditions, uses solar renewable resources—which are plentiful in Africa—uses bio-sourced materials, and examines how these… More > Graphic Abstract

    Energy Efficiency of a Solar Green Building Using Bio-Sourced Materials for Indoor Temperature and Humidity Optimization

  • 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

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