Search Results (156)

The growing need for high-efficiency and reliable propulsion systems in naval applications, particularly within the evolving landscape of submarine warfare, has led to an increased interest in multiphase Permanent Magnet AC motors. This study presents a modelling and simulation approach for a 3MW, seventeen-phase Permanent Magnet AC motor designed for submarine propulsion, integrating an AI-based drive control system. Despite the advantages of multiphase motors, such as higher power density and enhanced fault tolerance, significant challenges remain in achieving precise torque and variable speed, especially for externally mounted motors operating under deep-sea conditions. Existing control strategies often struggle with the inherent nonlinearities, unmodelled dynamics, and extreme environmental variations (e.g., pressure, temperature affecting oil viscosity and motor parameters) characteristic of such demanding deep-sea applications, leading to suboptimal performance and compromised reliability. Addressing this gap, this research investigates advanced control methodologies to enhance the performance of such motors. A MATLAB/Simulink framework was developed to model the motor, whose drive system leverages an AI-optimised dual fuzzy-PID controller refined using the Harmony Search Algorithm. Additionally, a combination of Indirect Field-Oriented Control (IFOC) and Space Vector PWM strategies are implemented to optimise inverter switching sequences for precise output modulation. Simulation results demonstrate significant improvements in torque response and control accuracy, validating the efficacy of the proposed system. The results highlight the role of AI-based propulsion systems in revolutionising submarine manoeuvrability and energy efficiency. In particular, during a test case involving a speed transition from 75 RPM to 900 RPM, the proposed AI-based controller achieves a near-zero overshoot compared to an initial control scheme that exhibits 75.89% overshoot. Full article

This research develops a dual physics-based machine learning system to forecast fuel consumption and CO₂ emissions for a 100 m oil tanker across six operational scenarios: Original, Paint, Advanced Propeller, Fin, Bulbous Bow, and Combined. The combination of hydrodynamic calculations with Monte Carlo simulations provides a solid foundation for training machine learning models, particularly in cases where dataset restrictions are present. The XGBoost model demonstrated superior performance compared to Support Vector Regression, Gaussian Process Regression, Random Forest, and Shallow Neural Network models, achieving near-zero prediction errors that closely matched physics-based calculations. The physics-based analysis demonstrated that the Combined scenario, which combines hull coatings with bulbous bow modifications, produced the largest fuel consumption reduction (5.37% at 15 knots), followed by the Advanced Propeller scenario. The results demonstrate that user inputs (e.g., engine power: 870 kW, speed: 12.7 knots) match the Advanced Propeller scenario, followed by Paint, which indicates that advanced propellers or hull coatings would optimize efficiency. The obtained insights help ship operators modify their operational parameters and designers select essential modifications for sustainable operations. The model maintains its strength at low speeds, where fuel consumption is minimal, making it applicable to other oil tankers. The hybrid approach provides a new tool for maritime efficiency analysis, yielding interpretable results that support International Maritime Organization objectives, despite starting with a limited dataset. The model requires additional research to enhance its predictive accuracy using larger datasets and real-time data collection, which will aid in achieving global environmental stewardship. Full article

This technical report presents a compelling case for the use of very-high-power, very-short-duration (VHPSD) radiofrequency ablation as a promising and efficient strategy for treating symptomatic premature ventricular contractions (PVCs) originating from the right ventricular outflow tract (RVOT). The patient with frequent, symptomatic PVCs and a 24% burden underwent successful ablation using a 90 W/4 s recipe via the QDOT MICRO™ catheter. The procedure resulted in immediate and sustained elimination of PVCs, with only 4 s of ablation time, near-zero fluoroscopy, no complications, and no PVC recurrence at 6 months. VHPSD ablation, though originally developed for atrial fibrillation, demonstrated remarkable procedural efficiency, precision, and lesion efficacy in this case. Compared to standard power, long-duration (SPLD) ablation, VHPSD offers the potential to significantly reduce procedural time, minimize tissue edema, and lower complication risk, particularly advantageous in anatomically challenging areas or in situations where maintaining stable catheter contact for extended periods is difficult or unfeasible. This technical report suggests the transformative potential of VHPSD as a first-line ablation strategy for RVOT-PVCs, provided careful mapping and appropriate technique are used. It underscores the need for further prospective studies to validate its broader safety, efficacy, and role in PVC management, particularly in cases involving intramural origins. Full article

Cloud computing has witnessed widespread adoption across numerous sectors, primarily due to its substantial storage capacity and powerful computational resources. In this context, secure data sharing in cloud environments is critically important. Identity-based broadcast proxy re-encryption (IB-BPRE) has emerged as a promising solution; however, existing IB-BPRE schemes lack dynamic functionality—specifically, the ability to support user revocation and addition without updating re-encryption keys. Consequently, data owners must frequently reset and distribute these keys in response to user membership changes, leading to increased system complexity and communication overhead. In this paper, we propose an identity-based broadcast proxy re-encryption scheme with dynamic functionality (IB-BPRE-DF) to address this challenge. The proposed scheme utilizes a symmetric design of re-encryption keys to enable dynamic user updates while preserving a constant re-encryption key size. Furthermore, IB-BPRE-DF is constructed under the $(f,g,F)$-GDDHE assumption and achieves semantic security in the random oracle model. Performance evaluations demonstrate that IB-BPRE-DF significantly reduces both the communication overhead (by maintaining a constant size for the re-encryption key and re-encrypted ciphertext) and the computational burden (with near-zero computational cost for generating the re-encryption key) for resource-constrained users. This work provides a practical and scalable cryptographic solution for secure and efficient data sharing in dynamic cloud environments. Full article

To extend the spectral utilisation of In₂S₃, an In₂S₃/C₃N₄ nanocomposite was prepared. The effects of different sulphur sources, electrodes, and bias voltages on the optoelectronic performance were examined. Photoelectric properties in response to light sources with wavelengths of 405, 532, 650, 780, 808, 980, and 1064 nm were investigated using Au electrodes and the carbon electrodes with 5B pencil drawings. This study shows that the aggregation states of the In₂S₃/C₃N₄ nanocomposite possess photocurrent switching responses in the broadband region of the light spectrum. Combining two types of partially visible light-absorbing material extends utilisation to the near-infrared region. Impurities or defects embody an electron-donating effect. Since the energy levels of defects or impurities with an electron-donating effect are close to the conduction band, low-energy lights (especially NIR) can be utilised. The non-equilibrium carrier concentration (photogenerated electrons) of the nanocomposites increases significantly under NIR photoexcitation conditions. Thus, photoconductive behaviour is manifested. A good photoelectric signal was still measured when zero bias was applied. This demonstrates self-powered photoelectric response characteristics. Different sulphur sources significantly affect the photoelectric performance, suggesting that they create different defects that affect charge transport and base current noise. It is believed that interfacial interactions in the In₂S₃/C₃N₄ nanocomposite create a built-in electric field that enhances the separation and transfer of electrons and holes produced by light stimulation. The presence of the built-in electric field also leads to energy band bending, which facilitates the utilisation of the light with longer wavelengths. This study provides a reference for multidisciplinary applications. Full article

This study evaluates four hybrid infrastructure scenarios for supporting battery electric buses (BEBs) and fuel cell electric buses (FCEBs), analyzing different combinations of grid power, solar energy, battery storage, and fuel cell systems. A multi-stage framework—comprising energy demand forecasting, infrastructure capacity planning, and multi-criteria decision-making (MCDM) evaluation incorporating total cost of ownership (TCO), carbon emissions, and energy resilience—was developed and applied to a real-world transit depot. The results highlight critical trade-offs between financial, environmental, and operational objectives. The limited rooftop solar configuration, integrating solar energy through a Solar Power Purchase Agreement (SPPA), emerges as the most cost-effective near-term solution. Offsite solar with onsite large-scale battery storage and offsite solar with fuel cell integration achieve greater sustainability and resilience, but they face substantial cost barriers. The analysis underscores the importance of balancing investment, emissions reduction, and resilience in planning zero-emission bus fleets. Full article

Islanded microgrids commonly use droop control methods for autonomous power distribution; however, this approach causes system frequency deviation when common loads change. This deviation can be eliminated using secondary control methods, but the core of this approach is to generate compensation values equal to the offset amount to add to the controller, thereby eliminating deviations from rated values. Such a mechanism can actually achieve the same effect by setting power reference values within the droop control method. The power references within the controller need to be adjusted dynamically, and they are associated with common load variations. Therefore, establishing a fitting relationship between the adjustment of power reference and changes in common loads can achieve better frequency regulation, keeping the system frequency operating within rated frequency ranges. These two types of data are correlated, however, due to physical parameters, the fitting between them is not strictly fixed in a mathematical sense. Thus, to find their interconnected relationships, using intelligent methods becomes crucial. This paper proposes a shallow neural network-based method to achieve fitting relationships. Moreover, to address power inputs with zero values, an input enhancement method is proposed to prevent potential gradient vanishing and ineffective learning problems. Thus, through precise matching between power commands and load consumption, the system frequency can be maintained near rated values. Various simulation scenarios demonstrate the feasibility and effectiveness of the proposed method. Full article

This review paper presents an overview of fuel cell electrochemical systems that can be used for clean large-scale power generation and energy storage as global energy concerns regarding emissions and greenhouse gases escalate. The fundamental thermochemical and operational principles of fuel cell power generation and electrolyzer technologies are discussed with a focus on high-temperature solid oxide fuel cells (SOFCs) and solid oxide electrolysis cells (SOECs) that are best suited for grid scale energy generation. SOFCs and SOECs share similar promising characteristics and have the potential to revolutionize energy conversion and storage due to improved energy efficiency and reduced carbon emissions. Electrochemical and thermodynamic foundations are presented while exploring energy conversion mechanisms, electric parameters, and efficiency in comparison with conventional power generation systems. Methods of converting hydrocarbon fuels to chemicals that can serve as fuel cell fuels are also presented. Key fuel cell challenges are also discussed, including degradation, thermal cycling, and long-term stability. The latest advancements, including in materials selection research, design, and manufacturing methods, are also presented, as they are essential for unlocking the full potential of these technologies and achieving a sustainable, near zero-emission energy future. Full article

The increasing global demand for clean energy and sustainable industrial processes necessitates innovative approaches to energy production and chemical synthesis. This study proposed and simulated an innovative integrated system for the co-production of power, hydrogen, and dimethyl ether (DME), combining the high-efficiency Allam–Fetvedt cycle with co-electrolysis and indirect DME synthesis. The Allam–Fetvedt cycle generated electricity while capturing CO₂, which, along with water, was used in solid oxide electrolyzers (SOEs) to produce syngas via co-electrolysis. The resulting syngas was converted to methanol and subsequently to DME. Aspen HYSYS was used to model and simulate the process, and heat/mass integration strategies were implemented to reduce energy demand and optimize resource utilization. The proposed integrated process enabled an annual production of 980,021 metric tons of DME, 189,435 metric tons of hydrogen, and 7698.27 metric tons of methanol. The energy efficiency of the Allam–Fetvedt cycle reached 55%, and heat integration reduced the system’s net energy demand by 14.22%. Despite the high energy needs of the electrolyzer system (81.28% of net energy), the overall energy requirement remained competitive with conventional methods. Carbon emissions per kilogram of DME were reduced from 1.16 to 0.77 kg CO₂ through heat integration and can be further minimized to 0.0308 kg CO₂/kg DME (near zero) with renewable electrification. Results demonstrated that 96% of CO₂ was recycled within the Allam–Fetvedt cycle, and the rest (the 4% of CO₂) was captured and converted to syngas, achieving net-zero carbon emissions. This work presents a scalable and sustainable pathway for integrated clean energy and chemical production, advancing toward industrial net-zero targets. Full article

Supercritical oxy-fuel combustion, which allows for the high efficiency of power generation with near-zero CO₂ emissions, is considered a promising method to reduce the carbon footprint in the power energy sector. One of the problems in the widespread use of oxy-fuel combustion is a lack of comparative studies on the existing oxy-fuel combustion kinetic mechanisms depending on mixture composition, which complicates the choice of a kinetic mechanism for modeling oxy-fuel combustion. In this paper, a comparative verification of the kinetic mechanisms of GRI-Mech 3.0, UoS sCO₂ 2.0, OXY-NG, and Skeletal was performed using published experimental data on the ignition delay time of methane under conditions of oxy-fuel combustion. A comparative numerical study of the kinetic mechanisms in the wide range of pressures, CO₂ mass fractions in oxidizer (γ), and excess oxidizer ratios (α) by the ignition delay time is also carried out. It was found that the limits of applicability of all of the mechanisms studied are absent when modeling the ignition delay time, the most accurate mechanism to model the IDT of methane in oxy-fuel conditions being UoS sCO₂ 2.0, while the other three mechanisms are overall much inferior to it in terms of accuracy. However, Skeletal and GRI-Mech 3.0 mechanisms can be used to model the IDT during the oxy-fuel combustion of methane under both atmospheric and supercritical conditions, although only in a narrow range of γ. Full article

Fe-based amorphous and nanocrystalline alloys, such as FINEMET and its improved variants, are highly valued as green energy-saving materials due to their unique magnetic properties, including high permeability, low coercivity, and near-zero saturation magnetostriction. These characteristics have enabled their extensive use in power electronics and information technology. However, the full potential of these alloys remains unfulfilled due to insufficient understanding of their stress sensitivity. This study focuses on the development history, heat treatment, annealing processes, chemical composition, and underlying mechanisms of Fe-based amorphous and nanocrystalline alloys, aiming to provide insights into stress-induced magnetic anisotropy and guide the development of greener and more efficient soft magnetic materials. Full article

The 2050 global ambition for a carbon-neutral society is increasing the penetration of the most competitive variable renewable technologies, onshore wind and solar PV. These technologies are known for their near-zero marginal costs but highly variable time-dependent generation. Power systems with major penetrations of variable generation need high balancing flexibility to guarantee their stability by maintaining the equilibrium between demand and supply. Electricity markets were designed for dispatchable technologies. Support schemes are used to incentivize and de-risk the investment in variable renewables, since actual market designs are riskier for their active participation. This study presents three strategic bidding strategies for the active participation of variable renewables in electricity markets based on probabilistic quantile-based forecasts. This case study examines the levels of active market participation for a wind power producer (WPP) in the Iberian electricity market and the Portuguese balancing markets, where WPPs are financially responsible for imbalances and operate without support schemes in the first and second stages of the Iberian market designs. Results from this study indicate that the WPP has the potential to increase its market value between 36% and 155% if participating in the tertiary and secondary balancing markets completely adapted to its design, respectively. However, considering the use of strategic bidding in actual market designs, by participating in the secondary reserve, the WPP can increase its market value by 10% and 45% when compared with perfect foresight and operational cases, respectively. Full article

This paper proposes a novel joint precoding and artificial noise design framework for generalized spatial directional modulation (AN-GSDM) in unmanned aerial vehicle (UAV) communications, aimed at enhancing the physical-layer security of downlink UAV communication systems. The key innovation lies in the dynamic co-optimization of multi-beam control and artificial noise (AN) power allocation under mobility constraints, enabling real-time adaptation to varying channel conditions. This approach jointly optimizes the precoding matrix and power-control factor, facilitating the effective management of multi-beams and AN to maximize the secrecy rate. The secrecy rate expression is derived, and the corresponding joint optimization problem is formulated. Due to the non-convex nature of the problem and the lack of a closed-form solution, an alternating iterative algorithm is proposed. This algorithm alternates between optimizing the precoding matrix using gradient descent and deriving a suboptimal closed-form solution for the power-control factor. Simulation results confirm that the proposed algorithm significantly enhances security by maximizing the secrecy rate, reducing eavesdroppers’ achievable rate to near zero, while simultaneously maintaining legitimate user’s rate. The approach not only strengthens security but also preserves system effectiveness, demonstrating robust convergence properties. This makes it a practical and promising solution for secure UAV communication. Full article

Promoting complete decarbonization by entrusting the energy supply through renewable sources (wind, photovoltaic, solar thermal, etc.) is one of the key strategies in the building sector. However, renewable energy’s intermittent and space–time mismatch characteristics pose challenges to its compatibility with the power grid. Challenges can be mitigated by introducing thermal and electrical storage to increase the self-consumption of renewable energy in the buildings. This work proposes a comparison between different energy systems equipped with a heat pump, solar plant (photovoltaic or photovoltaic thermal), and thermal and electrical storage. All year-round performances of the different energy system configurations have been simulated using the TRNSYS 17.2 software. The energy analyses revealed that the energy system equipped with a photovoltaic plant, when incorporating the two storages, improves self-consumption (Rsc) from 34.1% to 69.4 and self-sufficiency (Dss) from 27.9% to 59.9%, respectively. Additionally, the energy system equipped with photovoltaic thermal collectors and both storages further improve the system performance; an Rsc of 96.2% and Dss of 86.9% are attained. These results demonstrate that the previous energy system configuration can facilitate the near attainment of net-zero energy buildings. Furthermore, the proposed energy system is characterized by a minimal energy imbalance between the building’s energy demand and the energy produced, thereby reducing the need for energy exchange with the electrical grid. Full article

In the near-zero negative dispersion region of highly nonlinear fiber, the process of wavelength conversion based on the mechanism of intra-pulse stimulated Raman scattering is sensitive to the parameters of pumping pulse and fiber length under the combined effects of nonlinearity and dispersion. Therefore, we experimentally demonstrate the process in detail by using conventional soliton pulses with three sets of pulse parameters and two highly nonlinear fiber lengths of 400 m and 500 m. The experimental results show that, under the combined action of dispersion and several types of nonlinear mechanisms, the wavelength conversion processes are apparently different when using pulses with different parameters to pump different lengths of highly nonlinear fibers. Specifically, the separation degree of the frequency-shifted pulse spectrum and pumping pulse spectrum, and the corresponding redshift rate and pump power consumption all show significantly different results. The experimental results can guide the selection of more suitable parameters for the pumping pulse and the length of highly nonlinear fiber to achieve a better effect of wavelength redshift or spectrum broadening for various practical applications. Full article