Search Results (302)

This article presents a non-linear MEC for a linear PM motor, and its experimental validation. In the MEC model, winding flux leakage and iron saturation are considered. In addition, two different linear PM motor models (bread-loaf and surface-type) are examined for linear PM motors. An iterative method is used to predict the magnetic behavior of saturated magnetic steel. The proposed MEC for linear PM motors is compared with finite element analysis (FEA) to determine its accuracy and suitability. FEA is widely regarded as a highly accurate and reliable tool for analyzing linear PM motors. However, its primary limitation lies in its considerable computational time requirement. This disadvantage becomes particularly problematic during the early stages of the design process. Therefore, the proposed model addresses this limitation. Also, experimental results validate the practicality of the MEC. Finally, the proposed model can be a tool for different slot/pole combinations. Thus, the model can be considered suitable for both bread-loaf and surface-type PM motors. Full article

In this study, a computational thermo-fluid dynamics simulation of a wide-slot jet impingement heating process is performed. The present configuration consists of a turbulent incompressible air jet impinging orthogonally on an isothermal cold plate at a Reynolds number of around 11,000. The two-dimensional mean turbulent flow field is numerically predicted by solving Reynolds-averaged Navier–Stokes (RANS) equations, where the two-equation eddy viscosity k-$\omega$ model is utilized for turbulence closure. As the commonly used shear stress transport variant overpredicts heat transfer at the plate due to excessive turbulent diffusion, the recently developed generalized k-$\omega$ (GEKO) model is considered for the present analysis, where the primary model coefficients are suitably tuned. Through a comparative analysis of the various solutions against one another, in addition to reference experimental and numerical data, the effectiveness of the generalized procedure in predicting both the jet flow characteristics and the heat transfer at the plate is thoroughly evaluated, while determining the optimal set of model parameters. By improving accuracy within the RANS framework, the importance of model adaptability and parameter tuning for this specific fluid engineering application is demonstrated. This study offers valuable insights for improving predictive capability in turbulent jet simulations with broad engineering implications, particularly for industrial heating or cooling systems relying on wide-slot jet impingement. Full article

Nickel-based superalloy Hastelloy C276 is widely used in high-performance industries due to its strength, corrosion resistance, and thermal stability. However, these same properties pose substantial challenges in machining, resulting in high tool wear, surface defects, and dimensional inaccuracies. This study investigates methods to enhance machining performance and surface quality by evaluating the tribological behavior of TiSiN/TiAlN-coated carbide inserts under six cooling and lubrication conditions: dry, MQL with coconut oil, Cryo-LN₂, Cryo-LCO₂, MQL–Cryo-LN₂, and MQL–Cryo-LCO₂. Open-slot finishing was performed at constant cutting parameters, and key indicators such as cutting zone temperature, tool wear, surface roughness, chip morphology, and microhardness were analyzed. The hybrid MQL–Cryo-LN₂ approach significantly outperformed other methods, reducing cutting zone temperature, tool wear, and surface roughness by 116.4%, 94.34%, and 76.11%, respectively, compared to dry machining. SEM and EDS analyses confirmed abrasive, oxidative, and adhesive wear as the dominant mechanisms. The MQL–Cryo-LN₂ strategy also lowered microhardness, in contrast to a 39.7% increase observed under dry conditions. These findings highlight the superior performance of hybrid MQL–Cryo-LN₂ in improving machinability, offering a promising solution for precision-driven applications. Full article

This paper presents a symmetry-driven broadband circularly polarized magnetoelectric dipole antenna with bandpass filtering response, where the principle of symmetry is strategically employed to enhance both radiation and filtering performance. The antenna’s circular polarization is achieved through a symmetrical arrangement of two orthogonally placed metallic ME dipoles combined with a phase delay line, creating balanced current distributions for optimal CP characteristics. The design further incorporates symmetrical parasitic elements—a pair of identical inverted L-shaped metallic structures placed perpendicular to the ground plane at −45° relative to the ME dipoles—which introduce an additional CP resonance through their mirror-symmetric configuration, thereby significantly broadening the axial ratio bandwidth. The filtering functionality is realized through a combination of symmetrical modifications: grid slots etched in the metallic ground plane and an open-circuited stub loaded on the microstrip feed line work in tandem to create two radiation nulls in the upper stopband, while the inherent symmetrical properties of the ME dipoles naturally produce a radiation null in the lower stopband. This comprehensive symmetry-based approach results in a well-balanced bandpass filtering response across a wide operating bandwidth. Experimental validation through prototype measurement confirms the effectiveness of the symmetric design with compact dimensions of 0.96${\lambda }_0$ × 0.55${\lambda }_0$ × 0.17${\lambda }_0$ (${\lambda }_0$ is the wavelength at the lowest operating frequency), demonstrating an impedance bandwidth of 66.4% (2.87–5.05 GHz), an AR bandwidth of 31.9% (3.32–4.58 GHz), an average passband gain of 5.5 dBi, and out-of-band suppression levels of 11.5 dB and 26.8 dB at the lower and upper stopbands, respectively, along with good filtering performance characterized by a gain-suppression index (GSI) of 0.93 and radiation skirt index (RSI) of 0.58. The proposed antenna is suitable for satellite communication terminals requiring wide AR bandwidth and strong interference rejection in L/S-bands. Full article

In recent years, distributed energy power supply systems have been widely used in remote areas and extreme environments. However, the intermittent and uncertain output power may cause power grid fluctuations, leading to higher harmonics in electromechanical equipment, especially motors. For permanent magnet synchronous motor (PMSM) systems, an electromagnetic (EM) vibration can cause problems such as energy loss and mechanical wear. Therefore, it is necessary to design control algorithms that can effectively suppress EM vibration. To this end, a vibration suppression algorithm for fractional-slot permanent magnet synchronous motors based on a d-axis current injection is proposed in this paper. Firstly, this paper analyzes the radial electromagnetic force of the fractional-slot PMSM to identify the main source of EM vibration in fractional-slot PMSMs. Based on this, the intrinsic relationship between the EM vibration of fractional-slot PMSMs and the d-axis and q-axis currents is explored, and a method for calculating the d-axis current to suppress the vibration is proposed. Experimental verification shows that the proposed algorithm can effectively suppress EM vibration. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

Conventional adhesively bonded joints, such as single-lap, curved-lap, wavy-lap, double-lap, stepped-lap, and scarf joints, are widely used for aerospace, automotive, and medical applications. These adhesively bonded joints exhibit different load transfer mechanisms and stress distributions within adhesive layers, which depend primarily on their geometries and mechanical properties of bonded materials. As such, joint geometry and material properties play a critical role in determining the capability of the joints to withstand high loads, resist fatigue, and absorb energy under impact loading. This paper investigates the effects of geometry and material dissimilarity on the performance of both conventional bonded and interlocking joints under tensile loading based on the information available in the literature. In addition, bonding and load transfer mechanisms were analysed in detail. It was found that stress concentration often occurs at free edges of the adhesive layer due to geometric discontinuities, while most of the load is carried by these regions rather than its centre. Sharp corners further intensify resulting stresses, thereby increasing the risk of joint failure. Adhesives typically resist shear loads better than peel loads, and stiffness mismatches between adherents induce an asymmetric stress distribution. Nonetheless, similar materials promote symmetric load sharing. Among conventional joints, scarf joints provide the most uniform load distribution. In interlocking joints such as dovetail, T-slot, gooseneck, and elliptical types, the outward bending of the female component under tension can lead to mechanical failure. Full article

This article presents a comprehensive overview of recent advancements in photonic crystal fiber (PCF)-based sensors, with a particular focus on the surface plasmon resonance (SPR) phenomenon for biosensing. With their ability to modify core and cladding structures, PCFs offer exceptional control over light guidance, dispersion management, and light confinement, making them highly suitable for applications in refractive index (RI) sensing, biomedical imaging, and nonlinear optical phenomena such as fiber tapering and supercontinuum generation. SPR is a highly sensitive optical phenomenon, which is widely integrated with PCFs to enhance detection performance through strong plasmonic interactions at metal–dielectric interfaces. The combination of PCF and SPR technologies has led to the development of innovative sensor geometries, including D-shaped fibers, slotted-air-hole structures, and internal external metal coatings, each optimized for specific sensing goals. These PCF-SPR-based sensors have shown promising results in detecting biomolecular targets such as excess cholesterol, glucose, cancer cells, DNA, and proteins. Furthermore, this review provides an in-depth analysis of key design parameters, plasmonic materials, and sensor models used in PCF-SPR configurations, highlighting their comparative performance metrics and application prospects in medical diagnostics, environmental monitoring, and chemical analysis. Thus, an exhaustive analysis of various sensing parameters, plasmonic materials, and sensor models used in PCF-SPR sensors is presented and explored in this article. Full article

The Internet of Things (IoT) aims to wirelessly connect billions of physical things to the IT infrastructure. Although there are several radio access technologies available, few of them meet the needs of Internet of Things applications, such as long range, low cost, and low energy consumption. The low data rate of low-power wide-area network (LPWAN) technologies, particularly SigFox, makes them appropriate for Internet of Things applications since the longer the radio link’s useable distance, the lower the data rate. Network reliability is the primary goal of SigFox technology, which aims to deliver data messages successfully through redundancy. This raises concerns about SigFox’s scalability and leads to one of its flaws, namely the high collision rate. In this paper, the goal is to prevent collisions by switching to time division multiple access (TDMA) from SigFox’s Aloha-based medium access protocol, utilizing only orthogonal channels, and eliminating redundancy. Consequently, during a designated time slot, each node transmits a single copy of the data message over a particular orthogonal channel. To achieve this, a multi-agent, off-policy reinforcement learning (RL) Q-Learning technique will be used on top of SigFox. In other words, the objective is to increase SigFox’s scalability through the use of Reinforcement Learning based time slot allocation (RL-SCAP). The findings show that, especially in situations with high node densities or constrained communication slots, the proposed protocol performs better than the basic SCAP (Slot and Channel Allocation Protocol) by obtaining a higher Packet Delivery Ratio (PDR) in average of 60.58%, greater throughput in average of 60.90%, and a notable decrease in collisions up to 79.37%. Full article

The rapid development of 5G and next-generation wireless systems has increased the demand for antennas that support circular polarization (CP), wide frequency coverage, and a compact size. Achieving wideband CP performance in a low-profile and simple structure remains a key challenge for modern antenna designs. In response to this, this paper presents a compact wide-slot antenna with a single feed, offering a wide operational bandwidth and circularly polarized radiation. The proposed design is excited by a 50 Ohm microstrip feedline, and it is fabricated on an (54 × 50 × 1.6 mm³) FR4 dielectric substrate. On the bottom side of the dielectric substrate, the ground plane is engraved to form a square-shaped radiating slot. The shape of the tuning stub of the antenna is modified in order to attain a wide impedance bandwidth and an axial ratio bandwidth (ARBW). The modifications include inserting a rectangular strip and thin horizontal strips into the tuning stub after tapering its upper corner. On the other hand, the radiating slot is appended by two rectangular stubs. The radiation of the resulted structure has right-hand circular polarization (RHCP). The measured results of the proposed antenna show a −10 dB impedance bandwidth equal to 78% (2.65 GHz, 2.08–4.73 GHz), whereas its broadside 3 dB ARBW is 71.6% over the frequencies (2.31 GHz, 2.07–4.38 GHz), which is compatible with various wireless communication applications. Furthermore, the peak value of the measured gain is equal to 4.68 dB, and its value is larger than 2 dBi along the operational bandwidth of the antenna. Full article

Induction motors have a simple structure, have low manufacturing costs and are widely used. However, various vibration effects with mechanical or electromagnetic origins are also very common. To analyze the impact of rotor skewing on electromagnetic vibrations in induction motors, this paper investigated the skew factor of skewed rotor slots and proposes an electromagnetic force wave analysis method. The method aimed to optimize the skew angle parameters for vibration amplitude reduction, with its effectiveness verified through simulations and experiments. Taking a 7.5 kW four-pole induction motor with 36 stator slots and 28 rotor slots as the research object, the suppression law of different skew parameters on force waves generated by stator harmonics was obtained. Results show that when the rotor is skewed by an angle equivalent to three stator teeth pitch, electromagnetic forces of different orders are attenuated by approximately 5% on average. Physical rotors with skew angles of 0°, 10°, 12.8°, 14°, and 20° were manufactured for experimental validation, while considering the influence of rotor skewing on starting torque and maximum torque. The study concludes that the amplitude of tooth harmonics varies with the skew coefficient, consistent with the skew factor analysis. By analyzing motor vibration with the skew coefficient, the amplitude relationship of electromagnetic vibration under different optimization parameters can be determined, thereby selecting reasonable skew parameters for rotor optimization. Full article

Terahertz (THz) antennas are among the critical components required for enabling the transition to sixth-generation (6G) wireless networks. Although research on THz antennas for 6G communication systems has garnered significant attention, a standardized antenna design has yet to be established. This study introduces the modeling of a full-metal transverse slotted waveguide antenna (TSWA) for 6G and beyond. The proposed antenna operates across the upper regions of the V-band and the entire W-band. Designed and simulated using widely adopted full-wave analysis tools, the antenna achieves a peak gain of 17 dBi and a total efficiency exceeding 90% within the band. Additionally, it exhibits pattern-reconfigurable capabilities, enabling main lobe beam steering between 5° and 68° with low side lobe levels. Simulations are conducted to assess the power handling capability (PHC) of the antenna, including both the peak (PPHC) and average (APHC) values. The results indicate that the antenna can handle 17 W of APHC within the W-band and 3.4 W across the 60–160 GHz range. Furthermore, corona discharge and multipaction analyses are performed to evaluate the antenna’s power handling performance under extreme operating conditions. These features make the proposed TSWA a strong candidate for high-performance space applications, 6G communication systems, and beyond. Full article

We consider the scenario in which the source sends status updates, or packets, to the receiver through an infinite capacity transmitter, where the transmitted packets are subject to potential illegal eavesdropping. Time is discretized into identical time slots. In recent years, the age of information (AoI) metric, which was defined as the time has elapsed since the generation instant of the latest received packet, has been widely applied to characterize the freshness of obtained packets. Due to the presence of eavesdroppers, some packets may be eavesdropped during their transmissions, causing information leakages. To assess an infinite-capacity system’s performance of securely transmitting status updates, in this paper, we define an AoI-related metric called the freshness advantage of the legitimate receiver, F, to be average instantaneous gap between eavesdropper’s and legitimate receiver’s AoI. For arbitrarily distributed packet interarrival times, and assuming that in each time slot with probabilities ${\gamma }_d$, ${\gamma }_E$, the transmitted packet is received by the legitimate receiver and the eavesdropper, we derive the explicit formula of F. The concise expression shows that F is fully determined by the average interarrival time and the ratio of ${\gamma }_d$ to ${\gamma }_E$. For special cases where the interarrival time follows geometric distributions, we first determine the explicit distribution of instantaneous AoI gap. Then, given ${\gamma }_d$ and ${\gamma }_E$, we derive the optimal packet generation rate $p^{\ast }$ that minimizes the combined performance Q, which is constructed as the average AoI minus the freshness advantage F. When imposing timeliness and security constraints at the same time, the feasible regions of p and ${\gamma }_d$ such that both two required performances can be satisfied are depicted and discussed. Finally, we investigate the impacts of different parameters on F and show the tradeoffs between timeliness performance and security performance through numerical simulations. Full article

We propose a new ultra-wideband antipodal Vivaldi antenna design based on the Klopfenstein curve, incorporating exponential slots, horns, and apertures to improve the antenna’s return loss and increase its gain in high-frequency bands. The antenna achieves high gain and wide bandwidth characteristics, with measured −10 dB bandwidth ranging from 2 GHz to 20 GHz, maximum gain of 14 dBi, and gain exceeding 10 dBi from 3.5 GHz to 14 GHz. Full article

The Internet of Things (IoT) is revolutionizing communication by connecting everyday objects to the Internet, enabling data exchange and automation. Low-Power Wide-Area networks (LPWANs) provide a wireless communication solution optimized for long-range, low-power IoT devices. LoRa is a prominent LPWAN technology; its ability to provide long-range, low-power wireless connectivity makes it ideal for IoT applications that cover large areas or where battery life is critical. Despite its advantages, LoRa uses a random access mode, which makes it susceptible to increased collisions as the network expands. In addition, the scalability of LoRa is affected by the distribution of its transmission parameters. This paper introduces a Reinforcement Learning-based Time-Slotted (RL-TS) LoRa protocol that incorporates a mechanism for distributing transmission parameters. It leverages a reinforcement learning algorithm, enabling nodes to autonomously select their time slots, thereby optimizing the allocation of transmission parameters and TDMA slots. To evaluate the effectiveness of our approach, we conduct simulations to assess the convergence speed of the reinforcement learning algorithm, as well as its impact on throughput and packet delivery ratio (PDR). The results demonstrate significant improvements, with PDR increasing from 0.45–0.85 in LoRa to 0.88–0.97 in RL-TS, and throughput rising from 80–150 packets to 156–172 packets. Additionally, RL-TS achieves 82% reduction in collisions compared to LoRa, highlighting its effectiveness in enhancing network performance. Moreover, a detailed comparison with conventional LoRa and other existing protocols is provided, highlighting the advantages of the proposed method. Full article