Rapid advancements in 3D printing technology have revolutionized antenna fabrication, allowing for the creation of intricate, lightweight, and high-performance structures with exceptional precision. This paper presents the design, fabrication, and experimental evaluation of a 3D-printed waveguide antenna operating in the X-band frequency range (8-11 GHz). The antenna was manufactured using Masked Stereolithography Apparatus (MSLA) technology with Magma X 12 K Dura ABS resin, which was selected for its excellent mechanical strength and dielectric properties. A 0.2 mm thick silver conductive coating was applied to enhance the electrical conductivity and minimize the surface resistance. The proposed antenna is based on a WR-90 rectangular waveguide configuration with an optimized aperture, which ensures minimal reflection loss and high radiation efficiency. Experimental results indicate an impedance bandwidth of 1.34 GHz, spanning from 8.56 GHz to 9.9 GHz, with an optimal resonant frequency at 9.45 GHz. The measured and simulated S₁₁ parameters exhibited strong agreement, validating effective impedance matching and minimal energy dissipation. Furthermore, radiation pattern analysis revealed a directional gain of 6.85 dBi and an overall radiation efficiency of 98.35%. The measured 3 dB beamwidths were 60.5˚ in the E-plane and 105.8˚ in the H-plane, confirming the suitability of the antenna for applications in satellite communication, radar, and wireless sensing. The results demonstrate the viability of MSLA-based additive manufacturing for high-frequency waveguide antennas, offering a cost-effective, lightweight, and high-performance alternative to the traditional fabrication techniques. This study highlights the potential of 3D printing as an innovative approach for the development of next-generation microwave and millimeter-wave communication systems.

In complex electromagnetic scenarios where multiple deceptive jamming signals are simultaneously aliased in the timefrequency domain, conventional single-channel electronic detection systems struggle to effectively separate and classify overlapping jamming sources. To address this limitation, this paper investigates an array detection-based classification scheme for multi-source jamming. First, due to the spatial degrees of freedom offered by array systems, the Direction-of-Arrival (DOA) of each jamming source is precisely estimated using the MUSIC algorithm. Then, the adaptive digital beamforming (ADBF) filters are designed based on the estimated DOA parameters, enabling spatial-domain extraction of individual jamming signals. Finally, the DOA information is integrated into the Pulse Description Word (PDW) of each separated jamming measurement, which can facilitate adaptive K-Means clustering with enhanced class separability. Simulation results demonstrate that the proposed method achieves a 22.4% improvement in classification accuracy compared to existing single-channel detection approaches, while maintaining computational efficiency.

Current stress has a significant impact on the operation of power electronic devices, and the reduction of current stress can improve the safety and reliability of the system. First, this paper proposes a novel asymmetric duty cycle modulation strategy for the primary side of a modular multilevel type (MMC) dual active bridge converter (DAB) to increase the control freedom of the primary side. Secondly, a novel optimization strategy based on a long-short-term memory network (LSTM) classification is proposed in this paper to optimize the current stress. The output power of the system is classified by LSTM，and minimum current stresses at different powers are optimized by a novel meta-heuristic iterative optimization based on generalized quadratic interpolation (GQI). Finally, the feasibility of the scheme is verified by hardware-in-the-loop experiments.

Double Stator Hybrid Excitation Flux Switching Generator (DS-HEFSG) has attracted significant interest in power-generating research owing to its potential for improved performance and sustainability. This research examines the utilization of hybrid excitation to enhance the efficiency of a three-phase DS-HEFSG specifically engineered for low-speed power applications such as renewable energy systems like wind and tidal turbines. The innovative method presents a double stator hybrid configuration for a traditional double stator generator, with performance evaluation performed via 2D finite element simulations. The findings indicate that the DS-HEFSG surpasses traditional topologies, rendering it an optimal selection for this generator configuration. The proposed design significantly increases the 18.76% cogging torque value while the electromotive force increases by approximately 21.62%. The proposed design also decreases permanent magnet eddy-current losses by 24.33%. Enhanced performance is noted in electromagnetic torque, torque ripple, output power, and overall efficiency. These advancements contribute to energy savings and lower maintenance costs, reducing reliance on fossil fuels and supporting the transition to greener energy solutions. The proposed DS-HEFSG with hybrid excitation is a viable alternative for efficient low-speed power production.

This paper presents an innovative microstrip patch antenna (MPA) designed and optimized for Ku-band satellite communications. The proposed design incorporates an asymmetric U-shaped slot and a partial ground plane, constructed using an FR4 substrate with dimensions of 18 × 16 × 1.6 mm³ (0.416λ × 0.37λ × 0.03λ, where λ is the wavelength at 6.94 GHz). A genetic algorithm is employed to optimize the U-shaped slot and the ground plane dimensions, enhancing the antenna's wideband performance while preserving its compact form factor. Simulation results indicate that the optimized design achieves two operational frequency bands with reflection coefficients (S₁₁) less than -10 dB: a narrowband from 6.83 GHz to 7 GHz, with a resonant frequency of 6.94 GHz, and a wideband from 10.26 GHz to 17.19 GHz, with a resonant frequency of 14.94 GHz. This extensive frequency range enables the antenna to effectively support direct broadcast services (DBSs) and fixed satellite services (FSS). The design's effectiveness was confirmed through prototype fabrication and testing, demonstrating strong agreement with simulated results and proving the antenna's compactness and exceptional wideband performance.

This study investigates the properties of a ternary B₂O₃-TeO₂-BaO glass system, prepared through the melt-quenched technique. The chemical formula used is (50 - x/2)B₂O₃ + (50 - x/2)TeO₂ + xBaO, with x varying from 15 to 35 mol.%. The research explores how the gamma and neutron radiation shielding capabilities were analyzed. It finds that higher BaO content enhances gamma-ray shielding but does not significantly affect neutron shielding. The glass sample BTB35 emerged as the optimized candidate among the developed samples for gamma radiation shielding applications. Also, the obtained results for the MFP was compared to commercial shielding glasses, and other measurements on glasses show the superiority of BTB35 as commercial transparent radiation shielding glass.

The feasibility of using passive radiometric detection of chaotic electromagnetic signals emanating from low density plasma plumes of the jet exhaust gases to detect low radar cross section aircrafts is analyzed for the frequency band 3.10⁸-3.10¹² Hz. The aircraft exhaust plume gas formation is modelled with a number of discrete different dimensions ellipsoids, with each having different electron densities and temperatures. Electromagnetic radiation analysis of emitting signals is computed applying fluctuation-dissipation theorem and geometric considerations. The detection range of characteristic military jet aircraft is computed numerically for the whole frequency band, from UHF to 3 THz. It is shown that high range detection can be achieved at upper microwave frequencies.

Aiming at the prevalent issue of limited dataset scale in radar target micro-Doppler effect-based human action recognition, this study constructs an improved Deep Convolutional Generative Adversarial Network (DCGAN) for radar sample data augmentation and integrates it with a Convolutional Neural Network (CNN) for human action classification. First, a millimeter-wave radar data acquisition system was established to collect human action echo signals. The raw data were preprocessed to extract micro-Doppler features, forming a 2D micro-Doppler time-frequency spectrogram dataset. Second, modifications were made to the original DCGAN by replacing the optimizer of the discriminator network and introducing an L2 regularization term to enhance the quality of micro-Doppler time-frequency spectrogram generation. Finally, a CNN architecture was implemented to classify the augmented human action samples. Experimental results demonstrate that the enhanced DCGAN-CNN framework achieves robust human action classification performance, achieving an accuracy rate of up to 97.5%. This validates the superior capability of generative adversarial networks in few-shot scenarios for radar-based human action recognition.

To address the challenges in constructing the measurement matrix within the compressive sensing-based method of moments (CS-MoM) framework, this paper presents a novel dynamic extraction method based on row norm significance for impedance matrix compression. The proposed method first sorts the impedance matrix rows in descending order according to their row norm importance, followed by a dynamic extraction process that adapts the extraction density based on row significance. This strategy ensures dense extraction of high-importance rows to maintain matrix representativeness, while sparse extraction of low-importance rows preserves global structural coverage. Finally, through the validation of numerical results from three different computational models, it is demonstrated that the proposed method improves computational accuracy while ensuring computational efficiency compared to the uniform extraction-based novel CS-MoM method.

Recent advancements and innovations in wireless power transfer (WPT) technology have led to an increased demand for systems with high power transfer efficiency (PTE) and extended transmission distances to meet the needs of end users. However, many existing WPT systems suffer from limited PTE and restricted transmission ranges due to their reliance on inductive coupling. A significant drawback of inductive coupling is the sharp decline in PTE as the distance between the transmitter and receiver coils increases. To address these limitations, this study proposes the design of an inductive WPT system enhanced by the integration of metamaterials (MTMs) to improve PTE through magnetic field manipulation. By strategically positioning MTMs between the transmitter (Tx) and receiver (Rx) coils, the efficiency and range of WPT systems can be significantly enhanced. MTMs exhibit unique properties, such as negative refraction and evanescent wave amplification, which are particularly promising for improving PTE in WPT systems. At a separation distance of 70 mm, the implementation of negative permittivity MTMs and double-negative MTMs yields a remarkable improvement in PTE, achieving an increase of 180% compared to a conventional WPT system without MTM integration. Systems with MTM maintain better PTE at increasing lateral and angular misalignments, but at 90° misalignment, power transfer is almost impossible, even with MTM, due to complete misalignment of the fields.This study aims to provide a comprehensive analysis of the development and performance of negative permittivity and double-negative MTM-based WPT systems, offering critical insights into their potential for enhancing WPT efficiency and range.

Aiming at the problems of low ability of speed control by means of magnetic field weakening of surface-mounted permanent magnet synchronous motor and large torque pulsation and more magnetic leakage of interior permanent magnet synchronous motor, a new structure of surface-mounted and interior hybrid permanent magnet synchronous motor is proposed. By establishing a finite element model of the motor and simulating it, and comparing the electromagnetic characteristic curves of the motor after simulation with those of the surface-mounted permanent magnet synchronous motor and interior permanent magnet synchronous motor, the results show that the motor proposed in this paper has the advantages of both good weak magnetic performance and higher torque output. In the optimization of surface-mounted and interior hybrid permanent magnet synchronous motor, with the goal of achieving high torque value, low torque ripple, and low cogging torque, a multi-objective optimization strategy combining genetic algorithm (GA) optimized back-propagation (BP) network and non-dominated sorting genetic algorithm (NSGA-II) is adopted. Firstly, a comprehensive sensitivity analysis of the degree of influence of the design variables on the optimization objective is carried out, based on which the parameter variables are stratified, and then an accurate prediction model of the parameter variables and optimization objective is established by using GA-BP. Finally, the multi-objective optimization is carried out by NSGA-II, and the optimal design is selected from the generated Pareto frontiers. After comparing the electromagnetic performances of the motor before and after optimization, the effectiveness as well as the superiority of the multi-objective optimization design method is verified.

All wireless communication systems are moving towards higher and higher frequencies day by day which are severely attenuated by rains in outdoor environment. To design a reliable RF system, an accurate prediction method of rain attenuation is established and used globally based on local rain intensity measurement. Required rain intensity used for attenuation prediction is generally measured at a point with 1-min integration time or converted from higher integration time to 1-min. Recent measurements of rain intensity with a 10-second integration time indicate that intensity is not uniform over a 1-minute duration. Consequently, the statistics of rain intensity distribution and attenuation predictions are influenced by measurements with integration times shorter than 1 minute. It has been established that an integration time of 0.01% provides the optimal fit for actual rain rate data. This paper presents the rain intensity distributions from data measured with 2-min, 1-min, 30-sec, 20-sec, and 10-sec integration times, and it has impact on rain rate distributions as well as rain attenuation predictions.

With the advancement of millimeter wave communication technology, reconfigurable antennas have garnered significant attention due to their adaptability. However, their radiation gain and sidelobe suppression performance are often constrained by factors such as diode package size and array scale. To address these challenges, this paper proposes a three-state frequency reconfigurable array antenna with high gain and low sidelobe characteristics, specifically designed to meet the demands of millimeter-wave communication. By optimizing the feed network and radiating element design, the proposed antenna achieves enhanced gain and improved sidelobe suppression. The design employs a dual-port feeding architecture that integrates a Taylor non-uniform amplitude distribution with a series-parallel hybrid feed network. This configuration ensures phase consistency while minimizing the number of diodes to just four, significantly reducing insertion loss and structural complexity. The antenna prototype is fabricated using standard printed circuit board (PCB) technology, with overall dimensions of 60.4 × 63 × 0.508 mm³. Measurement results indicate that the antenna exhibits an impedance bandwidth spanning from 27.5 GHz to 28.5 GHz and from 34.5 GHz to 35.5 GHz. The corresponding peak gains are 19.69 dBi and 19.51 dBi, with the sidelobe levels of are 18.93 dB and 18.03 dB respectively. The proposed antenna demonstrates excellent radiation characteristics and significantly enhanced radiation efficiency. With its simple structure, dual-band radiation capability, high gain, and low sidelobe levels, this antenna is highly suitable for millimeter-wave wireless communication systems. It offers a high-performance solution for multi-band communication in 5G/6G networks.

Accurately estimating spacecraft charging requires consideration of an appropriate secondary electron yield (SEY) of spacecraft materials. SEY is influenced by factors such as surface roughness, oxidation, and contamination. Using SEY values for materials not representative of actual spacecraft conditions can lead to significantly inaccurate spacecraft charging predictions. Against the use of default values for smooth and clean elemental Al, this work examines the impact of SEY of aluminum (Al) in its relevant states over a spacecraft's lifespan in favour of the reliable estimation of absolute charging. It specifically focuses on the Impact of SEY on the absolute charging of a pyramidal horn antenna, one of the essential spacecraft modules. For modeling of charging, the antennas are assumed to be in appropriate states of Al, i.e. oxidized Al for the beginning of life and Al with thin Carbon(C) - rich contamination for the end-of-life of a spacecraft. The observed deviation in absolute charging will determine a more realistic approach to protect a spacecraft against Electrostatic Discharge (ESD).

Conventionally designed Vivaldi antennas are predominantly fabricated using PCB technology, which limits their long-term applicability in high-power systems. This paper proposes a three-dimensional all-metal slant 45°-polarized Vivaldi antenna suitable for high-power applications. The design incorporates a resonant cavity and optimized slot-line parameters to broaden the operational bandwidth. A 16 × 16 array configuration was developed, with parasitic elements integrated to suppress edge effects. The optimal prototype was fabricated and experimentally validated. Simulation and measurement results demonstrate that the proposed all-metal Vivaldi antenna achieves a voltage standing wave ratio (VSWR) below 2.5 across a frequency bandwidth of 6-18 GHz, along with a maximum beam scanning angle of 48°. This paper demonstrates a practical solution for balancing wideband performance (6-18 GHz) with high-power handling capabilities in phased array applications.

This project proposal addresses the critical need for precise measurement of thin dielectric coatings, which are essential in industries such as aviation, aerospace, and automotive for enhancing structural integrity and protecting against environmental factors. Manual application of these coatings often results in uneven thickness, necessitating a streamlined measurement method. Leveraging advancements in microwave technology, particularly the use of complementary split ring resonators (CSRR), this project introduces a novel measurement approach for coatings on Carbon Fiber Reinforced Polymer (CFRP) composites. By employing electric field coupling of a leaky wave antenna between a cylindrical dielectricloaded sensor and the coatings on CFRP through a double circular ring slot, the method identifies a correlation between resonance frequency and coating thickness. The cavity is integrated with a Vector Network Analyzer (VNA) to detect S₁₁ peaks at the resonance frequency, enabling precise measurement. Initial design comparisons using CST software resulted in a sensor antenna with optimal impedance matching and sensitivity, which was subsequently fabricated and tested in a microwave lab. Remaining objectives include developing a 4th-order regression model to predict coating thickness ranging from 0 to 2 mm for Polyethylene Terephthalate (PET) on CFRP composites and validating the method for industrial applications in aero-engine parts, gas turbines, and automotive structures. Future enhancements will focus on refining the technique for very thin coatings and exploring drone-based inspection methods for comprehensive aircraft analysis. This innovative approach promises a reliable solution for measuring coating thickness, which is crucial for maintaining the performance and safety of advanced composite materials.

In Terahertz (THz) frequencies, using traditional phase delay components is extremely difficult and graphene has the potential to be used in THz. Graphene is typically used at less than λ/16 dimensions. However, it has the potential to change the properties of a unit cell in reflectarray and act as an electronic phase-shifting element at λ/2 dimensions. Therefore, this paper proposes the design and application of graphene in unit cells to develop reflectarray beam steering. A metal-graphene hybrid structure is proposed in this work for designing the reconfigurable reflectarray antenna (RRA). The unit cell operating at 1.025 THz frequency, consists of a thin graphene sheet as a phase-shifting element inside a golden ring, where graphene is used as the phase delay component. The variation in the chemical potential of graphene leads to changes in the reflection coefficient phase for each unit cell. A circular aperture array comprising a maximum of 489 elements shows a total of 80° beam-steering with side-lobe levels of less than -10 dB and a maximum gain of over 20 dBi. The -1 dB bandwidth of 12% was obtained at the centre frequency of 1025 GHz between 950 GHz and 1075 GHz. The aperture efficiency of the designed RRA is found to be 11%. This type of antenna could be an advent for the development of terahertz Reflecting Intelligent Surface (RIS).

Biomedical devices (BDs) monitor vital signs and diagnose illnesses to improve patients' lives. These BDs rely on battery power, which is often short-lasting. To address this limitation, wireless power transfer (WPT) has been proposed in research as a solution for wirelessly recharging BD batteries. This paper aims to enhance WPT in a nonradiative near-field system for implanted BDs by designing and fabricating a triple-layer receiver coil operating in the 13.56 MHz ISM band. First, three square coil models --- single-layer, double-layer, and triple-layer—were developed and simulated using HFSS ANSYS software. The coil models were tested at air gaps ranging from 2 to 40 mm between the transmitter and receiver coils. The single-layer and double-layer coils, each with a receiver coil size of 10×10×0.5 mm, achieved transfer efficiencies of 76.19% and 80.03%, respectively, at an air gap of 10 mm. In contrast, the triple-layer coil, designed with a receiver coil size of 10×10×1.5 mm, attained a transfer efficiency of 87.83% at the same air gap. Additionally, the study analyzed the specific absorption rate (SAR), which was measured at 0.1823 W/kg for 1 g of tissue. Second, the triple-layer square coil was validated through fabrication and experimental testing in different environments, including air, acrylic, and biological tissue (beef). The results demonstrated transfer efficiencies of 80%, 77%, and 63% in air, acrylic, and tissue, respectively. Moreover, the experimental results closely matched the simulation ones, confirming that the triple-layer square coil model accurately represents real-world performance.

The inherent volatility and uncertainty associated with photovoltaic (PV) power generation present significant challenges to maintaining grid stability. As the level of PV integration into the grid continues to rise, the importance of accurately predicting its power output becomes increasingly critical. This study presents a new PV power prediction model utilizing the K-means++-BiLSTM-Transformer framework. Initially, the Pearson correlation coefficient is computed to determine the key factors influencing the prediction of PV power significantly. Following this, the K-means++ clustering algorithm is applied to analyze historical power data, categorizing it into three distinct groups corresponding to different weather conditions. Finally, the BiLSTM-Transformer architecture is employed to develop a power output prediction model tailored for the three weather scenarios. The prediction model is subsequently optimized using Bayesian methods to determine the optimal model configuration for each specific weather condition. Experimental findings demonstrate that the proposed K-means++-BiLSTM-Transformer similar day PV power prediction model exhibits superior accuracy, enhanced generalization, and increased robustness compared to alternative prediction models.

In radar target detection, long-term coherent integration (LTCI) is widely employed to improve the signal-to-noise ratio (SNR) and enhance the detection capability for weak and small targets. Meanwhile, the airborne radar, with advantages of wide-area surveillance, high sensitivity, and strong maneuver ability, demonstrates significant superiority in detecting high-speed targets. However, during the flight of the airborne radar platform, motion errors and the relative motion of high-speed targets can cause significant range migration (RM) and Doppler frequency migration (DFM), degrading coherent integration performance. To this end, this paper proposes a coherent integration method for high-speed target in airborne radar based on the symmetric autocorrelation function, scaled Fourier transform, and sequence reversing autocorrelation function (SAF-SFT-SRAF). Detailed comparisons between SAF-SFT-SRAF and several typical methods demonstrate that the proposed method effectively balances computational complexity and detection performance.