Search Results (3,467)

High-power linear alternators (HPLAs) are key energy conversion components in free-piston Stirling generators (FPSGs), yet their output performance strongly depends on the coupled matching among the gas pressure wave, piston dynamics, and external electrical load. In this work, the electrical load-matching characteristics and loss mechanisms of a gas-coupled HPLA were investigated experimentally and numerically. A thermodynamic–dynamic–electromagnetic coupling model, validated against gas-coupled dynamic experiments, is established to account for the position-dependent electromagnetic parameters and the coupled gas mechanical–electrical interaction. The results show that load resistance mainly governs the current level and the loss composition, whereas series capacitance shifts the electrical phase and modifies the effective electromagnetic stiffness and damping acting on the piston. Consequently, the maximum power condition does not coincide with complete electrical resonance: allowing the capacitance to deviate from resonance raises the maximum output power from 13.54 kW to 14.58 kW, a gain of about 7.7%. Moreover, as the load resistance increases, the dominant loss migrates from current-dependent electromagnetic loss to mechanical damping loss, so that the maximum power point and the maximum efficiency point are clearly separated. These findings establish a coupled load-matching framework for selecting the operating point and external load according to design priority, rather than by electrical resonance alone. Full article

Axial-flux motor (AFM) can achieve high torque and power density; however, integrated electromagnetic and thermal design is required to manage losses and heat generation during high-power operation. In this study, an AFM with a target output power of 160 kW for electric vehicles was analyzed using three-dimensional electromagnetic and thermal-fluid analyses. Electromagnetic analysis evaluated back EMF, cogging torque, torque, output power, efficiency, and losses. Current phase-angle control was applied at high speeds considering the 700 V line-to-line voltage limit of the 800 V inverter. At 300 A and 4500 rpm, the motor achieved an output power of 150 kW with an efficiency of approximately 94%. Electromagnetic losses were applied as heat sources in the thermal analysis. In the Base model, nonuniform oil flow caused local high-temperature regions. The model incorporating eight ribs in the oil-flow path and 12 rotor blades for enhanced air cooling reduced the maximum coil temperature from 194 °C to 170 °C and the maximum stator temperature from 205 °C to 113 °C. The model reduced the standard deviations of coil and stator temperatures by 50.6% and 58.6%, respectively. The proposed multi-physics method predicts electromagnetic and thermal characteristics and supports operating control and cooling system design. Full article

Artificial neural networks (ANNs) offer efficient surrogates for radio-frequency (RF) passive-device modeling and design, but prediction accuracy alone does not establish their engineering reliability. This review examines four overlapping analytical perspectives: data generation and sampling, forward modeling, knowledge-enhanced modeling, and inverse modeling and design. Its passive-device-focused synthesis separates computational costs by workflow stage, distinguishes physical-property guarantees from enforcement and tests, and examines the feasibility and coverage of inverse-design solutions. Direct passive-device applications are distinguished from transferable electromagnetic methods. Across the reviewed workflows, adaptive sampling reduced the need for costly labeling, while structured and hybrid representations improved response approximation within the tested domains. Multivalued and generative inverse models accommodated non-unique solutions, although candidate diversity should be assessed separately from feasibility and solution coverage. Coarse models, transfer functions, and physics-informed losses provide useful structural priors but do not automatically guarantee network properties or reliable extrapolation. The experimental results demonstrated the practical potential for the tested devices and processes. These findings call for reproducible benchmarks and process-aware validation that link modeling accuracy to physical reliability and engineering applicability. Full article

Herein, high-entropy ferrites (HEFs) represent a transformative frontier in solid-state chemistry and materials physics, shifting design paradigms from conventional mono- or co-substituted ceramics toward multi-component, single-phase solid solutions. Stabilized by a massive configurational entropy (ΔS_conf > 1.5 R), these systems incorporate five or more principal cations into a single crystalline matrix, such as cubic spinel (Fd3̅m), perovskite, or hexagonal structures. This comprehensive review systematically evaluates recent breakthroughs in HEF design, tracing the continuous lineage from advanced synthesis methodologies, including modified Pechini sol–gel and hydrothermal routes, to local coordination environments and macroscopic functional expressions. We detail how intense local lattice distortions and polyhedral buckling alter metal–oxygen ligand bond parameters, disrupting traditional collinear A-O-B superexchange pathways to induce quantum magnetic frustration, low-temperature spin-glass behavior, and spontaneous exchange bias effects. Beyond fundamental physics, this work highlights the multi-cation “cocktail effect” across cutting-edge applications, emphasizing its role in high-frequency electromagnetic interference (EMI) shielding, multi-redox heterogeneous catalysis, and high-capacity electrochemical energy storage. Finally, we address current computational bottlenecks in Density Functional Theory (DFT+U) simulations and propose a roadmap for accelerating phase stability predictions and magnetic footprint tuning through the integration of high-throughput workflows and closed-loop, data-driven machine learning architectures. By bridging the gap between thermodynamic theory and targeted application, this review provides a foundational framework for the next generation of entropy-stabilized functional devices. Full article

Magnetic field ripple in the audible-frequency range can induce magnetostriction in ferromagnetic components, causing vibration and noise even in non-rotating systems such as electric vehicle battery systems. Magnetic shielding can reduce such excitation; however, shielding materials used in this range are generally ferromagnetic and may themselves undergo magnetostriction, potentially degrading NVH performance. Therefore, magnetic shielding materials should provide effective field attenuation while suppressing their own vibration to improve system-level NVH performance. In this study, a magnetic shielding test setup and an electromagnetic finite-element model were developed. The electromagnetic model was compared with experimental plate-shield measurements and subsequently used for comparative investigations of the effects of shielding configuration, open-area ratio, and thickness, while the associated NVH performance was evaluated experimentally. A mesh-type structure with a continuous magnetic flux path achieved shielding performance comparable to that of a plate-type structure. Experiments using a 0.635 mm steel-wire mesh provided a magnetic shielding effectiveness of approximately 3.73 dB at 3 kHz and reduced the target vibration component at 6 kHz by 55.8% and system noise by 5 dB. These results demonstrate that mesh-type magnetic shielding can attenuate audible-frequency magnetic field ripple while improving system-level NVH performance, indicating potential application to electric vehicle battery systems and other electromagnetic systems. Full article

Ground-penetrating radar (GPR) denoising requires large paired datasets that preserve weak target echoes while representing realistic underground clutter, but field measurements are difficult to label, and high-fidelity electromagnetic simulations are costly to scale. This paper proposes a fast denoising dataset-generation method based on a transformer network constrained by an underground clutter physical model. The method decomposes each generated B-scan into a noisy image, a clean target response, a target mask, and three physically interpretable clutter components: direct antenna coupling, random background clutter, and interface-induced multipath. A reference B-scan is used only to estimate gray-level, vertical-energy, and spectral statistics, while transformer modulation branches adjust the physically generated clutter components without copying reference image details. In a 100-sample experiment, the proposed generator produced $512\times 512$ B-scans on a CUDA-enabled GPU in 38.36 s, corresponding to 2.61 B-scans/s and 15.64 exported maps/s. The dataset contained 600 maps, including 500 supervision or component maps. The mean reference correlation was −0.0210, indicating low pixel-level dependence on the reference image. Compared with representative GAN, diffusion, and forward-modeling generators, the proposed method provides explicit target and clutter labels for denoising-oriented dataset construction. Five matched gprMax/FDTD conditions yielded a direct-referenced propagation-delay MAPE of 4.70% and a hyperbola-curvature MAPE of 14.41%, while larger amplitude and multipath errors revealed the expected fidelity–efficiency trade-off of the simplified generator. Full article

This paper presents a staged two-terminal fault-location method for transmission lines with series compensation, based on incremental quantities and a least-squares error (LSE) formulation. The fault distance is first established through an analytical estimator with a bounded linear capacitive correction. This distance is subsequently held fixed during subsample time alignment and the emulation of the nonlinear capacitor and metal-oxide varistor (MOV), thereby preventing the later correction stages from shifting the fault location solely to reduce the fitting residual. Among the 18 paired Common Format for Transient Data Exchange (COMTRADE) records, 10 cases corresponded to the reference distance category, including seven instances with series compensation and three instances without compensation. For these 10 records, the proposed procedure achieved a mean absolute error of 2.26 km, with eight cases within 5 km; excluding the record used during method development, it was 2.48 km, with seven of nine within 5 km. For the compensated subset, the mean absolute error decreased from 4.44 km (raw LSE) to 3.04 km (from 3.94 to 3.50 km excluding that record), whereas the uncompensated subset yielded 0.43 km. Sensitivity and stress analyses quantify the influence of the incremental delay and delimit the applicability of the time-alignment and residual-diagnosis stages. The results show the performance of the staged formulation on the available records while indicating the need for broader field and electromagnetic-transient validation before generalization to other compensation levels, MOV characteristics, and fault-resistance conditions. Full article

Programmable transmissive metasurfaces provide a flexible platform for dynamic electromagnetic wavefront manipulation, yet simultaneously achieving multiple functionalities with a low-complexity binary architecture remains challenging. In this work, a 1-bit programmable transmissive metasurface is proposed for reconfigurable far-field holographic imaging and near-field orbital angular momentum (OAM) vortex-beam generation at 5.5 GHz. The proposed meta-atom employs two complementary switching states to realize nearly identical transmission amplitudes with an approximately ${180}^{\circ }$ transmission-phase difference, enabling efficient binary phase modulation. Based on the designed meta-atom, a $25\times 25$ programmable array is constructed, where different electromagnetic functions are realized solely by updating the spatial coding sequence without modifying the physical structure. For far-field manipulation, binary holographic phase distributions are encoded to reconstruct representative “H” and “S” images, and the full-wave simulated results agree well with the theoretical predictions. For near-field manipulation, focused OAM beams with topological charges $l=1$ and $l=2$ are generated at an observation plane located 180 mm from the metasurface. The resulting intensity distributions exhibit pronounced vortex characteristics, while the corresponding phase profiles show the expected $2\pi$ and $4\pi$ azimuthal phase variations. OAM modal decomposition further confirms that the desired modes dominate the generated fields. These results demonstrate that a single 1-bit programmable transmissive aperture can support dynamically switchable electromagnetic functions in different propagation regimes, offering a low-complexity approach for reconfigurable holography, structured-wave generation, and software-defined microwave systems. Full article

Mainlobe active deception jamming significantly degrades radar target detection in complex electromagnetic environments. Current anti-jamming detection approaches inadequately exploit the spatiotemporal information inherent in target echoes, thereby fundamentally limiting their capacity for reliable detection and robust true–false discrimination. Therefore, this paper proposes a trajectory-guided two-stage multi-frame fusion detection (TSMF-Det) model based on range-Doppler (R-D) maps. Initially, a lightweight candidate detector is utilized to generate high-recall candidate boxes, which are then linked into cross-frame trajectories via temporal association. Subsequently, a spatiotemporal refinement network (STRNet) is designed to aggregate multi-frame temporal and multi-scale spatial features, enabling fine-grained true–false target discrimination and bounding-box refinement. Finally, an adaptive peak-center fusion module dynamically achieves high-precision estimation of range and velocity parameters. Experiments on a comprehensive dataset encompassing six typical active deception jamming scenarios demonstrate that TSMF-Det yields an average detection probability of 0.97. Comparative experiments show that TSMF-Det maintains stable target detection under strong jamming while providing effective false-target rejection and accurate range–velocity estimation. By exploiting multi-frame spatiotemporal features, TSMF-Det provides an effective anti-jamming detection framework for cognitive radar systems. Full article

Seismoelectric responses generated in fluid-saturated porous media contain indirect geophysical information related to subsurface interfaces, material contrasts, and electrokinetic coupling. Many three-dimensional simulations adopt a quasi-static electromagnetic approximation, which neglects displacement-current contributions and cannot provide a complete description of full-wave electromagnetic propagation. In this study, we present a hybrid spectral-element and finite-element time-domain framework for three-dimensional full-wave seismoelectric modeling based on the Pride–Biot equations and the magnetic vector potential–electric scalar potential (A–$\varphi$) formulation. The poroelastic wavefield is first computed using a high-order spectral-element method, and the resulting relative fluid–solid velocity is introduced as the source term for the electromagnetic problem. An implicit backward-difference scheme is employed to accommodate the substantial difference between seismic and electromagnetic wave speeds. The coupled A–$\varphi$ systems are solved using a flexible generalized minimal residual method with an upper-triangular block preconditioner based on an approximate Schur complement and algebraic multigrid cycles. This solver strategy is adopted as a practical treatment for the large, sparse, nonsymmetric, and strongly coupled systems generated by the three-dimensional formulation. The proposed framework is validated through numerical experiments involving half-space and layered media, a fault damage zone model, and a modified SEG/EAEG salt-dome model. The results reproduce the expected coseismic and interfacial responses and demonstrate the accuracy, numerical stability, and computational feasibility of the method in heterogeneous three-dimensional structures. The framework provides an effective forward-modeling tool for analyzing full-wave seismoelectric responses and for generating synthetic data for future subsurface sensitivity and joint-inversion studies. Full article

Based on the governing equations of the electromagnetic radiation field and the theory of multi-layer media propagation, the governing equations for electromagnetic wave attenuation are derived. A stable solution to the resulting large-scale sparse linear system is obtained using Tikhonov regularization. A typical collapse column forward model is established using locally refined triangular mesh discretization. Forward and inverse modeling are conducted at three transmission frequencies: 0.3 MHz, 0.5 MHz, and 1.5 MHz. The results indicate that the 1.5 MHz frequency yields the best vertical resolution, with inversion results most closely matching the modeled anomaly location. In the field application at working face number 3308 using 1.5 MHz, the local polynomial interpolation inversion delineates an anomalous vertical extent of approximately 70 m (75–145 m), whereas the Kriging interpolation method yields a vertical extent of about 140 m (20–160 m), representing a reduction of approximately 50% in the vertical extent of the delineated anomaly. Post-mining exposure reveals the X16 collapse column, with a major axis of 53 m and a minor axis of 34 m, which is generally consistent with the detection results. This study confirms that local polynomial interpolation combined with locally refined triangular meshing effectively enhances the vertical resolution of radio wave transillumination, providing reliable technical support for the accurate delineation of concealed collapse columns. Full article

Efficient maximum power extraction under rapidly varying wind conditions remains a major challenge for variable-speed wind energy conversion systems (WECSs). This paper proposes a nonlinear derivative synergetic mode controller (DSMC) for robust rotor speed regulation in a permanent magnet synchronous generator (PMSG)-based WECS operating with a tip speed ratio (TSR)-based maximum power point tracking (MPPT) strategy. The TSR algorithm continuously determines the optimal rotor speed corresponding to the maximum power coefficient, while the reference electromagnetic torque is generated to maintain operation at the optimal aerodynamic condition. The proposed DSMC is designed to accurately regulate the turbine speed despite the nonlinear dynamics of the WECS and external disturbances caused by fluctuating wind speeds. To demonstrate its effectiveness, the proposed controller is systematically compared with a robust integral sliding mode controller (ISMC) and conventional proportional–integral and integral–proportional controllers under identical operating conditions. A comprehensive MATLAB 2021/Simulink model incorporating the aerodynamic characteristics of the wind turbine and the electrical dynamics of the PMSG is developed and evaluated using a realistic variable wind speed profile. The comparative assessment is performed using key performance indicators, including rotor speed tracking, tip-speed ratio regulation, power coefficient, extracted power, electromagnetic torque response, transient behavior, and steady-state performance. The simulation results demonstrate that the proposed DSMC achieves faster dynamic response, smaller tracking errors, reduced oscillations, and enhanced robustness against wind speed variations compared with the benchmark controllers. Consequently, the proposed control strategy maintains operation closer to the optimal TSR, improves energy capture efficiency, and ensures stable and smooth power extraction without increasing the computational complexity of the TSR-MPPT algorithm. These characteristics make the proposed controller an effective and practical solution for high-performance PMSG-based WECSs. Full article

High-precision electromagnetic localization shows great promise for applications in medical treatment, embodied intelligence, entertainment, and gaming. However, six-degree-of-freedom (6-DoF) coil pose estimation is essentially a highly nonlinear inverse problem. Numerical iterative solvers, such as the Levenberg–Marquardt (LM) algorithm, are sensitive to poor initial guesses and prone to getting trapped in local optima. This limitation has become a major bottleneck for improving the accuracy and robustness of electromagnetic localization systems. To address this problem, we propose a network termed TGNet (Transmitter Geometry-guided Network) that provides reliable initial guesses for the iterative solver. The network mainly consists of three parts: (i) a dual-branch module that encodes the spatial distribution of the transmitting coil as physical priors, thereby narrowing the ambiguous solution space and effectively mitigating pose ambiguity arising from multiple local extrema; (ii) a decoupled regression head that estimates the coil’s 6-DoF position and orientation independently, reducing cross-coupling complexity; and (iii) a numerical simulation-based data generation strategy that produces large-scale datasets of magnetic field measurements paired with ground-truth 6-DoF poses for fully supervised training, circumventing the difficulty of collecting real-world labeled data. Using TGNet predictions as initial guesses for the LM algorithm, we achieved average position and orientation errors of 1.5 mm and 0.6°, respectively, in real localization experiments. In contrast, using random data as initial guesses for the LM algorithm, the average position and orientation errors were 31.1 mm and 7.9°, confirming that the proposed initialization improves accuracy. First, TGNet reliably avoids local minima, as the LM algorithm converges at all test points in the localization space. Second, TGNet reduces the iteration counts of the LM algorithm, decreasing them from 39 to 14. Overall, TGNet provides a robust and efficient solution for high-performance electromagnetic localization. Full article

Virtual synchronous generator (VSG) control changes electromagnetic torque in doubly fed induction generator (DFIG) wind turbines and can redistribute structural loading. This study couples Fatigue, Aerodynamics, Structures, and Turbulence (FAST) v8.16 with MATLAB/Simulink to compare vector control and VSG control with current-aligned protection. A six-unit electrical equivalent is coupled to one flexible WindPACT 1.5 MW turbine through consistent coordinate, speed, torque, and power-base mappings. Load-step responses illustrate transient electromechanical coupling, and three paired turbulent realizations at a nominal wind speed of 9 m/s quantify short-term fatigue loading. The 1 Hz damage-equivalent loads (DELs) are evaluated over 60–120 s using unbinned rainflow counting without mean-stress correction. Relative to vector control, VSG changes the mean DEL by −4.43% for tower fore–aft, −0.06% for tower side-to-side, +24.76% for drivetrain torque, +1.88% for blade flapwise, and −0.67% for blade edgewise loading. Numerical-resolution and initial-state checks show that the smaller differences require cautious interpretation. The results identify a trade-off between tower fore–aft and drivetrain loading for complete control implementations under the evaluated conditions. Full article

Grid-forming (GFM) control is an important technical solution for addressing the declining voltage-support capability and inertia level of modern power systems. By integrating a high-voltage directly connected grid-side converter with supercapacitors, the grid-forming static power generator (GFM-SPG) can provide active- and reactive-power support to high-voltage power grids. This paper investigates a GFM-SPG with a two-stage converter topology and proposes a coordinated control strategy for the two-stage converters. The transient response characteristics of the GFM-SPG are classified into three operating regions, and the effects of key control parameters are analyzed to establish basic parameter design guidelines. To simultaneously enhance grid inertial support and transient voltage-support capability, a variable inertia time-constant control strategy is further proposed. Under normal operating conditions, a relatively large inertia time constant is adopted to provide inertial support, whereas a small inertia time constant is employed during voltage ride-through to enable rapid phase synchronization and prioritize reactive-power support. The proposed control strategy is validated through electromagnetic transient simulations and hardware-in-the-loop (HIL) experiments. The results demonstrate that the two-stage GFM-SPG can achieve stable DC-bus voltage regulation and provide effective inertia and transient voltage support under different grid operating conditions. Full article