Search Results (26,973)

Maintaining high power delivery under uncertain landing positions is a key challenge for wireless charging of unmanned aerial vehicles (UAVs). This paper presents a data-driven power optimization method based on the Soft Actor-Critic algorithm for multi-transmitter single-receiver wireless power transfer (MTSR-WPT) systems. To support effective learning without explicit online parameter identification, a physics-informed dual-current state representation is constructed from measurable current responses, combining a zero-phase current with the current response under the applied phase command. The agent is trained using a reward defined directly from normalized load power, and the transmitter voltage phases serve as the control actions. In simulations of a five-transmitter system, the learned policy achieves about 97% of the theoretical maximum power in the training region and about 96% in the expanded evaluation region. Additional robustness studies show strong performance under moderate measurement noise and substantial recovery under model mismatch after short fine-tuning. Experimental validation on a physical prototype confirms the effectiveness of the method, yielding an average power improvement of 188% from a zero-phase baseline and reaching 87% of the maximum power measured on the hardware platform. These results support the proposed method as a practical data-driven alternative to model-dependent MTSR-WPT power optimization for UAV wireless charging. Full article

In this work the feasibility of fully autonomous hydrogen homes designed for complete off-grid operation is presented. A detailed mathematical modeling and optimization model is developed to evaluate the technical performance and economic feasibility of hydrogen fuel cell-powered residential systems with no grid connection or fallback. The system integrates primary and standby Proton Exchange Membrane (PEM) fuel cells, multi-day hydrogen storage, advanced power conditioning, and comprehensive controls to achieve reliable year-round power supply. The analysis encompasses a complete 20-year lifecycle cost assessment. The results demonstrate that fully autonomous hydrogen homes achieve 99.85% system availability with 13.1 h of potential downtime annually, providing reliable energy independence. The levelized cost of electricity over the 20-year system lifetime is calculated at 0.4543 US$/kWh at baseline hydrogen prices of 6 US$/${\mathrm{kg}}_{{\mathrm{H}}_2}$, substantially higher than grid-connected alternatives. The analysis identifies critical sensitivity to hydrogen pricing and demonstrates that at hydrogen costs below 3 US$/${\mathrm{kg}}_{{\mathrm{H}}_2}$ (achievable with mature green hydrogen production), competitive payback periods of 12–15 years are possible in high-cost electricity regions. This study concludes that hydrogen-based autonomous homes represent a viable long-term solution for residential energy independence, particularly in remote or off-grid locations where grid connection is impractical or in regions with high electricity tariffs and developing green hydrogen production capacity. Full article

Crosslinked polyethylene (XLPE) is a widely used cable insulation material for power cables at various voltage levels, offering excellent electrical, mechanical, and thermal stability. However, during the continuous extrusion moulding process, prolonged shear action and localized temperature accumulation can easily induce premature crosslinking. This leads to a decline in melt rheological properties and reduced processing stability, as well as having an adverse effect on the microstructure and overall performance of the formed insulation layer. This study systematically investigated the impact of shear-induced pre-crosslinking on the mechanical properties and dielectric characteristics of XLPE cable insulation materials through experimental testing methods. The experimental results demonstrate that, while premature crosslinking has a minimal effect on mechanical properties, it significantly deteriorates dielectric performance, as evidenced by increased conduction current, reduced breakdown strength, and compromised microstructural integrity. These findings suggest that, to improve the quality and reliability of XLPE cable production, engineering designs should prioritize controlling the pre-crosslinking process to ensure stable dielectric performance. Full article

To satisfy the requirements of voltage support and fault-current limitation for electric-vehicle (EV) charging stations connected to weak distribution networks, an increasing number of charging infrastructures are adopting grid-forming (GFM) converters and vehicle-to-grid (V2G) control strategies. Under AC short-circuit faults and voltage-sag conditions, limiting the fault current injected by the converter is essential to reduce overcurrent risk to power semiconductor devices. For this, an adaptive virtual-impedance-based low-voltage ride-through (LVRT) method is proposed for GFM converters in EV charging stations. First, an overcurrent grading criterion is constructed based on real-time current measurements. In the moderate-overcurrent region, an adaptive virtual reactance is introduced to achieve soft current limiting. In the severe-overcurrent region, hard current limiting is implemented by further increasing the virtual reactance and blocking overcurrent bridge arm. In addition, a virtual-reactance recovery mechanism is designed to ensure smooth post-fault restoration. Based on an RCP + HIL platform, experiments are conducted to validate the proposed fault current-limiting method. Experiment results demonstrate that the proposed method can rapidly suppress fault current, maintain voltage-support capability, and shorten post-fault restoration time. Full article

Background/Objectives: Groin pain syndrome (GPS) is a frequent and heterogeneous condition in athletes, often associated with persistent pain and functional limitation. Both focused extracorporeal shockwave therapy (f-ESWT) and exercise-based rehabilitation have been proposed as conservative treatment options, but evidence for their combined use in GPS remains limited. This prospective single-arm pilot study aimed to describe temporal changes in pain and function following a multimodal conservative program combining f-ESWT and structured rehabilitation in athletes with GPS, using validated groin-specific outcome measures. Methods: Thirty-one consecutive adult soccer players (mean age 28.4 ± 5.8 years; 77.4% male) with clinically and MRI-confirmed GPS underwent three weekly f-ESWT sessions (Duolith; 2400 pulses/session; 4 Hz; energy flux density 0.20 mJ/mm²) integrated within a supervised 16-week rehabilitation program (progressive adductor strengthening, core stabilization, and stretching). Outcomes were assessed at baseline (T0), 1 month (T1), and 4 months (T2): HAGOS (primary), VAS pain, and Roles and Maudsley (RM). Within-subject changes were analyzed using repeated-measures ANOVA with Bonferroni correction. Results: Statistically significant temporal changes were observed across all outcomes (all p < 0.001). HAGOSs changed from 47.23 ± 7.79 at T0 to 77.94 ± 16.18 at T1 and 90.00 ± 14.26 at T2 (partial η² = 0.89). VAS decreased from 6.81 ± 1.25 to 3.68 ± 1.11 and 1.90 ± 1.45 (partial η² = 0.91). RM decreased from 2.39 ± 0.50 to 1.52 ± 0.57 and 1.26 ± 0.63 (partial η² = 0.72). No adverse events were reported. Conclusions: In this single-arm pilot study, the multimodal program combining f-ESWT and structured rehabilitation was associated with temporal changes in groin-specific function and pain that exceeded established MCID thresholds. However, in the absence of a control group, these findings are purely descriptive and hypothesis-generating. The observed changes cannot be attributed to f-ESWT specifically, as the 16-week rehabilitation program likely contributed substantially to the outcomes. These preliminary observations require confirmation through adequately powered randomized controlled trials comparing the combined intervention to rehabilitation alone. Full article

Power fluctuations and scheduling uncertainties caused by large-scale renewable energy grid integration have made the existing homogeneous energy storage solutions struggle in some cases to balance economic efficiency with dynamic response speed. To address the above challenge, this paper proposes a hybrid energy storage system integrating superconducting magnetic energy storage and hydrogen electric storage, and a corresponding dual-layer model predictive control energy management framework is therefore designed. This framework lies on its cross-timescale hierarchical coordination mechanism. Analytic validation in a typical high-fluctuation renewable microgrid scenario demonstrates that compared to conventional single-layer control strategies, the proposed management system reduced total operating costs by 55.5%, extended system stabilization time by 64.2%, decreased hydrogen storage system mode switching frequency by 59.9%, and simultaneously lowered computational burden by over 97%. This effectively enhanced power supply reliability and extended equipment service life. This innovative framework provides a practical solution for coordinated energy storage control in microgrids having a high ratio of renewable penetration. Full article

In frequency-modulated continuous-wave (FMCW) radar systems, the detection of Doppler-extended targets (DETs) is a critical challenge. The micro-Doppler effects induced by the motion of extended targets such as pedestrians cause the echo energy to spread along the Doppler dimension. As a result, a single range-Doppler cell is unlikely to form a pronounced amplitude peak above the background noise level. Consequently, existing constant false alarm rate (CFAR) methods that rely on single-cell amplitude decisions tend to suffer from performance degradation in DET scenarios and exhibit limited adaptability under varying clutter conditions. To solve these issues, we propose a nonlinear transform–based variability index CFAR detector for DET (DET-NTVI-CFAR), with the aim of improving detection probability and maintaining stable false alarm control in complex clutter backgrounds. This work constructs a detection statistic by applying a nonlinear transform to the accumulated power cells and derives the threshold from the corresponding probability distribution model. A variability index CFAR (VI-CFAR) decision strategy is introduced to select the appropriate detection branch under different operating conditions. In the threshold design stage, the false alarm probability expressions of three sub-detection methods are derived to guide the selection of threshold parameters. Simulation results demonstrate that the proposed method achieves stable false alarm control and improves detection probability in various environments. Field test results also confirm the applicability of the DET-NTVI-CFAR detector. Full article

The increasing integration of inverter-based distributed energy resources (DERs) significantly reduces power system inertia, posing critical challenges to transient stability. Traditional fault ride-through strategies, relying on passive and localized rules, often fail to provide effective coordinated support in low-inertia grids. To address these limitations, this paper proposes a Transient Dynamic Features Adaptation Distributed Cooperative Control (TDA-DCC) framework. This approach integrates a dynamic context-aware policy network based on multi-head attention mechanisms to extract temporal features from local observations, allowing agents to anticipate transient dynamics rather than merely reacting to instantaneous states. A multi-agent deep deterministic policy gradient algorithm is employed to optimize a global multi-dimensional objective function encompassing frequency, voltage, and rotor angle stability. Furthermore, to ensure engineering reliability, a hybrid execution architecture is introduced, which embeds a deterministic safety monitor to switch between the intelligent policy and a robust backup controller during extreme anomalies. Case studies on a modified IEEE 39-bus system demonstrate that the proposed method significantly enhances transient stability margins and robustness against sensor failures compared to conventional baselines. Full article

The qEEG findings of subjects with Down syndrome (DS) have not been described in the context of bipolar montage. Resting-state EEG (rsEEG) with a bipolar montage was performed in 22 young adults (26.0 ± 1.2 years) with DS but without psychiatric or neurological pathology and matched control subjects of the same sex and age, and the results were conventionally and numerically analyzed. Channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum was calculated and used to compute the area for the delta, theta, alpha and beta bands and was log-transformed. Shannon’s spectral entropy (SSE) and coherence by bands were computed. Finally, we also calculated the peak frequency distribution of the alpha band. qEEG revealed alterations in the rsEEG that were not detected visually. Subjects with DS showed a significant generalized increase in the power of the delta and theta bands, along with a decrease in the power of the alpha band in the posterior half of the scalp. This alpha activity also exhibited features corresponding to older euploid subjects, showing interhemispheric asynchrony in one-third of the individuals. The beta band power was significantly increased in the frontal lobes and adjacent regions, such as the parietal and mid-temporal regions. Individuals with DS showed a generalized decrease in parieto-occipital synchronization associated with intelligence quotient. Left temporal synchronization was also lower. The synchronization of specific channel pairs was greater in subjects with DS in the frontal lobe and much lower in the occipital and temporal regions. These results indicate that alterations in band structure and synchronization in subjects with DS are highly specific and can aid in the clinical evaluation of these individuals. Full article

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification. Full article

Flexible interconnection systems (FISs) improve distribution flexibility, yet they remain vulnerable to pronounced nonlinear instability and potentially severe DC-link voltage collapse during large disturbances such as constant power load (CPL) surges. Conventional linear control methods are often unable to prevent deep transient voltage dips under these conditions. To address this issue, this paper proposes a novel large-signal stability criterion based on mixed potential function (MPF) theory. Unlike conventional Lyapunov-based approaches, the proposed formulation explicitly incorporates the dynamics of the DC capacitor, thereby enabling the derivation of a closed-form stability boundary. On this basis, the proportional gains of the outer voltage loop are first optimized to guarantee an adequate static stability margin. Subsequently, a power differentiation feedforward control strategy is developed. Rather than passively counteracting transients, the proposed method dynamically adjusts the DC voltage reference according to the rate of change in power, thereby actively reshaping the transient trajectory. In this way, the simple PI control framework is preserved while avoiding the heavy computational burden associated with advanced methods such as model predictive control. Simulation results show that the proposed strategy increases the permissible CPL step power by 8.7%, from 92 kW to 100 kW. Moreover, under severe load surges and weak grid conditions, the method prevents voltage collapse and maintains the transient trajectory above the practical 600 V safe-operation threshold. This computationally efficient strategy significantly improves the robustness and continuity of operation of practical FISs. Full article

To accurately control the hot workability of 7050 aluminum alloy and determine the optimal process window, systematic hot compression experiments were carried out on the Gleeble-3500 thermal simulation test machine under the multi-group process conditions of deformation temperature 300~450 °C, strain rate 0.001~1 s⁻¹, and maximum deformation of 60%. The high-temperature rheological curve data were collected, and the key hot deformation parameters, such as deformation activation energy Q, Zener–Hollomon (Z) parameter, and power dissipation efficiency η, were calculated based on the experimental results. The random forest prediction model between process parameters and thermal deformation parameters was innovatively constructed to realize the accurate quantification of the parameter relationship. On this basis, the multi-objective process optimization was further carried out by coupling the TOPSIS and EWMs. Finally, the optimal hot deformation process parameters of 7050 aluminum alloy were determined as 410~450 °C and 0.001~1 s⁻¹. The microstructure analysis showed that the main deformation mechanism of the material in the optimized region was dynamic recrystallization, which could effectively ensure the microstructure uniformity and mechanical property stability of the formed parts. Full article

In this work, an accelerated non-uniform corrosion method controlled by time and current was employed to fabricate power-on accelerated corrosion specimens of hybrid steel fiber-reinforced concrete (HSFRC) gradient beams. Experimental research was conducted to investigate their impact resistance, revealing the dynamic response patterns of these gradient beams with varying steel fiber contents. By analyzing the evolutionary characteristics of impact load, displacement, energy dissipation, equivalent impact bearing capacity, and dynamic amplification factor, the influence of steel fibers with different sizes and contents on the bearing capacity degradation and mechanical properties of HSFRC gradient beams under the same corrosion conditions was clarified. The synergistic enhancement mechanism of multi-scale steel fibers in the beams was elucidated, highlighting the complementary effects of long fibers and short fibers at different stages of material damage. Results show that the incorporation of steel fibers can effectively improve the impact resistance of reinforced concrete gradient beams, with a maximum improvement of approximately 2.5 times. Compared with gradient beams reinforced with single long fibers, the peak impact force of HSFRC gradient beams increases by about 16%, and different steel fiber ratio plays a significant role in regulating impact resistance. Within the corrosion range of 3% to 5%, the equivalent impact bearing capacity of gradient beams is negatively correlated with the reinforcement corrosion rate. Full article

With the growing penetration of photovoltaic (PV) generation, robust uncertainty characterization is essential for secure operation, economic dispatch, and flexibility planning. This review surveys PV scenario generation from three perspectives: (i) explicit probabilistic approaches (distribution fitting, Copula-based dependence modeling, autoregressive moving average (ARMA)-type time-series methods, and clustering/dimensionality reduction), (ii) deep generative models (GANs, VAEs, and diffusion models), and (iii) hybrid Statistical Relational AI (SRAI) frameworks. We discuss the strengths of explicit models in interpretability and tractability, and their limitations in representing high-dimensional nonlinear, multimodal, and multiscale spatiotemporal dependencies. We also examine the ability of deep generative methods to synthesize diverse scenarios across meteorological regimes and multiple sites, while noting persistent challenges in interpretability, physical consistency, and deployment. To bridge these gaps, we outline an SRAI-oriented integration pathway that embeds statistical structure, meteorology–power relations, spatiotemporal coupling, and operational constraints into generative architectures. Finally, we highlight directions for future research, including unified evaluation protocols, cross-regional data collaboration, controllable extreme-scenario generation, and computationally efficient generative designs. Full article

Background/Objectives: We investigated whether ingestion of caffeine (~1 h before) was beneficial to subsequent morning (07:30 h), mood, strength and cognitive measures. Methods: Fourteen recreationally active males were recruited and completed six sessions: (i) one repetition maximum (1RM) for bench press and back squat; (ii) two familiarization sessions of strength measures; (iv) three experimental conditions administered in a double-blinded, randomized counterbalanced design order, either caffeine (Caffeine [CAFF], 300 mg or 2.8–4.3 mg/kg body weight), placebo (Placebo [PLAC]) ingested at 06:30 h, or no-pill control (No Pill [NoPill]). For each experimental session, on arrival at the laboratory, rectal and skin temperature were measured as well as a battery of cognitive performance through a battery of tests (trail-making test, Rey’s auditory verbal learning test, and Stroop word–colour interference test). Thereafter, maximum voluntary contraction on an isometric chair (MVC) without and with stimulation was conducted, and three repetitions were performed at 40, 60 and 80% of 1RM for bench press and back squat. Average power (AP), average velocity (AV), peak velocity (PV), mean propulsive velocity (MPV), average acceleration (RDV), displacement (D) and time-to-peak velocity (tPV) were recorded using MuscleLab linear encoders. Rating of perceived exertion and effort was asked after each set (RPE). The data was analysed using a general linear model with repeated measures. Results: MVC peak-force values with and without stimulation showed a significant increase in the CAFF condition compared to values for NoPill and with stimulation PLAC conditions (stim: Δ9.0 and 8.7%; no stim: 8.3%; p < 0.05; η²_p = 0.33 and 0.42). Greater muscle % activation was achieved for the CAFF than the other conditions (~6%, p ≤ 0.042; η²_p = 0.33). In the non-stimulated MVC, RPE was perceived as easier (4.8%, p = 0.04). AV and MPV values were higher in both bench press (Δ3.3 and 4.6%) and back squat (Δ7.7 and 9.2%) in CAFF than the PLAC condition (p = 0.031; η²_p = 0.24 and 0.23 and 0.24 and 0.32). CAFF improved auditory total recall compared to NoPill (9.5%, p = 0.040; η²_p = 0.22). Conclusions: Early morning ingestion of caffeine improved MVC to levels observed by others in the evening, as well as some aspects of bench press, back squat and recall performance. Caffeine ingestion had no effect on core temperature, mood, tiredness, alertness or other measures of cognitive performance. Full article