Search Results (17,246)

This paper presents a comparative analysis of three magnetic-integrated LCL-derived filter configurations for suppressing high-frequency switching harmonics in avionics power-conversion systems: the integrated LLCL filter, the magnetic-integrated multi-trap LCL filter, and the magnetic-integrated trapped-LCL filter. The high-frequency harmonics considered in this study originate primarily from the pulse-width-modulated (PWM) switching process and can increase current distortion, electrical and magnetic losses, component stress, and the potential for electromagnetic interference in aircraft electrical systems. To enable a consistent comparison, the three filter configurations are evaluated within a unified analytical framework under common system-level operating conditions, while retaining their topology-specific passive and magnetic parameters according to their respective design requirements. The framework distinguishes aggregate total harmonic distortion (THD) from attenuation at targeted switching-frequency bands and incorporates the effects of resonant branches and magnetic coupling. The simulated current THD values of the LLCL, multi-trap LCL, and trapped-LCL filters are 0.82%, 0.84%, and 1.13%, respectively, while their estimated total filter losses are 24.98 W, 59.74 W, and 40.49 W. At the 1 kW operating point, these losses correspond to 2.50%, 5.97%, and 4.05% of rated power, respectively. The results show that the LLCL filter achieves the lowest aggregate THD and estimated loss under the investigated conditions, whereas the multi-trap and trapped-LCL configurations provide additional capability for targeted attenuation of selected switching-frequency components through their resonant structures. Hardware-in-the-loop (HIL) results further support the electrical filtering and dynamic behavior of the investigated concepts. The comparison demonstrates that minimum THD, minimum loss, targeted switching-harmonic attenuation, and magnetic integration are distinct design objectives; therefore, topology selection should be based on the specific requirements and constraints of the intended avionics application. Full article

Environmental regulations and stricter emission limits are driving the development of advanced fuel supply systems. Precise fuel metering under varying engine loads has become critical, with modern strategies using multiple injections of very short duration. However, injector behavior, particularly nonlinear flow characteristics, is not fully understood. This study presents an experimental analysis of the flow characteristics Q = f (t_inj) and opening dynamics of five low-pressure gas injectors with different valve system designs. The tests were conducted for injection times t_inj = 0–20 ms. For t_inj > 2.5 ms, the characteristics were very well described by a linear model (R² > 0.995), whereas for t_inj < 2.5 ms, there was a clear deviation from the linear relationship between flow rate and injection time. Analysis of the electrical signals, outlet pressure, and body vibrations made it possible to identify the mechanistic sources of the observed nonlinearity. It was demonstrated that the initial lack of flow results from an electromechanical delay associated with the rise in current and the electromagnetic force required to overcome the spring force, friction, and inertia of the valve element. The subsequent movement of the valve contributing factors a dynamic change in the flow cross-sectional area and, consequently, a nonlinear change in flow rate. Additionally, the change in the position of the valve element affects the inductance of the coil and the nature of the electromagnetic force. Near the maximum lift, the element bounces off the stop, causing a momentary change in its position and a local decrease in flow rate. Only after the valve element’s motion stabilizes does the flow transition to a nearly linear relationship. The response times of the injectors ranged from 0.60 to 1.30 ms, and the times to reach full opening ranged from 1.08 to 2.14 ms, corresponding, respectively, to the onset and the transition to the steady-state region of the characteristic curve. The results indicate that the nonlinearity of the short-time portion of the characteristic has a mechanistic, electromechanical nature and results from the coupling of electromagnetic phenomena, the motion of the valve element, and the varying flow cross-section. This means that accurately modeling it requires taking into account the actual dynamics of valve-opening, particularly in the case of strategies that use short and repeated injection pulses. These findings highlight a significant limitation in fuel dosing precision and emphasize the need to incorporate nonlinear injector models or dynamic corrections in ECU control algorithms—an essential step for further reducing exhaust emissions. Full article

Reliable estimation of aquifer transmissivity (T) is fundamental for groundwater assessment, development, and sustainable management. Although pumping tests provide the most reliable estimates of transmissivity, their application is often constrained by the limited availability of wells and the high cost of testing, particularly in data-scarce regions such as the Raya Valley, northern Ethiopia. This study evaluates the potential of electrical transverse resistance (Tr), derived from Vertical Electrical Sounding (VES), as a proxy for estimating transmissivity in unconsolidated aquifers. A total of 44 VES datasets integrated with pumping test data from nearby wells were used to develop empirical T–Tr relationships. The Schlumberger electrode array was employed with a maximum current electrode spacing (AB) of 1000 m, while an additional 263 VES datasets acquired between 1996 and 2024 were analyzed to characterize subsurface electrical variability. The results reveal strong linear relationships between transmissivity and transverse resistance. Normalization of transverse resistance to account for pore-water resistivity produced comparable relationships, with differences of only 1–3%, indicating that normalization provides limited additional benefit. Independent validation using 16 pumping-test datasets demonstrated excellent agreement between measured and estimated transmissivity values (R² = 0.99). The transmissivity values used to develop the empirical equations ranged from 120 to 1180 m²/d. These relationships were derived specifically from unconsolidated aquifers within the Raya Valley and should therefore be applied within this hydrogeological context. Their applicability to confined sedimentary aquifers and fractured volcanic formations, which were not represented in the present dataset, remains uncertain. Further studies involving these hydrogeological settings are needed to evaluate and potentially extend the applicability of the proposed relationships. The developed T–Tr relationships provide a reliable and cost-effective approach for estimating transmissivity in saturated unconsolidated aquifers where pumping-test data are limited and may be transferable to hydrogeologically similar environments. Full article

Accelerator magnet power supplies are typical high-power power electronic impulsive loads in large scientific facilities. During fast excitation, the rapid rise of magnet current may cause transient power impacts and voltage sags at the point of common coupling, which can be easily confused with traditional disturbance sources such as motor starting, transformer inrush, and short-circuit faults. To support power-quality evaluation and disturbance-source tracing in distribution networks, this paper investigates the grid-side impact characteristics of accelerator magnet power supplies and proposes a physically interpretable identification method. Different current ramp-rate cases are analyzed to reveal the relationship between fast excitation, PCC power impact, and voltage fluctuation. The results show that increasing the current ramp rate significantly intensifies the active-power impact and PCC voltage fluctuation, with the maximum voltage fluctuation reaching 10.20% under the high-ramp-rate case. Based on these characteristics, a two-layer identification method combining S-transform-based voltage-sag detection and fuzzy comprehensive evaluation is proposed. The method uses multidimensional electrical features, including power change rate, three-phase unbalance, power factor, active/reactive impact ratio, and current harmonic distortion, to distinguish different disturbance sources. Verification results show that the proposed method can effectively identify fast-excitation disturbances of magnet power supplies and distinguish them from typical traditional voltage sag sources. The study provides a reference for power-quality evaluation and disturbance-source tracing of accelerator magnet power supplies connected to distribution networks. Full article

With the growth of emerging data centers and electric vehicles, DC power distribution and hybrid microgrids are attracting growing attention. Due to the lack of a natural zero-crossing point in DC current, reliable DC fault protection is critical. This paper introduces a transient-minimized fault protection scheme utilizing Z-source circuit breakers (ZCBs), leveraging their unique features during the activation process. These features are analyzed to provide the theoretical foundation for achieving transient-minimized DC fault protection, which eliminates high spikes in fault current, relieves stress on power devices in the system, and enhances transient stability. The effectiveness of this method is validated through simulation tests of a 100 MVA islanded hybrid microgrid using ZCBs based on experimentally verified models. Test results demonstrate that system oscillation is reduced by 13% in frequency and 74% in voltage, while completely eliminating voltage sags. With the help of ZCBs, the system also recovers more quickly after fault clearance. The results also demonstrate that the proposed method remains effective under various fault and load conditions. Full article

Silica aerogels are among the most extraordinary porous materials produced through sol–gel chemistry, distinguished by ultralow density, exceptionally high porosity, large specific surface area, and extremely low thermal conductivity. Despite these characteristics, widespread application of conventional silica aerogels has been constrained by inherent brittleness, poor mechanical strength, and moisture sensitivity. Significant research has therefore focused on silica aerogel composites, in which reinforcing or functional phases—fibers, polymers, carbon nanomaterials, metal oxides, and biopolymers—are integrated into the silica network to enhance mechanical robustness, flexibility, hydrothermal stability, electrical conductivity, catalytic activity, and multifunctionality while largely preserving the parent aerogel’s desirable properties. We review the synthesis, characterization, properties, and applications of silica aerogel composites. Sol–gel processing and drying technologies are discussed, followed by composite-formation strategies and the advanced techniques used to evaluate structural, mechanical, thermal, surface, and functional properties. The effects of reinforcing phases on mechanical performance, thermal conductivity, and hydrothermal stability are analyzed, and current and emerging applications in thermal insulation, environmental remediation, catalysis, acoustic damping, aerospace systems, biomedical engineering, and energy storage are highlighted. Finally, key challenges and future directions involving multifunctional materials, green synthesis, and data-driven materials design are discussed. Full article

The long-term safety of geological disposal facilities (GDFs) depends in part on the integrity of metallic waste canisters exposed to evolving thermal, geochemical and microbial conditions. Although abiotic corrosion is comparatively well characterised, the significance of microbiologically influenced corrosion (MIC) remains uncertain. This review critically compares carbon steel, stainless steel, copper, and titanium under GDF-relevant conditions, distinguishing chemical MIC (CMIC) from electrical MIC (EMIC) and examining the roles of sulphate-reducing bacteria, biofilms, and extracellular electron transfer. Reported behaviour varies markedly: carbon-steel studies have reported localised attack approaching 1 mm within 12 months, while SRB-associated copper corrosion rates of up to 9.8 μm year⁻¹ have been measured, yet other long-term experiments show little or no detectable microbial acceleration. These contrasts indicate that microbial presence alone is not predictive of corrosion severity; temperature, redox state, groundwater chemistry, bentonite density, nutrient availability, and passive-film stability are critical controls. The distinctive contribution of this review is an integrated, material-to-material assessment linking abiotic corrosion, CMIC and EMIC mechanisms with repository-specific environmental constraints, and current GDF development. It also identifies key uncertainties arising from methodological variability and short-term laboratory testing, supporting priorities for standardised, long-term, and in situ studies. Full article

Multivariate time series forecasting requires modeling both hierarchical temporal dynamics and complex inter-variable dependencies, a dual requirement that often degrades predictive performance and incurs high computational costs in standard Transformer architectures. Unlike current channel-independent models that ignore vital cross-variable synergies, or dense-attention frameworks that suffer from quadratic computational noise, our approach extracts structurally sparse dependencies. To address these specific limitations, this study introduces the FCA-Transformer. The proposed framework integrates a Feature Pyramid Network (FPN) to isolate macroscopic trends from high-frequency localized fluctuations via hierarchical downsampling. Concurrently, a structured Transformer-based Cross-Attention (TCA) mechanism employs Dimensional Segmentation with Weighting (DSW) and a Two-Stage Attention (TSA) layer to map topological variable interactions, effectively extracting robust cross-variable pathways and mitigating distributional noise. Extensive empirical evaluations across three real-world multivariate benchmarks (ETTh1, Electricity, and Exchange Rate) demonstrate that the FCA-Transformer achieves an average reduction of up to 4.39% in MSE and 5.11% in MAE compared to leading baselines. These findings indicate that the proposed architecture successfully reconciles multi-scale feature extraction with lightweight dependency modeling, enhancing structural generalization and providing a scalable framework for real-time temporal analysis in complex industrial environments. Full article

High-temperature proton-exchange membrane fuel cells (HT-PEMFCs) generate useful thermal energy that can be recovered for additional power production. This study investigates an integrated HT-PEMFC–organic Rankine cycle (ORC) system by combining response surface methodology (RSM) with thermodynamic energy analysis. A 17-run response-surface design was used to quantify the effects of pressure, temperature, and current density on polarization voltage. Power density was derived directly from the RSM-predicted voltage using P_d = iE to preserve physical consistency. The electrochemical model was benchmarked against published phosphoric-acid-doped polybenzimidazole HT-PEMFC polarization data under comparable conditions. The constrained optimization identified an operating condition of 400 kPa, 443 K, and approximately 1.198 A cm⁻², giving a predicted voltage of 0.5395 V and a power density of approximately 0.6462 W cm⁻². This represents a 12.9% increase in power density relative to the adopted reference condition. Separately, the reference thermodynamic case produced 13.08 kW of gross HT-PEMFC stack electrical power and 15.45 kW of thermal output assumed available to the ORC. The available legacy R409A reference case was evaluated at an evaporator pressure of 2 MPa, yielding approximately 1.24 kW of ORC net power and a net thermal efficiency of about 8.02%. The resulting combined modeled electrical output was approximately 14.32 kW before unmodeled balance-of-plant auxiliary power consumption, with the ORC contribution corresponding to about 9.5% of the gross HT-PEMFC stack output. The results demonstrate the complementary potential of physically consistent HT-PEMFC operating-condition optimization and waste-heat recovery, while the ORC results remain specific to the retained R409A reference dataset. Full article

Transcranial magnetic stimulation (TMS) enables non-invasive, focal modulation of cortical circuits by inducing electric currents in the brain through electromagnetic induction, thereby influencing neuronal excitability and synaptic plasticity. High inter- and intra-individual variability has led, however, to moderate efficacy and reproducibility of stimulation and treatment protocols, motivating a shift toward brain-state-dependent stimulation. Over the past decade, real-time phase-triggered EEG-TMS has established the oscillatory phase—particularly focusing on the sensorimotor mu rhythm—as a key determinant of cortical excitability and plasticity modulation. The field, however, remains largely confined to univariate, sensor-space analyses of local mu-rhythm phase, missing large-scale network dynamics. Recent advances in online EEG source reconstruction and multivariate machine and deep learning (ML/DL) approaches have begun to move beyond local phase toward whole-brain, network-level state estimation, achieving encouraging preliminary accuracies in predicting trial-by-trial cortical excitability, with promising applications in network-dysregulation conditions such as chronic pain. Integrating source-space reconstruction and individual biological variability, and adaptive ML/DL pipelines into closed-loop frameworks promises to move beyond generic stimulation protocols toward selective, network-targeted neuromodulation tailored to the individual’s dynamic brain state. Against this background, this review provides a critical overview of current achievements and limitations, while highlighting emerging methodological directions toward fully brain-state-adaptive and network-targeted EEG-TMS. We further present an illustrative use case of adaptive EEG-TMS for pain modulation, where treatment responses remain heterogeneous and the relevant dynamics are distributed across networks, and which therefore stands to gain most from individualized, network-targeted protocols. Full article

Electrochemical machining is widely recognized as a high-efficiency, low-cost and high-precision non-traditional machining technology for the manufacturing of turbine blade components. Nevertheless, in the practical electrochemical machining of turbine blades, the uneven spatial distribution of electric field intensity within the inter-electrode machining gap inevitably causes inconsistent anodic dissolution, which significantly deteriorates the final surface quality of machined blades. A set of comparative machining experiments were conducted on Inconel 625 superalloy. The experimental results fully verified that pulsed current machining could effectively improve the surface integrity and surface quality, and the optimal matching electrical parameters were successfully determined through systematic data analysis. The essential improvement mechanism lied in the effective suppression of stray current-induced scattered dissolution under pulsed power supply, which was highly consistent with the numerical simulation conclusions. Full article

Modelling of geothermal heat pump systems rarely integrates detailed surface and subsurface components. Simplifications such as neglecting the geothermal gradient, the different geological units intersected by the systems, and/or variable building loads, are common across current modeling approaches. These simplifications are particularly problematic for deep systems (e.g., >1 km). A new approach is presented to model a well doublet or a deep borehole heat exchanger (DBHE) with several heat pumps, which combines a comprehensive subsurface numerical model with codes capable of handling variable heat demand throughout the year. Groundwater flow and heat transfer are simulated with the subsurface model. Operating flow rates and number of activated heat pumps are adjusted during the simulation according to their efficiency and demand at a given time. Simulated heat production is constrained by technical and safety criteria to reflect realistic building conditions. The codes allow the simulation of cases in which the geothermal system is designed to partly meet demand, while maximizing its contribution. The thermal power production and electric consumption of the system are calculated. An illustrative example is provided for a sedimentary basin with a low geothermal gradient (~23.5 °C/km) using the Bécancour area in eastern Canada. Full article

A bidirectional DC–DC converter is the part that lets an electric vehicle both draw a fast charge and push power back during vehicle-to-grid (V2G) operation, so its control decides how well the DC link holds up when the load jumps or the power reverses. This paper sets out a full switching-level model of a synchronous half-bridge converter that sits between a 400 V battery pack and a 750 V DC link at 50 kW, and it controls that converter with a two-loop sliding-mode scheme: an inner sliding-mode current loop with a boundary layer to limit chatter and an outer loop that holds the link voltage. The controller is written out term by term and compared against a conventional PI cascade on the same plant. Under a 40 to 100 percent load step, the sliding-mode controller settles the link in 0.71 ms with a 2.42 percent dip, against 1.75 ms and 4.20 percent for the PI cascade, and its response barely changes when the inductor is 40 percent larger and its resistance is 50 percent higher than the controller assumes, which is the invariance property sliding-mode control is meant to give. Power reverses from full discharge to full charge in 0.255 ms, about four and a half times faster than the same PI cascade taken through the reversal. A converter loss model, with conduction evaluated per switch from the RMS current, puts peak efficiency at 98.69 percent near 23 kW and 98.39 percent at the rated 50 kW. The converter is then driven by a real-world charging-demand profile taken from 41,213 charging sessions recorded at the Newcastle Helix site, and it holds the DC link within 9.12 V across the day. Every figure comes from the accompanying code and can be regenerated. Full article

We review recent calculations and numerical simulations showing the formation of coherent states of protons in hydrogen-loaded metals with a cubic crystal lattice. The characteristic frequencies discussed here are the local proton frequency, the plasma frequency, and the resonant confined electromagnetic frequency; depending on the adopted parameters, they are of order ${10}^{13}$–${10}^{14}\mathrm{Hz}$. They are far from the much higher frequency corresponding to the full electron-capture energy transfer. In these states protons oscillate coherently and in a fixed phase relation with a strong high-frequency electric field which is trapped in the material, especially if the material is made of micro-powders. The energy gap of the coherent ground state is estimated to be well above thermal energies, of the order of a fraction of an eV per particle, and therefore large enough to make the state robust against thermal fluctuations. The analytical calculations address the realistic case of a large number of protons, in the rotating-wave approximation. The numerical calculations are presently limited to a small number of protons but go beyond the rotating-wave approximation and allow one to take into account a dissipation term associated with the strong oscillating electric field. The next task of this theoretical model is to compute the excited states of the coherent system. A simplified interacting-qubit model gives evidence of collective transition energies larger than the single-oscillator spacing. It does not yet establish whether a realistic external pump can populate such collective excited states with appreciable probability, nor the overall pump-to-capture conversion efficiency in a realistic proton lattice. If suitable states can be populated, their de-excitation could make some electron-capture processes energetically possible, with generation of slow neutrons. This dynamical mechanism offers an alternative to the Widom–Larsen hypothesis of “heavy electrons”, and is closer to current models in mainstream physics. The consequences, in terms of nuclear transmutations, of neutron generation via electron capture would be similar to those already known in the literature. Full article

Accurate battery state estimation is essential for electric-vehicle battery management systems (BMSs), directly improving their safety, durability, and operational reliability. This study proposes an integrated degradation-diagnosis framework that is, to our knowledge, among the first to combine electrochemical impedance spectroscopy (EIS), direct-current internal resistance (DCIR), and state of health (SoH) within a single, quantitative, low-complexity analysis of a hybrid-vehicle NCM811 lithium-ion battery module. Cycling-test data measured at 0, 400, 800, and 1200 cycles were reanalyzed using power-law regression, end-of-life (EOL) extrapolation, and cross-metric correlation analysis; the dataset was then extended to 2000 cycles (six checkpoints in total) to test the reliability of long-term lifetime prediction. Three findings are experimentally demonstrated. First, the ohmic resistance remained essentially constant during cycling, whereas the interfacial resistance increased by +422.7%, identifying interfacial (not bulk) resistance growth as the dominant degradation pathway. Second, power-law models substantially outperformed conventional exponential models for RE, DCIR, and SoH (R² = 0.998, 0.999, and 0.990, respectively, vs. R² = 0.870 for the exponential SoH model); extending the dataset from four to six checkpoints narrowed the resulting EOL model-form uncertainty from a 3.5-fold to a 1.6-fold discrepancy (2776 vs. 9831 cycles, narrowing to 3124 vs. 4908 cycles). Third, a strong linear relationship between DCIR and SoH (R² = 0.956) was obtained, indicating that resistance-only monitoring can approximate SoH without full impedance measurement. Beyond these demonstrated results, the proposed framework offers potential value for SoH estimation, battery condition diagnosis, and state-estimation algorithm development in advanced BMSs; these broader applications have not been experimentally validated in this study and are discussed as directions for future work. Full article