Search Results (684)

Both the CESM-simulated NNU-2K dataset and proxy reconstructions of Indian Summer Monsoon (ISM) precipitation over the past two millennia reveal a significant centennial-scale period, including periodicities of 105, 150, and 200 years. The 105- and 200-year cycles identified in the NNU-2K all-forcing (AF) experiment closely match those found in the volcanic single-forcing (Vol) experiment, suggesting that volcanic activity is a major driver of these variations. Volcanic forcing induces global cooling, which reduces the land–sea thermal contrast and weakens the monsoon circulation. Furthermore, stronger cooling in the Northern Hemisphere decreases the interhemispheric temperature gradient and weakens the trans-equatorial pressure gradient. This, in turn, suppresses cross-equatorial low-level flow from the Southern Hemisphere, further reducing ISM precipitation. The 105- and 150-year periodicities are also consistent with those in the total solar irradiance (TSI) single-forcing experiment, indicating a substantial response to solar variability. Increased solar irradiance enhances Northern Hemisphere warming, strengthening both the interhemispheric temperature gradient and the cross-equatorial pressure gradient. These changes facilitate stronger northward cross-equatorial flow in the lower troposphere, intensifying the ISM and increasing precipitation. Concurrently, solar forcing amplifies the thermal contrast between the Eurasian continent and the Indian Ocean, further reinforcing monsoon circulation. The 150-year cycle is also evident in the control (Ctrl) experiment, implicating internal climate variability as an additional mechanism. Analysis reveals a quasi-decadal Pacific Decadal Oscillation (PDO)-like sea surface temperature anomaly in the North Pacific. Its negative phase is linked to reduced sea-level pressure over the ISM region, enhanced low-level convergence, and increased precipitation. It also strengthens the Mascarene High over the Indian Ocean, intensifying the Somali Jet and southwesterly monsoon winds, which promote greater moisture transport into the ISM domain. Full article

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short circuits. It is therefore necessary to detect ITSCs at an early stage. In the literature, ITSC detection is often based on current signal processing methods. One of the challenges that these methods face is the presence of imperfections in the stator coils, which also affects the three-phase symmetry. Moreover, when the stator coils are connected in parallel, this type of fault becomes important, as circulating currents will flow between the parallel windings. This, in turn, increases the thermal stress on the insulation and the permanent magnets, while also exacerbating the vibrations of the generator. In this study, a finite-element analysis (FEA) model has been developed to simulate a dual-rotor PMSG under conditions of coil asymmetry. To further investigate the impact of this asymmetry, mathematical modeling has been conducted. For fault detection, negative-sequence current (NSC) analysis and torque monitoring have been used to distinguish coil asymmetry from ITSCs. While both methods demonstrate potential for fault identification, NSC induced small amplitudes and the torque analysis was unable to detect ITSCs under low-severity conditions, thereby underscoring the importance of developing advanced strategies for early-stage ITSC detection. The innovative aspect of this work is that, despite these limitations, the combined use of NSC phase-angle tracking and torque harmonic analysis provides, for the first time in a core-less PMSG with parallel-connected coils, a practical way to distinguish ITSC from coil asymmetry, even though both faults produce almost identical signatures in conventional current-based indices. Full article

This study presents the design and development, fabrication, and experimental testing of a four-circular-coil system capable of generating controlled, very low-frequency magnetic fields for biomedical applications. The system is tailored for use with a bioreactor cultivating mesenchymal stem cells, ensuring highly uniform magnetic fields within the area of interest (AOI). An asymptotic approach—the Multiple-Turn Thin-Wire Approximation (MTTWA)—was employed for fast calculations and modeling of multi-turn coil systems with massive windings. The MTTWA-calculated magnetic field distribution of the four-multi-turn coil system was verified with Ansys Maxwell simulations, showing good agreement. The coils and coil system were designed and fabricated, along with a prototype of the exposure system to validate both numerical modeling and simulation results, achieving magnetic field uniformity of at least 97% within the AOI. In the fabricated four-coil exposure setup, symmetric coils are connected in parallel with two separate amplifier-controlled outputs, enabling precise adjustment of field strength, uniformity, and intentional inhomogeneity for specialized experiments. An automated measurement system has been designed and fabricated to measure the magnetic field within the AOI volume with a spatial resolution of 1 mm. Full article

With the development of distributed energy sources such as photovoltaic and wind power, power grids have imposed increasingly higher requirements on power quality. As common nonlinear loads in power grids, multi-pulse rectifiers (MPRs) inject significant harmonics into the grid side. To reduce harmonic pollution at the source, this paper proposes a novel triple-passive harmonic suppression method to reduce the input current harmonics of MPRs. The proposed 48-pulse rectifier comprises a main circuit based on delta-connected auto-transformer (DCT) and a triple-passive harmonic suppression circuit (TPHSC). The TPHSC consists of two interphase reactors (IPRs) and eight diodes. Based on Kirchhoff’s Current Law (KCL), the output currents of the main circuit are calculated, and the operating modes of the TPHSC are analyzed. From the main circuit’s output currents and the DCT topology, the rectifier’s input currents are derived, and the optimal turns ratio of the IPRs for minimizing the input current total harmonic distortion (THD) is determined. The total capacity of the IPRs accounts for only 2.3% of the output load power. Experimental results show that the measured input current THD is close to the theoretical value of 3.8%. Overall, the proposed rectifier offers a cost-effective solution with stronger harmonic suppression capability, making it suitable for applications requiring low grid harmonic pollution. Full article

Inter-turn short-circuit (ITSC) faults in motor drives can induce substantial circulating currents and localized thermal stress, ultimately degrading winding insulation and compromising torque stability. To enhance the operational reliability of open-winding (OW) five-phase fault-tolerant fractional-slot concentrated-winding interior permanent-magnet (FTFSCW-IPM) motor drive systems, this paper proposes a real-time fault-tolerant control strategy that provides current suppression and torque stabilization under ITSC conditions. Upon fault detection, the affected phase is actively isolated and connected to an external dissipative resistor, thereby limiting the fault-phase current and inhibiting further propagation of insulation damage. This reconfiguration allows the drive system to uniformly accommodate both open-circuit (OC) and ITSC scenarios without modification of the underlying control architecture. For OC operation, an equal-amplitude modulation scheme based on carrier-based pulse-width modulation (CPWM) is formulated to preserve the required magnetomotive-force distribution. Under ITSC conditions, a feedforward compensation mechanism is introduced to counteract the disturbance generated by the short-circuit loop. A principal contribution of this work is the derivation of a compensation term that can be estimated online using zero-sequence voltage (ZSV) together with measured phase currents, enabling accurate adaptation across varying ITSC severities. Simulation and experimental results demonstrate that the proposed method effectively suppresses fault-phase current, maintains near-sinusoidal current waveforms in the remaining healthy phases, and stabilizes torque production over a wide range of fault and load conditions. Full article

Economic and technological factors necessitate the use of alternative fuels during oil shale combustion, a process that generates substantial amounts of solid waste with varying ash compositions. This study evaluates the potential of two such waste materials: (i) fly ash derived from the combustion of oil shale (a fine particulate residue from burning crushed shale rock, sometimes combined with biomass), and (ii) short carbon fibres recovered from the pyrolysis (a process of decomposing materials at high temperatures in the absence of oxygen) of waste wind turbine blades. Oil shale ash from two different sources was investigated as a partial cement replacement, while recycled short carbon fibres (rCFs) were incorporated to enhance the functional properties of mortar composites. Results showed that carbonate-rich ash promoted the formation of higher amounts of monocarboaluminate (a crystalline hydration product in cement chemistry), leading to a refined pore structure and increased volumes of reaction products—primarily calcium silicate hydrates (C–S–H, critical compounds for cement strength). The findings indicate that the mineralogical composition of the modified binder (the mixture that holds solid particles together in mortar), rather than the fibre content, is the dominant factor in achieving a dense microstructure. This, in turn, enhances resistance to water ingress and improves mechanical performance under long-term hydration and freeze–thaw exposure. Life cycle assessment (LCA, a method to evaluate environmental impacts across a product’s lifespan) further demonstrated that combining complex binders with rCFs can significantly reduce the environmental impacts of cement production, particularly in terms of global warming potential (−4225 kg CO₂ eq), terrestrial ecotoxicity (−1651 kg 1,4-DCB), human non-carcinogenic toxicity (−2280 kg 1,4-DCB), and fossil resource scarcity (−422 kg oil eq). Overall, the integrative use of OSA and rCF presents a sustainable alternative to conventional cement, aligning with principles of waste recovery and reuse, while providing a foundation for the development of next-generation binder systems. Full article

The possibility of determining the phase and current errors of an existing or newly designed current instrument transformer on the basis of special characteristics of the core material is examined. One of the characteristics represents the dependence between the magnetic field intensity on the core sheet surface, measured at the instant when induction is at its peak, and the mean peak induction in the cross section of the sheet. The other characteristic represents the dependence between the field intensity value measured at the instant when induction passes through zero and the peak induction value. The characteristics must be determined for the sinusoidal shape of the induction curve. The secondary winding of the current instrument transformer should be uniformly distributed along the core. One must know the following: the number of turns in the primary and secondary winding, respectively, the resistance of the secondary winding and the resistance at the secondary winding output when the primary current is being converted. Indicated relations provide a clear formula for designing effective current transformers. The main contribution of this paper is to present the method for estimating the parameters of current transformer a priori, relying on characteristics of the core material. However, this formula combined with elements of artificial intelligence—nature-inspired optimization algorithms—results in a convenient tool for optimal core geometry design. The paper presents an extension of the method to a smart design approach with application of the Birch-inspired Optimization Algorithm (BiOA). Full article

The downstream decay of induced swirling flow within an internal passage has implications for heat transfer enhancement, species mixing, and combustion processes. For this paper, swirling flow in an internal passage was investigated using both experimental and computational techniques. Two staggered rows of 8 vanes each with an NACA 0015 profile, intended to turn the near-wall flow 45° to the flow direction, were installed on the top and bottom surfaces of the Roughness Internal Flow Tunnel (RIFT) wind tunnel. The vanes induced opposite lateral components in—the flow near the upper and lower surfaces of the rectangular test section of the RIFT and induced a swirling flow pattern within the passage. A 4-camera tomographic particle tracking velocimetry (PTV) system was used to evaluate airflow within a 40 mm × 40 mm × 60 mm measurement volume at the tunnel midline 0.5 m downstream of the induced swirl. Mean flow velocity measurements were collected at hydraulic diameter-based Reynolds numbers of 10,000, 20,000, and 30,000. To validate PTV measurements, particularly the camera-plane normal component of velocity, traces across the measurement volume were taken using a five-hole probe. The results of both measurement methods were compared to a computational simulation of the entire RIFT test section using a shear stress transport (SST) k-ω, Improved Delayed Detached Eddy Simulation (IDDES) turbulence model. The combined particle tracking measurements and five-hole probe measurements provide a method of investigating the turbulent flow model and simulation results, which are needed for future simulations of flows found inside swirl-inducing combustor nozzles. Full article

With the large-scale integration of wind power into the grid, the accuracy of wind farm cluster power prediction has become a key factor for the sustainability of modern power systems. Reliable ultra-short-term forecasts support the secure dispatch of high-penetration renewable energy, reduce wind curtailment, and improve the low-carbon and economical operation of power systems. Aiming at the problem of significant differences in wind turbine characteristics, this paper proposes a prediction method based on an improved density-based spatial clustering of applications with noise (DBSCAN) and a hybrid deep learning model. First, the wind speed signal is decomposed at multiple scales using successive variational modal decomposition (SVMD) to reduce non-stationarity. Subsequently, the DBSCAN parameters are optimized by the fruit fly optimization algorithm (FOA), and dimensionality reduction is performed by principal component analysis (PCA) to achieve efficient clustering of wind turbines. Next, the representative turbines with the highest correlation are selected in each cluster to reduce computational complexity. Finally, the SVMD-TCN-BiGRU-MSA-GJO hybrid model is constructed, and long-term dependence is extracted using a temporal convolutional network (TCN); the temporal features are captured by bidirectional gated recurrent units (BiGRUs); the feature weights are optimized by a multi-head self-attention mechanism (MSA), and the hyper-parameters are, in turn, optimized by golden jackal optimization (GJO). The experimental results show that this method reduces the MAE, RMSE, and MAPE by 14.02%, 12.9%, and 13.84%, respectively, and improves R² by 3.9% on average compared with the traditional model, which significantly improves prediction accuracy and stability. These improvements enable more accurate scheduling of wind power, lower reserve requirements, and enhanced stability and sustainability of power system operation under high renewable penetration. Full article

An increase in the temperature of the magnetic core causes narrowing of its hysteresis loop and reduction in the saturation magnetic flux density. Therefore, at the same operating point on the magnetization characteristic, the nonlinear effect may become stronger. In the case of the inductive current transformers, this may result in change in their transformation accuracy and increased self-generation of the low-order higher harmonics to the secondary current. Consequently, the equivalent methods used to determine their values of current error and phase displacement without operating conditions resulting from the presence of the secondary current provide less reliable results, which is particularly important for inductive current transformers with high transformation accuracy requirements and may also be significant in certain borderline cases when determining its accuracy class and the value of error is close to the limit. However, ambient temperature does not affect the transformation accuracy of conventional inductive current transformers, as their internal operating temperature is solely driven by the relatively high RMS values of the rated secondary current (1 A or 5 A) and the large number of secondary winding turns evenly distributed over the magnetic core. During thermal testing of a current transducer operating in a closed-loop feedback configuration with a Hall sensor, a deterioration of its conversion accuracy was observed at high ambient temperatures. This was caused primarily by the thermal expansion of the magnetic core, which leads to a change in the dimensions of the air gap where the Hall sensor is placed, and thus also to a change in the electrical parameters of the feedback loop circuit. Full article

Winding numbers are key indices in the depiction, modelling, and testing of dynamical processes. They capture phase progression on closed curves and are robust for quasiperiodic dynamics, but their status for chaotic Poincaré sections is unclear. This study tests whether any non-trivial winding-type index can be extracted from chaotic Poincaré maps using three approaches: (i) phase-angle analysis, (ii) Kabsch optimal-rotation estimation, and (iii) local turning-angle averaging. To benchmark feasibility and error, we compare four systems: the standard circle map, the same circle map embedded on two planar fractal curves (Koch snowflake and Hilbert curve), a quasiperiodic Duffing–van der Pol (DVP) Poincaré map, and a chaotic DVP Poincaré map. For the quasiperiodic map, all methods yield consistent, accurate winding numbers. For the transitional systems (circle map and its fractal embeddings), indices remain non-trivial but more deviated. In stark contrast, chaotic Poincaré maps produce only trivial indices across all methods. These results indicate a crucial fact about the modelling of chaotic Poincaré maps. That is, although being fractal, they are not merely chaotic maps on fractal curves; rather, they reflect a tighter coupling of geometry and dynamics. Practically, the recoverability of a non-trivial winding index offers a simple diagnostic to distinguish quasiperiodicity from chaos in Poincaré data or corresponding models. The constructed chaotic-map-on-fractal systems also act as test-bed models that bridge ideal one-dimensional mappings and realistic two-dimensional Poincaré sections. Full article

This paper introduces a new four-switch, high-voltage, high-step-up converter employing two transformers. The topology enables Zero-Voltage Switching (ZVS) across all primary switches for operating conditions ranging from no load to full load. A voltage-quadrupler and a voltage-doubler rectifier are used on the secondary sides of the transformers, enabling reduced turn-off current for the voltage-quadrupler diodes and Zero-Current Switching (ZCS) turn-off for the voltage-doubler diodes, thereby ensuring high efficiency across diverse load levels. Notably, the voltage stress experienced by the voltage-multiplier diodes is significantly lower than the output voltage, thereby rendering the converter exceptionally suitable for high-voltage applications such as electron beam welding (EBW). The voltage gain surpasses that of the conventional phase-shift full-bridge (PSFB) converter, permitting a lower transformer turns ratio and thus reducing winding resistivity. The removal of the substantial output inductor leads to a lighter and more compact design, eliminating insulation concerns associated with inductor windings. This paper details the operation of the proposed converter, supported by experimental results from a 500-W prototype with a 150-V input and 2-kV output, which confirm its high performance and operational advantages. Full article

Storm surge dynamics in coastal zones and estuaries are complex, driven by coupled oceanic and terrestrial interactions that enhance the risk of coastal disasters. This study investigates storm surge characteristics and mechanisms in the Macao Cross Tidal Channel (MCTC), located in the Macao Sea Area (MSA). A tide-surge coupled numerical model was established using the unstructured grid Finite Volume Community Ocean Model (FVCOM). The model was rigorously validated against tide gauge data from Typhoon Hato, demonstrating strong performance, with a skill score of 0.95 and a correlation coefficient exceeding 0.94. The spatiotemporal characteristics and mechanisms of storm surge dynamics in the MCTC were elucidated. The results show that the MCTC’s complex geometry induces a geometric funneling effect, which substantially amplifies the storm surge compared with adjacent locations in the estuary and open sea. During the typhoon period, coastal geomorphology affects winds, tide levels, currents, and waves, which in turn spatially and temporally modulate the storm surge. Wind is the primary driver, but its effect is modulated by nonlinear interactions with waves, including enhanced bottom friction and wave set-down. In isolation, the wind-induced component contributed approximately 106% of the peak total surge. This overestimation quantitatively highlights the critical role of nonlinear interactions, where wave-enhanced bottom friction acts as a major energy sink, and wave set-down directly suppresses the water level at the channel entrance. The individual peak contributions from atmospheric pressure and wave were approximately 5% and 17%, respectively, but these peaks occurred out of phase with the storm surge. Energy transformation analysis based on the Bernoulli principle revealed a distinct conversion from potential to kinetic energy in the constricted transverse waterway, while the longitudinal waterway exhibited a more gradual energy change. These findings enhance the mechanistic understanding of storm surges in complex, constricted estuaries and can inform targeted strategies for coastal hazard mitigation in the Macao region. Full article

This study presents a pulse generator employing a saturable pulse transformer (SPT) in conjunction with a fast recovery diode, integrated within an all-solid-state pulse-forming network (PFN). The saturation inductance of the SPT serves as a component of the initial LC section of the PFN, thereby contributing to the preservation of output waveform integrity. The secondary energy storage capacitor is charged through the primary circuit and the SPT, subsequently discharging into the load under the regulation of the SPT. An increase in the SPT’s transformation ratio corresponds to a rise in its saturated inductance, which in turn prolongs the pulse rise time. To mitigate this effect, a fast recovery diode is incorporated to sharpen the pulse front. Specifically, upon saturation of the SPT, current reverses through the fast recovery diode, effectively short-circuiting the load. When the inductor current attains a predetermined threshold, the diode reverts to reverse cut-off and rapidly switches off, enabling the PFN to discharge swiftly into the load and generate a high-voltage pulse characterized by a rapid rising edge. Furthermore, augmenting the number of secondary windings on the SPT—each connected to a PFN module—and arranging multiple PFNs in series facilitates an increase in output voltage. Experimental evaluations demonstrated that a three-stage PFN pulse generator attained a peak voltage of −16.9 kV on an 80 Ω matched load, with pulse currents exceeding 200 A while maintaining a 19 ns front edge. These results indicate that the proposed approach is effective for producing high-voltage, narrow pulses with rapid rise times. Additionally, the pulse power generator is capable of delivering repetitive pulses of −16.9 kV at a frequency of 20 kHz in burst mode. Full article

Efficient wind power forecasting is critical in achieving large-scale integration of wind energy in modern electricity systems. On the other hand, limited availability of wealthy, long-term historical data of wind power generation for many sites of interest often challenges the training of tailored forecasting models, which, in turn, introduces uncertainty concerning the anticipated operational status of similar early-life, or even prospective, wind farm projects. To that end, this study puts forward a spatiotemporal, national-level forecasting exercise as a means of addressing wind power data scarcity in Greece. It does so by developing a hybrid wavelet-enhanced deep learning model that leverages long-term historical data from a reference site located in central Greece. The model is optimized for 24-h day-ahead forecasting, using a hybrid architecture that incorporates discrete wavelet transform for feature extraction, with deep neural networks for spatiotemporal learning. Accordingly, the model’s generalization is evaluated across a number of geographically distributed sites of different quality wind potential, each constrained to only one year of available data. The analysis compares forecasting performance between the original and target sites to assess spatiotemporal robustness of the model without site-specific retraining. Our results demonstrate that the developed model maintains competitive accuracy across data-scarce locations for the first 12 h of the day-ahead forecasting horizon, designating, at the same time, distinct performance patterns, dependent on the geographical and wind potential quality dimensions of the examined areas. Overall, this work underscores the feasibility of leveraging data-rich regions to inform forecasting in under-instrumented areas and contributes to the broader discourse on spatial generalization in renewable energy modeling and planning. Full article