Search Results (209)

Currently, the shear-extrusion behavior of solid propellants (SPs), which comprise a significant volume fraction of micro-/nanoscale solid particles (e.g., octogen/HMX), nitroglycerin as a plasticizer/solvent, nitrocellulose as a binder, and other functional additives, is still insufficiently understood. While the rheology of highly filled polymers has been extensively documented, the rheological behavior of SPs within the practical processing temperature range of 80–95 °C remains poorly understood. This study investigated, in particular, the pressure dependence of the viscosity of SPs melts during steady-state shear flow. Steady-state shear measurements were conducted using a twin-bore capillary rheometer with capillary dies of varying diameters and lengths to explore the viscosity dependence of SPs. The results reveal that interface defects between octogen particles and the polymer matrix generate a melt pressure range of 3–30 MPa in the long capillary die, underscoring the non-negligible impact of pressure on the measured viscosity (η). At constant temperature and shear rate, the measured viscosity of SPs exhibits strong pressure dependence, showing notable deviations in pressure sensitivity (β), which was found to be greatly relevant to the contents of solvent and solid particles. Such discrepancies are attributed to the compressibility of particle–particle and particle–polymer networks during capillary flow. The findings emphasize the critical role of pressure effect on the rheological properties of SPs, which is essential for optimizing manufacturing processes and ensuring consistent propellant performance. Full article

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems. Full article

The durability of reinforced concrete structures in aggressive environments is strongly influenced by the ingress of chloride and other harmful ions, which is further complicated under partially saturated conditions, due to the coexistence of liquid and gas phases within the pore network. This study aimed to develop a predictive moisture–chemical–temperature model and to elucidate the mechanisms governing ion transport in partially saturated concrete. A multi-species hygro-chemo-thermo transport model was formulated based on the Nernst–Planck equation, incorporating electroneutrality, zero current conditions, and the coupled effects of moisture and temperature gradients. The model was numerically implemented using a parallel FE method with the Crank–Nicolson scheme, supported by domain decomposition and SPMD techniques for high computational efficiency. As a result, experimental validation was performed through chloride ponding tests under varying temperature conditions (20 °C, 35 °C, 50 °C), water-to-cement ratios (0.55, 0.65), and relative humidity differences (100%, 60%). The simulation results showed good agreement with the experimental data and confirmed that the proposed model can effectively predict chloride penetration under both isothermal and non-isothermal conditions. Additionally, the simulations revealed that moisture gradients accelerate ion transport, as the inward migration of the moisture front enhances the diffusion rates of chloride, sodium, and calcium ions until a steady-state moisture distribution is reached. Full article

In this paper, an advanced model of a switched reluctance generator (SRG) with mutual coupling, iron losses, and remanent magnetism is presented. The proposed equivalent circuit for each SRG phase is represented by the winding resistance, phase inductance and electromotive forces (EMFs) induced by mutual flux-linkage and remanent magnetism. In the advanced SRG model, the phase inductance and equivalent iron-loss resistance need not be known, as the components of the phase current flowing through them are determined directly from appropriate look-up tables, making the advanced SRG model simpler. Both the magnitude of the mutual flux-linkage and its time derivative are considered in the advanced model. The proposed model only requires knowledge of data that can be obtained using the DC excitation method and does not require knowledge of the SRG material properties. For the first time, the remanent magnetic flux of the SRG is modeled and the induced EMS caused by it is included in the advanced SRG model. Stray losses within the SRG are considered negligible. Connection to an asymmetric bridge converter is assumed. Magnetization angles of individual SRG phases are provided by the terminal voltage controller. The results obtained with the advanced SRG model are compared with experiments carried out in the steady-state of the 8/6 SRG with a rated power of 1.1 kW SRG over a wide range of load, terminal voltage, turn-on angle, and rotor speed in single-pulse mode suitable for high-speed applications. Full article

Background: Auditory steady-state responses (ASSRs) are sustained potentials used to assess the physiological integrity of the auditory pathway and objectively estimate hearing thresholds. ASSRs are typically analyzed using statistical procedures to remove the subjective bias of human operators. Knowing when to terminate signal averaging in ASSR testing is critical for making efficient clinical decisions and obtaining high-quality data in empirical research. Here, we report on stimulus-specific (frequency, level) properties and operating ranges of a novel ASSR detection metric based on mutual information (MI). Methods: ASSRs were measured in n = 10 normal-hearing listeners exposed to various stimuli varying in modulation rate (40, 80 Hz) and level (80–20 dB SPL). Results: MI-based classifiers applied to ASSR recordings showed that the accuracy of ASSR detection ranged from ~75 to 99% and was better for 40 compared to 80 Hz responses and for higher compared to lower stimulus levels. Receiver operating characteristics (ROCs) were used to establish normative ranges for MI for reliable ASSR detection across levels and rates (MI = 0.9–1.6). Relative to current statistics for ASSR identification (F-test), MI was a more efficient metric for determining the stopping criterion for signal averaging. Conclusions: Our results confirm that MI can be applied across a broad range of ASSR stimuli and might offer improvements to conventional objective techniques for ASSR detection. Full article

Microbial electrolysis cells (MECs) represent a pioneering technology for sustainable hydrogen production by leveraging bioelectrochemical processes. This study investigates the performance of a single-chamber cathodic MEC, where a cation exchange membrane separates the electrically active bioanode from the cathode. The system was constantly fed with a synthetic carbonaceous solution, employing a working potential of +0.3 V vs. SHE and an organic loading rate of 2 gCOD/Ld with a hydraulic retention time of 0.3 d. Notably, no methanogenic activity was detected, likely due to the establishment of an alkaline pH in the cathodic chamber. Under these conditions, the system exhibited good performance, achieving a current density of approximately 115 A/m³ and a hydrogen production rate of 1.28 m³/m³d. The corresponding energy consumption for hydrogen production resulted in 6.32 kWh/Nm³ H₂, resulting in a slightly higher energetic cost compared to conventional electrolysis; moreover, an average energy efficiency of 85% was reached during the steady-state condition. These results demonstrate the potential of MECs as an effective and sustainable approach for biohydrogen production by helping the development of greener energy solutions. Full article

In this study, a numerical investigation of unsteady natural convection heat transfer (HT) and entropy generation (EG) is performed within a trapezoid-shaped cavity containing thermally stratified water. The cavity’s bottom wall is heated, the sloped walls are thermally stratified, and the top wall is cooled. The finite volume (FV) method is employed to solve the governing equations. This study uses a Prandtl number (Pr) of 7.01 for water, an aspect ratio (AR) of 0.5, and Rayleigh numbers (Ra) varying between 10 and 10⁶. To examine the flow behavior within the cavity, various relevant parameters are determined for different Ra values. These parameters include streamline and isotherm contours, temperature time series, limit point and limit cycle analysis, average Nusselt number (Nu) at the heated walls, average entropy generation (E_avg), and average Bejan number (Be_avg). It is found that the flow transitions from a steady symmetrical state to a chaotic state as the Ra value increases. During this transition, three bifurcations occur. The first is a pitchfork bifurcation between Rayleigh numbers of 9 × 10⁴ and 10⁵, followed by a Hopf bifurcation between Rayleigh numbers of 10⁵ and 2 × 10⁵. Finally, another bifurcation occurs, shifting the flow from periodic to chaotic between Rayleigh numbers of 4 × 10⁵ and 5 × 10⁵. The present study shows an increase in E_avg of 94.97% between Rayleigh numbers of 10³ and 10⁶, while the rate of increase in Nu is 81.13%. The findings from this study will enhance understanding of the fluid flow phenomena in a trapezoid-shaped cavity filled with stratified water. The current numerical results are compared and validated against previously published numerical and experimental data. Full article

In this article, a new high step-up interleaved DC–DC converter is presented for renewable energy systems. The converter circuit is based on the interleaved two-phase boost converter and integrates a voltage-lift capacitor and a voltage multiplier cell. A high voltage gain of the converter can be achieved with a reasonable duty ratio and the voltage stresses of semiconductor devices are reduced. Because of low voltage stress, the switches with low on-resistance and the diodes with low forward voltage drops can be adopted to minimize the conduction losses. Additionally, the switching losses are reduced because the switches are turned on under zero-current switching (ZCS) conditions. Due to the existence of leakage inductances of the coupled inductors, the diode reverse-recovery problem is alleviated. Moreover, the leakage energy is recycled and the voltage spikes during switch turn-off are avoided. The parallel input architecture and interleaved operation reduce the input current ripple. The operating principles, steady-state characteristics, and design considerations of the presented converter are proposed in detail. Furthermore, a closed-loop control is designed to maintain a well-regulated output voltage despite variations in input voltage and output load. A prototype converter with a rated 1000 W output power is realized for demonstration. Finally, experimental results show the converter effectiveness and verify the theoretical analysis. Full article

The power transformer is a critical primary device in the power grid, and the verification of its winding mechanical stability is of paramount importance in ensuring the safe and stable operation of the power grid. In the conventional numerical calculation methods for verifying the mechanical stability of power transformer windings, the influence of temperature variations at the winding hot spots on winding mechanical stability has not been taken into account. In reality, factors such as the transformer’s operating load rate, ambient temperature, and the duration of short-circuit fault currents passing through will affect the mechanical stability margin of the transformer windings. Under conditions such as winding aging, deformation, or other reasons, the transformer windings may become unstable due to material parameter degradation, leading to insufficient mechanical stability margin. This paper analyzes the mechanical stability of power transformer windings considering the impact of the temperature field. Initially, a numerical model for calculating short-circuit currents in transformers was established to compute the short-circuit current under three-phase short-circuit-to-ground conditions as an excitation. Subsequently, a 3D electromagnetic force finite element calculation model was developed to determine the electromagnetic forces experienced under this condition. The results of the calculated electromagnetic forces were then used in a numerical calculation method to assess the mechanical stability of the windings. Furthermore, a 3D transformer electromagnetic–thermal flow finite element model was created to calculate the steady-state temperature rise under various operating conditions of the transformer. This model is validated through transformer temperature rise tests, and transient temperature rises under different operating conditions are calculated. The obtained data are fitted using the nonlinear least squares method to derive a fitting function for the winding hot spot temperature concerning load rate, ambient temperature, and short-circuit time. Taking into consideration the influence of temperature on the yield strength and modulus of elasticity of transformer winding materials, the variation in mechanical stability margin of transformer windings due to temperature effects is analyzed. Additionally, the operating domain for preventing the transformer from becoming unstable under three-phase short-circuit impacts is calculated for different degrees of material parameter degradation. This method provides an effective reference for transformer design and operation, demonstrating clear practical value. Full article

Modeling of friction stir welding (FSW) is challenging, as there are large gradients in both strain rate and temperature (typically between 450 and 500 °C in aluminum alloys) that must be accounted for in the constitutive law of the material being joined. Constitutive laws are most often calibrated using flow stresses from hot compression or hot torsion testing, where strain rates are much lower than those seen in the stir zone of the FSW process. As such, the current work employed a recently developed method to measure flow stresses at high strain rates and temperatures in AA 2219-T67, and these data were used in the development of a finite element (FE) simulation of FSW. Because heat generation during FSW is primarily a function of friction between the rapidly spinning tool and the plate, the choice of friction law and associated parameters were also studied with respect to FE model predictions. It was found that the Norton viscoplastic friction law provided the most accurate modeling results, for both the transient and steady-state phases of an FSW plunge experiment. It is likely that the superior performance of the Norton law was its ability to account for temperature and rate sensitivity of the plate material sheared by the tool, while the Tresca-limited Coulomb law favored contact pressure, with essentially no temperature or rate dependence of the local material properties. With optimized friction parameters and more accurate flow stresses for the weld zone, as measured by a high-pressure shear test, a 65% overall reduction in model error was achieved, compared to a model that employed a material law calibrated with hot compression or hot torsion test results. Model error was calculated as an equally weighted comparison of temperatures, torques, and forces with experimentally measured values. Full article

It is certain that electrical properties—whether slow (sec) or fast (nsec), even optical (fsec)—are described by Maxwell’s equations, and there are terms that depend on the rate of the change of the electric and magnetic fields. In particular, Maxwell’s equation for the curl of the magnetic field contains both the steady-state conduction current and a term depending upon the temporal derivative of the electric displacement field. The latter is referred to as the displacement current and is generally believed to have been included originally by Maxwell himself, although there is evidence it was earlier considered by Kirchhoff. Maxwell’s equations and Kirchoff’s circuit laws both are important over the wide range of frequencies with which electronics traditionally deal. Additionally, the displacement current is an important contribution to these in both classical and quantum mechanics. Here, the development of the displacement current, its importance in both classical and quantum mechanics, and some applications are provided to illustrate the fundamental role that it plays in the dynamics of a wide range of systems. Full article

An HVDC-GIL system with a conical spacer in a radioactive environment is studied in this work using simulated data on COMSOL^® Multiphysics. Electromagnetic simulations on a 2D model were performed with varying ion-pair generation rates and potential applied to the system. This article explores machine learning methods to derive time to steady state, dark current, gas conductivity, and surface charge density expressions. The focus was on constructing symbolic representations, which could be interpretable and less prone to overfitting, using the symbolic regression (SR) and sparse identification of nonlinear dynamics (SINDy) algorithms. The study successfully derived the intended expressions, demonstrating the power of symbolic regression. Predictions of dark currents in the gas–ground electrode interface reported an absolute error and mean absolute percentage error (MAPE) of 1.04 × ${10}^{-4}$ pA and 0.01%, respectively. The solid–ground electrode interface reported an error of 8.99 × ${10}^{-5}$ pA and MAPE of 0.04%, showing strong agreement with simulation data. Expressions for time to steady state had a test error of approximately 110 h with MAPE of around 3%. Steady-state gas conductivity expression achieved an absolute error of 0.55 log(S/m) and MAPE of 1%. An interpretable equation was created with SINDy to model the time evolution of surface charge density, achieving a root mean squared error of 1.12 nC/m²/s across time-series data. These results demonstrate the capability of SR and SINDy to provide interpretable and computationally efficient alternatives to time-consuming numerical simulations of HVDC systems under radiation conditions. While the model provides useful insights, performance and practical applications of the expressions can improve with more diverse datasets, which might include experimental data in the future. Full article

Heaters are critical components in various heating control systems, and their faults are often a primary cause of system failure, drawing significant attention from engineers and researchers. Early and accurate fault diagnosis is crucial to prevent cascading failures. Many diagnostic methods target faults under generally stable and simple operating conditions, such as constant load or steady-state temperature. However, real-world scenarios are often complex and variable, involving dynamic loads, nonlinear temperature rises, and other challenges, which limit diagnostic accuracy. To address this issue, this paper proposes an intelligent fault diagnosis model based on a one-dimensional convolutional neural network (CNN), using the heater’s current and voltage as the input to the neural network. The effectiveness and accuracy of the proposed model were validated through experimental data under two different conditions, achieving an average accuracy rate of 98%. The disconnection faults were generated during actual operation and occurred in the early stages, differing significantly from artificially simulated faults, thereby increasing the difficulty of accurate diagnosis. Analysis and comparison of the experimental results demonstrate the feasibility of the intelligent diagnostic model and its high diagnostic accuracy. Full article

Currently, steady-state analysis predominates in combustion chamber design, while dynamic combustion characteristics remain underexplored, and there is a lack of a comprehensive index system to assess dynamic combustion behavior. This study conducts a numerical simulation of the dynamic characteristics of the combustion chamber, employing a method combining large eddy simulation (LES) and Flamelet Generated Manifold (FGM). The inlet air temperature, air flow rate, and fuel flow rate were varied by 1%, 2%, and 3%, respectively, with a pulsation period of 0.008 s. The effects of nine different inlet parameter pulsations on both time-averaged and instantaneous combustion performance were analyzed and compared to benchmark conditions. The results indicate that small pulsations in the inlet parameters have minimal impact on the steady-state time-averaged performance. In the region near the cyclone outlet, which corresponds to the flame root area, pronounced unsteady flame characteristics were observed. Fluctuations in inlet parameters led to an increase in temperature fluctuations near the flame root. Analysis of the outlet temperature results for each operating condition reveals that inlet parameter fluctuations can mitigate the inherent combustion instability of the combustion chamber and reduce temperature fluctuations at the outlet hot spot. Full article

The limits of direct current (DC) injection and output current distortion of grid-connected photovoltaic (PV) inverters are specified in the IEEE 1547-2018 standard. The standard prescribes limits of output current harmonics, but the input voltage and power at which output current distortion is measured are not specified. This manuscript presents the results of DC injection and output current distortion measurements for three commercial single-phase PV inverters, with 3 kVA, 3.3 kVA, and 6 kVA rated power. During the measurements, the inverters are powered by a programmable DC source that emulates the power voltage characteristic of a PV array, providing different input conditions. In addition to steady-state measurements at constant input voltage and power, the change in the output current spectrum over time during the maximum power point tracking (MPPT) is also measured. The results show that the output current distortion depends on the input voltage and power. Moreover, the current distortion of some of the tested inverters exceeds the limits specified by the standard in some cases. The presented results suggest that further research on the dependence of the output current distortion from PV inverters on their input power and voltage is needed. Full article