Current Fluctuations Research Articles

Current fluctuations in finite-sized one-dimensional non-interacting passive and active systems

Abstract We investigate the problem of effusion of particles initially confined in a finite one-dimensional box of size $L$. We study both passive as well active scenarios, involving non-interacting diffusive particles and run-and-tumble particles, respectively. We derive analytic results for the fluctuations in the number of particles exiting the boundaries of the finite confining box. The statistical properties of this quantity crucially depend on how the system is prepared initially. Two common types of averages employed to understand the impact of initial conditions in stochastic systems are annealed and quenched averages. It is well known that for an infinitely extended system, these different initial conditions produce quantitatively different fluctuations, even in the infinite time limit. We demonstrate explicitly that in finite systems, annealed and quenched fluctuations become equal beyond a system-size dependent timescale, $t \sim L^2$. For diffusing particles, the fluctuations exhibit a $\sqrt{t}$ growth at short times and decay as $1/\sqrt{t}$ for time scales, $t \gg L^2/D$, where $D$ is the diffusion constant. Meanwhile, for run-and-tumble particles, the fluctuations grow linearly at short times and then decay as $1/\sqrt{t}$ for time scales, $t \gg L^2/D_{\text{eff}}$, where $D_{\text{eff}}$ represents the effective diffusive constant for run-and-tumble particles. To study the effect of confinement in detail, we also analyze two different setups (i) with one reflecting boundary and (ii) with both boundaries open.

Holistic Dynamic Modeling and Simulation of Alkaline Water Electrolysis Systems Based on Heat Current Method

Hydrogen production technology is becoming increasingly important with the rapid development of hydrogen energy. Among existing hydrogen production technologies, alkaline water electrolysis (AWE) is drawing wide attention due to its advantages such as high maturity and low cost, and its performance analysis and optimization are important for applications. However, the AWE system contains processes with different physical and mathematical properties such as electrochemical reaction and heat transport processes, bringing difficulties to the system modeling. Moreover, the electrical and thermal processes have different characteristic time scales, and the system shows a sophisticated dynamic behavior, which has not been well studied yet. Here, a homomorphic dynamic model of the AWE system in the form of electrical circuit is built to describe the thermal and electrochemical processes uniformly, where the two parts are integrated via the energy conservation seamlessly. The model is verified by comparing with the experimental data and shows a high accuracy. The dynamic simulation analysis is conducted to investigate the dynamic response characteristics of the system under current step changes and fluctuations. The temperature overshoot and oscillation phenomena caused by delays in heat transport processes are studied. Results show that the time delay yields a maximum temperature overshoot of 10 °C, which would reduce the lifespan of the stack. This also highlights the importance of dynamic system analysis.

Analysis of Permanent Magnet Demagnetization during the Starting Process of a Line-start Permanent Magnet Synchronous Motor

Neodymium (NdFeB) rare earth Permanent Magnets (PMs) are widely used in the manufacturing of Line-Start Permanent Magnet Synchronous Motors (LSPMSMs). During the initial startup of LSPMSMs, irreversible PM demagnetization often occurs. This research provides a thorough examination of the PM demagnetization process during the initiation of a 15-kW, 3000-rpm LSPMSM, which was converted from a squirrel-cage Induction Motor (IM) featuring a 3-bar PM. Utilizing Ansys/Maxwell2D software for simulations and conducting experiments, this study reveals that upon starting the LSPMSM, demagnetization occurs at the two outermost PM pairs. This leads to unstable motor operation at synchronous speed, significant current fluctuations, and a substantial decrease in performance. The findings suggest that to ensure effective LSPMSM operation, it is crucial to either restrict frequent restarts or select an appropriate PM type to prevent partially irreversible demagnetization, thereby enhancing power efficiency.

A new optimal space vector modulation with DTC switching strategy for induction motor control

Efforts to achieve swift and precise dynamic torque control have been central in AC drive research. Recent advancements in embedded computer systems have highlighted direct torque control (DTC) and field-oriented control (FOC) as key methods for enhancing torque dynamics, both utilizing space vector modulation (SVM) to optimize voltage source inverter positioning. This study introduces a novel synthesis by integrating DTC with SVM to address limitations in conventional DTC, which suffers from limited voltage vector availability, leading to undesirable torque behavior and significant current fluctuations. The primary goal is to develop an optimal switching modulator for the fastest torque response through the combined application of DTC and SVM. The proposed strategy optimizes DC bus usage, reduces torque fluctuations, minimizes total harmonic distortion in AC motor current, decreases switching losses, and ensures seamless digital system integration. Simulations using MATLAB/SIMULINK demonstrate significant torque, current, and flux linkage ripple reductions, validating the approach's effectiveness. This integration overcomes established limitations, extending the capabilities of motor control methodologies and offering enhanced performance and operational integrity in induction motor drive systems.

Current fluctuations of a self-interacting diffusion on a ring

Abstract We investigate fluctuations in the average speed or current of a self-interacting diffusion (SID) on a ring, mimicking the non-Markovian behaviour of an agent influenced by its own path. We derive the SID's phase diagram, showing a delocalisation-localisation phase transition from self-repelling to self-attracting. Current fluctuations are analysed using: (i) an adiabatic approximation, where the system reaches its stationary distribution before developing current fluctuations, and (ii) an original extension of level 2.5 large deviations for Markov processes combined with perturbation theory. Both methods provide upper bounds to current fluctuations, with the former tighter than the latter in all localised regimes, and both equally tight in the self-repelling region. Both methods accurately estimate the asymptotic variance and suggests a phase transition at the onset of the localised regime.

Advanced transient switching and coordinated power control strategies for flexible interconnection of multiple microgrids

Multiple microgrid (MG) distribution systems are facing challenges owing to variations in the operational statuses of the individual MGs, which experience voltage and current fluctuations during transient interconnections. The impedances of the interconnecting lines further exacerbate the unevenness of power distribution among the MGs, hence threatening the operational stability of the system. To achieve flexible and seamless interconnections between multiple MGs, we fully analyzed the interconnected structures and operation modes of the MGs; then, we designed a transient switching control method based on investigation of the transient interconnection processes to ensure smooth transition of the MGs. Additionally, to balance the power distribution among the interconnected MGs, a voltage–current-based coordinated power control strategy was synthesized using advanced synchronized fixed-frequency technology. Simulation case studies were conducted, and the results indicate that the proposed coordinated power control scheme effectively facilitated instantaneous interconnections between the isolated regions, thereby avoiding voltage disturbances and current surges. Furthermore, it efficiently equalized and distributed the output power from the distributed energy sources, thereby enhancing the operational flexibilities and stabilities of the MGs and distribution system.

Propagation gap for shear waves in binary liquids: Analytical and simulation study.

Transverse collective excitations in 50-50 and 80-20 Lennard-Jones binary liquid mixtures are studied for different mass ratio of components R at fixed numerical densities. Increasing the mass ratio results in a growing difference between frequencies of shear waves and transverse optic modes. We report an increase in the propagation gap width for shear waves with mass ratio of components and compare it to the gap width expression, known from the transverse dynamics of simple liquids. A four-variable dynamic model of transverse dynamics in binary liquids with an account of cross correlations between total-mass and mass-concentration transverse current fluctuations is solved analytically in the long-wavelength region. An equation for the propagation gap of shear waves for binary liquids is reported and analyzed.

Analysis on density of states and ION/IOFF ratio of GaN/GaN-graphene nanoribbon tunnel FET for enhanced bio-sensing applications

Abstract This research introduces a new analytical model that studies the effect of ferro-dielectric on the operational performance of TFETs doped with halogens. The effect of source and drain depletions, voltage-drain & gate, thickness and capacitance of gate insulator are all investigated in this study. Accurate measurements of the surface potential are required to ascertain the transconductance, gate-to-drain capacitance, and lateral electric field of the device. Our model, which employs Ferroelectric Halo-Doped double gate (FHDD)-gated device designs, has been demonstrated to produce results that nearly match those produced from TCAD simulations. This was accomplished by doing a comparative analysis of the outcomes derived from both sets of simulations. Furthermore, the performance of the suggested structure of TFET, which integrates a dielectric of Fe and GaN heterostructure, surpasses that of other similar devices (fT) in terms of ON current, ON/OFF ratio, transconductance, and cut-off frequency. A ferroelectric dielectric was used to create a ferroelectric heterostructure. This study also centers on the creation and application of a graphene nanoribbon field effect transistor (GNR-TFET) to detect sugar molecules, specifically fructose, xylose, and glucose. The detecting signal is generated by utilizing the fluctuation in the electrical current of the GNR-TFET caused by the presence of individual sugar molecules. The GNR-TFET exhibits noticeable variations in the density of states, transmission spectrum, and current when exposed to individual sugar molecules. The sensor under investigation is being developed and examined using a combination of semi-empirical modeling and non-equilibrium Green's functional theory (SE + NEGF). According to the research, the modified GNR TFET has the ability to quickly and accurately detect individual sugar molecules in real-time.

Optimization of chemical engineering control for large-scale alkaline electrolysis systems based on renewable energy sources

In the context of renewable energy, dynamic control is crucial for large-scale alkaline water electrolysis systems. Under traditional Proportional-Integral-Derivative (PID) control, the system's temperature and impurity levels may exceed safe limits during sudden load changes, compromising system safety. Therefore, this study proposes a control strategy based on mathematical models of system temperature and impurities, including Model Predictive Control (MPC) for temperature and Optimal Curve Tracking (OCT) for impurities. The MPC controller offsets the disturbances in temperature caused by current fluctuations through state prediction, while the OCT controller ensures that impurity levels remain within safe limits. Real-time application of these control strategies is achieved through MATLAB-PLC communication, validating controller performance. Experimental results show that the MPC controller exhibits excellent dynamic response and stability in controlling the stack temperature, with a maximum temperature peak deviation of only 2.9 K and a temperature fluctuation range of 5.9 K. This represents a reduction of 1.6 K in peak deviation compared to traditional PID controllers and significantly decreases the temperature fluctuation range. The OCT controller also demonstrates good safety and stability in controlling hydrogen to oxygen (HTO) impurity levels, consistently maintaining the HTO content at the set upper limit of 1.5%, thereby expanding the safe operational range of the system and reducing the need for frequent adjustments to the system setpoints.

Current fluctuations in the symmetric zero-range process below and at critical density.

Characterizing current fluctuations in a steady state is of fundamental interest and has attracted considerable attention in the recent past. However, the bulk of the studies are limited to systems that either do not exhibit a phase transition or are far from criticality. Here we consider a symmetric zero-range process on a ring that is known to show a phase transition in the steady state. We analytically calculate two density-dependent transport coefficients, namely, the bulk-diffusion coefficient and the particle mobility, that characterize the first two cumulants of the time-integrated current. We show that on the hydrodynamic scale, away from the critical point, the variance of the time-integrated current in the steady state grows with time t as sqrt[t] and t at short and long times, respectively. Moreover, we find an expression of the full scaling function for the variance of the time-integrated current and thereby the amplitude of the temporal growth of the current fluctuations. At the critical point, using a scaling theory, we find that, while the above-mentioned long-time scaling of the variance of the cumulative current continues to hold, the short-time behavior is anomalous in that the growth exponent is larger than one-half and varies continuously with the model parameters.

MOBILE APPLICATION FOR MONITORING THE GROWTH OF DONATED KIRAY TREES ON THE CISADANE RIVERBANK

The riverbank of the Cisadane in South Tangerang, Indonesia, is experiencing erosion issues due to significant fluctuations in water levels and currents. Planting trees with deep and dense root, such as Kiray trees, on the riverbank slopes can help slow down the erosion. Many institutions/individuals have planted trees in the area; however, the survival rate of the tree saplings is rarely monitored. The monitoring of 50 Kiray trees planted by Binus University in June 2024 shows that only 50% of the saplings survive after 2 months. In order to improve the survival rate, it is necessary to monitor the growth of the trees in more detail. This study proposed to develop a mobile application that can be used by many people to register and monitor the growth of the planted trees. The mobile application have been designed based-on the discussion with the riverbank community, to allow multiple users to register and update the data of the trees, including their height and location from time to time.

Optimal operation control strategy for off-grid photovoltaic hydrogen production system considering hydrogen production efficiency

Off-grid photovoltaic hydrogen production is an effective solution for improving photovoltaic (PV) utilization and obtaining green hydrogen. The main challenge faced by off-grid photovoltaic hydrogen production systems (OGPHPS) is how to deal with the randomness, intermittency, and volatility of PV generation. Therefore, this paper proposes an optimal operation control strategy (OOCS). First, a model of OGPHPS is established, comprising photovoltaics, batteries, and an electrolytic array (ELA). Second, a two-step optimization strategy (TSOS) that integrates both long-term and short-term time scales is proposed. In the first step of TSOS, the day-ahead optimization of the operation state of ELA is conducted according to day-ahead power prediction. A constraint was proposed to balance the operation time of the electrolyzer. In the second step of TSOS, according to the ultra-short time power prediction and the electrolyzer efficiency curve, the rolling optimization of the operating power distribution of ELA is carried out. Through TSOS, PV generation consumption is maximized by ELA, the continuous operational stability of OGPHPS is enhanced, and the lifespan of electrolyzer is extended. Third, to alleviate the influence of instantaneous power fluctuation on the system, an energy management strategy (EMS) for OGPHPS is proposed. Finally, a simulation model of OGPHPS was established, and the simulation results showed that the direct current bus voltage fluctuation was within 3%. Compared to the chain allocation strategy, the OOCS achieves higher hydrogen production under the same solar irradiance conditions. Particularly in low irradiance, OOCS has more sufficient consumption of PV generation and higher hydrogen production efficiency.

Enhancing mixed gas discrimination in e-nose system: sparse recurrent neural networks using transient current fluctuation of SMO array sensor

Despite recent significant advancements in gas sensor array technology, accurately identifying gases in mixed environments remains challenging. This difficulty is primarily due to the rapid and competing processes of gas molecules attaching to (adsorption) and detaching from (desorption) the sensor. In this study, we present a simple method to fabricate a 2 × 4 SMO-based gas sensor array, coupled with a sparse recurrent neural network (SRNN) that employs weight regularization. The recurrent layers of the SRNN process nonlinear information and capture temporal dependencies in the sensor data, while the regularization technique simplifies the model, making it both efficient and easier to interpret. Additionally, we introduce a novel feature: the dynamics of current, labeled as ΔI. This feature enables the SRNN model to efficiently detect the adsorption and desorption of gas molecules. We demonstrate that our model can distinguish between three intuitively indistinguishable datasets of gas species (NO2, HCHO, and a mixture) with up to 92 % accuracy. By utilizing the fast and competitive adsorption/desorption information of gas molecules, our model can be applied to various gas combination environments, unlike conventional gas sensing data measured over longer periods. By integrating the sensor array with the advanced SRNN model, we pave the way for sophisticated e-nose systems, with potential applications in advanced gas sensing technologies, such as disease diagnosis through exhaled breath analysis and the detection of toxic species in mixed gas environments.

Correlation Between Microscopic Current Fluctuations Observed at Ultra-Microelectrodes and Macroscopic Bulk Electrolysis Performance in Redox-Active Microemulsions

Microemulsions (μEs) have been proposed as redox flow battery (RFB) electrolytes that maximize ionic conductivity and charge capacity by synergizing two immiscible phases. However, charge transfer during electrolysis in μEs is poorly understood. Here, we show that ultramicroelectrode electrolysis of ferrocene-loaded μEs −20%, 60%, and 90% water - reveals stochastic current fluctuations. These are differentiated in the scanning electrochemical microscopy (SECM) geometry, where power spectral density analysis showed distinct changes in the frequency contributions. SECM in the substrate generation-tip collection mode showed that fluctuations arise under mass-transfer control. Significant differences in the diffusion coefficient of ferrocene species were deducted from SECM approach curves, suggesting phase transfer behavior. Using bulk electrolysis, we calculated the charge accessibility and cycling behavior in the μEs. A decrease in the stochastic behavior of the μEs seems to correlate to a higher accessibility and cycling performance, with the 90% water μE displaying the best reversibility and the 60% the lowest. Altogether, these results suggest that Marangoni-type convection driven by concentration gradients and/or μE restructuring during charge transfer play a role in the electrochemical performance of μEs. This presents opportunities for screening and diagnosing the performance of these emerging RFB electrolytes.

Research on Stator Sections Switching Process of High-Thrust Linear Motors

The high-thrust linear motor used for the electromagnetic launch is switched by switches composed of anti-shunt thyristors. During the switching process, different current path states will appear, which will lead to changes in motor parameters and current fluctuation. Focusing on the air-core synchronous linear motor with parallel and series power supply, this paper analyzes the change in current path caused by the change in the trigger signal of anti-parallel thyristors in the process of sectionalized stator switching. The motor circuit model of the switching process is derived. A new sectionalized stators switching method is proposed to realize the smooth switching of the sectionalized stators linear motor. Finally, the correctness of the analysis and modeling is verified by simulation, and the effectiveness of the sectionalized stators switching method is tested by using the test prototype.

Hydrogen permeation behavior of X80 pipeline steel under alternating wet-dry environment in the South China Sea

The riser sections of offshore pipelines are subject to cathodic potentials, alternating wet-dry (AWD) cycles and stresses in the service environment. The hydrogen permeation of X80 offshore pipeline with different cathodic potentials, dry/wet ratios, and constant tensile stress in AWD environment were investigated by the self made experimental equipment, which includes the three modules, i.e., the constant stress loading, the two-component cell hydrogen permeation, and AWD environment. Results showed that hydrogen permeation current fluctuates with the AWD, which is different from that in the bulk solution. In one AWD cycle, the permeation increases in the wetting stage and decreases in the dry stage. The smaller the dry/wet ratio, the longer the hydrogen permeation current keeps high level which is caused by the dense corrosion product layer. The hydrogen permeation currents in the elastic stress are greater than those in the plastic deformation, and unstressed conditions is the smallest.

Switching dynamics in Al/InAs nanowire-based gate-controlled superconducting switch

The observation of the gate-controlled supercurrent (GCS) effect in superconducting nanostructures increased the hopes for realizing a superconducting equivalent of semiconductor field-effect transistors. However, recent works attribute this effect to various leakage-based scenarios, giving rise to a debate on its origin. A proper understanding of the microscopic process underlying the GCS effect and the relevant time scales would be beneficial to evaluate the possible applications. In this work, we observed gate-induced two-level fluctuations between the superconducting state and normal state in Al/InAs nanowires (NWs). Noise correlation measurements show a strong correlation with leakage current fluctuations. The time-domain measurements show that these fluctuations have Poissonian statistics. Our detailed analysis of the leakage current measurements reveals that it is consistent with the stress-induced leakage current (SILC), in which inelastic tunneling with phonon generation is the predominant transport mechanism. Our findings shed light on the microscopic origin of the GCS effect and give deeper insight into the switching dynamics of the superconducting NW under the influence of the strong gate voltage.

Multi‐objective optimization of inductive power transfer system with reconfigurable topology for misalignment tolerance

AbstractAt present, most of the analyses or studies about inductive power transfer (IPT) with constant current (CC) output and constant voltage (CV) output are carried out without considering misalignment conditions or different gaps. An IPT system satisfying battery charging demand and anti‐misalignment requirements simultaneously is infrequent. This paper proposes a multi‐objective particle swarm optimization method of IPT reconfigurable topology to realize CC and CV modes at varying resistance conditions and wide coupling ranges. The output characteristics of an inductor–capacitor–capacitor (LCC)–LCC compensation circuit have been explored, and it is found that the secondary‐side compensated capacitors have a greater impact on the output power, which can be used to improve power regulation ability accompanied by coupling varying. Eight optimization compensated parameters of the reconfigurable topology are obtained from the Pareto front to achieve the required CC and CV charging outputs. By switching the compensated capacitors, the selected parameters can make the current and voltage fluctuation less than 9.3% and 7.9%, respectively, during the coupling charging range from 0.3 to 0.22. Moreover, primary zero voltage switching operation is achieved to enable high efficiency. The simulation and the experimental verification are carried out to verify the validity of the proposed method.

Predicting temperature of a Li-ion battery under dynamic current using long short-term memory

The growing energy demands of modern society have led to an increased reliance on secondary batteries, particularly lithium-ion (Li-ion) batteries, due to their superior energy density and power output. These batteries perform most effectively and safely within a specific temperature range, making it essential to develop accurate models for predicting temperature variations under diverse operational and environmental conditions. In particular, it is crucial to forecast temperature changes resulting from random and dynamic current fluctuations, reflecting real-world usage scenarios while considering the surrounding battery system environment. In this study, we employed a long short-term memory (LSTM) network to develop a surrogate model capable of predicting the battery’s core temperature over time, given varying current loads and heat transfer coefficients. The LSTM model demonstrated remarkable accuracy, achieving an average prediction accuracy of 99% in simulating temperature changes induced by arbitrary currents.

Does the Formation of a Taylor Cone in a Pulsating Electrospray Directly Impact Mass Spectrometry Signals?

Electrospray ionization (ESI) remains the dominant technique in mass spectrometry (MS)-based analyses. Here, we investigated the relationship between a crucial aspect of ESI, the formation of the Taylor cone, and the MS ion current by utilizing a triple quadrupole (QqQ) mass spectrometer coupled with a streaming high-speed camera and a 3-ring electrode system. In one test, ion current over a 30-s plume gate (a ring electrode) opening was compared with the Taylor cone occurrence analyzed offline, with Spearman's correlation coefficients consistently near 0 despite parameter variations. In another test, real-time detection of Taylor cones was synchronized with QqQ-MS, selectively opening (de-energizing) the plume gate based on the Taylor cone status. This approach enabled matching the ion current with the Taylor cone occurrence. There was no apparent difference between the MS signals recorded in the presence and absence of a Taylor cone. Additionally, a Faraday plate was employed as a detector in offline experiments, revealing agreement between the frequency of liquid meniscus (Taylor cone) oscillation (∼1.92 kHz)-measured by high-speed imaging-and the frequency of spray current (∼1.93 kHz). We suggest that the lack of positive correlations in the MS experiments is due to intrinsic ion carryover during transit from the ion source to the detector and due to the insufficient data acquisition rate of the mass spectrometer, which erases short-term fluctuations of ion current.