Discharge Conditions Research Articles

Influence of Hydrogen Additive on Electrophysical Parameters and Emission Spectra of Tetrafluoromethane Plasma

The influence of the addition of hydrogen on the electrophysical parameters and emission spectra of tetrafluoromethane under conditions of a direct current glow discharge has been studied. It has been established that gas temperature changes nonlinearly with increasing proportion of hydrogen in the plasma-forming mixture. The emission spectra of tetrafluoromethane plasma with hydrogen were obtained and analyzed. It is shown that plasma radiation is represented by atomic and molecular components, and the dependences of the line radiation intensities on the external conditions of the discharge are determined by the excitation of emitting states during direct electron impacts.

Effects of pulse rise time and pulse width on discharge mode transition of SDBD plasma under repetitive pulses

Abstract Affected by environmental states and power supply parameters, the discharge mode of surface dielectric barrier discharge plasma may gradually transfer from O3 mode to NOx mode, resulting in various gas-phase species for different applications. Despite the intensive study of attempts to control this discharge mode transition by changing discharge conditions and power excitations in recent years, the effects of the pulse rise time and the pulse width on the discharge mode transition have not been discussed. In the present study, a surface dielectric barrier discharge was excited by repetitive pulses with different pulse rise times or pulse widths, and the time-varying concentrations of key long-lived species (O3 and NO2) were quantified. The results demonstrated that it was possible to modulate the discharge mode by adjusting pulse rise time/pulse width. The quenching of O3 was observed to occur at a faster rate and the mode transition was noted to occur at an earlier point in time as the pulse rise time decreased from 225 ns to 125 ns and the pulse width increased from 0.5 μs to 4 μs. The employment of a zero-dimensional model for the analysis of plasma chemical kinetics revealed that the reduction in pulse rise time and the prolongation of pulse width resulted in an increase in the mean vibrational energy of N2(v) and a more rapid electrode temperature rise caused by plasma heating. The former enhanced the generation of NO, while the latter accelerated the thermal decomposition of O3, thereby promoting the speed of mode transition.

Study on the parameter identification of lithium-ion battery model under high-rate pulse discharge conditions

With the rapid development of the new energy sector and lithium-ion (Li-ion) battery technologies, using Li-ion batteries with high energy density and high discharge rate to form the primary energy subsystem can further improve the compactness and miniaturization level of pulsed power systems. In traditional electric power systems, Li-ion batteries normally operate under the discharge condition of low current and long time. However, as the main power source of pulsed power systems, it is required that Li-ion batteries should have the capability for high-rate pulse discharge. To ensure the safe and reliable operation of the battery energy storage system, it is necessary to conduct the parameter identification of the Li-ion battery model to establish an accurate pulse discharge model under such working conditions. This paper focuses on the discharge characteristics of a cylindrical high-rate single Li-ion battery with a capacity of 3 Ah. At a 20 C rate, the discharge data were obtained when the pulse repetition frequency was 10 Hz and the duty cycle was 90%. By using the mathematical expressions of the Thevenin equivalent circuit model, the recursive relationship of the circuit parameters was obtained, and the parameter identification of the battery model was conducted based on the experimental data by using the genetic algorithm. The results show that the fitting accuracy of the parameter identification reaches 0.9995, indicating the high precision of the model for the Li-ion battery. This work provides a significant reference for the modeling and parameter identification of Li-ion batteries under high-rate pulse discharge conditions.

Design and test of a module of a breathable Electrostatic Shield for the MITICA 1 MV negative ion Beam Source

The electrical insulation of the MITICA Beam Source at 1 MV is a challenging issue, which has not been fully addressed so far on the basis of experimental results and of theoretical models available in literature. Being MITICA the full-size prototype of the Heating Neutral Beam Injector for the ITER fusion experiment, its electrical insulation is constituted just by vacuum gaps and alumina insulators, since other insulating materials such as SF6 gas or fibreglass-reinforced plastic (FRP) would be quickly degraded by the expected neutron flux produced by fusion reaction. Extrapolations based on HV tests on reduced-scale models have recently indicated the risk of electrical breakdowns in the vacuum gap between electrodes nominally operating at -1 MV and the vacuum vessel (at ground potential). The risk of electrical breakdown can be mitigated by introducing an intermediate Electrostatic Shield (ES), which essentially is an equipotential (metallic) enclosure surrounding the HV electrode, so as to divide the vacuum gap in two independent insulating gaps of 400 kV and 600 kV respectively. However, for optimal negative ion production, the ion source shall operate in H2 or D2 at a pressure of ∼ 0.3 Pa and unavoidably produces a flow of gas leaking out in the surrounding vacuum. Thus, the presence of an intermediate shield can substantially increase the background gas pressure in the vacuum gaps, and, due to the large gap length (0.6 m), exacerbate the risk of breakdown when the pressure approaches the conditions of Paschen-type discharges. In addition to this, RF-induced breakdowns were found on the rear side of the ion source during the operation of the prototype source SPIDER, which were somewhat correlated to a relatively high hydrogen pressure in that area. For these reasons, a structure capable of constituting a full equipotential barrier all around the BS and, at the same time, having sufficient gas conductivity (breathability) to allow efficient pumping of background gas, has been designed. In the first part of the paper, the requirements and design optimization of a breathable module of the intermediate ES are described. Then, an experimental campaign for the validation of the electrode implementation the test configurations and the experimental procedure is discussed.

Experimental study on the thermal management performance of immersion cooling for 18650 lithium-ion battery module

Direct liquid cooling technology stabilizes the battery module at the ideal operating temperature by leveraging the coolant's high heat capacity and its heat dissipation ability through circulation. This study introduced a forced-flow immersion cooling method employing transformer oil as the cooling medium for 18650 lithium-ion battery modules. The performance of this cooling system design was assessed under various discharge rates, coolant flow rates, and channel positions. Experimental data reveals that the average temperature of the oil-immersion-cooled battery module was around 26.3% lower than that of the naturally air-cooled battery module under a 2C discharge condition with zero flow rate. The cooling capacity of the oil-immersion system was limited, with theoretical analyses indicating an optimal flow rate of 200mL/min. Four unique cooling channel configurations was designed: side center inlet to center outlet, side upper inlet to lower outlet, front upper inlet to lower outlet, and front center inlet to center outlet. The peak temperatures of the battery module for these setups were 31.7 ℃, 31.0 ℃, 31.0 ℃, 31.0 ℃, and 31.6 ℃, respectively, with a temperature difference of about 2 ℃. Notably, the side upper inlet to lower outlet channel configuration displays superior cooling performance. These findings contribute to advancing more efficient cooling systems and offer valuable insights for optimizing direct liquid-cooled thermal management systems for lithium-ion batteries in the future.

Mutitask Learning Network for Partial Discharge Condition Assessment in Gas-Insulated Switchgear

Mutitask Learning Network for Partial Discharge Condition Assessment in Gas-Insulated Switchgear

Evaluation of the highly sinuous bend sequences using an ecohydraulic model to ascertain the suitability of fish habitats for river ecological conservation

The spatial and temporal patterns of river meanders play a crucial role not only in shaping the hydrogeomorphic properties of channels and floodplains but also in ascertaining the suitability of fish habitats for river ecological conservation. This study evaluates hydrodynamic features and fish habitat quality in six highly sinuous bend sequences along the Black River in China’s Qinghai plateau. The ecohydraulic model system was used to simulate hydrodynamics, habitat suitability, and sediment transport to determine the habitat quality of the highly sinuous bend sequences. The results have successfully identified differences in the suitability of various bends for fish spawning. Bend 1 was found to be the most suitable among all bends, while bends 5 and 6 were deemed unsuitable specifically during higher flood flows. Cases 3 and 4 were discovered to be highly suitable for fish habitat under normal discharge scenarios. Conversely, cases 5 and 6 were the least suitable, with cases 5 and 6 exhibiting the worst habitat quality, with HSI values nearing zero under high discharge. The study concluded that regulated discharge conditions could support fish spawning in these sinuous bends, with lower flood flows promoting habitat suitability and higher flood flows fragmenting habitat quality. The findings highlight the importance of diverse hydrodynamic and geomorphic conditions in creating suitable fish habitats across varying flow conditions, offering insights into the conservation and management of mountain rivers to protect endangered fish species and aquatic organisms.

VUV imaging of type-I ELM filamentary structures and their temporal characteristics on EAST

In the H-mode experiments conducted on the Experimental Advanced Superconducting Tokamak (EAST), fluctuations induced by the so-called edge localized modes (ELMs) are captured by a high-speed vacuum ultraviolet (VUV) imaging system. Clear field line-aligned filamentary structures are analyzed in this work. Ion transport induced by ELM filaments in the scrape-off layer (SOL) under different discharge conditions is analyzed by comparing the VUV signals with the divertor probe signals. It is found that convective transport along open field lines towards the divertor target dominates the parallel ion particle transport mechanism during ELMs. The toroidal mode number of the filamentary structure derived from the VUV images increases with the electron density pedestal height. The analysis of the toroidal distribution characteristics during ELM bursts reveals toroidal asymmetry. The influence of resonance magnetic perturbation (RMP) on the ELM size is also analyzed using VUV imaging data. When the phase difference of the coil changes periodically, the widths of the filaments change as well. Additionally, the temporal evolution of the ELMs on the VUV signals provides rise time and decay time for each single ELM event, and the results indicate a negative correlation trend between these two times.

Battery temperature estimation at wide C-rates using the LSTM model based on polarization characteristics

Data-driven based approaches have achieved significant results in estimating battery temperature. Nevertheless, the present challenge emanates from the dearth of theoretical guidance governing the training strategy of the model, leading to an inefficient training process and constrained accuracy, especially under specific conditions. In this paper, a Long Short-Term Memory (LSTM) neural network based on polarization characteristics is proposed to estimate the battery discharge temperature. Firstly, the LSTM temperature estimation model is established and the hyperparameters are optimized by Genetic Algorithm (GA). The results show that the accuracy of the traditional model is less satisfactory, with the Maximum Error (ME) of 3.79 °C. Subsequently, the voltage and polarization heat production characteristics of the battery are analyzed under various discharge conditions. It is found that the heat production of the battery is smaller at 0–1.5C, and the heat production characteristics are similar at medium-rate, but the change of heat production is significant when C-rate exceeds 3C. Finally, a LSTM temperature estimation model based on polarization characteristics is proposed, which divides the datasets according to heat production characteristics. Further, a strategy for predicting temperatures in later stages based on limited data from the current condition is also proposed, this mothed combines with the transfer learning method to rapidly develop models for different high-rate conditions. The ME of the model on the test set is 1.1 °C, and the training time is reduced by 32.93 s. The results show that the LSTM temperature estimation model based on polarization characteristics has higher accuracy and training efficiency than the traditional LSTM temperature estimation model.

Study on clinical profile, risk factors, morbidity and mortality patterns of intrauterine growth restricted babies admitted in neonatal intensive care unit of tertiary care hospital, Vijayapura

Background: Intrauterine growth restriction (IUGR) is an important clinical problem associated with increased perinatal mortality and morbidity. The neonate may be either constitutionally small or small due to pathophysiological changes with maternal, placental or foetal factors involved. A foetus with IUGR has not achieved its genetic growth potential. In addition, emerging evidence suggests that they are also more likely than normal weight babies to suffer from degenerative diseases like hypertension, diabetes and cardiovascular diseases in adulthood. Methods: This is a cross-sectional study carried out in the neonatal unit, tertiary care hospital, Vijayapura. This study was carried out between April 2022 to April 2024. 120 IUGR babies were included in this study. Results: Of the 120 babies 22 (18.3%) have died in the hospital. 19 (15.5%) have been discharged with abnormal neurological examination and 79 (66.3%) have been discharged with good condition at discharge condition. Morbidity pattern of IUGR shows that hypoglycaemia (63.3%) and perinatal asphyxia (45.0%) are the commonest complication. Other commoner are sepsis (33.3%), hypocalcaemia (30.0%), hypothermia (28.3%) and thrombocytopenia (25.0%). Conclusions: Perinatal asphyxia and meconium aspiration are significantly associated with abnormal neurological examination at discharge. Perinatal asphyxia, pulmonary haemorrhage and persistent PH are significantly associated with death during the hospital stay. 73 (77.5%) mothers had one or more risk factors. Malnutrition is the commonest (40.0%), other are anaemia (34.2%), pregnancy-induced hypertension (PIH) (18.3%), multiple gestations (8.3%) and lower age of the mother.

Joint Model Parameter Identification and EKF Algorithm for the SOC Estimation of LFP Battery

Abstract Accurately estimating the state of charge (SOC) of batteries is crucial for achieving the safety and efficient driving of electric vehicles. To address the negative impact of voltage platform flatness and accumulated errors in current sampling, the SOC estimation method jointing model parameter identification and extended Kalman filter (EKF) algorithm is proposed and verified through simulation in this paper. Firstly, the parameter identification method is obtained based on the second-order dual polarization model, and effective identification of the parameters under different SOC is achieved using experimental conditions of hybrid pulse power characteristic and constant current discharge. On this basis, a function model with SOC as the independent variable and model parameters as the dependent variable is established by jointing model parameter identification and EKF algorithm, and the iterative estimation of SOC is achieved through the 1stopt and cftool methods. Finally, the SOC estimation accuracy of the proposed method is validated under three operating conditions that adopt the latest standards and are closer to the actual driving environment. The simulation results show that the SOC estimation method jointing model parameter identification and EKF algorithm has higher accuracy and smaller fluctuations than the traditional AH integration method, and the mean squared error (MSE) of estimation for the four test conditions are less than 0.29%, 0.72% and 0.25%, respectively.

Plasma electron density profile tomography for EAST based on integrated data analysis

Abstract Plasma electron density is a crucial parameter in plasma studies. Accurately inverting the plasma electron density profile is vital for plasma control experiments and the investigation of plasma physical mechanisms. This paper proposes an integrated data analysis (IDA) method based on Bayesian inference, which integrates polarimetric interferometry (POINT), hydrogen cyanide (HCN) laser
interferometer, and microwave reflectometer (RFL) diagnostics for inverting the plasma electron density profile. To enhance inversion accuracy, a Gaussian prior probability of the non-stationary hyperparameter is used. This prior probability effectively simulates
situations where there is a large plasma electron density gradient in the pedestal, especially under the condition of high-confinement mode discharge. Compared to the use of Gaussian prior probability for the stationary hyperparameter, the proposed IDA
method based on the non-stationary hyperparameter prior probability achieves higher inversion accuracy.

Extreme ultraviolet emission spectra of a low-pressure microwave neon discharge

In this paper, in order to reveal the discharge mechanism and optimize the extreme ultraviolet (EUV) emission lines in intensity of a low-pressure microwave (MW) neon discharge, the EUV neon spectra is carefully characterized under varied MW powers and neon pressures. The corona balance is verified to be valid for the neon upper levels of the measured EUV lines, and the electron temperature T e is derived by the modified Boltzmann plot method and the line-ratio method. Both results of the methods present a decreasing trend of T e with growing neon pressure, but the values in a range of 1.87-5.77 eV deduced by the former method is in general lower than that calculated by the latter with a range of 2.23–5.58 eV in similar neon pressure range. It is also found that the increase of MW power from 90 to 135 W only leads to a slight increasing of T e . A global model is applied to estimate the electron density n e , which is found to lie in the order of magnitude of 1010 cm−3. The dependence of the plasma parameters on different discharge conditions is analysed in detail, which in turn provide a favourable basis for further optimization of the promising low-pressure MW discharge radiation source.

Weakening the Space Charge Layer Effect Through Tethered Anion Electrolyte and Piezoelectric Effect Toward Ultra-Stable Zinc Anode.

The space charge layer (SCL) dilemma, caused by mobile anion concentration gradient and the rapid consumption of cations, is the fundamental reason for the generation of zinc dendrites, especially under high-rate discharge conditions. To address the issue, a physical (PbTiO3)/chemical (AMPS-Zn) barrier is designed to construct stable zinc ion flow and disrupt the gradient of anion concentration by coupling the ferroelectric effect with tethered anion electrolyte. The ferroelectric materials PbTiO3 with extreme-high piezoelectric constant can spontaneously generate an internal electric field to accelerate the movement of zinc ions, and the polyanionic polymer AMPS-Zn can repel mobile anions and disrupt the anions concentration gradient by tethering anions. Through numerical simulations and analyses, it is discovered that a high Zn2+ transference number can effectively weaken the SCL, thus suppressing the occurrence of zinc dendrites and parasitic side reactions. Consequently, an asymmetric cell using the PbTiO3@Zn demonstrates a reversible plating/stripping performance for 2900h, and an asymmetric cell reaches a state-of-the-art runtime of 3450h with a high average Coulombic efficiency of 99.98%. Furthermore, the PbTiO3@Zn/I2 battery demonstrated an impressive capacity retention rate of 84.0% over 65000 cycles by employing a slender Zn anode.

Online Capacity Estimation for Lithium-Ion Batteries in Partial Intervals Considering Charging Conditions

Abstract Employed extensively for lithium-ion battery health assessment and capacity estimation, incremental capacity analysis (ICA) traditionally requires substantial time investment under standard charge and discharge conditions. However, in practical usage, Li-ion batteries rarely undergo full cycles. This study introduces aging temperature cycles within different partial intervals of the battery, integrating local ICA curves, peak range analysis, and incremental slope (IS) as an auxiliary feature. The extracted partial incremental capacity curves serve as features for state of health (SOH) estimation. The proposed temperature-rate-based SOH estimation method relies on a mechanistic function, analyzing relationships between temperature, different partial intervals, aging rate, and aging. Experimental tests on FCB21700 batteries demonstrate accurate SOH estimation using only partial charge curves, with an average error below 2.82%. By manipulating charging and discharging ranges, the method significantly extends battery lifespan, offering promising widespread applications.

Numerical Investigation of the Thermal Performance of Air-Cooling System for a Lithium-Ion Battery Module Combined with Epoxy Resin Boards

Lithium-ion batteries (LIBs) have the lead as the most used power source for electric vehicles and grid storage systems, and a battery thermal management system (BTMS) can ensure the efficient and safe operation of lithium-ion batteries. Epoxy resin board (ERB) offers a wide range of applications in LIBs due to its significant advantages such as high dielectric strength, electrical insulation, good mechanical strength, and stiffness. This study proposes an air-cooled battery module comprised of sixteen prismatic batteries incorporating an ERB layer between the batteries. To compare the performance of the ERB-based air-cooling system, two other air-cooling structures are also assessed in this study. Three-dimensional numerical models for the three cases are established in this paper, and the heat dissipation processes of the battery module under varying discharge rates (1C, 2C, and 5C) are simulated and analyzed to comprehensively evaluate the performance of the different cooling systems. Comparative simulations reveal that incorporating ERB into the battery assembly significantly reduces battery surface temperatures and promotes temperature uniformity across individual batteries and the entire pack at various discharge rates. Notably, under 5C discharge conditions, the ERB-based thermal management system achieves a maximum battery surface temperature increase of 16 °C and a maximum temperature difference of 8 °C between batteries. Additionally, this paper also analyzes the impact of battery arrangement on air-cooling system performance. Therefore, further optimization of the structural design or the integration of supplementary cooling media might be necessary for such demanding conditions.

Investigating a novel and highly efficient approach for the fabrication of diamond profile rollers using Wire Electrical Discharge Conditioning (WEDC)

The fabrication of high-precision and high-performance profile rollers represents the main challenge of utilizing profile rollers as dressers to condition conventional grinding wheels. This results in high demands for an efficient process to manufacture profile rollers (form dressing wheels). Conventionally, diamond profile rollers have been produced through infiltration or negative electroplating methods. Nevertheless, these manufacturing methods suffer significant drawbacks, including extended production times and substantial costs. This study presents an innovative approach to fabricating diamond profile rollers using Wire Electrical Discharge Conditioning (WEDC). The WED-Conditioning emerges as an effective alternative to profile metal-bonded rotary diamond dressing tools. This innovative method leads to the production of diamond profile rollers in significantly shorter timeframes and at a more economical cost compared to the conventional manufacturing method with comparable quality. The research delves into the influence of profile roller specifications and conditioning strategies on the achievable profile accuracy and topography of the profile rollers. Also, the wear behavior of the WEDC-conditioned profile roller over long-term conditioning of conventional grinding wheels was studied. The findings highlight the significant contribution of the appropriate selection of WEDC strategies to the profile accuracy, with the potential to achieve profile accuracies comparable with conventional profile rollers. As well, grain size emerges as the primary determinant of achievable profile accuracy for profile rollers. The findings of this study could provide insights into optimizing the manufacturing process for super abrasive diamond profile rollers, thereby enabling their widespread use in the grinding industry.

Evaluation of water quality fluctuation in the tidal reach under the impact of on shore wastewater discharges based on MIKE 21 model in dongguan, China

The text discusses the study of water quality simulation in the lower reaches of the Dongjiang River basin—tidal river section. Utilizing MIKE 21 software, an integrated 2D hydrodynamic-water quality coupled mathematical model was constructed for the lower reaches and estuary area of the Dongjiang River. The model simulated the hydrodynamic characteristics near the wastewater outlet and the impact of pollutant discharge on the water quality in the study area. The simulation results indicate: (1) During wet and dry seasons, the overall flow pattern remains consistent, with the ebb current velocity slightly greater than the flood tide current velocity beside the outlet. The flow velocity is generally greater during wet season compared to dry season. Interestingly, the flow direction during flood and ebb tides is completely opposite and tides have a great impact on the maximum flow velocity in Xialu Connecting channel. (2) Under normal discharge conditions, the increment of COD, NH3-N, and TP in most areas of Zhongtang Waterway, Daoyun Waterway, and Hengchong Waterway is less than 5 mg/L, 0.1 mg/L, and 0.02 mg/L, respectively, indicating a minor impact on water quality; While in the event of an accidental discharge, the concentration increment is in the range of 5–30 mg/L, 0.1–0.25 mg/L, and 0.02–0.05 mg/L, respectively. COD causes the most significant water quality changes and will severely impact the water environment of the Dongjiang River basin. Furthermore, pollutant dispersion is more extensive during dry seasons due to reduced river flow and weaker dilution capacity. (3) Overall, the results underscore the critical importance of accounting for both tidal and seasonal dynamics in simulation of estuarine water quality.

Numerical investigation of plasma properties in Ar/SiH4 inductively coupled plasmas considering electron energy distribution functions

In thin film deposition, Ar/SiH4 mixtures are widely used to make polysilicon (poly-Si) and hydrogenated amorphous silicon (a-SiH) layers. Despite extensive research conducted on this mixture, little research has focused on the variations in plasma properties, radicals, and ions that occur during plasma discharge in inductively coupled plasma (ICP) equipment compared to capacitive coupled plasma equipment. In this paper, we investigate the properties of the plasma generated through mathematical modeling of Ar/SiH4 inductive coupled plasma discharge by using the electron energy distribution function (EEDF) obtained by solving the Boltzmann equation. We closely examine the variation in plasma properties and the correlation of plasma variables by controlling the radio frequency power and gas pressure during the process conditions. The Boltzmann equation was computed by assuming the two-term approximation, resulting in a Druyvesteyn-like EEDF due to the high-pressure conditions. To validate the simulation model, the 2D simulation results were compared with probe measurements performed in a two-turn ICP chamber. The results demonstrated encouraging agreement with the measured data. This research not only enhances our comprehension of the discharge characteristics but also establishes a framework for optimizing the discharge conditions to enhance the process and effectively regulate external variables.

A Novel Hybrid Approach for Remaining Useful Life (RUL) and Short-Term Capacity Prediction of Batteries

Lithium-ion battery management requires an accurate determination of the batteries’ remaining usable lives. A novel hybrid method used for the RUL and short-term capacity prediction of batteries is presented in this manuscript. The proposed technique is combined with a White Shark Optimizer (WSO) with the Multi-kernel Support Vector Machine (MSVM); therefore, it is called the WSO-MSVM technique. The major goal of this WSO-MSVM method is to attain effective future capacities and RUL forecast for the Lithium-Ion Battery (LIB) with reliable management of uncertainty. The hybrid technique solves the difficulty of forecasting the RUL of LIB. This proposal trains the WSO-MSVM model using the LIB data. The trained model is utilized to forecast the capacity and RUL of LIBs. In this proposed system, capacity, current, and voltage are considered in the discharge operation. The proposed technique validates good reliability and prediction accuracy with this suitable mechanism. Compared to the existing techniques like artificial neural network (ANN), ant lion optimizer-optimized artificial neural network, and adaptive network-based fuzzy inference system, the proposed technique shows fewer errors under charge and discharge conditions. In addition, the uncertainty intervals of the proposed WSO-MSVM technique for the predicted RUL may include the actual remaining life of the battery. The proposed technique’s charging error is lower the other exciting methods.