Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combine...Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combined electrical-thermal-mechanical stress over long operating times.In this paper,the chemical characteristics of oil-pressboard insulation samples subjected to electrical-thermal-mechanical ageing for different times are studied.An image processing algorithm is used to analyse the discharge propagation characteristics of the samples under combined alternating current(AC)-direct current(DC)voltage,and the current pulse curves and phase resolved partial discharge spectrogram corresponding to the discharge images are analysed.An improved wavelet packet algorithm is used to denoise the discharge current pulse.Finally,the influence of electrical-thermal-mechanical ageing on discharge characteristics is analysed using radar charts.The condition of oil-pressboard insulation is one of the main factors determining the life expectancy of converter transformers.The results obtained here therefore have practical significance for understanding the process of insulation failure caused by accelerated ageing of oil-pressboard insulation.展开更多
The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who ha...The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who have established entrance into their upper-division programs will have demonstrated cognitive proficiency in math and logical operations, abstract and analytical reasoning and language usage, to include writing. In this study the question was asked: is there a correlation between an upper-division electrical engineering students’ analytical reasoning ability and their descriptive writing ability? Descriptive writing is taken here to mean a students’ ability to identify key physical aspects of a mathematical model and to express—in words—a concise and well-balanced description that demonstrates a deep conceptual understanding of the model. This includes more than a description of the variables or the particular application to an engineering problem;it includes a demonstrated recognition of the basic physics that govern the model, certain limitations (idealizations) inherent in the model, and an understanding of how to make practical experimental measurements to verify the governing physics in the model. A student at this level may demonstrate proficiency in their analytical reasoning skills and hence be capable of correctly solving a given problem. However, this does not guarantee that the same student is skilled in associating equations with their physical meaning on a deep conceptual level or in understanding physical limitations of the equation. Consequently, such a student may demonstrate difficulty in mapping their comprehension of the model into written language that demonstrates a sound conceptual understanding of the governing physics. The findings represent a sample of two independent class sections of Electrical and Computer Engineering junior’s first course in Microe-lectronic Devices and Circuits during fall semesters 2012 and 2013 at a private mid-size university in NW Oregon. A total of three exams were administered to each of the 2012/2013 groups. Correlations between exam scores that students achieved on their descriptive writing of microelectronics phenomena and their analytical problem-solving abilities were examined and found to be quite significant.展开更多
In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhausti...In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.展开更多
This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obsta...This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.展开更多
Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows rais...Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.展开更多
Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(...Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(EEG)signals recorded by placing electrodes on the scalp of subjects;however,accurate prediction of MI tasks remains a challenge due to noise that is incurred during the EEG signal recording process,the extraction of a feature vector with high interclass variance,and accurate classification.The proposed method consists of preprocessing,feature extraction,and classification.First,EEG signals are denoised using a bandpass filter followed by Independent Component Analysis(ICA).Multiple channels are combined to form a single surrogate channel.Short Time Fourier Transform(STFT)is then applied to convert time domain EEG signals into the frequency domain.Handcrafted and automated features are extracted from EEG signals and then concatenated to form a single feature vector.We propose a customized two-dimensional Convolutional Neural Network(CNN)for automated feature extraction with high interclass variance.Feature selection is performed using Particle Swarm Optimization(PSO)to obtain optimal features.The final feature vector is passed to three different classifiers:Support Vector Machine(SVM),Random Forest(RF),and Long Short-Term Memory(LSTM).The final decision is made using the Model-Agnostic Meta Learning(MAML).The Proposed method has been tested on two datasets,including PhysioNet and BCI Competition IV-2a,and it achieved better results in terms of accuracy and F1 score than existing state-of-the-art methods.The proposed framework achieved an accuracy and F1 score of 96%on the PhysioNet dataset and 95.5%on the BCI Competition IV,dataset 2a.We also present SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)explainable techniques to enhance model interpretability in a clinical setting.展开更多
As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation c...As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.展开更多
In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along...In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.展开更多
This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,5...This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.展开更多
This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-a...This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.展开更多
The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials off...The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.展开更多
The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperat...The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperature increased, the average grain size increased from 6.1 to 8.7μm and the sintered density decreased from 5.52 to 5.43 g/cm3. The breakdown field decreased from 3856 to 922 V/cm with an increase in the sintering temperature up to 900 °C, whereas a further increase to 2352 V/cm at 925 °C. The nonlinear coefficient increased pronouncedly from 4.6 to 30.0 with an increase in the sintering temperature. The varistor ceramics sintered at 850 °C exhibited the best clamping characteristics, with the clamp voltage ratio of the range of 2.22-2.88 for pulse current of 1-25 A. The varistor ceramics sintered at 925 °C exhibited the strongest stability, with %ΔE1 mA/cm2=-8.8% after applying the multi-pulse current of 25 A.展开更多
The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were...The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were fabricated by a catalytic chemical vapor deposition method. A1203 composites with different CNT concentrations were synthesized. The electrical characteristic of A1203/CNTs composites was examined. These composites were machined by the EDM process according to the various EDM parameters, and the characteristics of machining were analyzed using field emission scanning electron microscope （FESEM）. The electrical conductivity has a increasing tendency as the CNTs content is increased and has a critical point at 5% A1203 （volume fraction）. In the machining accuracy, many tangles of CNT in A1203/CNTs composites cause violent spark. Thus, it causes the poor dimensional accuracy and circularity. The results show that conductivity of the materials and homogeneous distribution of CNTs in the matrix are important factors for micro-EDM of A1203/CNTs hybrid composites.展开更多
Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying...Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying degrees by asset owners,applied research leading to a systematic development of such a maintenance strategy is the need of the day.Such a strategy should also adopt a wholesome"systemic"approach so that the realization of the overall objectives of maintenance is maximized.E-maintenance has several potential benefits for large engineering plants.In this paper,a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs.Firstly,an integrated condition and time based maintenance framework is proposed for LEPs.Secondly,reference is drawn to models for condition and time based maintenance at systemic levels.As a part of the ab initio development of a condition monitoring system for a LEP,one of the characteristics of the condition monitoring system,namely,predictability,is discussed in detail as a sample for a systemic study.Thirdly,emphasis is laid on the information and expertise available in the domain of plant design,operation and maintenance and the same is tapped for incorporation in maintenance decision making.展开更多
Precise control over the charge carrier dynamics throughout the device can result in outstanding performance of perovskite solar cells(PSCs).Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)is the mo...Precise control over the charge carrier dynamics throughout the device can result in outstanding performance of perovskite solar cells(PSCs).Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)is the most actively studied hole transport material in p-i-n structured PSCs.However,charge transport in the PEDOT:PSS is limited and inefficient because of its low conductivity with the presence of the weak ionic conductor PSS.In addition,morphology of the underlying PEDOT:PSS layer in PSCs plays a crucial role in determining the optoelectronic quality of the active perovskite absorber layer.This work is focused on realization of a non-wetting conductive surface of hole transport layer suitable for the growth of larger perovskite crystalline domains.This is accomplished by employing a facile solventengineered(ethylene glycol and methanol)approach resulting in removal of the predominant PSS in PEDOT:PSS.The consequence of acquiring larger perovskite crystalline domains was observed in the charge carrier dynamics studies,with the achievement of higher charge carrier lifetime,lower charge transport time and lower transfer impedance in the solvent-engineered PEDOT:PSS-based PSCs.Use of this solventengineered treatment for the fabrication of MAPbI3 PSCs greatly increased the device stability witnessing a power conversion efficiency of 18.18%,which corresponds to^37%improvement compared to the untreated PEDOT:PSS based devices.展开更多
A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and...A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and a production chamber housing the exploding wire load and ambient gas. With the EEW device, nanosize powders of titanium oxides, titanium nitrides, copper oxides, and zinc oxides are successfully synthesized. The average particle size of synthesized powders under different experimental conditions is in a range of 20nm–80nm. The pressure of ambient gas or wire vapor can strongly affect the average particle size. The lower the pressure, the smaller the particle size is. For wire material with relatively high resistivity, such as titanium, whose deposited energy Wd is often less than sublimation energy W s due to the flashover breakdown along the wire prematurely ending the Joule heating process, the synthesized particle size of titanium oxides or titanium nitrides increases with overheat coefficient k （k = W d /Ws ） increasing.展开更多
Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementati...Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementation of multiband reconfigurable RF components with microfabrication techniques and advanced materials.RF applications of fabrication methods such as surface and bulk micromachining techniques are reviewed,especially on the development of RF microelectromechanical systems(MEMS)and other tunable components.Works on the application of ferroelectric and ferromagnetic materials are investigated,which enables RF components with continuous tunability,reduced size,and enhanced performance.Methods and strategies with nano-patterning to improve high frequency characteristics of ferromagnetic thin film(e.g.,ferromagnetic resonance frequency and losses)and their applications on the development of fully electrically tunable RF components are fully demonstrated.展开更多
Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for p...Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for phase-contrast imaging of small insects such as mosquitoes and ants in which it was possible to observe clearly their detailed internal structures,which can never be seen with conventional x-ray radiography.Electrical explosion of a wire array(EEWA)in vacuum is the initial stage in the formation of a wire-array Z-pinch.The evolution ofEEWAwas observed with x-ray backlighting using two X-pinches as x-ray sources.It was found that each wire in an EEWA exhibits a core–corona structure instead of forming a fully vaporized metallic vapor.This structure is detrimental to the plasma implosion of a Z-pinch.By inserting an insulator as a flashover switch into the cathode,formation of a core–corona structure was suppressed and core-freeEEWAwas realized.EEWin gases was used for nanopowder production.Three parameters(vaporization rate,gas pressure,and energy deposited in the exploding plasma)were found to influence the nanoparticle size.EEWin water was used for shock-wave generation.The shock wave generated by melting could be recorded with a piezoelectric gauge only in underheat EEW.ForEEW with a given stored energy but different energy-storage capacitor banks,the small capacitor bank produced a rapidly rising current that deposited more energy into the wire and generated a stronger shock wave.展开更多
WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge m...WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge machining(EDM) is one of the most effective methods for making holes because the hardness is not a dominant parameter in EDM. This paper describes the characteristics of the discharge conditions for micro-hole EDM of tungsten carbide with a WC grain size of 0.5 μm and Co content of 12%. The EDM process was conducted by varying the condenser and resistance values. A R-C discharge EDM device using arc erosion for micro-hole machining was suggested. Furthermore, the characteristics of the developed micro-EDM were analyzed in terms of the electro-optical observation using an oscilloscope and field emission scanning electron microscope.展开更多
基金supported by the Central Guided Local Science and Technology Development Project(Grant YDZX2022001).
文摘Converter transformers are the core components of ultra-high voltage(UHV)transmission systems.The main cause of faults in converter transformers is irreversible deterioration of oil-pressboard insulation under combined electrical-thermal-mechanical stress over long operating times.In this paper,the chemical characteristics of oil-pressboard insulation samples subjected to electrical-thermal-mechanical ageing for different times are studied.An image processing algorithm is used to analyse the discharge propagation characteristics of the samples under combined alternating current(AC)-direct current(DC)voltage,and the current pulse curves and phase resolved partial discharge spectrogram corresponding to the discharge images are analysed.An improved wavelet packet algorithm is used to denoise the discharge current pulse.Finally,the influence of electrical-thermal-mechanical ageing on discharge characteristics is analysed using radar charts.The condition of oil-pressboard insulation is one of the main factors determining the life expectancy of converter transformers.The results obtained here therefore have practical significance for understanding the process of insulation failure caused by accelerated ageing of oil-pressboard insulation.
文摘The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who have established entrance into their upper-division programs will have demonstrated cognitive proficiency in math and logical operations, abstract and analytical reasoning and language usage, to include writing. In this study the question was asked: is there a correlation between an upper-division electrical engineering students’ analytical reasoning ability and their descriptive writing ability? Descriptive writing is taken here to mean a students’ ability to identify key physical aspects of a mathematical model and to express—in words—a concise and well-balanced description that demonstrates a deep conceptual understanding of the model. This includes more than a description of the variables or the particular application to an engineering problem;it includes a demonstrated recognition of the basic physics that govern the model, certain limitations (idealizations) inherent in the model, and an understanding of how to make practical experimental measurements to verify the governing physics in the model. A student at this level may demonstrate proficiency in their analytical reasoning skills and hence be capable of correctly solving a given problem. However, this does not guarantee that the same student is skilled in associating equations with their physical meaning on a deep conceptual level or in understanding physical limitations of the equation. Consequently, such a student may demonstrate difficulty in mapping their comprehension of the model into written language that demonstrates a sound conceptual understanding of the governing physics. The findings represent a sample of two independent class sections of Electrical and Computer Engineering junior’s first course in Microe-lectronic Devices and Circuits during fall semesters 2012 and 2013 at a private mid-size university in NW Oregon. A total of three exams were administered to each of the 2012/2013 groups. Correlations between exam scores that students achieved on their descriptive writing of microelectronics phenomena and their analytical problem-solving abilities were examined and found to be quite significant.
基金funded by the Huaiyin Institute of Technology—Institute of Smart Energy.
文摘In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
基金supported by the National Science and Technology Council of under Grant NSTC 114-2221-E-130-007.
文摘This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘Automated detection of Motor Imagery(MI)tasks is extremely useful for prosthetic arms and legs of stroke patients for their rehabilitation.Prediction of MI tasks can be performed with the help of Electroencephalogram(EEG)signals recorded by placing electrodes on the scalp of subjects;however,accurate prediction of MI tasks remains a challenge due to noise that is incurred during the EEG signal recording process,the extraction of a feature vector with high interclass variance,and accurate classification.The proposed method consists of preprocessing,feature extraction,and classification.First,EEG signals are denoised using a bandpass filter followed by Independent Component Analysis(ICA).Multiple channels are combined to form a single surrogate channel.Short Time Fourier Transform(STFT)is then applied to convert time domain EEG signals into the frequency domain.Handcrafted and automated features are extracted from EEG signals and then concatenated to form a single feature vector.We propose a customized two-dimensional Convolutional Neural Network(CNN)for automated feature extraction with high interclass variance.Feature selection is performed using Particle Swarm Optimization(PSO)to obtain optimal features.The final feature vector is passed to three different classifiers:Support Vector Machine(SVM),Random Forest(RF),and Long Short-Term Memory(LSTM).The final decision is made using the Model-Agnostic Meta Learning(MAML).The Proposed method has been tested on two datasets,including PhysioNet and BCI Competition IV-2a,and it achieved better results in terms of accuracy and F1 score than existing state-of-the-art methods.The proposed framework achieved an accuracy and F1 score of 96%on the PhysioNet dataset and 95.5%on the BCI Competition IV,dataset 2a.We also present SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation Mapping(Grad-CAM)explainable techniques to enhance model interpretability in a clinical setting.
基金supported by Science and Technology Project of China Southern Power Grid Company(036000KK52222007(GDKJXM20222121)).
文摘As renewable energy penetration continues to rise,enhancing power system flexibility has become a critical requirement.Photovoltaic–storage–charging stations(PSCSs)are key components for enhancing local regulation capability and promoting renewable integration.However,evaluating the adjustable capability of such hybrid stations while considering security constraints remains a major challenge.This paper first analyzes the adjustable capabilities of all the resources within such a station based on the power-energy boundary(PEB)model.Then,an optimal formulation is proposed to obtain the adjusted parameters of the aggregate feasible region(AFR)model,which embeds low-dimensional linear models within high-dimensional linear models to improve the accuracy.To solve this formulation,it is transformed using duality theory and an alternating optimization algorithm is designed to obtain the solution.Finally,a multi-station adjustable capability aggregation method considering security constraints is introduced.Simulation results verify that the proposed method effectively reduces infeasible regions and improves smoothness of aggregated boundaries,providing an accurate and practical tool for flexibility evaluation in PSCSs and offering guidance for aggregators and system planners.
文摘In real industrial microgrids(MGs),the length of the primary delivery feeder to the connection point of the main substation is sometimes long.This reduces the power factor and increases reactive power absorption along the primary delivery feeder from the external network.Besides,the giant induction electro-motors as the working horse of industries requires remarkable amounts of reactive power for electro-mechanical energy conversions.To reduce power losses and operating costs of the MG as well as to improve the voltage quality,this study aims at providing an insightful model for optimal placement and sizing of reactive power compensation capacitors in an industrial MG.In the presented model,the objective function considers voltage profile and network power factor improvement at the MG connection point.Also,it realizes power flow equations within which all operational security constraints are considered.Various reactive power compensation strategies including distributed group compensation,centralized compensation at the main substation,and distributed compensation along the primary delivery feeder are scrutinized.A real industrial MG,say as Urmia Petrochemical plant,is considered in numerical validations.The obtained results in each scenario are discussed in depth.As seen,the best performance is obtained when the optimal location and sizing of capacitors are simultaneously determined at the main buses of the industrial plants,at the main substation of the MG,and alongside the primary delivery feeder.In this way,74.81%improvement in power losses reduction,1.3%lower active power import from the main grid,23.5%improvement in power factor,and 37.5%improvement in network voltage deviation summation are seen in this case compared to the base case.
文摘This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.
基金supported by the IITP(Institute for Information&Communications Technology Planning&Evaluation)under the ITRC(Information Technology Research Center)support program(IITP-2025-RS-2024-00438288)grant funded by the Korea government(MSIT)+1 种基金National Research Council of Science&Technology(NST)grant by the MSIT(Aerospace Semiconductor Strategy Research Project No.GTL25051-000)supported by the IC Design Education Center(IDEC),Korea。
文摘This work presents a systematic analysis of proton-induced total ionizing dose(TID)effects in 1.2 k V silicon carbide(SiC)power devices with various edge termination structures.Three edge terminations including ring-assisted junction termination extension(RA-JTE),multiple floating zone JTE(MFZ-JTE),and field limiting rings(FLR)were fabricated and irradiated with45 Me V protons at fluences ranging from 1×10^(12) to 1×10^(14) cm^(-2).Experimental results,supported by TCAD simulations,show that the RA-JTE structure maintained stable breakdown performance with less than 1%variation due to its effective electric field redistribution by multiple P+rings.In contrast,MFZ-JTE and FLR exhibit breakdown voltage shifts of 6.1%and 15.2%,respectively,under the highest fluence.These results demonstrate the superior radiation tolerance of the RA-JTE structure under TID conditions and provide practical design guidance for radiation-hardened Si C power devices in space and other highradiation environments.
基金supported by the IITP(Institute of Information & Communications Technology Planning & Evaluation)-ITRC(Information Technology Research Center) grant funded by the Korea government(Ministry of Science and ICT) (IITP-2025-RS-2024-00437191, and RS-2025-02303505)partly supported by the Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education. (No. 2022R1A6C101A774)the Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia, through Large Research Project under grant number RGP-2/527/46
文摘The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.
文摘The effect of sintering temperature on microstructure, electrical properties, and pulse aging behavior of （V2O5-Mn3O4-Er2O3）-doped zinc oxide varistor ceramics was systematically studied. When the sintering temperature increased, the average grain size increased from 6.1 to 8.7μm and the sintered density decreased from 5.52 to 5.43 g/cm3. The breakdown field decreased from 3856 to 922 V/cm with an increase in the sintering temperature up to 900 °C, whereas a further increase to 2352 V/cm at 925 °C. The nonlinear coefficient increased pronouncedly from 4.6 to 30.0 with an increase in the sintering temperature. The varistor ceramics sintered at 850 °C exhibited the best clamping characteristics, with the clamp voltage ratio of the range of 2.22-2.88 for pulse current of 1-25 A. The varistor ceramics sintered at 925 °C exhibited the strongest stability, with %ΔE1 mA/cm2=-8.8% after applying the multi-pulse current of 25 A.
基金Project(2010-0008-277) supported by Program of Establishment of an Infrastructure for Public Usepartly by NCRC (National Core Research Center) through the National Research Foundation of Korea funded by the Ministry of Education
文摘The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were fabricated by a catalytic chemical vapor deposition method. A1203 composites with different CNT concentrations were synthesized. The electrical characteristic of A1203/CNTs composites was examined. These composites were machined by the EDM process according to the various EDM parameters, and the characteristics of machining were analyzed using field emission scanning electron microscope （FESEM）. The electrical conductivity has a increasing tendency as the CNTs content is increased and has a critical point at 5% A1203 （volume fraction）. In the machining accuracy, many tangles of CNT in A1203/CNTs composites cause violent spark. Thus, it causes the poor dimensional accuracy and circularity. The results show that conductivity of the materials and homogeneous distribution of CNTs in the matrix are important factors for micro-EDM of A1203/CNTs hybrid composites.
文摘Large engineering plants(LEPs)have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance.Although this requirement is appreciated to varying degrees by asset owners,applied research leading to a systematic development of such a maintenance strategy is the need of the day.Such a strategy should also adopt a wholesome"systemic"approach so that the realization of the overall objectives of maintenance is maximized.E-maintenance has several potential benefits for large engineering plants.In this paper,a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs.Firstly,an integrated condition and time based maintenance framework is proposed for LEPs.Secondly,reference is drawn to models for condition and time based maintenance at systemic levels.As a part of the ab initio development of a condition monitoring system for a LEP,one of the characteristics of the condition monitoring system,namely,predictability,is discussed in detail as a sample for a systemic study.Thirdly,emphasis is laid on the information and expertise available in the domain of plant design,operation and maintenance and the same is tapped for incorporation in maintenance decision making.
基金supported by NSF MRI (1428992)NASA EPSCoR (NNX15AM83A)+3 种基金U.S.–Egypt Science and Technology (S&T) Joint FundSDBoR R&D ProgramEDA University Center Program (ED18DEN3030025)supported by the U.S. Department of Energy, Office of Science, under Contract No. DE-AC0206CH11357.
文摘Precise control over the charge carrier dynamics throughout the device can result in outstanding performance of perovskite solar cells(PSCs).Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)is the most actively studied hole transport material in p-i-n structured PSCs.However,charge transport in the PEDOT:PSS is limited and inefficient because of its low conductivity with the presence of the weak ionic conductor PSS.In addition,morphology of the underlying PEDOT:PSS layer in PSCs plays a crucial role in determining the optoelectronic quality of the active perovskite absorber layer.This work is focused on realization of a non-wetting conductive surface of hole transport layer suitable for the growth of larger perovskite crystalline domains.This is accomplished by employing a facile solventengineered(ethylene glycol and methanol)approach resulting in removal of the predominant PSS in PEDOT:PSS.The consequence of acquiring larger perovskite crystalline domains was observed in the charge carrier dynamics studies,with the achievement of higher charge carrier lifetime,lower charge transport time and lower transfer impedance in the solvent-engineered PEDOT:PSS-based PSCs.Use of this solventengineered treatment for the fabrication of MAPbI3 PSCs greatly increased the device stability witnessing a power conversion efficiency of 18.18%,which corresponds to^37%improvement compared to the untreated PEDOT:PSS based devices.
基金Project supported by the National Natural Science Foundation of China (Grant No. 50677034)the State Key Laboratory of Control and Simulation of Power System and Generation Equipment, China (Grant No. SKLD11M04)the State Key Laboratory of Electrical Insulation and Power Equipment, China (Grant No. EIPE12201)
文摘A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and a production chamber housing the exploding wire load and ambient gas. With the EEW device, nanosize powders of titanium oxides, titanium nitrides, copper oxides, and zinc oxides are successfully synthesized. The average particle size of synthesized powders under different experimental conditions is in a range of 20nm–80nm. The pressure of ambient gas or wire vapor can strongly affect the average particle size. The lower the pressure, the smaller the particle size is. For wire material with relatively high resistivity, such as titanium, whose deposited energy Wd is often less than sublimation energy W s due to the flashover breakdown along the wire prematurely ending the Joule heating process, the synthesized particle size of titanium oxides or titanium nitrides increases with overheat coefficient k （k = W d /Ws ） increasing.
基金Projects(1253929,1910853)supported by the National Natural Science Foundation of China。
文摘Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementation of multiband reconfigurable RF components with microfabrication techniques and advanced materials.RF applications of fabrication methods such as surface and bulk micromachining techniques are reviewed,especially on the development of RF microelectromechanical systems(MEMS)and other tunable components.Works on the application of ferroelectric and ferromagnetic materials are investigated,which enables RF components with continuous tunability,reduced size,and enhanced performance.Methods and strategies with nano-patterning to improve high frequency characteristics of ferromagnetic thin film(e.g.,ferromagnetic resonance frequency and losses)and their applications on the development of fully electrically tunable RF components are fully demonstrated.
文摘Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for phase-contrast imaging of small insects such as mosquitoes and ants in which it was possible to observe clearly their detailed internal structures,which can never be seen with conventional x-ray radiography.Electrical explosion of a wire array(EEWA)in vacuum is the initial stage in the formation of a wire-array Z-pinch.The evolution ofEEWAwas observed with x-ray backlighting using two X-pinches as x-ray sources.It was found that each wire in an EEWA exhibits a core–corona structure instead of forming a fully vaporized metallic vapor.This structure is detrimental to the plasma implosion of a Z-pinch.By inserting an insulator as a flashover switch into the cathode,formation of a core–corona structure was suppressed and core-freeEEWAwas realized.EEWin gases was used for nanopowder production.Three parameters(vaporization rate,gas pressure,and energy deposited in the exploding plasma)were found to influence the nanoparticle size.EEWin water was used for shock-wave generation.The shock wave generated by melting could be recorded with a piezoelectric gauge only in underheat EEW.ForEEW with a given stored energy but different energy-storage capacitor banks,the small capacitor bank produced a rapidly rising current that deposited more energy into the wire and generated a stronger shock wave.
基金supported by a Grant-in-aid for the National Core Research Center Program from MOST and KOSEF, Korea (No.R15-2006-022-01001-0)partly supported by Pusan National University Research Grand,2008
文摘WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge machining(EDM) is one of the most effective methods for making holes because the hardness is not a dominant parameter in EDM. This paper describes the characteristics of the discharge conditions for micro-hole EDM of tungsten carbide with a WC grain size of 0.5 μm and Co content of 12%. The EDM process was conducted by varying the condenser and resistance values. A R-C discharge EDM device using arc erosion for micro-hole machining was suggested. Furthermore, the characteristics of the developed micro-EDM were analyzed in terms of the electro-optical observation using an oscilloscope and field emission scanning electron microscope.
