The acceleration of a high-charge electron bunch to 10 GeV in a 10-cm nanoparticle-assisted wakefield accelerator

An intense laser pulse focused onto a plasma can excite nonlinear plasma waves.Under appropriate conditions,electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic velocities.This scheme is called a laser wakefield accelerator.In this work,we present results from a laser wakefield acceleration experiment using a petawatt-class laser to excite the wakefields as well as nanoparticles to assist the injection of electrons into the accelerating phase of the wakefields.We find that a 10-cm-long,nanoparticle-assisted laser wakefield accelerator can generate 340 pC,10±1.86 GeV electron bunches with a 3.4 GeV rms convolved energy spread and a 0.9 mrad rms divergence.It can also produce bunches with lower energies in the 4–6 GeV range.

Stepped-up development of accelerator mass spectrometry method for the detection of ^(60)Fe with the HI-13 tandem accelerator

The Moon provides a unique environment for investigating nearby astrophysical events such as supernovae.Lunar samples retain valuable information from these events,via detectable long-lived“fingerprint”radionuclides such as^(60)Fe.In this work,we stepped up the development of an accelerator mass spectrometry(AMS)method for detecting^(60)Fe using the HI-13tandem accelerator at the China Institute of Atomic Energy(CIAE).Since interferences could not be sufficiently removed solely with the existing magnetic systems of the tandem accelerator and the following Q3D magnetic spectrograph,a Wien filter with a maximum voltage of±60 kV and a maximum magnetic field of 0.3 T was installed after the accelerator magnetic systems to lower the detection background for the low abundance nuclide^(60)Fe.A 1μm thick Si_(3)N_(4) foil was installed in front of the Q3D as an energy degrader.For particle detection,a multi-anode gas ionization chamber was mounted at the center of the focal plane of the spectrograph.Finally,an^(60)Fe sample with an abundance of 1.125×10^(-10)was used to test the new AMS system.These results indicate that^(60)Fe can be clearly distinguished from the isobar^(60)Ni.The sensitivity was assessed to be better than 4.3×10^(-14)based on blank sample measurements lasting 5.8 h,and the sensitivity could,in principle,be expected to be approximately 2.5×10^(-15)when the data were accumulated for 100 h,which is feasible for future lunar sample measurements because the main contaminants were sufficiently separated.

Role of End-ring Configuration in Shaping IE4 Induction Motor Performance

The performance characteristics,particularly the starting performance of direct line-fed induction motors,which are mainly influenced by the design of the rotor,are crucial considerations for end-users.It is quite a challenging issue for motor manufacturers to enhance the starting performance of existing mass-produced motors with minimal modifications and expenses.In this paper,a simple and cost-effective method to improve the starting performance of a commercial squirrel-cage induction motor(SCIM)is proposed.The influence of geometric parameters of the end-ring on the performance characteristics,including starting(locked rotor)torque,pull-up and break down torque,starting current,rotor electric parameters,current density,power losses,and efficiency have been comprehensively investigated.It has been revealed that among the other end-ring design parameters,the ring thickness has a significant effect on the performance characteristics.An optimal end-ring thickness is determined,and its performance characteristics have been compared to those of its initial counterpart.Numeric and parametric analyses have been conducted using a 2D time-stepping finite element method(FEM).The FEM results were validated using experimental measurements obtained from an 11 kW SCIM prototype.

Harmonics in the Squirrel Cage Induction Motor Analytic Calculation Part III: Influence on the Torque-speed Characteristic

The harmonics that appear in the squirrel cage asynchronous machine have been discussed in great detail in the literature for a long time. However, the systematization of the phenomenon is still pending, so we made an attempt to fill this gap in the previous parts of our study by elaborating formulas for calculation of parasitic torques. It was a general demand among those who work in this field towards the author to verify his formulas with measurements. In the literature, it seems,only one detailed, purposeful series of measurements has been published so far, the purpose of which was to investigate the effect of the number of rotor slots on the torque-speed characteristic curve of the machine. The main goal of this study is to verify the correctness of the formulas by comparing them with the referred series of measurements. Relying on this, the expected synchronous parasitic torques were developed for the frequently used rotor slot numbers-as a design guide for the engineer.Thus, together with our complete table for radial magnetic pull published in our previous work, the designer has all the principles, data and formulas available for the right number of rotor slots for his given machine and for the drive system. This brings this series of papers to an end.

On-chip ultrafast stackable dielectric laser positron accelerator

We present a first on-chip positron accelerator based on dielectric laser acceleration.This innovative approach significantly reduces the physical dimensions of the positron acceleration apparatus,enhancing its feasibility for diverse applications.By utilizing a stacked acceleration structure and far-infrared laser technology,we are able to achieve a seven-stage acceleration structure that surpasses the distance and energy gain of using the previous dielectric laser acceleration methods.Additionally,we are able to compress the positron beam to an ultrafast sub-femtosecond scale during the acceleration process,compared with the traditional methods,the positron beam is compressed to a greater extent.We also demonstrate the robustness of the stacked acceleration structure through the successful acceleration of the positron beam.

A Study of the TPS Based Beam-Matching Concept for Medical Linear Accelerators at a Tertiary Hospital

The flexibility in radiotherapy can be improved if patients can be moved between any one of the department’s medical linear accelerators (LINACs) without the need to change anything in the patient’s treatment plan. For this to be possible, the dosimetric characteristics of the various accelerators must be the same, or nearly the same. The purpose of this work is to describe further and compare measurements and parameters after the initial vendor-recommended beam matching of the five LINACs. Deviations related to dose calculations and to beam matched accelerators may compromise treatment accuracy. The safest and most practical way to ensure that all accelerators are within clinical acceptable accuracy is to include TPS calculations in the LINACs matching evaluation. Treatment planning system (TPS) was used to create three photons plans with different field sizes 3 × 3 cm, 10 × 10 cm and 25 × 25 cm at a depth of 4.5 cm in Perspex. Calculated TPS plans were sent to Mosaiq to be delivered by five LINACs. TPS plans were compared with five LINACs measurements data using Gamma analyses of 2% and 2 mm. The results suggest that for four out of the five LINACs, there was generally good agreement, less than a 2% deviation between the planned dose distribution and the measured dose distribution. However, one specific LINAC named “Asterix” exhibited a deviation of 2.121% from the planned dose. The results show that all of the LINACs’ performance were within the acceptable deviation and delivering radiation dose consistently and accurately.

Uniformity Control of Scanned Beam in 300 MeV Proton and Heavy Ion Accelerator Complex at SESRI

In recent years,heavy ion accelerator technology has been rapidly developing worldwide and widely applied in the fields of space radiation simulation and particle therapy.Usually,a very high uniformity in the irradiation area is required for the extracted ion beams,which is crucial because it directly affects the experimental precision and therapeutic effect.Specifically,ultra-large-area and high-uniformity scanning are crucial requirements for spacecraft radiation effects assessment and serve as core specification for beamline terminal design.In the 300 MeV proton and heavy ion accelerator complex at the Space Environment Simulation and Research Infrastructure(SESRI),proton and heavy ion beams will be accelerated and ultimately delivered to three irradiation terminals.In order to achieve the required large irradiation area of 320 mm×320 mm,horizontal and vertical scanning magnets are used in the extraction beam line.However,considering the various requirements for beam species and energies,the tracking accuracy of power supplies(PSs),the eddy current effect of scanning magnets,and the fluctuation of ion bunch structure will reduce the irradiation uniformity.To mitigate these effects,a beam uniformity optimization method based on the measured beam distribution was proposed and applied in the accelerator complex at SESRI.In the experiment,the uniformity is successfully optimized from 75%to over 90%after five iterations of adjustment to the PS waveforms.In this paper,the method and experimental results were introduced.

Microstructural evolution and strengthening mechanism of aligned steel fiber cement-based tail backfills exposed to electromagnetic induction

Cemented tailings backfill(CTB)not only boosts mining safety and cuts surface environmental pollution but also recovers ores previously retained as pillars,thereby improving resource utilization.The use of alternative reinforcing products,such as steel fiber(SF),has continuously strengthened CTB into SFCTB.This approach prevents strength decreases over time and reinforces its long-term durability,especially when mining ore in adjacent underground stopes.In this study,various microstructure and strength tests were performed on SFCTB,considering steel fiber ratio and electromagnetic induction strength effects.Lab findings show that combining steel fibers and their distribution dominantly influences the improvement of the fill’s strength.Fill’s strength rises by fiber insertion and has an evident correlation with fiber insertion and magnetic induction strength.When magnetic induction strength is 3×10^(-4) T,peak uniaxial compressive stress reaches 5.73 MPa for a fiber ratio of 2.0vol%.The cracks’expansion mainly started from the specimen’s upper part,which steadily expanded downward by increasing the load until damage occurred.The doping of steel fiber and its directional distribution delayed crack development.When the doping of steel fiber was 2.0vol%,SFCTBs showed excellent ductility characteristics.The energy required for fills to reach destruction increases when steel-fiber insertion and magnetic induction strength increase.This study provides notional references for steel fibers as underground filling additives to enhance the fill’s durability in the course of mining operations.

A Novel Quantization and Model Compression Approach for Hardware Accelerators in Edge Computing

Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro-posed to improve the efficiency for edge inference of Deep Neural Networks(DNNs),existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead,and their efficiency is bounded by the bottleneck of computation latency and memory footprint.To tackle this challenge,we present an efficient inference approach on the basis of PoT quantization and model compression.An integer-only scalar PoT quantization(IOS-PoT)is designed jointly with a distribution loss regularizer,wherein the regularizer minimizes quantization errors and training disturbances.Additionally,two-stage model compression is developed to effectively reduce memory requirement,and alleviate bandwidth usage in communications of networked heterogenous learning systems.The product look-up table(P-LUT)inference scheme is leveraged to replace bit-shifting with only indexing and addition operations for achieving low-latency computation and implementing efficient edge accelerators.Finally,comprehensive experiments on Residual Networks(ResNets)and efficient architectures with Canadian Institute for Advanced Research(CIFAR),ImageNet,and Real-world Affective Faces Database(RAF-DB)datasets,indicate that our approach achieves 2×∼10×improvement in the reduction of both weight size and computation cost in comparison to state-of-the-art methods.A P-LUT accelerator prototype is implemented on the Xilinx KV260 Field Programmable Gate Array(FPGA)platform for accelerating convolution operations,with performance results showing that P-LUT reduces memory footprint by 1.45×,achieves more than 3×power efficiency and 2×resource efficiency,compared to the conventional bit-shifting scheme.

Analytical Model and Topology Optimization of Doubly-fed Induction Generator

As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and accurate design optimization of DFIGs,this paper proposes a novel hybriddriven surrogate-assisted optimization method.It firstly establishes an accurate subdomain model of DFIGs to analytically predict performance indexes.Furthermore,taking the inexpensive analytical dataset produced by the subdomain model as the source domain and the expensive finite element analysis dataset as the target domain,a high-precision surrogate model is trained in a transfer learning way and used for the subsequent multi-objective optimization process.Based on this model,taking the total harmonic distortion of electromotive force,cogging torque,and iron loss as objectives,and the slot and inner/outer diameters as parameters for optimizing the topology,achieve a rapid and accurate electromagnetic design for DFIGs.Finally,experiments are carried out on a 3MW DFIG to validate the effectiveness of the proposed method.

Cambricon-QR:a sparse and bitwise reproducible quantized training accelerator

Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negligible accuracy loss.Cambricon-Q is the ASIC design proposed to efficiently support quantized training,and achieves significant performance improvement.However,there are still two caveats in the design.First,Cambricon-Q with different hardware specifications may lead to different numerical errors,resulting in non-reproducible behaviors which may become a major concern in critical applications.Second,Cambricon-Q cannot leverage data sparsity,where considerable cycles could still be squeezed out.To address the caveats,the acceleration core of Cambricon-Q is redesigned to support fine-grained irregular data processing.The new design not only enables acceleration on sparse data,but also enables performing local dynamic quantization by contiguous value ranges(which is hardware independent),instead of contiguous addresses(which is dependent on hardware factors).Experimental results show that the accuracy loss of the method still keeps negligible,and the accelerator achieves 1.61×performance improvement over Cambricon-Q,with about 10%energy increase.

A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode

Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.

A Stable Fuzzy-Based Computational Model and Control for Inductions Motors

In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.

Coupled Numerical Simulation of Electromagnetic and Flow Fields in a Magnetohydrodynamic Induction Pump

Magnetohydrodynamic(MHD)induction pumps are contactless pumps able to withstand harsh environments.The rate of fluid flow through the pump directly affects the efficiency and stability of the device.To explore the influence of induction pump settings on the related delivery speed,in this study,a numerical model for coupled electromagnetic and flow field effects is introduced and used to simulate liquid metal lithium flow in the induction pump.The effects of current intensity,frequency,coil turns and coil winding size on the velocity of the working fluid are analyzed.It is shown that the first three parameters have a significant impact,while changes in the coil turns have a negligible influence.The maximum increase in working fluid velocity within the pump for the parameter combination investigated in this paper is approximately 618%.As the frequency is increased from 20 to 60 Hz,the maximum increase in the mean flow rate of the working fluid is approximately 241%.These research findings are intended to support the design and optimization of these devices.

Dual-negative-objective Coordinated Control of Brushless Doubly Fed Induction Generator under Unbalanced Grid Voltage

This article proposes a dual-negative-objective coordinated control strategy for brushless doubly fed induction generator(BDFIG)based wind power generation system under unbalanced grid voltage.To alleviate the mechanical stress and impaction on rotating shaft,the negative control objective(NCO)of machine side converter(MSC)is set to suppress the ripple of electromagnetic torque.While the NCO of grid side converter(GSC)is selected to suppress the oscillation of total output active power or the unbalanced degree of total output current for BDFIG generation system.In comparison with traditional single converter control scheme of the MSC or GSC,dual NCOs can be satisfied at the same time due to the enlarged freedom degree in the proposed improved coordinated control system for back-toback converters.The effectiveness of proposed control strategy is validated by simulation and experimental results on a dual-cagerotor BDFIG(DCR-BDFIG)prototype.

Is Induction of Labor with Early Rupture of Membranes Associated with an Increased Rate of Clinical Chorioamnionitis?

Objective: The objective of this study was to determine if early rupture of membranes (ROM) in women undergoing induction of labor (IOL) at term is associated with an increased rate of clinical chorioamnionitis. Study Design: A retrospective cohort study was performed on women undergoing IOL. Early ROM was defined as ROM at a modified Bishop score less than 5, cervical dilation less than 4 cm, or cervical effacement less than 80%. The rate of clinical chorioamnionitis was compared between women with early and late ROM. Results: The rate of clinical chorioamnionitis was 8.6% (24/279). ROM at an effacement of less than 80% was associated with a rate of clinical chorioamnionitis of 15.4% (12/78) compared to 6.0% (12/201) at an effacement of equal to or greater than 80%, p = 0.017. The rate of cesarean delivery was higher for patients with early ROM by any definition: 32% compared to 17.5% by modified Bishop score (p = 0.031), 32.4% versus 18.2% by cervical dilation (p = 0.049), and 33.3% versus 14.9% by cervical effacement (p = 0.001). Conclusions: In patients undergoing IOL, early ROM may be associated with an increased rate of clinical chorioamnionitis when performed at a cervical effacement of less than 80% and an increased rate of cesarean delivery.

Research on intelligent search-and-secure technology in accelerator hazardous areas based on machine vision

Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.

Performance and Safety Improvement of Induction Motors based on Testing and Evaluation Standards

The induction motor,which converts electrical energy into mechanical energy,has been recognized as the cornerstone of industrialization.The rotor of an induction motor can be either a squirrel cage rotor or a wound-type rotor,both existing as magnetless topologies.Three-phase squirrel cage induction motors are frequently utilized in industrial drives because they are dependable,have high starting torque,are selfstarting and affordable.Single-phase induction motors,on the other hand,are commonly used for small loads such as domestic appliances in form of modest fans,pumps and electric power tools.In South Africa,there have been reports of fires and explosions resulting in live and property loss because of induction motors that have not been thoroughly tested or are incorrectly labelled in terms of ratings,electrical safety and performance.The goal of this study is targeted at preventing end-user injuries and failures caused by non-compliant induction motors,by evaluating locally manufactured/imported induction motors based on tests and evaluation from standards(IEC and SANS).The study is conducted using experimental procedures at the Explosion Prevention Technology and Rotating Machines(EPT and RM)laboratory,South African Bureau of Standards(SABS),South Africa.The main finding from the study shows differences in the nameplate characteristics of various induction motors which could have detrimental effects such as production and operational downtime in their end-use industries,at later stages.

FPGA Accelerators for Computing Interatomic Potential-Based Molecular Dynamics Simulation for Gold Nanoparticles:Exploring Different Communication Protocols

Molecular Dynamics(MD)simulation for computing Interatomic Potential(IAP)is a very important High-Performance Computing(HPC)application.MD simulation on particles of experimental relevance takes huge computation time,despite using an expensive high-end server.Heterogeneous computing,a combination of the Field Programmable Gate Array(FPGA)and a computer,is proposed as a solution to compute MD simulation efficiently.In such heterogeneous computation,communication between FPGA and Computer is necessary.One such MD simulation,explained in the paper,is the(Artificial Neural Network)ANN-based IAP computation of gold(Au_(147)&Au_(309))nanoparticles.MD simulation calculates the forces between atoms and the total energy of the chemical system.This work proposes the novel design and implementation of an ANN IAP-based MD simulation for Au_(147)&Au_(309) using communication protocols,such as Universal Asynchronous Receiver-Transmitter(UART)and Ethernet,for communication between the FPGA and the host computer.To improve the latency of MD simulation through heterogeneous computing,Universal Asynchronous Receiver-Transmitter(UART)and Ethernet communication protocols were explored to conduct MD simulation of 50,000 cycles.In this study,computation times of 17.54 and 18.70 h were achieved with UART and Ethernet,respectively,compared to the conventional server time of 29 h for Au_(147) nanoparticles.The results pave the way for the development of a Lab-on-a-chip application.

Design and implementation of dual-mode configurable memory architecture for CNN accelerator

With the rapid development of deep learning algorithms,the computational complexity and functional diversity are increasing rapidly.However,the gap between high computational density and insufficient memory bandwidth under the traditional von Neumann architecture is getting worse.Analyzing the algorithmic characteristics of convolutional neural network(CNN),it is found that the access characteristics of convolution(CONV)and fully connected(FC)operations are very different.Based on this feature,a dual-mode reronfigurable distributed memory architecture for CNN accelerator is designed.It can be configured in Bank mode or first input first output(FIFO)mode to accommodate the access needs of different operations.At the same time,a programmable memory control unit is designed,which can effectively control the dual-mode configurable distributed memory architecture by using customized special accessing instructions and reduce the data accessing delay.The proposed architecture is verified and tested by parallel implementation of some CNN algorithms.The experimental results show that the peak bandwidth can reach 13.44 GB·s^(-1)at an operating frequency of 120 MHz.This work can achieve 1.40,1.12,2.80 and 4.70 times the peak bandwidth compared with the existing work.