Time-resolved characteristics of a nanosecond pulsed multi-hollow needle plate packed bed dielectric barrier discharge

In this paper,self-designed multi-hollow needle electrodes are used as a high-voltage electrode in a packed bed dielectric barrier discharge reactor to facilitate fast gas flow through the active discharge area and achieve large-volume stable discharge.The dynamic characteristics of the plasma,the generated active species,and the energy transfer mechanisms in both positive discharge(PD)and negative discharge(ND)are investigated by using fast-exposure intensified charge coupled device(ICCD)images and time-resolved optical emission spectra.The experimental results show that the discharge intensity,number of discharge channels,and discharge volume are obviously enhanced when the multi-needle electrode is replaced by a multihollow needle electrode.During a single voltage pulse period,PD mainly develops in a streamer mode,which results in a stronger discharge current,luminous intensity,and E/N compared with the diffuse mode observed in ND.In PD,as the gap between dielectric beads changes from 0 to250μm,the discharge between the dielectric bead gap changes from a partial discharge to a standing filamentary micro-discharge,which allows the plasma to leave the local area and is conducive to the propagation of surface streamers.In ND,the discharge only appears as a diffusionlike mode between the gap of dielectric beads,regardless of whether there is a discharge gap.Moreover,the generation of excited states N_(2)^(+)(B^(2)∑_(u)^(+))and N2(C^(3)Π_(u))is mainly observed in PD,which is attributed to the higher E/N in PD than that in ND.However,the generation of the OH(A^(2)∑^(+))radical in ND is higher than in PD.It is not directly dominated by E/N,but mainly by the resonant energy transfer process between metastable N_(2)(A^(3)∑_(u)^(+))and OH(X^(2)Π).Furthermore,both PD and ND demonstrate obvious energy relaxation processes of electron-to-vibration and vibration-to-vibration,and no vibration-to-rotation energy relaxation process is observed.

二维矩形Strip Packing问题的算法研究与改进

二维矩形Strip Packing问题的约束条件及目标函数与基本型二维矩形Packing问题类似,都是在有限的矩形容器中,有效地摆放各个矩形块,以最大化容器利用率为目标。为了解决这一NP-hard问题,该文在邓见凯、王磊提出的拟人型全局优化算法的基础上进行了深入的算法研究与改进。针对Strip Packing问题特点,提出了QHG(Quasi-Human Group)算法,其核心改进涵盖了多个方面,包括扩充初始点集合、删除和替换评价标准以及扩大邻域空间搜索范围。和单个局部极小值点的迭代相比,对局部极小值点集合进行迭代所生成布局优度更高,跳坑策略用于跳出局部极小值点,将搜索引向有希望的区域,优美度枚举有望进一步提高布局优度。通过这些措施,QHG算法更好地模拟人类决策过程,提高了全局搜索的效率。为评估QHG算法性能,对8组标准问题实例(C组、N组、NT组、CX组、NP组、ZDF组、2sp组、bwmv组)进行了大量实验。实验结果表明,QHG算法生成的布局优度优于当前国际文献中的几种较先进算法,展现了其在Strip Packing问题上的卓越性能。

Packed Bed Thermocline Thermal Energy Storage for Medium-Temperature Concentrating Solar Systems: Numerical and Experimental Study

Thermal Energy Storage is becoming a necessary component of sustainable energy production systems as it helps alleviate intrinsic limitations of Renewable Energy Sources, such as intermittent use and mismatch between power demand and supply. This paper discusses a packed bed thermocline tank as a thermal energy storage solution. Firstly, this paper presents the development of a numerical model calculating heat transfers within the tank, based on a discretization over several nodes and the nodal formulation of the heat balance equation. The model considers a filler material and a heat transferring fluid and uses the finite difference method to calculate the temperature evolution of the two media across the tank. The model was validated with two different packed bed systems from the literature during a discharging process, presenting a good fit with the experimental results. Secondly, the experimental packed bed is presented and characterized for a charging cycle from ambient temperature to approximately 180?C. The charging experiment was accurately reproduced with the numerical model requiring minimal computational time. Two additional charging modes were simulated with different inlet HTF conditions: constant temperature and varying temperature following the profile produced by a thermal solar collector field. The temperature profiles obtained from the three charging modes were analysed and compared to each other. The proposed numerical and experimental tools will be used in future studies for a better understanding of the design and operating conditions of packed bed thermal energy storage systems.

Measurements of the effective mass transfer areas for the gas–liquid rotating packed bed

Rotating packed bed(RPB) is one of the most effective gas–liquid mass transfer enhancement reactors, its effective specific mass transfer area(ae) is critical to understand the mass transfer process. By using the NaOH–CO_(2) chemical absorption method, the aevalues of three RPB reactors with different rotor sizes were measured under different operation conditions. The results showed that the high gravity factor and liquid flow rate were major affecting factors, while the gas flow rate exhibited minor influence.The radius of packing is the dominant equipment factor to affect aevalue. The results indicated that the contact area depends on the dispersion of the liquid phase, thus the centrifugal force of rotating packed bed greatly influenced the aevalue. Moreover, the measured ae/ap(effective specific mass transfer area/specific surface area of packing) values were fitted with dimensionless correlation formulas. The unified correlation formula with dimensionless bed size parameter can well predict the experimental data and the prediction errors were within 15%.

Electric-controlled pressure relief valve for enhanced safety in liquid-cooled lithium-ion battery packs

The liquid-cooled battery energy sto rage system(LCBESS) has gained significant attention due to its superior thermal management capacity.However,liquid-cooled battery pack(LCBP) usually has a high sealing level above IP65,which can trap flammable and explosive gases from battery thermal runaway and cause explosions.This poses serious safety risks and challenges for LCBESS.In this study,we tested overcharged battery inside a commercial LCBP and found that the conventionally mechanical pressure relief valve(PRV) on the LCBP had a delayed response and low-pressure relief efficiency.A realistic 20-foot model of an energy storage cabin was constructed using the Flacs finite element simulation software.Comparative studies were conducted to evaluate the pressure relief efficiency and the influence on neighboring battery packs in case of internal explosions,considering different sizes and installation positions of the PRV.Here,a newly developed electric-controlled PRV integrated with battery fault detection is introduced,capable of starting within 50 ms of the battery safety valve opening.Furthermore,the PRV was integrated with the battery management system and changed the battery charging and discharging strategy after the PRV was opened.Experimental tests confirmed the efficacy of this method in preventing explosions.This paper addresses the safety concerns associated with LCBPs and proposes an effective solution for explosion relief.

Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data

Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.

Molecular packing tuning via chlorinated end group enables efficient binary organic solar cells over 18.5%

Designing novel nonfullerene acceptors(NFAs)is of vital importance for the development of organic solar cells(OSC).Modification on the side chain and end group are two powerful tools to construct efficient NFAs.Here,based on the high-performance L8BO,we selected 3-ethylheptyl to substitute the inner chain of 2-ethylhexyl,obtaining the backbone of BON3.Then we introduced different halogen atoms of fluorine and chlorine on 2-(3-oxo-2,3-dihydro-1Hinden-1-ylidene)malononitrile end group(EG)to construct efficient NFAs named BON3-F and BON3-Cl,respectively.Polymer donor D18 was chosen to combine with two novel NFAs to construct OSC devices.Impressively,D18:BON3-Cl-based device shows a remarkable power conversion efficiency(PCE)of 18.57%,with a high open-circuit voltage(V_(OC))of 0.907 V and an excellent fill factor(FF)of 80.44%,which is one of the highest binary PCE of devices based on D18 as the donor.However,BON3-F-based device shows a relatively lower PCE of 17.79%with a decreased FF of 79.05%.The better photovoltaic performance is mainly attributed to the red-shifted absorption,higher electron and hole mobilities,reduced charge recombination,and enhanced molecular packing in the D18:BON3-Cl films.Also,we performed stability tests on two binary systems;the D18:BON3-Cl and D18:BON3-F devices maintain 88.1%and 85.5%of their initial efficiencies after 169 h of storage at 85°C in an N2-filled glove box,respectively.Our work demonstrates the importance of selecting halogen atoms on EG and provides an efficient binary system of D18:BON3-Cl for further improvement of PCE.

A hierarchical enhanced data-driven battery pack capacity estimation framework for real-world operating conditions with fewer labeled data

Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.

Effect of the Particle Packing Configuration on Fixed Bed Performance

Fixed-bed reactors are generally considered the optimal choice for numerous multi-phase catalytic reactions due to their excellent performance and stability.However,conventional fixed beds often encounter challenges related to inadequate mass transfer and a high pressure drop caused by the non-uniform void fraction distribution.To enhance the overall performance of fixed beds,the impact of different packing configurations on performance was investigated.Experimental and simulation methods were used to investigate the fluid flow and mass transfer performances of various packed beds under different flow rates.It was found that structured beds exhibited a significantly lower pressure drop per unit length than conventional packed beds.Furthermore,the packing configurations had a critical role in improving the overall performance of fixed beds.Specifically,structured packed beds,particularly the H-2 packing configuration,effectively reduced the pressure drop per unit length and improved the mass transfer efficiency.The H-2 packing configuration consisted of two parallel strips of particles in each layer,with strips arranged perpendicularly between adjacent layers,and the spacing between the strips varied from layer to layer.

Enhanced Wolf Pack Algorithm (EWPA) and Dense-kUNet Segmentation for Arterial Calcifications in Mammograms

Breast Arterial Calcification(BAC)is a mammographic decision dissimilar to cancer and commonly observed in elderly women.Thus identifying BAC could provide an expense,and be inaccurate.Recently Deep Learning(DL)methods have been introduced for automatic BAC detection and quantification with increased accuracy.Previously,classification with deep learning had reached higher efficiency,but designing the structure of DL proved to be an extremely challenging task due to overfitting models.It also is not able to capture the patterns and irregularities presented in the images.To solve the overfitting problem,an optimal feature set has been formed by Enhanced Wolf Pack Algorithm(EWPA),and their irregularities are identified by Dense-kUNet segmentation.In this paper,Dense-kUNet for segmentation and optimal feature has been introduced for classification(severe,mild,light)that integrates DenseUNet and kU-Net.Longer bound links exist among adjacent modules,allowing relatively rough data to be sent to the following component and assisting the system in finding higher qualities.The major contribution of the work is to design the best features selected by Enhanced Wolf Pack Algorithm(EWPA),and Modified Support Vector Machine(MSVM)based learning for classification.k-Dense-UNet is introduced which combines the procedure of Dense-UNet and kU-Net for image segmentation.Longer bound associations occur among nearby sections,allowing relatively granular data to be sent to the next subsystem and benefiting the system in recognizing smaller characteristics.The proposed techniques and the performance are tested using several types of analysis techniques 826 filled digitized mammography.The proposed method achieved the highest precision,recall,F-measure,and accuracy of 84.4333%,84.5333%,84.4833%,and 86.8667%when compared to other methods on the Digital Database for Screening Mammography(DDSM).

DS Smith北美公司推出新的PackRight 2.0多元协作体验系统

7月26日,DSSmith推出了一种多元协作体验系统——PackRight 2.0。新产品的包装设计以互动研讨会为特色,帮助快消品(FMCG)、电子商务和其他行业的企业创新,使用DS Smith专有的循环设计指标可提高包装的可持续性。

得世推出P5 350 HS Pack瓦楞新产品

作为数字印刷和生产技术制造商,得世通过P 5350 HS Pack的推出扩展了其产品组合,P5 Pack系列计划于2024年第三季度上市。P5 Pack系列是专为瓦楞展示架和包装生产量身定制的产品,P5350 HS Pack将P5混合印刷系统的多功能性与在POP/POS和零售市场使用的各种材料上进行印刷的能力相结合。

3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images

Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.

Numerical simulation and physical analysis for dynamic behaviors of P/M TiAl alloy in hot-packed forging process

The hot forging of large-scale P/M TiAl alloy billet deformation was investigated based on a joint application of Deform-3D-based numerical simulation and physical simulation techniques.The temperature dependence on the thermal and mechanical properties of the billet was considered and the optimum hot working temperature of packed TiAl alloy was 1150-1200 °C.Based on the simulation,the material flow and thermo mechanical field variables,such as stress,strain,and temperature distribution were obtained and the relationships of load—displacement and load—time were figured out.To verify the validity of the simulation results,the experiments were also carried out in a forging plant,and a pancake with diameter of 150 mm was obtained exhibiting a regular shape.

优化的Packed R-树空间索引在森林资源管理中的应用

本文首先对R-树系列中典型的几种优化R-树索引结构进行分析,指出他们各自的优缺点以及适应的空间数据及其操作类型,然后进行森林资源管理系统中空间数据管理功能模块的需求分析,指出该模块在实际应用中,具有待处理的空间数据量稳定、更加关注查询效率、插入与删除操作不频繁等特点,最后对前面的两部分内容进行综合的对比分析,指出优化后的Packed R-树更能满足本文伊春公安局森林案件勘察管理系统空间数据管理功能模块的需求。

Hilbert packed R树在空中交通管制GIS显示中的研究与应用

现有空中交通管制(ATC)地理信息系统(GIS)重绘时遍历整个地图模型来绘制所有图元,影响了地图显示的速度。针对这一问题,设计了基于Hilbert packed R树的地图绘制算法,首先为每一个图层建立Hilbert packed R树索引,以此为基础每次重绘时采用深度优先遍历的绘制方法重绘地图。试验结果表明,该算法有效地提高了地图显示的速度。

动力电池PACK智能制造复合型人才定向培养研究

分析了新能源汽车核心能量源——动力电池PACK制造的现状,根据当前动力电池PACK智能制造人才培养的现状,对动力电池PACK智能制造复合型人才定向培养路径进行了研究,为其他跨专业领域的复合型人才培养提供启示。

Continuous Distillation Experiment with Rotating Packed Bed

The performance of a rotating packed bed （RPter solutioB） with three kinds of packings was investigated using alcohol/wan under continuous distillation conditions at atmospheric pressure. The effects of average high gravity factor （β）, reflux ratio （R）, and feedstock flux （F） on mass-transfer in distillation were examined separately. Experimental results indicated that the total number of theoretical units （NTU） of RPB increased with β, R, and F.Of the three kinds of packings, the wave thread packing of stainless steel （Packing-Ⅲ）-had the best mass transfer efficiency with the height equivalent of a theoretical plate （HETP） of approximately 7.35 mm- 23.58 ram, whereas the corrugated disk pacing of stainless steel,（Packing Ⅰ） had the worst one with the HETP of about 13.4 mm-48.07 mm.Correlations were cleveloped to describe the mass transfer efficiency for packings Comparing.experimental data with the data calculated by correlation, the average deviate obtained for each packing was 0.72%, 1.98%, and 2.7%, respectively, implying that the accuracy of correlations developed was reasonable.

Particle-resolved simulation of packed beds by non-body conforming locally refined orthogonal hexahedral mesh

The traditional fixed-bed reactor design is usually not suitable for the low tube-to-particle diameter ratios(N = D/d b 8) where the local phenomena of channeling near the wall and backflow in the bed are dominant. The recent"solid particle" meshing method is too complicated for mesh generation, especially for non-spherical particles in large random packed beds, which seriously hinders its development. In this work, a novel high-fidelity mesh model is proposed for simulation of fixed bed reactors by combining the immersed boundary and adaptive meshing methods. This method is suitable for different shapes of particles, which ingeniously avoids handling the complex "contact point" problem. Several packed beds with two different shapes of particles are investigated with this model, and the local flow in the bed is simulated without geometrical simplification. The predicted pressure drop across the fixed bed and heat transfer of the single particle are in good agreement with the corresponding empirical relations. Compared with spherical particles, the packed bed packing with pentaphyllous particles has lower pressure drop and better heat/mass transfer performance, and it shows that this method can be used for the screening of particle shapes in a fixed bed.

Characteristics of Fin Baffle Packing Used in Rotating Packed Bed

For an alcohol/water system and with fin baffle packing,continuous distillation experiments were carried out in a rotating packed bed(RPB)system at atmospheric pressure.The effects of the average high gravity factor(β),liquid reflux ratio(R)and feedstock flux(F)on the momentum transfer and mass transfer were investigated. The gas phase pressure drop of RPB increased with the average high gravity factor,liquid reflux ratio and feedstock flux,which was 13.55-64.37 Pa atβof 2.01-51.49,R of 1.0-2.5,and F of 8-24 L·h1for a theoretical tray in the RPB with fin baffle packing.The investigation on the mass transfer in the RPB with different packings showed that the number of transfer units of RPB with a packing also increased with the average high gravity factor,reflux ratio and feedstock flux.It is found that the fin baffle packing(packing III)presents the best mass transfer performance and lowest pressure drop for the height equivalent to a theoretical plate(HETP),which is 6.59-9.84 mm.