Evolution of nonmetallic inclusions in 80-t 9CrMoCoB large-scale ingots during electroslag remelting process

In combination with theoretical calculations,experiments were conducted to investigate the evolution behavior of nonmetallic inclusions(NMIs)during the manufacture of large-scale heat-resistant steel ingots using 9CrMoCoB heat-resistant steel and CaF_(2)–CaO–Al_(2)O_(3)–SiO_(2)–B_(2)O_(3)electroslag remelting(ESR)-type slag in an 80-t industrial ESR furnace.The main types of NMI in the consumable electrode comprised pure alumina,a multiphase oxide consisting of an Al_(2)O_(3)core and liquid CaO–Al_(2)O_(3)–SiO_(2)–MnO shell,and M_(23)C_(6)carbides with an MnS core.The Al_(2)O_(3)and MnS inclusions had higher precipitation temperatures than the M_(23)C_(6)-type carbide under equilibrium and nonequilibrium solidification processes.Therefore,inclusions can act as nucleation sites for carbide layer precipitation.The ESR process completely removed the liquid CaO–Al_(2)O_(3)–SiO_(2)–MnO oxide and MnS inclusion with a carbide shell,and only the Al_(2)O_(3)inclusions and Al_(2)O_(3)core with a carbide shell occupied the remelted ingot.The M_(23)C_(6)-type carbides in steel were determined as Cr_(23)C_(6)based on the analysis of transmission electron microscopy results.The substitution of Cr with W,Fe,or/and Mo in the Cr_(23)C_(6)lattice caused slight changes in the lattice parameter of the Cr_(23)C_(6)carbide.Therefore,Cr_(21.34)Fe_(1.66)C_(6),(Cr_(19)W_(4)C_(6),Cr_(18.4)Mo_(4.6)C_(6),and Cr_(16)Fe_(5)Mo_(2)C_(6)can match the fraction pattern of Cr_(23)C_(6)carbide.The Al_(2)O_(3)inclusions in the remelted ingot formed due to the reduction of CaO,SiO_(2),and MnO components in the liquid inclusion.The increased Al content in liquid steel or the higher supersaturation degree of Al_(2)O_(3)precipitation in the remelted ingot than that in the electrode can be attributed to the evaporation of CaF_(2)and the increase in CaO content in the ESR-type slag.

基于消息代理的OPC UA发布/订阅模式研究与实现

针对目前OPC UA客户端/服务器通信模式中存在的紧耦合、服务器性能瓶颈等问题,进行了OPC UA发布/订阅通信模式总体架构的研究。首先具体分析了UA的核心功能,包括地址空间技术和数据编码技术,并在两者的基础上,利用消息代理机制,完成了发布者和订阅者的功能开发。还通过实验进一步验证了功能的稳定性和对数据的传输能力,结果表明,此模式可以满足大多数工业需求。

Occurrence and distribution of hydroxylated isoprenoid glycerol dialkyl glycerol tetraethers(OH-GDGTs) in the Han River system, South Korea

We investigated the occurrence and distribution of terrestrial-derived hydroxylated isoprenoid glycerol dialkyl glycerol tetraethers(OH-GDGTs) in the Han River system and their potential impact on the application of the ring index of OH-GDGTs(RI-OH) as a sea surface temperature(SST) proxy in the eastern Yellow Sea. Thereby, we analyzed various samples collected along the Han River and from its surrounding areas(South Korea, n = 34). The OHGDGTs were found in all samples investigated. OH-GDGT-0 was the dominant OH-GDGT component in the estuary and marine samples while OH-GDGT-2 was generally dominant in the soils, the lake sediments and the river suspended particulate matter(SPM). Our results thus suggests a possible warm bias of the RI-OH-derived summer SSTs in the coastal zone to which a large amount of terrestrial organic matter is being supplied. Further studies are necessary to better assess the applicability of the RI-OH proxy in the eastern Yellow Sea.

Preparation and characterization of SMA/S-POSS hybrid membranes for direct methanol fuel cell applications

A novel sulfonated polyhedral oligomeric silsesquioxane(S-POSS) monomer was synthesized successfully in this article. S-POSS acted as a donor of sulfonic acid group and reacted with poly(styrene-co-maleic anhydride) (SMA). FT-IR spectroscopy confirmed the modification through introduction of peaks characteristic of ester linkages and carboxylic groups. The SMA/S-POSS hybrid membranes were fabricated from different S-POSS contents. The proton conductivity and methanol permeability of the hybrid membranes were studied with changing S-POSS content from 5wt.% to 30wt.%. It was found that the proton conductivity and the methanol permeability were dependent on the S-POSS content. Both of proton conductivity and methanol permeability properties improve with increasing S-POSS content. The proton conductivities of the hybrid membranes are in the range of 10-3-10-2 S·cm-1, and the range of methanol permeabilities was between 10-8 and 10-7 cm2·s-1. The membranes show good thermal properties characterized by thermogravimetric analysis (TGA).

Numerical evaluation of new Austrian tunneling method excavation sequences: A case study

The main aspects that require attention in tunnel design in terms of safety and economy are the precise estimation of probable ground conditions and ground behavior during construction. The variation in rock mass behavior due to tunnel excavation sequence plays an important role during the construction stage.The purpose of this research is to numerically evaluate the effect of excavation sequence on the ground behavior for the Lowari tunnel project, Pakistan. For the tunnel stability, the ground behavior observed during the actual partial face excavation sequence is compared with the top heading and bench excavation sequence. For this purpose, the intact rock parameters are used along with the characterization of rock mass joints related parameters to provide input for numerical modelling via FLAC 2D. The in-situ stresses for the numerical modelling are obtained using empirical equations. From the comparison of the two excavation sequences, it was observed that the actual excavation sequence used for Lowari tunnel construction utilized more support than the top heading and bench method. However, the actual excavation sequence provided good results in terms of stability.

Characterization of plasma electrolytic oxide formed on AZ91 Mg alloy in KMnO_4 electrolyte

The aim of this work is to investigate microstructure,corrosion resistance characteristics and nanohardness of the oxide layer on AZ91 Mg alloy by applying different voltage with KMnO4 contained solution.There are lots of closed pores that are filled with another oxide compound compared with the typical surface morphology with pore coated until 350 V of coating voltage.The thickness of oxide layer increases with increasing coating voltage.The oxide layer formed on AZ91 Mg alloy in electrolyte with potassium permanganate consists of MgO and Mn2O3.Corrosion potential of the oxide layer on AZ91 Mg alloy obtained at different plasma electrolytic oxidation(PEO) reaction stages increases with increasing coating voltage.The corrosion resistance of AZ91 Mg alloy depends on the existence of the manganese oxide in the oxide layer.The inner barrier layer composed of the MgO and Mn2O3 may serve as diffusion barrier to enhance the corrosion resistance and may partially explain the excellent anti-corrosion performance in corrosion test.Nanohardness values increase with increasing coating voltage.The increase in the nanohardness may be due to the effect of manganese oxide in the oxide layer on AZ91 Mg alloy coated from electrolyte containing KMnO4.

Scale adaptive fitness evaluation‐based particle swarm optimisation for hyperparameter and architecture optimisation in neural networks and deep learning

Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.

Supramolecular Polymer Intertwined Free-Standing Bifunctional Membrane Catalysts for All-Temperature Flexible Zn-Air Batteries

Rational construction of flexible free-standing electrocatalysts featuring long-lasting durability,high efficiency,and wide temperature tolerance under harsh practical operations are fundamentally significant for commercial zinc-air batteries.Here,3D flexible free-standing bifunctional membrane electrocatalysts composed of covalently cross-linked supramolecular polymer networks with nitrogen-deficient carbon nitride nanotubes are fabricated(referred to as PEMAC@NDCN)by a facile self-templated approach.PEMAC@NDCN demonstrates the lowest reversible oxygen bifunctional activity of 0.61 V with exceptional long-lasting durability,which outperforms those of commercial Pt/C and RuO_(2).Theoretical calculations and control experi-ments reveal the boosted electron transfer,electrolyte mass/ion transports,and abundant active surface site preferences.Moreover,the constructed alkaline Zn-air battery with PEMAC@NDCN air-cathode reveals superb power density,capacity,and discharge-charge cycling stability(over 2160 cycles)compared to the reference Pt/C+RuO_(2).Solid-state Zn-air batteries enable a high power density of 211 mW cm^(−2),energy density of 1056 Wh kg^(−1),stable charge-discharge cycling of 2580 cycles for 50 mA cm^(−2),and wide temperature tolerance from−40 to 70℃with retention of 86%capacity compared to room-temperature counterparts,illustrating prospects over harsh operations.

Lithium plating-free 1 Ah-level high-voltage lithium-ion pouch battery via ambi-functional pentaerythritol disulfate

Elevating the charge cut-off voltage beyond traditional 4.2 V is a commonly accepted technology to increase the energy density of Li-ion batteries(LIBs) but the risk of Li-dendrites and fire hazard increases as well. The use of ambi-functional additive, which forms stable solid electrolyte interphase(SEI) simultaneously at both cathode and anode, is a key to enabling a dendrites-free and well-working high-voltage LIB. Herein, a novel ambi-functional additive, pentaerythritol disulfate(PEDS), at 1 wt% without any other additive is demonstrated. We show the feasibility and high impacts of PEDS in forming lithium sulfateincorporated robust SEI layers at NCM523 cathode and graphite anode in 1 Ah-level pouch cell under4.4 V, 25 °C and 0.1 C rate, which mitigates the high-voltage instability, metal-dissolution and cracks on NCM523 particles, and prevents Li-dendrites at graphite anode. Improved capacity retention of 83%after 300 cycles is thereby achieved, with respect to 69% with base electrolyte, offering a promising path toward the design of practical high-energy LIBs.

Solid state synthesis of nano-mineral particles

Many researchers in academia and industries are interested in reducing particle sizes from few submicrometers to nano-meter levels.These nano-particles find application in several areas including ceramics,paints,cosmetics,microelectronics,sensors,textiles and biomedical,etc.This article reviews the present state of the art for solid state synthesis of mineral nano-particles by wet milling,including their operating variables such as ball size,solid mass fraction and suspension stability.This article concludes and recommends with a critical discussion of nano-particles synthesis and a few common strategies to overcome stability issues.

Multiscale Image Dehazing and Restoration:An Application for Visual Surveillance

The captured outdoor images and videos may appear blurred due to haze,fog,and bad weather conditions.Water droplets or dust particles in the atmosphere cause the light to scatter,resulting in very limited scene discernibility and deterioration in the quality of the image captured.Currently,image dehazing has gainedmuch popularity because of its usability in a wide variety of applications.Various algorithms have been proposed to solve this ill-posed problem.These algorithms provide quite promising results in some cases,but they include undesirable artifacts and noise in haze patches in adverse cases.Some of these techniques take unrealistic processing time for high image resolution.In this paper,to achieve real-time halo-free dehazing,fast and effective single image dehazing we propose a simple but effective image restoration technique using multiple patches.It will improve the shortcomings of DCP and improve its speed and efficiency for high-resolution images.A coarse transmissionmap is estimated by using the minimumof different size patches.Then a cascaded fast guided filter is used to refine the transmission map.We introduce an efficient scaling technique for transmission map estimation,which gives an advantage of very low-performance degradation for a highresolution image.For performance evaluation,quantitative,qualitative and computational time comparisons have been performed,which provide quiet faithful results in speed,quality,and reliability of handling bright surfaces.

Distribution characteristics of inclusions along with the surface sliver defect on the exposed panel of automobile:A quantitative electrolysis method

The specific distribution characteristics of inclusions along with the sliver defect were analyzed in detail to explain the formation mechanism of the sliver defect on the automobile exposed panel surface.A quantitative electrolysis method was used to compare and evaluate the three-dimensional morphology,size,composition,quantity,and distribution of inclusions in the defect and non-defect zone of automobile exposed panel.The Al2O3 inclusions were observed to be aggregated or chain-like shape along with the sliver defect of about 3–10μm.The aggregation sections of the Al2O3 inclusions are distributed discretely along the rolling direction,with a spacing of 3–7 mm,a length of 6–7 mm,and a width of about 3 mm.The inclusion area part is 0.04%–0.16%with an average value of 0.08%,the inclusion number density is 40 mm−2 and the inclusion average spacing is 25.13μm.The inclusion spacing is approximately 40–160μm,with an average value of 68.76μm in chain-like inclusion parts.The average area fraction and number density of inclusions in the non-defect region were reduced to about 0.002%and 1–2 mm^−2,respectively,with the inclusion spacing of 400μm and the size of Al2O3 being 1–3μm.

ESG Discourse Analysis Through BERTopic: Comparing News Articles and Academic Papers

Environmental,social,and governance(ESG)factors are critical in achieving sustainability in business management and are used as values aiming to enhance corporate value.Recently,non-financial indicators have been considered as important for the actual valuation of corporations,thus analyzing natural language data related to ESG is essential.Several previous studies limited their focus to specific countries or have not used big data.Past methodologies are insufficient for obtaining potential insights into the best practices to leverage ESG.To address this problem,in this study,the authors used data from two platforms:LexisNexis,a platform that provides media monitoring,and Web of Science,a platform that provides scientific papers.These big data were analyzed by topic modeling.Topic modeling can derive hidden semantic structures within the text.Through this process,it is possible to collect information on public and academic sentiment.The authors explored data from a text-mining perspective using bidirectional encoder representations from transformers topic(BERTopic)—a state-of-the-art topic-modeling technique.In addition,changes in subject patterns over time were considered using dynamic topic modeling.As a result,concepts proposed in an international organization such as the United Nations(UN)have been discussed in academia,and the media have formed a variety of agendas.

Automated Facial Expression Recognition and Age Estimation Using Deep Learning

With the advancement of computer vision techniques in surveillance systems,the need for more proficient,intelligent,and sustainable facial expressions and age recognition is necessary.The main purpose of this study is to develop accurate facial expressions and an age recognition system that is capable of error-free recognition of human expression and age in both indoor and outdoor environments.The proposed system first takes an input image pre-process it and then detects faces in the entire image.After that landmarks localization helps in the formation of synthetic face mask prediction.A novel set of features are extracted and passed to a classifier for the accurate classification of expressions and age group.The proposed system is tested over two benchmark datasets,namely,the Gallagher collection person dataset and the Images of Groups dataset.The system achieved remarkable results over these benchmark datasets about recognition accuracy and computational time.The proposed system would also be applicable in different consumer application domains such as online business negotiations,consumer behavior analysis,E-learning environments,and emotion robotics.

Thick free-standing electrode based on carbon-carbon nitride microspheres with large mesopores for high-energy-density lithium-sulfur batteries

The development of sulfur cathodes with high areal capacity and high energy density is crucial for the practical application of lithium-sulfur batteries(LSBs).LSBs can be built by employing(ultra)high-loading sulfur cathodes,which have rarely been realized due to massive passivation and shuttling.Herein,microspheres of a carbon-carbon nitride composite(C@CN)with large mesopores are fabricated via molecular cooperative assembly.Using the C@CN-based electrodes,the effects of the large mesopores and N-functional groups on the electrochemical behavior of sulfur in LSB cells are thoroughly investigated under ultrahigh sulfur-loading conditions(>15 mgS cm^(-2)).Furthermore,for high-energy-density LSBs,the C@CN powders are pelletized into a thick free-standing electrode(thickness:500^m;diameter:11 mm)via a simple briquette process;here,the total amount of energy stored by the LSB cells is 39 mWh,corresponding to a volumetric energy density of 440 Wh L-1 with an areal capacity of 24.9 and 17.5 mAh cm^(-2) at 0.47 and 4.7 mA cm^(-2),respectively(at 24mgS cm^(-2)).These results have significantly surpassed most recent records due to the synergy among the large mesopores,(poly)sulfide-philic surfaces,and thick electrodes.The developed strategy with its potential for scale-up successfully fills the gap between laboratory-scale cells and practical cells without sacrificing the high areal capacity and high energy density,providing a solid foundation for the development of practical LSBs.

Effect of Post-Rolling after ECAP on Superplastic Behavior of Commercial Al-Mg Alloy

A commercial Al-Mg alloy was subjected to equal channel angular pressing of 4 passes with and without postrolling, and the effects of post-rolling on the deformation characteristics of the alloy at 723 K were examined. Post-rolling was found to influence the deformation behavior significantly. The deformation behavior of the alloy processed only by equal channel angular pressing was characterized by (a) localized deformation indicated by severe surface prominence and depression, (b) the strain rate sensitivity of 0.33, and (c) moderate high strain rate superplastic elongations. By contrast, that of the alloy processed by equal channel angular pressing and post-rolling (70 % thickness reduction) was manifested by (a) uniform deformation associated with grain boundary sliding throughout the sample, (b) a sigmoidal behavior showing the strain rate sensitivity of 0.45 at the intermediate strain rates in the logarithmic stress-strain rate curve, and (c) very large high strain rate superplastic elongations.

Thermodynamics of Ti in liquid steels and slags

Thermodynamics of Ti in liquid steels and slags was studied in order to establish a data base for the prediction of TiO_x and TiN formation in liquid steels.The interaction parameters between Ti and i(i = Cr,Ti,Al, Si,Ni,Mo,Nb,N,O) in liquid iron and the equilibrium constants for the formation of TiN and TiO_x in liquid iron were determined as a function of temperature.In view of high Ti yield during ladle treatment,thermodynamics of titanium oxides in ladle slags was studied as well.Activity coefficient and redox equilibrium of TiO_x in MgO saturated CaO-Al_2O_3 slag are also discussed by measuring the distribution ratio of Ti between slag and iron melts and the Ti^(3+)/Ti^(4+) ratio in slag at 1 873 K.

Asymptotic and other estimates for semilinear parabolic problem in semi-infinite cylinder

The spatial decay of solutions to initial-boundary value problems for a semilinear parabolic equation in a semi-infinite cylinder of variable cross-section subject to zero condition on the lateral boundaries is investigated. A second-order differential inequality that shows the spatial decay O（exp（-z2/（4（t ＋ t0）））） for an L2p cross-sectional measure of the solution is obtained. A first-order differential inequality leading to growth or decay is also derived. In the case of growth, an upper bound for blow-up in space is obtained, while in the case of decay an upper bound for the total energy in terms of data is obtained.

Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging.In this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power control.To effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement learning.The transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network.In the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different topologies.The method is general and can be extended to various types of topologies.