检索结果-南通市图书馆

Development in oxide metallurgy for improving the weldability of high -strength low-alloy steel-Combined deoxidizers and microalloying elements

引用

International Journal of Minerals,Metallurgy and Materials 2024年第6期31卷 1263-1284页

作者： Tingting Li jian Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

The mechanisms of oxide metallurgy include inducing the formation of intragranular acicular ferrite(IAF)using micron-sized inclusions and restricting the growth of prior austenite grains(PAGs)by nanosized particles during welding.The chaotically oriented IAF and refined PAGs inhibit crack initiation and propagation in the steel,resulting in high impact toughness.This work summarizes the com-bined effect of deoxidizers and alloying elements,with the aim to provide a new perspective for the research and practice related to im-proving the impact toughness of the heat affected zone(HAZ)during the high heat input welding.Ti complex deoxidation with other strong deoxidants,such as Mg,Ca,Zr,and rare earth metals(REMs),can improve the toughness of the heat-affected zone(HAZ)by re-fining PAGs or increasing IAF contents.However,it is difficult to identify the specific phase responsible for IAF nucleation because ef-fective inclusions formed by complex deoxidation are usually multiphase.Increasing alloying elements,such as C,Si,Al,Nb,or Cr,con-tents can impair HAZ toughness.A high C content typically increases the number of coarse carbides and decreases the potency of IAF formation.Si,Cr,or Al addition leads to the formation of undesirable microstructures.Nb reduces the high-temperature stability of the precipitates.Mo,V,and B can enhance HAZ toughness.Mo-containing precipitates present good thermal stability.VN or V(C,N)is ef-fective in promoting IAF nucleation due to its good coherent crystallographic relationship with ferrite.The formation of the B-depleted zone around the inclusion promotes IAF formation.The interactions between alloying elements are complex,and the effect of adding dif-ferent alloying elements remains to be evaluated.In the future,the interactions between various alloying elements and their effects on ox-ide metallurgy,as well as the calculation of the nucleation effects of effective inclusions using first principles calculations will become the focus of oxide metallurgy.

关键词： oxide metallurgy technology heat affected zone high-strength low-alloy steel intragranular acicular ferrite microalloying element

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

State of the art in applications of machine learning in steelmaking process modeling

引用

International Journal of Minerals,Metallurgy and Materials 2023年第11期30卷 2055-2075页

作者： Runhao Zhang jian Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.

关键词： machine learning steelmaking process modeling artificial neural network support vector machine case-based reasoning data processing

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Compositional dependence of thermophysical properties in binary alkaline earth borate melts:Insights from structure in short-range and intermediate-range order

引用

Journal of Materials Science & Technology 2022年第36期131卷 195-203页

作者： jian Yang Il Sohn Department of Materials Science and Engineering Yonsei UniversitySeoul120749Korea State Key Laboratory of Cemented Carbide Zhuzhou 412000China

In this work,the thermal conductivity of alkaline earth borate melts was measured using hot-wire method from 1323 to 1623 K,and the thermal diffusivity was extrapolated from the thermal conductivity and heat capacity.The compositional dependence of thermophysical properties was interpreted according to the structure in short-range and intermediate-range order.Based on the Raman spectroscopy,X-ray photoelectron spectroscopy(XPS),and 11B magic-angle spinning nuclear magnetic resonance(MAS-NMR)spectra,modifier cation with higher field strength prefers the formation of non-bridging oxygens(NBOs)for the charge compensation at high BO_(1.5)/MO ratios.A lower amount of covalent bond and greater isolation of large borate groups lead to a lower thermal conductivity in calcium borate melt compared with strontium and barium borates.But the large size of Ba^(2+)encounters difficulty in fitting around B^[4]-OB^[4]linkages inside the overcrowded large borate groups when BO_(1.5)/BaO=2.5,promoting the formation of NBOs on the edge of borate groups for the charge compensation of modifier cations and leading to the decline in the thermal conductivity.Thermal conductivity plays a major role in regulating the thermal diffusivity at a given temperature since the compositional dependence of volumetric heat capacity is relatively weak compared with that of thermal conductivity.

关键词： Thermal conductivity Magic-angle spinning nuclear magnetic resonance(MAS-NMR) X-ray photoelectron spectroscopy(XPS) Raman spectroscopy Thermal diffusivity

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

引用

International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 508-517页

作者： Runhao Zhang jian Yang Han Sun Wenkui yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking process.The ELM model exhibites the best performance compared with the models of MLR and SVR.OS-ELM and FOS-ELM are applied for sequential learning and model updating.The optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the population.The variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization ratio.The lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one month.The hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,respectively.The coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,respectively.The system exhibits desirable performance for applications in actual industrial pro-duction.

关键词： basic oxygen furnace steelmaking machine learning lime utilization ratio dephosphorization online sequential extreme learning machine forgetting mechanism

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Influence analysis of calculated horizontally layered soil parameters on grounding parameters

引用

High Voltage 2023年第2期8卷 421-430页

作者： Yihua Dan Junjun Yin jian Yang Huizhang yang Department of Electronic Engineering Tsinghua UniversityBeijingChina School of Computer&Communication Engineering University of Science and Technology BeijingBeijingChina

Calculated parameters(soil layer resistivity,soil layer thickness,and the number of soil layers)of horizontally layered soil are usually obtained based on the measured apparent resistivity under different measurement distances,which are significant for the design,operation,and maintenance of grounding grids.Most existing calculation methods of soil parameters are just trying to make the calculation results approach the measurement data,ignoring the relationship among measurement data,the calculated soil parameters,and grounding parameters,which would increase the workload of the measurement.To better balance the distance range of the measurement data and the influence of the calculated horizontally layered soil on grounding parameters,this paper systematically studies the relationship among measured apparent soil resistivity,calculated horizontally layered soil parameters,and grounding parameters.The basic theories of apparent resistivity measurement,soil parameter calculation,and grounding parameter calculation are given,the influence of soil layer thickness on the measured apparent resistivity is studied,and the influence of the calculated soil parameters on the grounding resistance of different grounding models is analysed.Based on different scales of grounding grids,the results give a corresponding reference distance range of measured apparent soil resistivity.Therefore,this paper can help decrease the workload of soil resistivity measurement during grounding parameters analysis,which has far-reaching engineering significance.

关键词： soil parameters apparent

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Deep visual-linguistic fusion network considering cross-modal inconsistency for rumor detection

引用

Science China(Information Sciences) 2023年第12期66卷 16-32页

作者： yang yang Ran BAO Weili GUO De-Chuan ZHAN Yilong YIN jian Yang School of Computer Science and Engineering Nanjing University of Science and Technology National Key Laboratory for Novel Software Technology Nanjing University School of Software Shandong University

With the development of the Internet, users can freely publish posts on various social media platforms, which offers great convenience for keeping abreast of the world. However, posts usually carry many rumors, which require plenty of manpower for monitoring. Owing to the success of modern machine learning techniques, especially deep learning models, we tried to detect rumors as a classification problem automatically. Early attempts have always focused on building classifiers relying on image or text information, i.e., single modality in posts. Thereafter, several multimodal detection approaches employ an early or late fusion operator for aggregating multiple source information. Nevertheless, they only take advantage of multimodal embeddings for fusion and ignore another important detection factor, i.e., the intermodal inconsistency between modalities. To solve this problem, we develop a novel deep visual-linguistic fusion network(DVLFN) considering cross-modal inconsistency, which detects rumors by comprehensively considering modal aggregation and contrast information. Specifically, the DVLFN first utilizes visual and textual deep encoders, i.e., Faster R-CNN and bidirectional encoder representations from transformers, to extract global and regional embeddings for image and text modalities. Then, it predicts posts’ authenticity from two aspects:(1) intermodal inconsistency, which employs the Wasserstein distance to efficiently measure the similarity between regional embeddings of different modalities, and(2) modal aggregation, which experimentally employs the early fusion to aggregate two modal embeddings for prediction. Consequently, the DVLFN can compose the final prediction based on the modal fusion and inconsistency measure. Experiments are conducted on three real-world multimedia rumor detection datasets collected from Reddit, Good News, and Weibo. The results validate the superior performance of the proposed DVLFN.

关键词： multimodal learning Wasserstein distance rumor detection

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Vibration suppression of composite panel with variable angle tow design and inerter-based nonlinear energy sink

引用

浙江大学学报(英文版)A辑:应用物理与工程 2023年第8期24卷 653-672页

作者： Chen ZHOU jian Yang Yingdan ZHU Chendi ZHU Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Material Technology&EngineeringChinese Academy of SciencesNingbo 315201China Department of Mechanical Materials and Manufacturing EngineeringUniversity of Nottingham Ningbo ChinaNingbo 315100China International Academy of Marine Economy and Technology(IAMET) University of Nottingham Ningbo ChinaNingbo 315100China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Ningbo Institute of Dalian University of Technology Ningbo 315016China

This study investigates the vibration transmission and suppression of a laminated composite panel with variable angle tow(VAT)designs and an attached inerter-based passive nonlinear energy sink.Based on analytical and numerical methodologies,the substructure technique is used to obtain a steady-state dynamic response and the results are verified by experimental and analytical methods.It is demonstrated that fiber orientation has a significant impact on the natural frequencies.The dynamic responses and energy transmission path characteristics are determined and evaluated by forced vibration analysis.The main vibration transmission paths inside the structure are displayed using power flow density vectors.It is demonstrated that the dynamic responses of the plate can be changed considerably by using various fiber placement schemes and passive suppression devices.In addition,it is indicated that the vibration transmission paths are significantly influenced by the tailored fiber angles for improved dynamic performance.Our investigation enhances the understanding of enhanced vibration suppression designs of variable-stiffness composite plates with attached passive devices.

关键词： Laminated composite plate Variable stiffness Substructure method Passive device Power flow analysis

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Spectrum Usage Anomaly Detection from Sub-Sampled Data Stream via Deep Neural Network

引用

Journal of Communications and Information Networks 2023年第1期8卷 13-23页

作者： Han Zhang jian Yang Junting Chen Yue Gao Institute for Communication Systems the University of SurreyGuildford GU27XHUK Mobile Communications Innovation Center China Academy of Information and Communications TechnologyBeijing 100191China Future Network Intelligence Institute(FNii)and School of Science and Engineering the Chinese University of Hong KongShenzhen 518172China School of Computer Science Fudan UniversityShanghai 200433China.Institute for Communication Systemsthe University of SurreyGuildford GU27XHUK

Anomaly detection is an essential part of any practical system in order to remedy any malfunction and accident early to create a secure and robust system.Malicious users and malfunctioning cognitive radio(CR)devices may cause severe interference to legitimate users.However,there are no effective methods to detect spontaneous and irregular anomaly behaviors in sub-sampling data stream from wideband compressive spectrum sensing as an important function of a CR device.In this article,to detect anomaly utilization of spectrum from sub-sampled data stream,a multiple layer perceptron/feed-forward neural network(FFNN)based solution is proposed.The proposed solution would learn the pattern of legitimate and anomalous usages autonomously without expert's knowledge.The proposed neural network(NN)framework has also shown benefits such as more than 80%faster detection speed and lower detection error rate.

关键词： compressive sensing(CS) machine learning(ML) multicoset sampling anomaly detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A novel case of transcatheter mitral valve-in-valve replacement using Mi-thos^TM system

引用

Journal of Geriatric Cardiology 2020年第4期17卷 229-233页

作者： Jia-You TANG yang LIU jian Yang Department of Cardiovascular Surgery Xijing HospitalAir Force Military Medical UniversityShaanxiChina

Transcatheter mitral valve replacement(TMVR)has become an alternative to surgical mitral valve replacement for the treatment of patients with severe mitral insufficiency(MI)who are at very high or prohibitive surgical risk.[1]Because of impaired left ventricular dysfunction and previous cardiac surgery,some aged patients with degenerated bioprosthetic mitral valve and mitral regurgitation were refused to redo surgery.[2]Increasing demand are required for minimally invasive treatment of these patients.Hundreds of patients worldwide have been treated with a transcatheter mitral valve-in-ring or valve-in-valve procedure using transcatheter aortic valve.[3]However,rare case of transcatheter mitral valve-in-valve/ring replacement using transcatheter mitral valve system was reported.Here,we reported a successfully case of transcatheter mitral“valve-in-valve”replacement for the treatment of bioprosthetic mitral valve degeneration and severe regurgitation with domestic Mithos^TM valve.

关键词： Bioprosthesis degeneration Transcatheter mitral valve replacement Valve-in-valve

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Kinetics and mechanism of coal-based direct reduction of highchromium vanadium-titanium magnetite

引用

Journal of Iron and Steel Research(International) 2022年第11期29卷 1723-1733页

作者： jian Yang Tao jiang Shi-hong Ma Song-tao yang Mi Zhou School of Information Science and Engineering Northeastern UniversityShenyang 110819LiaoningChina School of Metallurgy Northeastern UniversityShenyang 110819LiaoningChina School of Materials and Metallurgy University of Science and Technology LiaoningAnshan 114051LiaoningChina

High-chromium vanadium-titanium magnetite(HCVTM)is a valuable resource containing metal elements such as iron,vanadium,titanium,and chromium.To recycle these elements,direct reduction is an efficient way.The mechanism and reaction kinetic parameters for the direct reduction of HCVTM were studied.Experimental results show that the reduction degree increases obviously when the C/O ratio and temperature increase.Thermodynamic analysis showed a dramatic mass loss in the direct reduction of HCVTM in the temperature range of 985-1160℃.From 1200 to 1350℃,the reduction curves for the isothermal reduction of HCVTM followed the same trend,with a sharp increase in the initial reaction zone and a slight increase in the reduction rate with increasing time,and finally,the isothermal reduction process of HCVTM was divided into several limiting stages with varying degrees,with inconsistent limiting factors for the reaction rate at different stages.The results also show that the activation energy decreases slightly at larger degrees of reduction.Also,the apparent rate constant k(T)increased with increasing reduction temperature,with lnk(T)showing a good linear relationship with temperature.

关键词： High-chromium vanadium-titanium magnetite Direct reduction Reduction rate Kinetic Thermodynamic Analysis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：