1 000 MPa级高强钢埋弧焊熔敷金属组织及性能

针对水电用1 000 MPa级高强钢设计了一种埋弧焊用焊丝、焊剂。借助JMat Pro软件对熔敷金属的组织和力学性能进行模拟,并通过拉伸试验、冲击试验、OM,SEM,EDS等手段对其进行评价。研究了熔敷金属成分和焊接热输入对熔敷金属组织及力学性能的影响。试验结果表明,研制的焊材焊接工艺性优良,通过控制合金元素含量使熔敷金属力学性能远高于标准值;重点分析了Cr含量对熔敷金属组织和力学性能的影响,熔敷金属中少量的Cr元素会提高针状铁素体含量,Cr元素含量较高时,会增加贝氏体含量,使熔敷金属强度不断提高,冲击韧性先提高后降低;随着焊接热输入的升高,熔敷金属中针状铁素体含量不断减少,先共析铁素体含量提高,组织粗化,熔敷金属强韧性不断降低。     

人工神经网络在高强高韧性管线钢埋弧焊丝研制中的应用

在试验的基础上，用人工神经网络建立了高强高韧性管线钢埋孤焊熔敷金属力学性能的预测模型。该模型预测的结果与试验值之间有很好的对应关系。模型的研究为熔敷金属力学的成分、性能设计和控制提供了有效的手段。     

结构钢焊条熔敷金属化学成分的人工神经网络预测系统

基于Matlab神经网络工具箱，设计了一个用于结构钢焊条熔敷金属化学成分预测的神经网络模型。该模型采用前向神经网络，利用BP算法，建立了熔敷金属化学成分与力学性能之间的关系。用此神经网络，既可预测结构钢焊条熔敷金属化学成分，也为深入研究结构钢焊条化学成分提供了有利的工具。     

Al和Mg元素对吉帕级熔敷金属组织和力学性能的影响

针对吉帕级熔敷金属韧性不足的现状,设计了4组焊丝,研究了Al,Mg元素对金属粉芯焊丝熔敷金属组织和力学性能的影响. 采用扫描电子显微镜对熔敷金属的显微组织进行了表征,通过力学性能测试表征了熔敷金属的力学性能. 结果表明,熔敷金属主要由马氏体、贝氏体构成. 随着熔敷金属中Al,Mg元素的添加量由0Al-0Mg增加至0.3Al-0.9Mg,其氧含量由0.0308%降为0.0143%,聚合贝氏体含量减少,板条马氏体含量增加. 夹杂物由传统的以Fe,Al,Si,Mn等元素的氧化物转变为以Al,Mg氧化物为主的球形细小夹杂物(MgO·Al₂O₃). 0.3Al-0.9Mg组与0Al-0Mg组相比较,夹杂物的平均尺寸降低了0.13 μm,抗拉强度增加了152 MPa,冲击吸收能量增加了11 J (?20 ℃).     

BHG-5焊丝熔敷金属力学性能及其微观组织特征

BHG-5是目前国内市场普遍应用的屈服强度890 MPa级高强钢气体保护焊焊丝,在80%Ar+20%CO_2气体保护焊条件下,该焊丝熔敷金属具有良好的力学性能。对该焊丝熔敷金属的力学性能及其微观组织进行了试验分析,探讨了焊丝熔敷金属组织和力学性能的相关性及其强韧化机制。     

Ti-4.5Al-2.0V合金熔敷金属的组织和性能

Ti-4.5Al-2.0V合金熔敷金属的成分、组织和性能的初步研究结果表明该合金制成熔敷金属后,杂质元素N、H含量将明显增加;室温下,熔敷金属的抗拉强度高于基体金属,塑性则相反;350℃时,熔敷金属的抗拉强度和塑性值与基体金属相当;Al含量在较低的范围内波动时对熔敷金属的拉伸性能影响不大.     

高强高韧性管线钢埋弧用焊丝的研制

研制的高强高韧性管线钢用埋弧焊丝与SJ10 1和SJ10 2焊剂匹配后的熔敷金属不仅具有很高的强度 (σs≥ 5 4 0MPa) ,而且还具有优良的低温韧性 (AKv - 1 0℃ ≥ 12 0J)。该焊丝的研制满足了屈服强度超过 5 0 0MPa以上管线钢对焊缝熔敷金属性能的要求。研究结果表明 ,要保证熔敷金属具有较佳的强韧性匹配 ,熔敷金属中的合金元素总量必须满足Ceq≥ 0 .38,Pcm≥ 0 .17,才能保证熔敷金属的强度 ,以及具有以针状铁素体为主焊缝组织 ;在文中的合金系统下 ,随着熔敷金属中C、Mn元素含量的增加 ,熔敷金属的针状铁素体组织的含量增加 ,韧性得到提高。随着焊剂碱度值的增加 ,熔敷金属中的氧含量降低 ,C、Mn元素增加 ,使得熔敷金属中的合金元素更趋向于最佳的配比 ,从而提高了韧性。     

基于人工神经网络的焊缝熔敷金属力学性能预测

基于神经网络预测技术提出了一种新思路。本文利用前向神经网络，使用BP算法对熔融金属的抗拉强度、屈服强度等力学性能指标进行研究。通过对实验数据样本进行训练，建立熔敷金属的抗拉强度、屈服强度与焊缝熔敷金属成分之间的隐性函数，用此神经网络，即可预测熔敷金属的抗拉强度和屈服强度。     

合金元素对耐候熔敷金属力学及耐蚀性能的影响

采用周浸加速腐蚀试验,模拟工业大气腐蚀环境,通过组织分析、锈层微观成分及形貌分析、电化学分析等手段,研究了Ni,Cr,Cu元素对耐候熔敷金属耐蚀性能及力学性能的影响规律. 结果表明,Ni元素有利于增加组织中针状铁素体含量,提高熔敷金属−40 ℃冲击韧性,Cr元素增加,熔敷金属−40 ℃冲击韧性降低. 合金元素有利于提高腐蚀锈层中的α-FeOOH的含量,增加锈层致密度,提高锈层阻抗,降低自腐蚀电流密度. Cu元素有利于提高熔敷金属腐蚀初期和后期的耐蚀性能;腐蚀初期,Cr元素提高耐蚀性能的作用不如Cu和Ni,但是腐蚀后期Cr提高锈层耐蚀性能的作用明显.     

气体含量对马氏体不锈钢熔敷金属冲击性能的影响

针对大型水轮机转轮用钢ZG0Cr13Ni5Mo马氏体不锈钢焊缝熔敷金属冲击性能与母材相比较低的问题,采用两种气体元素含量（O、N）不同的00Cr13Ni5Mo焊丝,同时在MAG焊及TIG焊中应用不同类型、不同配比的混合保护气体来改变熔敷金属中的气体元素（O、N）含量,研究气体元素（O、N）含量对熔敷金属冲击性能的影响,找出提高熔敷金属冲击性能的方法,使熔敷金属的冲击性能与母材达到更好的匹配。研究表明,气体含量对马氏体不锈钢熔敷金属冲击性能有明显的影响,熔敷金属中的气体元素含量越少,冲击性能越好,其中氧含量是决定熔敷金属冲击性能的主要因素。     

应用人工神经网络建立TC11钛合金化学元素与力学性能关系模型

在TC11钛合金大量实验数据的基础上,应用人工神经网络建立TC11钛合金的化学元素与力学性能关系模型。模型的输入参数包括Al、Mo、Zr、Si、Fe、C、O、N和H共9种化学元素;输出为常规力学性能指标(抗拉强度、屈服强度、延伸率和断面收缩率)。运用未知数据样本对已建立神经网络模型的预测能力进行检验,并以Al、Mo、Zr和C元素为研究对象,利用该模型分析TC11钛合金化学元素对力学性能的影响规律。结果表明:网络的预测值与实验值的相对误差均在10%以内,说明所建立的神经网络预测模型具有较精确的预测能力,而且能够清楚地反映出该合金化学元素与力学性能之间的非线性关系。     

D227、D237焊条堆焊金属组织及显微硬度研究

分别采用D227和D237两种堆焊焊条,在45号钢基体上进行了焊条电弧焊堆焊试验.分析了在相同焊接条件下获得的堆焊层金属的显微组织和显微硬度,讨论了合金元素对堆焊层金属显微组织及显微硬度的影响.研究表明,堆焊金属与基体金属具有良好的冶金结合,第一层堆焊金属受基体金属的稀释程度影响明显,界面处金属过渡层的宽度因焊条种类的不同而异;各层堆焊金属中合金元素Cr、Mo、V含量随堆焊层数的增加而提高,堆焊金属的显微组织及显微硬度与堆焊焊条合金元素的含量有关,与其硬质相的类型、性能及分布等有关.     

纳米金属沉积层对NdFeB磁粉及其磁体性能的影响

采用电化学方法在NdFeB磁粉表面沉积6种组合的单层或双层纳米厚度的金属层．测试了包覆磁粉的电极电位和磁性能，包覆磁粉制备的粘结磁体的电阻率。磁粉电极电位表现为NdFeB和沉积金属的混合电位。磁粉的磁性能变化与沉积金属的性质有关。磁体电阻率三月现为NdFeB和沉积金属的混合电阻率，沉积Zn/Ni双金属层的样品电阻率异常地增加．其矫顽力和最大磁能积均有不同程度的降低。     

Prediction of Tensile Property of Hydrogenated Ti600 Titanium Alloy Using Artificial Neural Network

An artificial neural network (ANN) model has been developed to analyze and predict the correlation between tensile property and hydrogenation temperature and hydrogen content of hydrogenated Ti600 titanium alloy. The input parameters of the neural network model are hydrogenation temperature and hydrogen content. The output is ultimate tensile strength. The accuracy of ANN model was tested by the testing data samples. The prediction capability of ANN model was compared with the multiple linear regression approach and response surface method. The combined influence of inputs on the tensile property is also simulated using ANN model. It is found that excellent performance of the ANN model was achieved, and the results showed good agreement with experimental data. Moreover, the developed ANN model can be used as a tool to control the tensile property of titanium alloys.     

Forecasting of mechanical properties of covered electrode containing La/CeO_2 based on fuzzy neutral network

In order to improve the mechanical properties of deposited metal of ilmenite type welding electrode,CeO_2/La rare earth elements were added into electrodes based on E4301 electrode, then electrodes were produced,test plates were welded, and mechanical properties were tested based on National Standards of China. For the sake of solving the problems of large amount of mechanical properties tests, long test cycle and high test cost during the conventional production process of electrode, a prediction model of the mechanical properties of deposited metal based on Takagi-Sugeno(T-S) fuzzy neural network was established. Mn, Si and C contents of medium manganese in electrode, CeO_2, and La contents of electrode and welding speed were selected as input variables of the prediction model, and the tensile strength, lower yield strength, elongation, impact energy and hardness of deposited metal were selected as output variables. Finally,predicting experiment was done under test samples, and results show that average relative prediction error of the tensile strength, lower yield strength, elongation and hardness are 0.91 %, 2.57 %, 4.94 % and 1.94 %, respectively, which reach the need of actual production. The results of prediction show that the mechanical properties of deposited metal of electrode containing rare earth can be forecasted accurately through material composition of electrode and welding parameters based on T-S fuzzy neural network model.     

Development of Corrosion Assessment Diagrams for High Temperature Chlorine Corrosion Part II: Development of “Dynamic” Quasi-stability Diagrams

The corrosion of metals at high temperatures in halogen containing environments differs from most other types of high temperature corrosion in that in addition to solid and liquid corrosion products volatile phases are also formed. The latter are not covered by the usual thermodynamic stability diagrams, which are often used for prediction of the corrosion products formed, and indirectly on whether corrosion has to be regarded as critical or not. The present paper aims at including the situation where gas phase corrosion products determine the extent of corrosion and a new type of diagram is developed and discussed for the example of chlorine containing environments. Part I of this paper (Latreche et al. Oxid Met 2009) was dedicated to the establishment of the basis for a new extended approach to a corrosion risk assessment diagram called the “dynamic” quasi-stability diagram. The present part deals with the principles of the new type of diagram and the establishment of specific diagrams for the most common alloying elements, i.e. Fe, Ni, Mo, Cr, Si, Al. For the development of the specific diagrams, the calculation of gas viscosities and gas diffusion coefficients of all relevant volatile potential corrosion products was conducted, with methods specified in the paper. The new “dynamic” quasi-stability diagrams were then compared to experimental results from kinetics investigations of pure metals, which showed quite good agreement with the experimental observations. Furthermore, the diagrams were used to assess the behaviour of the metallic elements in alloys. Again, in this case good agreement between prediction and experimental results was observed if the specific role of the different elements in the corrosion behaviour of the alloys was taken into account.     

合金溶液中溶质间活度相互作用系数预测模型EI北大核心CSCD

利用基于组分间性质差建立的统一外推模型(UEM),结合Miedema模型、Tanaka过剩熵关系式,给出了计算任意基体中溶质间活度相互作用系数的模型。该模型不仅在数学上可以覆盖由传统外推模型耦合Miedema模型导出的活度相互作用系数模型,还可以利用组分间的性质差大小定性解释由传统外推模型给出的活度相互作用系数模型的预测特点及其适用体系,且与实验结果吻合良好。     

Influence of the density of oxide on oxidation kinetics

A new kinetic model is proposed to describe the isothermal oxidation of metals and alloys in the form of sphere, flat plate and fiber shape with considering oxidation induced volume change or Pilling–Bedworth Ratio. The effects of temperature, oxygen partial pressure, particle size, sample shape on the oxidation reaction fraction are analyzed in the model through a physical meaning explicit function. The oxidation experimental data of zinc powders and plates were used to check the model. The results show that the calculated curves agree well with the experimental data and the model can give a good theoretical prediction. All of these will be useful for studying the oxidation of intermetallics either.