TC4钛合金超塑成形流变行为

针对TC4钛合金超塑成形过程中的流变行为、表征及其应用进行了研究。首先,通过恒应变率高温拉伸试验获得TC4钛合金在高温下的流变行为,发现动态回复主要作用于低应变率的变形,动态再结晶主要作用于高应变率下的应力软化机制。此外,建立一套修正的本构模型用以表征材料的高温流变行为,预测值与试验值之间的平均相对误差为13.09%,证实该本构模型适应于表征钛合金超塑成形的应力-应变关系。最后,基于本构模型,结合ABAQUS有限元软件的CREEP蠕变子程序,考虑应变补偿的影响,开发了一种针对TC4钛合金高温超塑行为数值模拟的方法。以高温拉伸试验为研究对象,分别针对数值模拟应变率、应力和应变结果进行分析,验证了该方法的有效性。     

Modeling the High Temperature Deformation Constitutive Relationship of TC4-DT Alloy Based on Fuzzy-neural Network

通过分析研究变形温度、应变速率及变形程度参数对TC4-DT钛合金高温变形行为的影响,建立了一种基于自适应模糊神经网络的TC4-DT钛合金高温变形本构关系预测模型。高温变形热模拟压缩试验的变形温度为750 ~1150 ℃,应变率为0.001~10 s–1,试样高度压缩率为50%。本研究中建立的网络模型集成了模糊推理系统误差反向传播(BP)神经网络的学习算法。结果表明,该模型的预测值与实验结果比较吻合,最大相对误差小于6%。本研究证明模糊神经网络是一种优化TC4-DT钛合金本构关系模型和优化变形工艺参数的有效、实用方法。     

基于Arrhenius模型和修正Johnson-Cook模型的TC21钛合金流动应力预测

使用Gleeble-3500热模拟试验机对TC21钛合金在温度为890～990℃、应变速率为0.01～10 s^-1下进行了热模拟压缩实验，研究了该合金的高温流变行为。在变形条件下，该合金的流变应力随应变的增大逐渐增加，在达到峰值后又逐渐减小。基于实验数据，分别采用Arrhenius模型和修正Johnson-Cook模型构建了TC21钛合金本构模型，并对这两个模型的预测精度进行了分析对比。结果表明，修正Johnson-Cook本构模型预测值的平均绝对相对误差e_AARE为7.2078%,相关系数r为0.96866;Arrhenius本构模型预测值的e_AARE为12.6699%,r为0.95794,修正Johnson-Cook本构模型的精度高于Arrhenius本构模型，且在整个参数范围内具有一定的精度，可以较好地描述TC21钛合金的高温流变行为。     

考虑应变率效应的轻量化座钣有限元分析（英文）

室温条件下,采用Instron实验机和分离式Hopkinson压杆(SHPB)实验装置对TC4钛合金进行压缩实验,得到了不同应变率下的真应力-真应变曲线。通过对应力-应变曲线拟合分析,建立了TC4钛合金的Johnson-Cook(JC)本构模型。基于该本构模型,采用ABAQUS/Explicit对TC4钛合金高应变率下的冲击压缩实验进行了数值模拟,通过实验结果与仿真数据的对比分析,验证了该本构模型参数的合理性。为实现迫击炮轻量化的目标,设计了一种新型轻量化TC4钛合金质迫击炮座钣。通过建立冲击载荷下迫击炮座钣的有限元模型,考虑材料的应变率效应,对座钣的强度和刚度进行了分析,得到了座钣的应力和位移的变化规律。     

基于位错理论的TC4钛合金的动态本构模型与数值模拟

为描述Ti-6Al-4V(TC4)两相钛合金在高应变率、高温载荷条件下的复杂力学行为,基于细观塑性变形机理和位错动力学理论,从细观尺度构建一种两相钛合金粘塑性本构模型,并阐释各本构参数与微结构特征量之间的关联及其表征的物理意义。为确定本构参数并提高参数的识别效率与精度,提出一种基于拉丁超立方抽样、Spearman秩相关分析的参数敏感度整体分析方法,并在参数敏感度分析结果和基本遗传算法的基础上,建立基于改进小生境算法、可疑峰值点判断策略和局域精确搜索技术的改进遗传算法,得到了TC4两相钛合金的本构参数。采用应力补偿更新算法,通过显式用户子程序接口VUMAT将两相钛合金本构模型嵌入ABAQUS有限元软件中,实现了钛合金在高应变率、高温条件下动态本构行为的数值模拟。对比模拟结果与实验数据发现,所构建的本构模型描述材料高应变率条件下力学行为的准确性优于Johnson-Cook模型的。     

TC11 钛合金流变行为及其应变分段本构模型(英文)

针对TC11钛合金,提出了基于应变分段的Arrhenius双曲正弦模型,并进行热模拟压缩试验,分析了TC11钛合金高温流变行为及流变参数对流变应力的影响。采用分段函数的Arrhenius双曲正弦方法,在不同应变区域下求出不同的材料参数,得到了更为精确的本构模型。对比试验结果表明,模型具有很高的精度,并对比了模拟结果,表明模型是可靠的。     

Flow Behavior and Constitutive Model Using Piecewise Function of Strain for TC11 Alloy

针对TC11钛合金,提出了基于应变分段的Arrhenius双曲正弦模型,并进行热模拟压缩试验,分析了TC11钛合金高温流变行为及流变参数对流变应力的影响。采用分段函数的Arrhenius双曲正弦方法,在不同应变区域下求出不同的材料参数,得到了更为精确的本构模型。对比试验结果表明,模型具有很高的精度,并对比了模拟结果,表明模型是可靠的。     

高应变率下TC4-DT钛合金的动态力学性能及塑性本构关系

为研究TC4-DT钛合金的动态力学性能及其本构关系,在1000~8000 s-1应变率范围内,利用分离式Hopkinson压杆试验装置对该材料进行动态压缩试验,得到高应变率下的真实应力-应变曲线。结果表明:高应变率时TC4-DT钛合金材料存在应变率增强、增塑以及应变强化效应,其流变应力表现出较强的应变率敏感性。通过微观组织观察,发现高应变率变形时出现绝热剪切带是材料流变应力急剧减小的主要原因。改进Johnson-Cook本构模型中的温度项,利用试验数据对TC4-DT钛合金在高应变率下的动态塑性本构关系进行拟合,得到室温下该材料的动态塑性本构方程,模型计算结果和试验结果证明该模型可以更好地预测TC4-DT钛合金高应变率下的塑性流变应力。     

激光冲击强化TC4钛合金强化层弹塑性本构参数反演分析

目的 获取TC4钛合金激光冲击强化层的弹塑性本构模型参数，结合纳米压痕试验和有限元模拟技术，进行激光冲击强化TC4钛合金的材料参数反演计算。方法 首先，在TC4钛合金试样侧面沿强化层深度方向进行纳米压痕测试，获得距表面不同距离处的载荷-压入深度曲线。进而，基于幂律应变硬化模型，通过无量纲方程和有限元模拟反演得到激光冲击强化TC4钛合金梯度强化层的弹塑性参数。最后，将反演获得的弹塑性本构模型材料参数用于有限元模拟，将模拟结果与试验结果进行对比，验证参数反演结果的合理性。结果 强化层表面的弹性模量和纳米硬度较母材分别提高了11%和30%，强化层内的应变硬化指数和屈服强度沿深度方向分别递增和递减。模拟的载荷-压入深度曲线与试验曲线吻合较好，最大压入载荷、弹性模量和纳米硬度的模拟误差分别小于1%、7%和3%，证实了参数反演结果的合理性。结论 通过无量纲方程反演算法得到的强化层本构参数有较强的可信度。激光冲击强化可有效提升TC4钛合金的表面力学性能，强化层的本构参数呈梯度分布，表面的抗塑性变形能力大幅提升。     

TC11钛合金压气机盘闭模锻造过程中的缺陷预测

TC11钛合金压气机盘在实际生产中存在各种缺陷,降低了压气机盘的使用性能。将基于试验数据建立的TC11钛合金高温塑性变形时的延性损伤演化模型以及本构模型与有限元相结合,对某TC11钛合金压气机盘等温闭模锻造过程中的温度、等效应变和损伤变量的分布进行了数值分析,同时预测了塑性失稳区的位置。为优化其成形工艺提供了一种有效的方法。     

Ti-6Al-4V热变形行为及利用多项耦合进行本构关系修正

采用热模拟试验机对钛合金Ti-6Al-4V进行高温压缩试验,研究其在850~1100 ℃温度下,0.001~0.1 s?1应变速率的流动应力行为。结果表明:钛合金Ti-6Al-4V具有应变速率、温度敏感性;随着温度的升高和应变速率的减小,流动应力逐渐降低,加工硬化速率与动态软化速率达到动态平衡。通过分析工艺参数对材料参数的影响,发现合金的材料参数(N、A、Q)随变形条件的变化而变化。在传统双曲正弦函数型Arrhenius方程的基础上提出一种考虑应变速率、温度和应变耦合修正的双曲正弦本构方程,并用相关系数R和平均相对误差(AARE)来评价所建立的本构模型的准确性,定量分析结果表明,修正的本构方程能够较准确地预测钛合金Ti-6Al-4V的流动应力。     

应用智能方法建立Ti-6Al-2Zr-1Mo-1V合金的本构关系(英文)

利用Thermecmastor-Z热模拟机进行Ti-6Al-2Zr-1Mo-1V钛合金在不同工艺参数(变形温度800,850,900,1000,1050°C,应变速率0.01,0.1,1,10s-1)条件下的热模拟压缩试验,研究变形温度和应变速率对Ti-6Al-2Zr-1Mo-1V钛合金流变应力的影响。以试验数据为基础,应用BP神经网络算法原理,建立该合金的高温流动应力与变形温度、应变和应变速率对应关系的高温本构关系预测模型。结果表明,运用神经网络方法建立的Ti-6Al-2Zr-1Mo-1V钛合金本构关系模型具有较高的预测精度,与试验结果吻合良好。此外,运用Visual Basic可视化编程语言设计并开发了具有神经网络功能的用户界面。     

Modeling and Simulation for the Stress Relaxation Beha- vior of Ti-6Al-4V at Medium Temperature

应力松弛是钛合金在升高温度和加载条件下的一个显著特性,也是热校形和热处理的理论基础。因此研究了一种Ti-6Al-4V钛板在923~1023 K温度范围内、几种应变水平下的拉伸应力松弛行为。结果表明,应力松弛速率随着温度的升高而增加,材料中的残余应力经过一段时间之后趋向应力松弛极限;另外,在相同温度下,不同应力水平的应力松弛极限相同。进而,建立了一种描述应力松弛行为的显式三次延迟函数,本构精度高达97%,可用于工艺设计及理论分析。最后,基于应力松弛和蠕变的关系,提出了一种隐式蠕变型本构方程描述应力松弛行为,并将识别的材料参数输入ABAQUS,数值模拟了Ti-6Al-4V的热应力松弛行为,发现模拟的应力变化规律符合应力松弛曲线,证明了蠕变型本构方程对应力松弛模拟的适用性。     

石油管用Ti-6Al-4V-0.1Ru钛合金高温流变行为及预测模型研究

通过使用Gleeble-3500热模拟试验机进行等温单轴压缩试验,研究了Ti-6Al-4V-0.1Ru钛合金在温度800到1100℃,应变速率0.01到10 s-1条件下的高温流变行为。结果表明,Ti-6Al-4V-0.1Ru钛合金的峰值应力随着变形温度的降低以及变形速率的增大而增大,软化机制在950℃以下为动态回复,在950℃以上为动态再结晶。通过使用线性回归的方法建立了Ti-6Al-4V-0.1Ru钛合金的Arrhenius本构模型,计算得到该合金的热激活能为720.477 kJ/mol,应变速率敏感指数为4.809。通过引入应变对材料常数α、n、A和Q的影响,建立了考虑应变的流变应力预测模型,通过对试验值和预测值的比对,相关系数达到96.9%,说明该模型具有较好的预测精度。     

Microstructure prediction of two-phase titanium alloy during hot forging using artificial neural networks and FE simulation

The microstructural evolution of titanium alloy under isothermal and non-isothermal hot forging conditions was predicted using artificial neural networks (ANN) and finite element (FE) simulation. In the present work, the change in phase volume fraction, grain size, and the volume fraction of dynamic globularization were modelled considering hot working conditions. Initially, an ANN model was developed for steady-state phase volume fraction. The input parameters were the alloy chemical composition (Al, V, Fe, O, and N) and the holding temperature, and the output parameter was the alpha/beta phase volume fraction at steady state. The non-steady state phase volume fraction under non-isothermal conditions was subsequently modelled on the basis of 4 input parameters such as initial specimen temperature, die (or environment) temperature, steady-state phase volume fraction at die (or environment) temperature, and elapsed time during forging. Resulting ANN models were coupled with the FE simulation (DEFORM-3D) in order to predict the variation of phase volume fraction during isothermal and non-isothermal forging. In addition, a grain size variation and a globularization model were developed for hot forging. To validate the predicted results from the models, Ti-6Al-4V alloy was hot-worked at various conditions and then the resulting microstructures were compared with simulated data. Comparisons between model predictions and experimental data indicated that the ANN model holds promise for microstructure evolution in two phase Ti-6Al-4V alloy.     

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

In this research, the hot processing parameters-impact toughness correlation of Ti-6Al-4V titanium alloy is studied. Fifty-four groups of hot processing treatments with different forging temperatures (930, 950, 970 °C), deformation degrees (20, 50, 80%), annealing temperatures (600, 700, 800 °C), and annealing time (1 and 5 h) were conducted. The orthogonal design was used to find the primary hot processing parameters influencing the impact toughness of Ti-6Al-4V alloy. The results show that the annealing temperature can exert the biggest influence on impact toughness. Low annealing temperature is essential to achieve high impact toughness value. In addition, the BP neural network was used to describe the quantitative correlation between hot processing parameters and impact toughness. The results show that the BP neural network exhibits good performance in predicting the impact toughness of Ti-6Al-4V alloy. The prediction error is within 5%. The BP neural network and the orthogonal design method are mutually confirmed in the present work. Finally, based on the microstructure analysis, the reasons responsible for above experimental results are explained.     

一种基于等温多塑性变形机制耦合的数值模拟方法

以TC4合金等温锻造为例,提出一种基于多塑性变形机制耦合的数值模拟方法。通过对等温锻造过程中塑性变形机制的研究和对应变速率敏感指数以及TC4合金动态再结晶的分析,建立材料常规塑性变形、超塑性变形和蠕变变形的判据。并依据多塑性变形机制判据来确定坯料内部各单元的实时塑性变形机制,同时采用相应的本构方程,使模拟结果更符合实际情况,从而能真实反映航空难变形材料的等温锻造工艺过程：普通塑性变形、超塑性变形和等温保压充填模具过程等。模拟结果表明,变形材料并非处于单一塑性变形机制,而是多种变形机制相互协调,并且随着变形的进行,材料各单元的变形机制也随之改变。等温锻造过程中,上述机制的改变与材料的动态再结晶密切相关     

An adaptive constitutive model of the Ti-6.29Al-2.71Mo-1.42Cr alloy in high-temperature deformation

In this paper, an adaptive constitutive model has been acquired with the help of a fuzzy set and an artificial neural network, so as to represent the deformation behavior of the Ti-6.29Al-2.71Mo-1.42Cr alloy in high-temperature deformation. In establishing this model for the constitutive relationship of this alloy, the process parameters of deformation temperature, strain rate, and strain were taken as three inputs, and the flow stress was taken as an output. Data from “teaching samples” and testing samples were obtained from the experimental results in the isothermal compression of the Ti-6.29Al-2.71Mo-1.42Cr alloy. By comparison of the calculated results with the experimental data from the testing samples, it was verified that the present adaptive constitutive model to predict the flow stress of the Ti-6.29Al-2.71Mo-1.42Cr alloy has good learning precision and generalization.     

Thermomechanicai coupling simulation and experimental study in the isothermal ECAP processing of Ti-6Al-4V alloy

The thermomechanical coupling simulation of the isothermal equal channel angular pressing(ECAP)of Ti-6Al-4V alloy was conducted.The effect of processing parameters,ECAP pass number and the residual billet on the effective strain,stress and temperature distribution was investigated.Based on the coupling simulation results,it is found that the shear factor,ram speed,deformation temperature,channel intersection angle and residual billet significantly affect the ECAP deformation behaviors.Meanwhile,the experimental study of the isothermal ECAP process of Ti-6Al-4V alloy using route C,in which the repeated rotation angle around the longitudinal billet axis before reinsertion in channel intersection angle of 120°.Furthermore,a large amount of recrystallization occurs and some prior α phase grains grow in the post-ECAP process of Ti-6Al-4V alloy.The yield strength of post-ECAP Ti-6Al-4V alloy increases compared with that of as-received Ti-6Al-4V alloy.     

Modeling of grain size in isothermal compression of Ti-6Al-4V alloy using fuzzy neural network

Isothermal compression of Ti-6Al-4V alloy was conducted in the deformation temperature range of 1093-1303 K,the strain rates of 0.001,0.01,0.1,1.0,and 10.0 s-1,and the height reductions of 20%-60% with an interval of 10%.After compression,the effect of the processing parameters including deformation temperature,strain rate,and height reduction on the flow stress and the microstructure was investigated.The grain size of primary α phase was measured using an OLYMPUS PMG3 microscope with the quantitative metallography SISC IAS V8.0 image analysis software.A model of grain size in isothermal compression of Ti-6Al-4V alloy was developed using fuzzy neural net-work(FNN) with back-propagation(BP) learning algorithm.The maximum difference and the average difference between the predicted and the experimental grain sizes of primary α phase are 13.31% and 7.62% for the sampled data,and 16.48% and 6.97% for the non-sampled data,respectively.It can be concluded that the present model with high prediction precision can be used to predict the grain size in isothermal compression of Ti-6Al-4V alloy.