TC4钛合金热变形参数混沌域微观机制确定性识别及细晶化加载新模式

发布时间：2018-06-22 01:10

本文选题：TC4钛合金 + BP神经网络　；参考：《重庆大学》2016年硕士论文

【摘要】：本文主要研究TC4钛合金微观组织演变与工艺参数的关系,识别动态再结晶细晶区,并优化得到此区域的较优加载参数,为TC4钛合金的微观组织控制提供理论依据。首先利用Gleeble-3500热模拟机在温度为1023K、1073K、1123K、1173K、1223K、1273K、1323K,应变速率为0.01s-1、0.1s-1、1s-1、10s-1下进行了TC4钛合金的热压缩,压缩量为60%。由此获得了该合金在变形条件下的应力-应变曲线,分析了其在高温下的变形特点。基于实验得到的应力-应变数据,建立了TC4钛合金双向反馈调节人工神经网络模型(BP-ANN),基于此模型扩充了TC4钛合金的研究数据。以扩充的数据为基础,计算并绘制了该合金的二维和三维功率耗散图和失稳图,叠加两图得到对应的加工图。结合金相图片分析,绘制了TC4钛合金的考虑应变的空间变形机制图,得到了再结晶细晶参数区间。结合数值模拟,优化出了再结晶细晶区域的较优应变速率加载参数。本文主要的研究内容及结论:(1)在温度为1023-1323K,应变速率为0.01-10s-1条件下对TC4钛合金实施了等温压缩,获得相应的实验应力应变数据,基于实验的应力应变数据建立了TC4钛合金BP-ANN模型。此模型很好的学习了流变应力随工艺参数的变化规律,精确的预测了TC4钛合金不同条件下的流变应力。基于建立的BP-ANN模型,预测实验之外的应力应变数据,扩充了研究数据,为TC4钛合金加工图和动态再结晶模型的计算及有限元的模拟提供了数据支持。(2)基于扩展的应力应变数据和动态材料模型理论,绘制了TC4钛合金在不同应变、不同温度及不同应变速率下的二维和三维加工图及变形机制图,并对其进行详细分析,得到TC4钛合金稳定变形的工艺参数范围是:温度范围为1198-1248K,应变速率范围为0.01-0.032s-1;温度范围为1223-1323K,应变速率范围为0.032-1s-1。从三维变形机制图中识别了细晶区域,细晶区域主要分成三种区域即?相的动态再结晶主导区,?相的动态再结晶和???相变共同作用区,超塑性区。(3)基于扩展的应力应变数据,建立了TC4钛合金的动态再结晶临界应变模型和运动学模型。(4)基于deform-2D有限元模拟软件,结合变形机制图中识别出的再结晶细晶参数区域,对热成形工艺进行了一系列应变速率加载方案的设计,通过比较不同条件下的晶粒尺寸,得到研究区域的较优应变速率加载参数。
[Abstract]:In this paper, the relationship between microstructure evolution and technological parameters of TC4 titanium alloy is studied, the dynamic recrystallization fine crystal region is identified, and the optimum loading parameters of this region are optimized, which provides a theoretical basis for the microstructure control of TC4 titanium alloy. First, the thermal compression of TC4 titanium alloy was carried out by Gleeble-3500 thermal simulator at 1023K / 1073KN 1123K / 1223K / 1223K / 1223K and strain rate 0.01s-10.1s / 1s ~ (-1) / s ~ (-1) ~ (10) s ~ (-1). The compression amount of TC4 titanium alloy was 60th / s ~ (-1). The stress-strain curves of the alloy were obtained and its deformation characteristics at high temperature were analyzed. Based on the stress-strain data obtained from the experiment, a bidirectional feedback regulated artificial neural network model (BP-ANN) for TC4 titanium alloy was established, and the research data of TC4 titanium alloy were expanded based on the model. Based on the extended data, the 2D and 3D power dissipation and instability diagrams of the alloy are calculated and drawn, and the corresponding machining diagrams are obtained by superposing the two diagrams. Based on metallographic analysis, the spatial deformation mechanism of TC4 titanium alloy considering strain was plotted, and the recrystallization fine grain parameter interval was obtained. Combined with numerical simulation, the optimal strain rate loading parameters of recrystallized fine-grained region were optimized. The main contents and conclusions of this paper are as follows: (1) TC4 titanium alloy was subjected to isothermal compression at 1023-1323K and strain rate of 0.01-10s-1, and the corresponding experimental stress-strain data were obtained. Based on the experimental stress-strain data, the BP-ANN model of TC4 titanium alloy was established. The rheological stress of TC4 titanium alloy under different conditions is predicted accurately by studying the rheological stress of TC4 titanium alloy under different conditions. Based on the established BP-ANN model, the stress-strain data outside the experiment are predicted, and the research data are expanded. It provides data support for the calculation of TC4 titanium alloy machining diagram, dynamic recrystallization model and finite element simulation. (2) based on extended stress-strain data and dynamic material model theory, TC4 titanium alloy under different strains is drawn. 2D and 3D machining drawings and deformation mechanism diagrams at different temperatures and different strain rates are analyzed in detail. The process parameters of stable deformation of TC4 titanium alloy are obtained as follows: temperature range 1198-1248K, strain rate range 0.01-0.032s-1, temperature range 1223-1323K, strain rate range 0.032-1s-1. The fine grain region is identified from the three-dimensional deformation mechanism diagram. The fine grain region is divided into three kinds of regions, I. e. Dynamic recrystallization of phase? Phase dynamic recrystallization and? (3) based on the extended stress-strain data, the dynamic recrystallization critical strain model and kinematics model of TC4 titanium alloy are established. (4) based on deform-2D finite element simulation software, the dynamic recrystallization critical strain model and kinematics model of TC4 titanium alloy are established. A series of strain rate loading schemes were designed for the hot forming process in combination with the recrystallized fine grain parameter region identified in the deformation mechanism diagram. The grain size of the hot forming process was compared under different conditions. The optimal strain rate loading parameters are obtained.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TG146.23

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