本文選題：TC4鈦合金 + BP神經(jīng)網(wǎng)絡(luò)�。� 參考：《重慶大學(xué)》2016年碩士論文

【摘要】：本文主要研究TC4鈦合金微觀組織演變與工藝參數(shù)的關(guān)系,識(shí)別動(dòng)態(tài)再結(jié)晶細(xì)晶區(qū),并優(yōu)化得到此區(qū)域的較優(yōu)加載參數(shù),為TC4鈦合金的微觀組織控制提供理論依據(jù)。首先利用Gleeble-3500熱模擬機(jī)在溫度為1023K、1073K、1123K、1173K、1223K、1273K、1323K,應(yīng)變速率為0.01s-1、0.1s-1、1s-1、10s-1下進(jìn)行了TC4鈦合金的熱壓縮,壓縮量為60%。由此獲得了該合金在變形條件下的應(yīng)力-應(yīng)變曲線,分析了其在高溫下的變形特點(diǎn)。基于實(shí)驗(yàn)得到的應(yīng)力-應(yīng)變數(shù)據(jù),建立了TC4鈦合金雙向反饋調(diào)節(jié)人工神經(jīng)網(wǎng)絡(luò)模型(BP-ANN),基于此模型擴(kuò)充了TC4鈦合金的研究數(shù)據(jù)。以擴(kuò)充的數(shù)據(jù)為基礎(chǔ),計(jì)算并繪制了該合金的二維和三維功率耗散圖和失穩(wěn)圖,疊加兩圖得到對(duì)應(yīng)的加工圖。結(jié)合金相圖片分析,繪制了TC4鈦合金的考慮應(yīng)變的空間變形機(jī)制圖,得到了再結(jié)晶細(xì)晶參數(shù)區(qū)間。結(jié)合數(shù)值模擬,優(yōu)化出了再結(jié)晶細(xì)晶區(qū)域的較優(yōu)應(yīng)變速率加載參數(shù)。本文主要的研究內(nèi)容及結(jié)論:(1)在溫度為1023-1323K,應(yīng)變速率為0.01-10s-1條件下對(duì)TC4鈦合金實(shí)施了等溫壓縮,獲得相應(yīng)的實(shí)驗(yàn)應(yīng)力應(yīng)變數(shù)據(jù),基于實(shí)驗(yàn)的應(yīng)力應(yīng)變數(shù)據(jù)建立了TC4鈦合金B(yǎng)P-ANN模型。此模型很好的學(xué)習(xí)了流變應(yīng)力隨工藝參數(shù)的變化規(guī)律,精確的預(yù)測了TC4鈦合金不同條件下的流變應(yīng)力�；诮⒌腂P-ANN模型,預(yù)測實(shí)驗(yàn)之外的應(yīng)力應(yīng)變數(shù)據(jù),擴(kuò)充了研究數(shù)據(jù),為TC4鈦合金加工圖和動(dòng)態(tài)再結(jié)晶模型的計(jì)算及有限元的模擬提供了數(shù)據(jù)支持。(2)基于擴(kuò)展的應(yīng)力應(yīng)變數(shù)據(jù)和動(dòng)態(tài)材料模型理論,繪制了TC4鈦合金在不同應(yīng)變、不同溫度及不同應(yīng)變速率下的二維和三維加工圖及變形機(jī)制圖,并對(duì)其進(jìn)行詳細(xì)分析,得到TC4鈦合金穩(wěn)定變形的工藝參數(shù)范圍是:溫度范圍為1198-1248K,應(yīng)變速率范圍為0.01-0.032s-1;溫度范圍為1223-1323K,應(yīng)變速率范圍為0.032-1s-1。從三維變形機(jī)制圖中識(shí)別了細(xì)晶區(qū)域,細(xì)晶區(qū)域主要分成三種區(qū)域即?相的動(dòng)態(tài)再結(jié)晶主導(dǎo)區(qū),?相的動(dòng)態(tài)再結(jié)晶和???相變共同作用區(qū),超塑性區(qū)。(3)基于擴(kuò)展的應(yīng)力應(yīng)變數(shù)據(jù),建立了TC4鈦合金的動(dòng)態(tài)再結(jié)晶臨界應(yīng)變模型和運(yùn)動(dòng)學(xué)模型。(4)基于deform-2D有限元模擬軟件,結(jié)合變形機(jī)制圖中識(shí)別出的再結(jié)晶細(xì)晶參數(shù)區(qū)域,對(duì)熱成形工藝進(jìn)行了一系列應(yīng)變速率加載方案的設(shè)計(jì),通過比較不同條件下的晶粒尺寸,得到研究區(qū)域的較優(yōu)應(yīng)變速率加載參數(shù)。
[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.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TG146.23

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本文編號(hào)：2050862