Characterization of grain growth behaviors by BP-ANN and Sellars models for nickle-base superalloy and their comparisons

In order to deeply understand the grain growth behaviors of Ni80A superalloy,a series of grain growth experiments were conducted at holding temperatures ranging from 1223 to 1423 K and holding time ranging from 0 to 3600 s.A back-propagation artificial neural network(BP-ANN)model and a Sellars model were solved based on the experimental data.The prediction and generalization capabilities of these two models were evaluated and compared on the basis of four statistical indicators.The results show that the solved BP-ANN model has better performance as it has higher correlation coefficient(r),lower average absolute relative error(AARE),lower absolute values of mean value(μ)and standard deviation(ω).Eventually,a response surface of average grain size to holding temperature and holding time is constructed based on the data expanded by the solved BP-ANN model,and the grain growth behaviors are described.

Derivation of Hillert-type 3D grain growth rate model with topological considerations and discussion on its grain size parameter

A Hillert-type three-dimensional grain growth rate model was derived throughthe grain topology-size correlation model, combined with a topology-dependent grain growth rateequation in three dimensions. It shows clearly that the Hillert-type 3D grain growth rate model mayalso be described with topology considerations of microstructure. The size parameter bearing in themodel is further discussed both according to the derived model and in another approach with the aidof quantitative relationship between the grain size and the integral mean curvature over grainsurface. Both approaches successfully demonstrate that, if the concerned grains can be wellapproximated by a space-filling convex polyhedra in shape, the grain size parameter bearing in theHillert-type 3D grain growth model should be a parameter proportional to the mean grain tangentradius.

MODELING OF FERRITE GRAIN GROWTH OF LOW CARBON STEELS DURING HOT ROLLING

For most commercial steels the prediction of the final properties depends on accurately calculating the room temperature ferrite grain size. A grain growth model is proposed for low carbon steels Q235B during hot rolling. By using this model, the initial ferrite grain size after continuous cooling and ferrite grain growing in coiling procedure can be predicted. In-plant trials were performed in the hot strip mill of Ansteel. The calculated final ferrite grain sizes are in good agreement with the experimental ones. It is helpful both for simulation of microstructure evolution and prediction of mechanical properties.

Austenite grain growth of medium-carbon alloy steel with aluminum additions during heating process

In this study, the effects of heating temperature(850–1100°C) and holding time(30–150 min) on the grain growth behavior of austenite in medium-carbon alloy steel were investigated by conducting experiments. The abnormal grain growth and mixed grain structure phenomenon are explained using an equilibrium precipitation phase diagram calculated by Thermo-Calc software package. The Al N particles were observed by field-emission scanning electron microscopy(FESEM), and the amount of AlN precipitations was detected by electron probe microanalysis(EPMA). Based on the research results, it was found that the average grain size of austenite in the test steel increased continuously with the increase of temperature and holding time. Furthermore, the abnormal growth of austenite occurred in the test steel at 950°C, and the heating temperature affected the austenite grain size more significantly. In addition, the decline in the amount of AlN second-phase particle in the test steel, which weakened the "pinning" effect on austenite grain boundaries, resulted in abnormal growth and the development of mixed austenite grain structures. The prediction model for describing the austenite grain growth of medium-carbon alloy steel during heating was established by regression analysis of the experimental data, and the model was verified to be highly accurate.

Austenite grain growth behavior of Q1030 high strength welded steel

The austenite grain growth behavior of Q1030 steel was studied under different heating conditions. The austenite grain size increases with the heating temperature and holding time increasing. Austenite grains grow in an exponential manner with rising heating tem- perature and in a parabolic manner with prolonging holding time. A mathematical model for describing the austenite grain growth behavior of Q 1030 steel was obtained on the basis of experimental results using regression analysis. When the heating temperatures lie between 1000 and 1100℃ at a certain holding time, abnormal grain growth appears, which causes mixed grains in Q1030 steel.

3D Stochastic Modeling of Grain Structure for Aluminum Alloy Casting

A 3D stochastic modeling was carried out to simulate the dendritic grains during solidification of aluminum alloys, including time-dependent calculations for temperature field, solute redistribution in liquid, curvature of the dendritic tip, and growth anisotropy. The nucleation process was treated by continuous nucleation. A 3D simplified grain shape model was established to represent the equiaxed dendritic grain. Based on the Cellular Automaton method, a grain growth model was proposed to capture the neighbor cells of the nucleated cell. During growing, each grain continues to capture the nearest neighbor cells to form the final shape. When a neighbor cell was captured by other grains, the grain growth along this direction would be stopped. Three-dimensional calculations were performed to simulate the evolution of dendritic grain. In order to verify the modeling results, the predictions were compared with the observation on samples cast in the sand mold and the metal mold.

铝合金细化剂细化行为研究现状与展望

晶粒细化处理能够显著改善铝合金的综合性能,对拓展其应用领域意义重大。本文基于异质形核,探讨了点阵错配模型、边边匹配模型以及自由生长模型,肯定了边边匹配模型在筛选潜在晶粒细化剂方面的高效性;根据自由生长模型关于异质相尺寸、形态、分布等对晶粒细化效果影响的理论研究,归纳了物理、化学方法调控第二相进而优化细化效果的研究进展,并且对第二相尺寸影响细化效果的原因进行了理论阐述,最后对优化晶粒细化剂的方向做了展望。

镍基高温合金SLM过程中熔池内的微观结构演变数值模拟

采用有限元耦合相场的方法研究IN718高温合金在激光选区熔化过程中熔池内的竞争性生长和晶粒/枝晶结构的演变。通过有限元解决热演化问题,然后将结果输入相场模型,相场模拟涉及晶粒成核、晶粒外延生长和晶粒竞争的微观结构演变。基于对熔池横向和纵向截面微观结构演变的分析,讨论SLM过程中枝晶竞争性生长的机制,并量化计算熔池中溶质元素Nb的浓度分布。结果表明,枝晶竞争性生长受温度梯度和晶体学取向的影响,具有高错配角(>22.5°)的不利取向晶粒将很快被有利取向晶粒淘汰。

MICROSTRUCTURAL MODEL OF GATORIZED WASPALOY IN THE ISOTHERMAL FORGING PROCESS

A microstructural model, which was used to predict the evolution of microstructure of Gatorized Waspaloy in the isothermal forging process, was developed in terms of dynamic recrystallization and grain growth. The following three steps of experiment were conducted during developing the model. (1) Specimens were compressed in the MTS testing machine. (2) Dynamic recrystallization and grain growth were discussed. (3) Dynamic recrystallization model and grain growth model were set up. The simulated results are in good agreement with the experimental data.

Potts-Ising model for simulation of polarization switching in polycrystalline ferroelectrics

This paper proposes a scheme based on the Potts and Ising models for simulating polarization switching of polycrystalline ferroelectrics using the Monte Carlo method. The polycrystalline texture with different average grain size is produced from the Potts model. Then Ising model is implemented in the polycrystalline texture to produce the domain pattern and hysteresis loop. The domain patterns and hysteresis loops have been obtained for polycrystalline texture with different average grain size. From the results of domain pattern evolution process under an applied electric field using this scheme, an extended domain, which covers more than one grain with polarization aligned roughly in the same direction, has been observed during the polarization reversal. This scheme can well reproduce the basic properties of polycrystalline ferroelectrics and is a valuable tool for exploring the physical properties of polycrystalline ferroelectrics.

0Cr16Ni5Mo1马氏体不锈钢奥氏体晶粒生长行为

研究了0Cr16Ni5Mo1马氏体不锈钢的奥氏体化相变及加热与等温过程中晶粒的生长行为。结果表明:加热速率对实验钢奥氏体化相变的开始(As)与结束(Af)温度影响显著,随着加热速率增加,相变温度呈明显上升趋势;实验钢的奥氏体化过程存在严重的组织遗传,导致得到粗大的晶粒;在进一步升温过程中,新的奥氏体晶粒会在原奥氏体晶界自发再结晶形核并长大;新晶粒在等温过程中的生长行为可用动力学模型D^(6.6)=1.883×10^(20)t^(1.617)e^((-353691.03/RT))进行描述。

Modeling the Completely Recrystallized Grain Growth of NiCrMoV Rotor Steel

The present study focuses on the completely recrystallized grain growth of NiCrMoV steel.All the samples were austenitised at 1250℃ for 5min,and then were compressed with strain rate of 0.01s^(-1) and finial strain of 0.8.Once the compression completed,the specimens were held for different time before water quenching.Based on the experimental results,the completely recrystallized grain growth model was established and the effects of temperature and holding time on austenite grain size were investigated.Comparison between the experimental and predicted results was carried out.A good agreement between the experimental and predicted results verifies the developed model.

Incoloy 825合金加热过程中晶粒长大行为研究

研究了Incoloy 825合金在1223~1473 K温度范围内保温0~150 min后的晶粒长大行为,分析了加热温度和保温时间对其晶粒尺寸的影响,构建了Incoloy 825合金晶粒长大的数学模型。结果表明,当温度低于1373 K时,晶粒长大缓慢,晶粒尺寸变化不大;当温度高于1373 K时,合金晶粒尺寸明显长大。通过回归分析,构建了Incoloy 825合金两段式晶粒长大数学模型,能够较好地预测该合金在不同加热温度、不同保温时间下的晶粒尺寸。

新型镍基粉末高温合金晶粒长大行为研究

对第四代粉末高温合金FGH4108晶粒长大行为进行研究。结果表明, γ'相在完全溶解温度以下固溶处理时,晶粒长大幅度较小,与初始组织差别不大(锻态,3~4μm);当达到 γ'相完全溶解温度时,晶粒发生明显长大;超过 γ'相完全溶解温度时,晶粒尺寸大幅增加(30~40μm),过固溶的几个温度下晶粒尺寸差别不大;保温初期晶粒尺寸显著增加,一定保温时间后晶粒尺寸不再随时间明显变化。温度和时间对晶粒尺寸的影响都与 γ'相对晶界迁移的阻碍作用有关,根据温度和时间的影响,对传统晶粒长大模型中界面迁移的表观激活能(Q)、时间指数(n)和广义迁移率常数(A_(0))进行修正,构建了新的模型,模型预测值与实验值的决定系数(R^(2))为0.9997,均方误差为0.12μm,预测精度较高,晶粒长大曲线各项特征能被准确预测出来。

F45MnVS非调质钢晶粒长大行为研究

为提高F45MnVS非调质钢的强韧性,本文以青岛特钢轧制生产的F45MnVS非调质钢棒材为实验材料,对F45MnVS非调质钢的奥氏体晶粒长大规律进行研究。通过热处理实验和显微组织观察,分析了加热温度和保温时间对F45MnVS非调质钢奥氏体晶粒尺寸变化的影响。同时,采用Arrhenius模型,建立实验钢晶粒长大模型。研究结果表明,随着加热温度的升高与保温时间的增加,实验钢晶粒尺寸随之增大。当温度在950~1200℃范围时,随着温度的升高,F45MnVS非调质钢奥氏体平均晶粒尺寸逐渐增大,由25.4μm增大至47.47μm,且增大速率比较稳定,当温度加热至1250℃时,F45MnVS非调质钢奥氏体晶粒显著粗化,平均晶粒尺寸达到了57.8μm;随着保温时间的增加,晶粒长大速率逐渐降低,且随着加热温度的升高,晶粒长大指数明显增大。通过拟合建立的实验钢奥氏体晶粒长大数学模型,获得实验钢平均晶粒长大指数n=0.04183,激活能Q=38004.13 J/moL,获得实验钢晶粒长大模型计算值与实验值平均相对误差为2.64%,验证了该数学模型具有较高的精度。该研究对材料显微组织和工艺参数的制定具有一定的指导价值。

基于Level Set方法的40CrMnMoA合金钢的奥氏体晶粒长大模型

为准确描述40CrMnMoA合金钢的奥氏体晶粒长大行为,借助Gleeble-1500D型热模拟机对40CrMnMoA合金钢进行了保温试验,温度为900~1150℃,时间为10~2000 s。基于试验结果,通过非线性回归建立了40CrMnMoA合金钢Burke-Turnbull奥氏体晶粒长大模型,构建了基于Level Set方法的40CrMnMoA合金钢奥氏体晶粒长大的介观尺度有限元模型并进行计算。结果表明:保温温度与保温时间对40CrMnMoA合金钢的晶粒长大行为均具有较大的影响。40CrMnMoA合金钢的奥氏体平均晶粒直径随保温时间的延长呈抛物线增长。所建立的Burke-Turnbull晶粒长大动力学模型具有较高的精度,试验值与计算值相关系数(R)为0.9932。40CrMnMoA合金钢奥氏体再结晶晶粒长大激活能(Q_(m))为142845.37 J/mol。通过对比仿真计算与试验所得的晶粒组织,验证了本文所建有限元模型可有效地预测40CrMnMoA合金钢的奥氏体晶粒长大演变过程。

GCr15钢奥氏体晶粒长大规律研究

利用Gleeble-3800型热模拟试验机研究不同加热温度和保温时间下GCr15钢的奥氏体晶粒长大规律。结果表明,奥氏体晶粒随加热温度的升高呈指数关系长大,随保温时间的延长近似呈抛物线关系长大,同时晶粒平均直径与保温时间的关系符合Beck方程,温度越高,晶粒生长指数越大。在已有模型的基础上,通过对试验数据进行非线性回归得到了描述GCr15钢奥氏体晶粒长大规律的数学模型。

低碳钢轧后冷却过程中的晶粒长大模型

钢材轧后冷却过程中的晶粒长大很大程度上决定着室温组织的晶粒尺寸，定量研究这一晶粒长大规律不仅可建立描述冷却过程中晶粒尺寸变化的模型，以利于计算机对微观组织变化过程的模拟，而且还为进一步的性能预报奠定基础。

Inconel 718合金方坯粗轧加热过程晶粒长大模型

以Inconel 718合金锻坯为研究对象,在1173—1423 K的温度范围内,研究了加热温度和时间对Inconel 718合金锻坯晶粒尺寸变化的影响,推导并验证了具有普适意义的适合Inconel 718合金锻坯粗轧加热过程的晶粒长大模型.研究结果表明:随加热时间的延长,在1173 K加热时,晶粒尺寸变化不显著;1173—1323 K加热时,晶粒尺寸呈线性长大;高于1323 K加热时,晶粒尺寸呈抛物线性长大.所建立的Inconel 718合金的晶粒长大模型适用于等温条件和非等温条件下晶粒尺寸演变的计算.