挤压速度和电磁铸造锭坯对AZ31镁合金板材组织和性能影响

文章研究挤压条件下挤压速度和电磁铸造锭坯对挤压态AZ31镁合金板材组织和性能的影响。研究结果发现,挤压速度比较低时,板材晶粒尺寸小,板材的表面质量比较好;随着挤压速度的降低,抗拉强度、屈服强度和延伸率都有一定的提高。由于镁合金是HCP的晶体结构,同时对挤压速度非常敏感,对变形均匀性影响比较大,因此造成挤压板材的内外晶粒大小不均。在电磁场的作用下,溶质在晶内的固溶度增大,同时晶粒大小也比常规铸造的细小,因此电磁铸造的锭坯经挤压机挤压后,挤压板材的晶粒尺寸比较细小,且强度和塑性都有所提高。     

低频电磁场对半连续铸造Al-Mg-Si-Cu合金显微组织的影响

采用低频电磁场半连续铸造工艺制备Al-Mg-Si-Cu铝合金铸锭,研究了低频电磁场对Al-Mg-Si-Cu铝合金铸锭组织的影响。结果表明,施加低频电磁场可以细化Al-Mg-Si-Cu铝合金铸锭的晶粒组织,减轻晶内元素的偏析程度。与常规半连续铸造相比,施加频率为20 Hz、电流为120 A的交变电磁场后,铸锭中的等轴晶组织增多,枝晶状组织减少,晶粒尺寸变得更加细小,铸锭边部和中心平均晶粒尺寸由常规半连续铸造的170和259μm分别降至133和187μm,同时有利于提高溶质元素在晶内的分布,很大程度上减轻了溶质元素的偏析。此外,低频电磁场的电磁振荡使得液穴内部温度场和流动场更趋均匀,溶质元素分配系数增大,结晶区间变小,抑制了树枝晶的生长,促进了Al-Mg-Si-Cu合金半连续铸锭中非枝晶组织的形成和溶质元素的强制固溶,并且抑制了溶质元素的偏析。     

Effect of grain refinement and dissolved hydrogen on the fluidity of A356 alloy

Abstract

The influence of grain refinement and dissolved hydrogen on the fluidity of A356 alloy has been investigated. A spiral casting test method, recently developed, has been used to measure fluidity in a reproducible way. The grain refinement reduces the grain size of the spirals, particularly at the tip, but no significant influence on the fluidity has been revealed. The hydrogen additions in the melt have not affected the fluidity but have, of course, significantly increased the porosity.     

基于遗传算法的Al-5%Cu合金电脉冲孕育处理参数优化

以实验为基础,利用神经网络和遗传算法优化Al-5%Cu合金的电脉冲孕育处理工艺参数。神经网络的输入参数为脉冲电压、脉冲时间和电脉冲孕育处理时熔体温度,输出参数是合金凝固组织的晶粒度。在神经网络训练的基础上,采用遗传算法优化神经网络的输入参数。结果表明,神经网络和遗传算法的组合建模获得了较好的优化结果。     

Industrial effects associated with the columnar to equiaxed transition in remelt ingots

Abstract

There have been many studies of the mechanisms involved in causing the solidification mode of an alloy to change from a columnar dendritic to an equiaxed structure, the columnar to equiaxed transition (CET). The parameters which cause the change are alloy segregation characteristics, freezing rate, undercooling and the presence or absence of nucleating sites for the equiaxial crystals. These parameters have been collected into theories which describe the CET and which generally satisfy the results found in laboratory or model systems. Although the effect has considerable scientific interest, the impact of a CET on the structure of an industrial ingot or casting is less widely recognised. In this report, we comment on the CET in relation to the structure of superalloy castings and ingots and on the formation of segregation defects in titanium alloy ingots. We conclude that one of the more important results of accurately modelling the solidification of these systems is that we may predict the casting conditions leading to the CET and also assess its impact on cast structure.     

电磁铸造2E12铝合金的铸态组织与力学性能

分别采用电磁铸造和普通连铸技术制备了2E12铝合金连铸锭.通过显微组织和力学性能的对比分析,研究施加电磁场对2E12铝合金连铸过程及铸锭性能的影响.结果表明,使用电磁铸造技术制备的2E12铝合金铸锭具有良好的表面质量和内部组织,以及优良的力学性能.其中,电磁铸造方法获得的2E12铝合金铸锭相对于普通连续铸造铸锭晶粒平均尺寸由58 μm减小至36 μm,抗拉强度提高了9.08%,伸长率提高了61.58%,断裂方式为准解理断裂.     

A356合金α(Al)的晶粒细化

采用 ＡｌＴｉＣ 晶粒细化中间合金对 Ａ３５６ 进行了晶粒细化试验,证明Ａ３５６ 合金的 α（Ａｌ）晶粒尺寸和枝晶干同时获得了明显的细化。这表明ＡｌＴｉＣ 合金可能是细化ＡｌＳｉ合金 α（Ａｌ）晶体组织和克服Ｓｉ中毒作用的良好晶粒细化剂。     

回顾与展望全球铝产品产量及对晶粒细化剂的需求

在全世界生产的铝加工材与铸造铝产品中约有75%在铸造中需添加晶粒细化剂Al-Ti-B中间合金等以细化铸锭的枝晶与产品的晶粒组织,提高它们的性能。对2001～2010年全世界原铝、再生铝、铝加工材、铸造铝产量作了简明的回顾,对2011～2020年它们的产量作了预测,在此期间对晶粒细化剂的需求也作了预测,特别是对中国铝工业的晶粒细化剂需求作了较为精细的预测,2011年中国对晶粒细化剂的需求量61 kt,2015年的115 kt,2020年的可超过200 kt。中国当前生产的晶粒细化剂在产量与品质方面足以满足本国的需求。     

基于GRNN神经网络优选高温合金铸件晶粒细化剂

对镍基高温合金铸件研制出四组元化学细化剂A-B-C-D,针对细化剂的优选问题,采用GRNN神经网络模拟细化剂各组元含量与铸件晶粒尺寸间的非线性关系。研究发现:加入A-B-C-D新型复合细化剂可以明显细化铸件晶粒;细化剂的最佳加入量为0.11wt%A、0.23wt%B、0.14wt%C、0.17wt%D,即组元A-B-C-D的最佳质量配比约为1∶2.1∶1.3∶1.5。     

低频电磁场对7050铝合金铸锭组织的影响

通过在常规半连续铸造过程中施加低频电磁场的方法制备了直径为162mm的7050铝合金铸锭,研究了电磁场对铸锭铸态组织的影响。结果表明,低频电磁场对7050铝合金铸态晶粒尺寸和组织形貌具有显著的影响。施加磁场后铸锭组织变得非常均匀、细小,平均晶粒尺寸由230μm细化至42μm左右,晶粒形貌由粗大枝晶转变等轴晶。电磁场频率和强度对晶粒细化具有重要的影响。对于低频电磁铸造162mm的7050铝合金铸锭,最佳电磁场参数:电磁场频率为25Hz,磁场强度为12800～16000At。     

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.     

The stochastic modeling of solidification structures in alloy 718 remelt ingots

A stochastic numerical approach was developed to model the formation of grain structure and secondary phases during the solidification of nickel-based alloy 718 remelt ingots. The significance of the present stochastic approach is that the simulated phases can be directly compared with actual phases from experiments at two different scales: grain characteristics can be visualized at the macroscale, while the amount, size, and distribution of secondary phases can be viewed at the microscale. The computer becomes a “dynamic metallographic microscope.” Stochastic modeling was applied to simulate the formation of solidification phases (γprimary phase and NbC and eutectic γ-Laves secondary phases) during the solidification of vacuum-arc-remelted and electroslag-remelted alloy 718 ingots. Modeling results, such as pool profile, grain-growth pattern, grain structure (both columnar and equiaxed grains), columnar-to-equiaxed transition, grain size, and secondary dendrite arm spacing, as well as amount, size, and location of both eutectic γ-Laves and NbC phases compared well with experimental data for cast alloy 718. This research demonstrates that the stochastic approaches are relatively fast, comprehensive, and more accurate than the deterministic approaches in predicting the solidification characteristics of remelt ingots and are mature enough to be used effectively by the metal industry for process development and optimization. Laurentiu Nastac earned his Ph.D. in metallurgical and materials engineering at the University of Alabama at Tuscaloosa in 1995. He is currently a senior staff engineer at Concurrent Technologies Corporation. Dr. Nastac is a member of TMS. Suresh Sundarraj earned his Ph.D. in mineral engineering at the University of Minnesota in 1994. He is currently a process modeling engineer for Concurrent Technologies Corporation. Dr. Sundarraj is also a member of TMS. Kuang-O Yu earned his Ph.D. in metallurgical engineering at the University of Kentucky in 1978. He is currently director of research and development at RMI Titanium Company. Dr. Yu is also a member of TMS. Yuan Pang earned his M.S. in mechanical engineering at the University of Akron in 1977. He is currently a principal engineer at Concurrent Technologies Corporation.     

Structures and macrosegregation of a 2024 aluminum alloy fabricated by direct chill casting with double cooling field

Central region coarse grains and centerline segregation are common defects in aluminum ingots fabricated by direct chill(DC)casting.A double cooling field was introduced into the DC casting process to reduce these defects,whereby the external cooling was supplied by the mold and water jets,and intercooling was achieved by inserting a rod of the same alloy into the molten pool along the central axis of the ingot.Rather than forming a good metallurgical interface during solid-liquid compound casting,in the present work,the purpose of inserting the rod is to enforce internal cooling and consequently decrease the sump depth.Moreover,the insertion provides more nucleation sites with the unmoltenα-Al particles.The structure and the macrosegregation of 2024 Al alloy ingots prepared by DC casting with and without the inserts were investigated.Results show that when the inserting position is 50 mm above the upper edge of the graphite ring,significant grain refinement in the central region of the ingot and a reduced centerline segregation are achieved.     

Macro- and microstructure analysis of SSM A356 produced by electromagnetic stirring

The objective of this work is to present the relationship between macro- and microstructure of the rheocast alloy A356 obtained by electromagnetic stirring. There is a direct relationship between grain size (macrostructure) and globule size/shape factor (microstructure): the smaller the grain size, the smaller are the globule size and shape factor. The A356 alloy was processed in a simple device, which constitutes a semi-continuous casting system, coupled with a power source. The A356 (Al–7.0 wt.%Si) alloy was electromagnetically stirred under different cooling rates (controlled by the casting speed of 1 and 3 cm/s) and different power levels (600–1200 W). Ingots with 45 mm of diameter and 3 kg with very refined and homogeneous rheocast structures were obtained. The direct relationship between macro- and microstructures of the ingots were exploited. A quality index is proposed to better characterise the rheocast structure.     

Design of an Ideal Grain-Refiner Alloy for Al-7Si Alloy Using Artificial Neural Networks

An ideal grain refiner has been designed for Al-7Si alloy by performing sensitivity analysis of trained artificial neural network (ANN) model. An ANNs model has been developed for solving these complex grain refinement phenomena in Al-7Si alloy. The model predictions and the analysis are well in agreement with the experimental results and existing metallurgical facts. Uncertainty in predictions helped in finding a new phenomenon at lower addition levels of grain refiner.     

Squeeze casting of aluminium alloys for higher formability in cold forging

Abstract

This research project investigated the process conditions of using squeeze casting process to produce aluminium alloy preforms or billets for subsequent cold forging process. The comparative effects of heat treatments, their microstructures and mechanical properties were evaluated. Through these studies and experiments, the main emphasis is on the study of commercial material Al 6061, Al 2014 and Al 356 alloys. The formability of the alloys was carried out using forward and backward extrusion test at 50% area reduction at room temperature (cold extrusion). It was found that when wrought aluminium 6061, 2014 and 356 alloys were squeeze cast to form the preforms, the preform microstructures revealed very fine microstructures that are feasible to be cold extruded. In addition, after thermal annealing treatment of 6061 squeeze cast preforms, the samples showed a similar value of work hardening exponent value of 0˙20 as compared to the wrought aluminium alloy 6061, with a workhardening exponent value of 0˙21 obtained from the static compression test. Wrought aluminium alloys generally cost twice the amount as compared with casting ingots. The microstructures of the squeeze cast 6061 alloy showed no visible cracks or inclusions after the deformation by extrusion. The results of the studies showed that Al 6061 preforms via squeeze cast technique may be cold extruded or formed, which provide an alternative means for the production of billets for the cold extrusion or forging process.     

基于人工神经网络的7055铝合金二次时效性能预测

利用人工神经网络对7055铝合金二次时效热处理工艺参数与时效性能样本集进行训练和学习,采用改进的BP网络算法Levenberg-Marquardt算法,建立7055铝合金二次时效热处理工艺BP神经网络模型。针对二次时效工艺特点,研究的工艺参数包括:预时效温度、预时效时间、二次时效温度和二次时效时间。结果表明:神经网络预测值与实验值吻合较好,说明神经网络模型具有较高的精度及良好的泛化能力,可有效地用于预测和分析二次时效工艺参数对7055铝合金时效性能的影响。     

低频电磁铸造对7050铝合金羽毛晶组织缺陷的影响

常规DC铸造7050铝合金铸锭常常含有羽毛晶组织缺陷.采用低频电磁铸造技术,半连续铸造制备了直径为200 mm的7050铝合金锭坯,考察了电磁场对羽毛晶组织缺陷的影响.结果表明,在低频电磁场作用下,半连续铸造组织得到显著细化,为均匀细小的球形和多边形等轴晶组织,有效抑制了羽毛晶组织缺陷的产生.     

Microstructures of an AlSi7Mg alloy by near-liquidus casting

Semi-solid ingots of an AlSi7Mg alloy were obtained using the method of near liquidus casting. Their micro- structures exhibit the characteristics of fine, equiaxed, and non-dendrite, which are required for semi-solid forming. The in- fluences of casting temperature, heat preservation time, and cooling rate on the microstructure were also investigated. The results show that in the temperature region near liquidus the grain size becomes small with a decrease in casting temperature. Prolonging the heat preservation time makes grain crassitude at the same temperature. And increasing the cooling rate makes grain fine. The microstructure of the alloy cast with iron mould is finer than that with graphite mould.     

Reheating microstructure of refined AZ91D magnesium alloy in semi-solid state

By means of equal channel angular extrusion (ECAE) test, upsetting test and metalloseope, reheating mierostruetures of raw casting ingots, materials prepared by SIMA and materials extruded by ECAE in semi-solid state were investigated. The results show that compared with those of raw casting ingots and materials prepared by SIMA, reheating microstrueture of materials extruded by ECAE is the best and the final grain size is the finest. With increasing holding time, a growing phenomenon occurs in reheating microstrueture of materials extruded by ECAE, which can be described by Ostwald ripening law. The average grain size increases firstly, subsequently decreases and the shape factor of grains approaches to 1 as the reheating temperature increases. With increasing equivalent strain, the average grain size decreases. This demonstrates that reheating material extruded by ECAE technology is a good method to prepare AZ91D magnesium alloy semi-solid billets.