1500热连轧精轧带钢温度场的数值模拟

采用有限差分方法建立数学模型,对莱钢1500热连轧精轧带钢温度场进行数值模拟,根据模型在VC编程平台编制计算程序,计算带钢在精轧7个道次任意时刻的温度场分布,并得到每道次出口处带钢的温降曲线.计算过程考虑了大部分热流量与内热源,并权衡计算精度与计算时间的矛盾,优化了网格细分与时间步长的取值.最后计算结果与实测值比较的误差为2～30℃,真实可靠.     

热轧高强钢氧化铁皮演变规律的研究

对HY490钢在精轧工艺下氧化铁皮的厚度演变进行了数值模拟。通过热轧试验验证了数值模拟结果,并对热轧试验氧化铁皮的结构进行了检测。采用冷弯试验测定了2种工艺条件下带钢表面氧化铁皮的粘附性。结果表明:数值模拟结果与现场实测值相符。此模拟方法解决了精轧过程中无法直接测量3次氧化铁皮厚度的问题,为通过调整生产工艺参数来控制氧化铁皮厚度提供了参考。热轧试验表明适当地降低开轧温度、终轧温度、卷取温度和缩短轧制道次间隔时间是控制氧化铁皮厚度和结构的有效手段。冷弯试验表明工艺1条件下氧化铁皮与钢板的粘附性较差,弯曲面铁皮呈细片状脱落。工艺2条件下铁皮与钢板结合牢固,弯曲面铁皮呈细粉末状,粘附性好。     

几何模型更新方法在板带热连轧精轧道次中的应用

为了更好的对精轧过程进行数值模拟,提供更为合理的轧制参数,以LS-DYNA软件中的单元更新方法模拟了精轧过程。建立好第1道次轧制模型并数值模拟,对第1道次计算结果进行了分析。以第一道次轧制后的单元形状为基础,进行单元更新,改变边界条件和载荷,对第2道次进行数值模拟,用同样方法对3～7道次进行数值模拟。该方法在准确地模拟了精轧过程中板带变化的同时,为各精轧道次提供准确的轧制参数。     

高速线材10道次精轧过程的有限元模拟

通过对钢厂高速线材热连轧过程的传热分析,借助ABAQUS软件建立了线材与轧辊的3维热机耦合模型,对42A钢(0.39%～0.46%C)从Φ16 mm精轧至Φ5.5 mm轧材的10道次精轧过程的温度场,应力-应变场和轧制力进行了模拟。得出精轧后轧件心部温度升高130℃,表面温度降低10℃,轧件降温主要是轧件的热辐射和水冷造成的。10道次轧制力的计算值与实测值的相对误差为1.88%～4.50%。     

道次间冷却对厚板控制轧制变形行为的影响

 厚规格钢板轧制中低压缩比难以消除连铸坯心部缺陷,容易引起厚规格钢板性能波动。采用数值模拟和试验研究相结合的方法,详细分析了道次间强冷却工艺对厚规格板坯温度变化和轧制变形的影响规律。结果表明,采用道次间强制水冷的方式进行“温控-形变”耦合控制,可以有效提高厚规格钢板心部变形量,改善内部质量。对比分析可知,高温粗轧阶段采用道次间冷却对钢板心部变形影响较大;精轧阶段进行道次间冷却,对钢板心部变形影响相对较小,同时将显著提升道次轧制力。     

热连轧粗轧区FES宽展模型及其优化

为了满足某厂1580热连轧机宽度控制精度需求,提高宽展模型的广泛适用性,利用ANSYS/LS-DYNA有限元软件,对热轧粗轧区立轧--平轧过程进行了模拟.根据模拟数据,系统地分析了轧件宽度、厚度、轧辊直径、立辊侧压量和厚度压下量对"狗骨"宽展、自然宽展和绝对宽展的影响规律.利用模拟数据并结合现场数据构造了FES(finite element simulation)"狗骨"宽展模型和自然宽展模型,并建立了PSO-BP神经网络(粒子群BP神经网络).最后,FES宽展模型与PSO--BP神经网络相结合预报第1、3和5道次的宽展,其预报值与实测值误差在1mm以内的均达到了99%以上,达到了宽度控制的精度要求.     

2205不锈钢-碳钢复合带肋钢筋的热轧

 为了研究覆层为2205不锈钢的复合钢筋的热加工范围,利用Gleeble-3800进行热模拟试验,得出2205不锈钢的高温流变曲线及热加工图,并最终确立复合钢筋的开轧温度不低于1 150 ℃。利用有限元软件对复合钢筋的粗轧和精轧道次进行数值模拟,结果表明,粗轧变形时,应变集中在轧件表层和1/4位置,随着变形不断向芯部渗透,塑性应变较大的位置不锈钢覆层较薄;在精轧k1道次变形时,发现在横肋根部的不锈钢覆层厚度最薄,在横肋顶部的覆层厚度最大。对复合钢筋的界面进行研究后发现,Cr、Ni、Mo的扩散距离为18~20 μm,从碳钢侧到不锈钢侧的微观组织依次为铁素体和珠光体、脱碳组织、复合界面、奥氏体不锈钢组织、铁素体和奥氏体不锈钢双相组织。     

WNQ570桥梁钢的静态再结晶行为

 为了研究轧制工艺对WNQ570桥梁钢再结晶行为的影响,采用Gleeble-3500热模拟试验机模拟了其双道次热变形过程,测试了试验钢的应力-应变曲线,建立了静态再结晶晶粒体积分数随变形温度和道次间隔时间变化的关系模型,分析了应变诱导析出抑制对静态软化行为的影响。研究结果表明：静态再结晶体积分数随变形温度的提高或道次间隔时间的延长而增大,应变诱导析出抑制静态再结晶的进行;静态再结晶激活能为240.47kJ/mol。研究结果为制订试验钢二阶段控轧工艺提供了依据。     

16MnNb中厚钢板控轧工艺的试验研究

通过热模拟和轧制试验,测定了16MnNb钢再结晶软化率与道次变形量及间隔时间的关系;确定出16MnNb中厚钢板控轧时的精轧温度区间和道次变形量分配原则;所提控轧工艺对含铌Q345钢同类品种板的生产有参考价值.     

TSCR生产X65管线钢过程的再结晶研究和MFS预测

在有限元差分法模拟温度场基础上,预测了管线钢TSCR过程的组织演变及断面分布规律,建立了考虑晶粒尺寸和再结晶影响的平均流变应力模型,提出了细晶轧制的工艺窗口.随着温度降低,精轧后几道次几乎没有再结晶发生;加大精轧区前两个道次压下量或者降低精轧入口温度可实现奥氏体晶粒细化;模型预测值与工业实测数据吻合良好.     

Multiscale Modeling and Simulation of Directional Solidification Process of Turbine Blade Casting with MCA Method

Nickel-based superalloy turbine blade castings are widely used as a key part in aero engines. However, due to the complex manufacturing processes, the complicated internal structure, and the interaction between different parts of the turbine blade, casting defects, such as stray grains, often happen during the directional solidification of turbine blade castings, which causes low production yield and high production cost. To improve the quality of the directionally solidified turbine blade castings, modeling and simulation technique has been employed to study the microstructure evolution as well as to optimize the casting process. In this article, a modified cellular automaton (MCA) method was used to simulate the directional solidification of turbine blade casting. The MCA method was coupled with macro heat transfer and micro grain growth kinetics to simulate the microstructure evolution during the directional solidification. In addition, a ray tracing method was proposed to calculate the heat transfer, especially the heat radiation of multiple blade castings in a Bridgman furnace. A competitive mechanism was incorporated into the grain growth model to describe the grain selection behavior phenomena of multiple columnar grains in the grain selector. With the proposed models, the microstructure evolution and related defects could be simulated, while the processing parameters optimized and the blade casting quality guaranteed as well. Several experiments were carried out to validate the proposed models, and good agreement between the simulated and experimental results was achieved.     

Validation of Multi‐scale Model Describing Microstructure Evolution in Steels

Properties of deformed steels depend on various microstructure parameters such as distribution of grain size and precipitates. Strain, strain rate and temperature inhomogeneities make quantitative prediction of microstructure difficult but the Finite Element method is able to model these inhomogeneities. Different scales of phenomena occurring in deformed materials are another difficulty in modelling. Microstructure evolution can be described by more realistic methods (e.g. Cellular Automata CA, Monte Carlo), which, on the other hand, are unable to simulate larger samples. Therefore, development of the methods capable of spanning multiple scales became a current challenge. CAFE modelling, which couples FE and CA methods, is the objective of the paper. The model consists of two layers. The micro‐scale layer, simulated by CA, represents microstructure evolution including nucleation and growth of the grains. Evolution of a dislocation density is described for every grain separately by solving differential equation. The FE thermal‐mechanical model is used as a macro‐scale part. Multistage plane strain compression tests for niobium steel are considered. Distributions of initial and final grain size are measured during the tests. The results from the CAFE model are compared to the measurements and to the predictions by a conventional model. The comparisons confirm the capability of the CAFE method to predict flow stress, recrystallized fraction and grain size distribution. Conventional approach gives a good agreement with experiments for an average grain size only.     

Dynamic Recrystallization of Hot Deformed 3Cr2NiMnMo Steel: Modeling and Numerical Simulation

Hot compression tests of 3Cr2NiMnMo steel were performed at temperatures in the range of 850 to 1100 °C and with strain rates of 10^?2s^?1 to 1s^?1. Both the constitutive equations and the hot deformation activation energy were derived from the correlativity of flow stress, strain rate and temperature. The mathematical models of the dynamic recrystallization of 3Cr2NiMnMo steel, which include the dynamic recrystallization kinetics model and the crystallization grain size model, are based on Avrami's law and the results of thermosimulation experiments. By integrating derived dynamic recrystallization models with the thermal-mechanical coupled finite element method, the microstructure evolution in hot compressive deformation was simulated. The distribution of dynamic recrystallization grains and grain sizes were determined through a comparison of the simulation results with the experimental results. The distribution of strain and dynamic recrystallization grain is also discussed. The similarity between the experimental results and the simulated results indicates that the derived dynamic recrystallization models can be applied effectively to predict and analyze the microstructure evolution in hot deformed 3Cr2NiMnMo steel.     

Tube Reversing and Extrusion (TRE) as a Novel Method for Producing UFG Thin Tubes

In the present research, a new severe plastic deformation method has been introduced for producing thin walled tubes with ultrafine grained substructure. The tube reversing and extrusion (TRE) technique was applied to a CP-aluminum and thin walled tubes with ultra-fine grained microstructure were successfully processed. The obtained results from tensile tests at room temperature showed the significant increase in mechanical properties of TRE processed thin walled tubes including yield and ultimate strengths and micro-hardness due to grain refinement. The microstructure evolution and deformation behaviour of commercially pure aluminium under TRE processing was simulated by the constitutive model as a micromechanical approach implemented in the finite element framework. The continuous dynamic recrystallization (the evolution of dislocation density and grain size) of aluminum tubes during TRE was considered as the main grain refinement mechanism in micromechanical constitutive model. Also, the flow stress of material in macroscopic scale was related to microstructure quantities. This was in contrast to the previous approaches in FEM simulations of SPD methods where the microstructure parameters such as grain size were not considered at all. The FEM simulated grain refinement behavior was consistent with the experimentally obtained results.     

Artificial Neural Network Modeling of Microstructure During CMn and HSLA Plate Rolling

An artificial neural network (ANN) model for predicting transformed microstructure in conventional rolling process and thermomechanical controlled process (TMCP) is proposed. The model uses austenite grain size and retained strain, which can be calculated by using microstructure evolution models, together with a measured cooling rate and chemical compositions as inputs and the ferrite grain size and ferrite fraction as outputs. The predicted results show that the model can predict the transformed microstructure which is in good agreement with the measured one, and it is better than the empirical equations. Also, the effect of the alloying elements on transformed products has been analyzed by using the model. The tendency is the same as that in the reported articles. The model can be used further for the optimization of processing parameters, microstructure and properties in TMCP.     

晶粒正常长大过程的元胞自动机模拟

 采用正六边形网格划分法,最近邻邻居关系以及概率性转换规则的二维元胞自动机（CA）法,对再结晶完成后的晶粒长大行为进行模拟。并利用正方形区域内圆形晶粒的收缩过程对模型的正确性进行验证。在此基础上,分析了微观结构的演化过程,给出了晶粒长大的动力学和界面能的变化,同时讨论了晶粒尺寸和晶粒边数的分布特点。结果表明：晶粒形态的演化过程遵循晶粒正常长大理论,晶粒尺寸和边数的分布具有时间不变性的特点,界面能的变化遵循能量降低原则。表明本模型能够较好的模拟晶粒的正常长大过程。     

低碳钢热变形奥氏体的再结晶行为

对热变形奥氏体的再结晶动力学和微观组织演变进行了模拟计算,对晶粒尺寸的模拟值和实测值作了比较,分析了化学成分对动态再结晶率的影响以及残余应变与变形温度的关系.结果表明:在温度较高、应变速率较低的条件下容易发生动态再结晶,随着变形温度的降低,发生动态再结晶的几率减小,而静态再结晶在前几道次进行得比较充分,随后进行得不充分,增加碳和锰的含量可以促进动态再结晶的发生,残余应变随变形温度的降低而增大,晶粒尺寸的模拟值和实测值吻合较好,表明所选用的模型有一定的参考价值.     

H型钢粗轧微观组织演化的数值分析

在ABAQUS软件的基础上,利用基于稳态判断的数值分析流程,构建了对H型材任意轧制道次进行微观组织演化模拟的分析平台。以某中型H型钢11道次热轧过程为研究对象,详细分析了粗轧过程轧件内奥氏体晶粒直径、温度、动态再结晶区域、动态再结晶奥氏体体积分数,以及道次间隙期间晶粒的长大和温度分布情况。     

Modeling of the Austenitization of Ultra-high Strength Steel with Cellular Automation Method

A model for simulating the austenitization of ultra-high strength steel during hot stamping is developed using a cellular automata approach. The microstructure state before quenching can be predicted, including grain size, volume fraction of austenite, and distribution of carbon concentration. In this model, a real initial microstructure is used as an input to simulate austenitization, and the intrinsic chemical difference is utilized to describe the ferrite and pearlite phases. The kinetics of austenitization is simulated by simultaneously considering continuous nucleation, grain growth, and grain coarsening. The UHSS is reduced to a Fe-Mn-C ternary system to calculate the driving force during extent growth in ferrite. The simulation results show that the transformation of ferrite to austenite can be divided into three stages in the condition of a heating rate of 10 K (?263 °C)/s. The transformation rate is determined by two factors, carbon concentration and temperature. The carbon concentration plays a major role at the early stages, as well as the temperature is the main factor at the later stages. The A _c3 calculated is about 1073 K (800 °C) close to the measured value [1067.1 K (794.1 °C)]. Austenite grain coarsening was calculated by a curvature-driven model. The simulated morphology of the microstructure agrees well with the experimental result. Most of the dihedrals of the grain boundaries at the triple junctions are close to 120 deg. Finally, tensile tests were implied, as dwelling time increased from 3 to 10 minutes, the austenite grain size increased from 6.95 to 9.44 μm while the tensile strength decreased from 276.4 to 258.3 MPa.     

Simulating Sediment Transport in a Flume with Forced Pool-Riffle Morphology: Examinations of Two One-Dimensional Numerical Models

One-dimensional numerical sediment transport models (DREAM-1 and DREAM-2) are used to simulate seven experimental runs designed to examine sediment pulse dynamics in a physical model of forced pool-riffle morphology. Comparisons with measured data indicate that DREAM-1 and -2 closely reproduce the sediment transport flux and channel bed adjustments following the introduction of fine and coarse sediment pulses, respectively. The cumulative sediment transport at the flume exit in a DREAM-1 simulation is within 10% of the measured values, and cumulative sediment transport at flume exit in a DREAM-2 simulation is within a factor of 2 of the measured values. Comparison of simulated and measured reach-averaged aggradation and degradation indicates that 84% of DREAM-1 simulation results have errors less than 3.3?mm, which is approximately 77% of the bed material geometric mean grain size or 3.7% of the average water depth. A similar reach-averaged comparison indicates that 84% of DREAM-2 simulation results have errors less than 7.0?mm, which is approximately 1.7 times the bed material geometric mean grain size or 11% of the average water depth. Simulations using measured thalweg profiles as the input for the initial model profile produced results with larger errors and unrealistic aggradation and degradation patterns, demonstrating that one-dimensional numerical sediment transport models need to be applied on a reach-averaged basis.