超混杂纤维金属层板成形方法研究进展

纤维金属层板(Fiber Metal Laminate, FMLs)作为一类兼具金属和复合材料优势的超混杂材料,凭借其优异的性能在航空航天和汽车领域应用广泛,其中商业化最成功的是玻璃纤维增强铝合金层板。首先按照组成金属与增强纤维的种类将纤维金属层板的分类进行介绍,并对其历史背景与研究进展进行了回顾。由于各成形方法涉及的变形机理不同,结合成形过程中几何尺寸和工艺参数对FMLs成形性能的影响,对其回弹、起皱、分层和开裂等成形缺陷和成形难点进行了分析。综述了现阶段国内外自成形、冲压成形、喷丸成形、充液成形和激光成形等技术的发展与应用现状,并对每种技术的优缺点及适用零件的类型进行探究。深入讨论了现有成形技术所遇到的挑战,其中重点对充液成形与冲压成形进行介绍。此外,简要介绍了FMLs在成形过程中的变形机理、变形模式和成形质量。在对各方面因素进行全面分析的基础上,讨论了FMLs成形技术未来的发展方向与挑战,此工作对科研人员未来开发新的成形方法具有一定意义。     

基于类等势场和响应面法的复杂锻件预成形优化设计

为实现复杂锻件的预成形设计,以连杆的热锻预成形设计为研究对象,建立基于类等势场和响应面分析的三维复杂锻件的预成形设计方法。在分析毛坯与终锻件间等势场分布规律与特点的基础上,采用逆向拟合法提取等势面及线面光顺处理,实现等势面的高效精确重构。针对长轴类锻件的预成形设计要求,提出沿零件的长、宽、高分别设置合理的缩放因子的非均匀缩放方法。实现了预成形件材料分布的合理调控,获得了优化的预锻件和辊锻毛坯,最终获得了充填完整、无任何成形缺陷且飞边小的连杆终锻件。数值模拟结果表明,所建立的方法能较好实现复杂锻件的预成形优化设计。     

基于双向渐进结构优化的叶片锻件预成形设计

为了实现体积成形的预成形优化设计,基于双向渐进结构(BESO)优化的思想,提出了一种针对体积成形预成形设计的新方法——拓扑优化法,并详细给出了该方法的优化策略、单元增删准则、插值处理等关键技术.利用自行开发的优化程序,结合DEFORM-2D有限元模拟软件,以理想充填模腔、最小飞边状态为目标,以静水压力的大小作为单元的增删准则,从毛坯的欠填充状态出发,对二维叶片锻件的预成形结构进行了优化设计.优化结果表明:该方法算法原理清晰明确,实现方便,整个过程集成化后,从模拟到优化均可实现自动进行,运行效率高,并具有较高的优化精度.     

基于有限元灵敏度分析的预锻模具形状优化设计

在控制锻件几何形状的前提下 ,采用有限元灵敏度分析方法 ,对预锻模具形状进行优化设计 .针对下模速度为零时 ,速度灵敏度边界条件为零 ,其形状在优化迭代过程中得不到优化的情况 ,对速度灵敏度边界条件提出改进措施 ,使上下模具形状同时能够得到优化 .最后给出了优化设计实例 ,验证该方法的可靠性 .     

有限元方法在金属塑性成形中的应用

有限元法是应用于金属塑性成形数值模拟中的一种有效的数值计算方法.详细介绍了弹塑性、刚塑性、粘塑性3种有限元法.刚塑性有限元法适用于大塑性变形,包括板带、型钢轧制和环件轧制的模拟分析等.弹塑性有限元法在金属塑性成形数值模拟中应用最广.与刚塑性方法相比,弹塑性有限元法还能有效处理卸载问题,计算残余应力和应变.而粘塑性有限元法适用于金属热变形或强化不显著的软金属变形.同时,结合国内外最新的具体实例说明了这些方法在金属塑性成形领域中的具体应用,展望了有限元方法在金属塑性成形中的发展.     

基于类等势场的粉末高温合金盘件预成形设计

根据能量最小原理和最小阻力原理,利用塑性变形过程中坯料的流动规律与静电场等势线分布类似这一特性,提出一种能够进行预成形设计的新方法——类等势场法,并采用该方法对粉末高温合金盘件进行预成形设计,从中优选出6组预成形形状,利用MSC/Super Form商用有限元软件对上述预制坯的等温成形过程进行了数值模拟,得到了6组粉末高温合金盘件在预锻到终锻过程中的应力率参数和应变率梯度.通过对盘件轮毂、辐板和轮缘3个部位6个典型单元体应力率参数g的比较与分析,以及整体盘件应变率梯度的比较,并参考预锻变形量和终锻变形量,认为选择3号预锻模为最佳方案.     

复杂构件锻造预成形坯料设计综述

锻件预成形坯料设计是保证成形工艺顺利进行、获得无缺陷锻件、降低锻造载荷的关键环节。对于大型复杂构件,其预成形坯料形状影响到制坯工艺的周期、成本、预成形组织性能。分别从基于反向模拟技术的预成形坯料设计、基于优化设计方法的预成形坯料设计、基于正向过程分析的预成形坯料设计等方面,评述了复杂构件锻造预成形坯料设计的国内外研究现状,指出了大型筋板类构件的预成形坯料形状要求以及设计方法。     

凝聚函数法求解粘弹性本构参数及温度场联合辨识问题

提出利用准静态位移信息对粘弹性本构参数及温度场进行联合识别的求解策略.建立了适于敏度分析的粘弹性与温度场耦合问题的正演数值模型,并将其反演归结为一个带有多个不等式约束的非线性规划问题,采用凝聚函数法将此问题转化为一个可微的单约束优化问题.在此基础上,采用乘子法进行求解,给出了数值验证,探讨了信息误差对反演结果的影响.     

基于FEA的板料成形工艺优化及评价函数研究

基于有限元和优化方法的板料成形工艺优化设计技术已经成为新的研究热点,建立合理的评价标准以形成目标函数,从而用于评价冲压件的成形性是其关键技术之一.提出局部成形性、整体成形性和综合成形性评价函数.基于试验设计法,结合方盒形件拉深以及发动机罩外板成形,验证了本文提出的评价函数具有良好的可靠性和易用性.     

TC4深筒形件超塑预成形模具型面设计及变摩擦厚度控制

以正反向超塑成形厚度均匀的TC4钛合金深筒形件为背景(厚度精度要求1.6mm±0.2mm),设计了多种预成形模形状,采用MSC.MARC有限元模拟研究了不同形状的预成形模对深筒形件侧壁厚度分布的影响, 并分析了预成形模和终成形模的表面摩擦系数分别对成形件壁厚分布的影响,提出了模具型面变摩擦控制厚度分布的方法.结果表明:预成形模对压边部分环形带区域和筒形件底部区域的局部预减薄,对最终侧壁的厚度分布有非常大的改善.同时,合理地增大预成形模的表面摩擦能显著增加预成形的局部减薄作用,对于提高工件最终壁厚分布均匀性有利.减小终成形模的摩擦,可以使板料整体变形均匀化,壁厚分布趋于均匀.根据有限元分析结果,对模具表面进行处理,并通过正反向超塑成形实验制得TC4钛合金深筒形件,其厚度分布满足1.6mm±0.2mm.     

PREFORM DIE SHAPE DESIGN IN METAL FORMING USING AN OPTIMIZATION METHOD

An optimization algorithm for preform die shape design in metal-forming processes is developed in this paper. The preform die shapes are represented by cubic B-spline curves. The control points of the B-spline are used as the design variables. The optimization objective is to reduce the difference between the realized and desired final forging shapes. The sensitivities of the objective function with respect to the design variables are developed in detail. The numerical examples show that the optimization method and the sensitivity analysis developed in this paper are very useful and the design results are satisfactory. Importantly, the preform die shapes designed by this method are easily manufacturable and can be implemented in practical metal-forming operations. This optimization method and the sensitivity analysis can also be applied in the preform design of complex industrial metal-forming problems. © 1997 by John Wiley & Sons, Ltd.     

OPTIMAL DESIGN FOR NON-STEADY-STATE METAL FORMING PROCESSES—II. APPLICATION OF SHAPE OPTIMIZATION IN FORGING

This paper is the second part of a two-part article about shape optimization of metal forming processes. This part is focused on numerical applications of the optimization method which has been described in the first paper. The main feature of this work is the analytical calculations of the derivatives of the objective function for a non-linear, non-steady-state problem with large deformations. The calculations are based on the differentiation of the discrete objective function and on the differentiation of the discrete equations of the forging problem. Our aim here is to show the feasibility and the efficiency of such a method with numerical examples. We recall the formulation and the resolution of the direct problem of hot axisymmetrical forging. Then, a first type of shape optimization problem is considered: the optimization of the shape of the initial part for a one-step forging operation. Two academic problems allow for checking the accuracy of the analytical derivatives, and for studying the convergence rate of the optimization procedure. Both constrained and unconstrained problems are considered. Afterwards, a second type of inverse problem of design is considered: the shape optimization of the preforming tool, for a two-step forging process. A satisfactory shape is obtained after few iterations of the optimization procedure.     

OPTIMAL DESIGN FOR NON-STEADY-STATE METAL FORMING PROCESSES—I. SHAPE OPTIMIZATION METHOD

We suggest a shape optimization method for a non-linear and non-steady-state metal forming problem. It consists in optimizing the initial shape of the part as well as the shape of the preform tool during a two-step forging operation, for which the shape of the second operation is known. Shapes are described using spline functions and optimal parameter values of the splines are searched in order to produce, at the end of the forging sequence, a part with a prescribed geometric accuracy, optimal metallurgical properties and for a minimal production cost. The finite element method, including numerous remeshing operations, is used for the simulation of the process. We suggest using a least-squares-type algorithm for the unconstrained optimization method (based on external penalty) for which we describe the calculation of the derivatives of the objective function. We show that it can reduce to calculations which are equivalent to the derivative calculations of steady-state processes and to evolution equations. Therefore, the computational cost of such an optimization is quite reasonable, even for complex forging processes. Lastly, in order to reduce the errors due to the numerous remeshings during the simulation, we introduce error estimation and adaptive remeshing methods with respect to the calculation of derivatives.     

考虑作动器联接方式的结构形状控制优化

以压电材料梁式作动器控制复合材料层合板形状的设计问题为对象,研究有限个独立控制参数条件下的形状最优控制问题。研究了作动器与信号发生器(独立控制参数)联接关系的参数化描述方式,建立了作动器联接方式与控制参数协同设计的问题提法;针对优化问题中离散变量(联接方式描述参数)和连续变量(控制参数)共存的特点,建立了遗传算法和线性最小二乘(Linear Least Square,LLS)方法相结合的求解策略和方法;在响应分析所采用的有限元模型中,采用粘结层单元描述本体结构与作动器之间的连接。复合材料层合板形状控制设计的实例,验证了该文中建立的问题提法、优化模型和求解策略的有效性。     

椭圆异型挤压塑性成形映射理论及模腔优化解析

针对金属椭圆异型挤压塑性成形及模腔优化的理论课题,应用复变共形映射数学研究成果,利用奇偶点相互迭代的三角插值法和法线收敛法,将三维金属异型挤压塑性成形问题转化为二维轴对称成形问题,求解异型挤压模腔曲面函数,建立映射函数解析方法,推导椭圆异型材挤压金属塑性成形连续流动场和应变速度场的数学解析式,并应用金属塑性成形能量极值原理,进行异型材挤压模腔参数的优化,同时为精密快速地实现挤压模腔的CAD/CAM一体化目标提供技术支持.     

特定弹性性能材料的细观结构设计优化

针对具有特定弹性性质的两相复合材料, 研究了特定性能材料优化设计问题的数学模型,提出了基于形状优化的材料设计方法。该方法利用形状优化技术, 设计两相复合材料的细观结构形式, 以使复合材料具有特定的弹性性质。材料的宏观性质由均匀化方法确定。最后给出了零泊松比材料的设计过程和结果。      

复合材料层合板稳定性的铺层优化设计

提出采用神经网络和遗传算法来优化设计复合材料层合板,建立了满足铺层结构稳定性的优化铺层体系,优化体系分两步进行优化,第一步,当给出总的铺层数时,由已建立的神经网络模型确定规定角度下的铺层数,确立基本的铺层结构,第二步,采用遗传算法优化这种铺层结构下的铺层顺序,最终在同样重量下获得了最佳的结构铺层.     

LAGRANGEAN RELAXATION AND SUBGRADIENT OPTIMIZATION APPLIED TO OPTIMAL DESIGN WITH DISCRETE SIZING

The discrete sizing problem in optimal design is adressed. Lagrangean dual approaches earlier published are briefly reviewed and it is noted that quite sophisticated procedures have been used to solve the dual problems. The simple concept of Lagrangean relaxation combined with subgradient optimization and Lagrangean heuristics has, however, not been applied to the discrete sizing problem. In this paper a scheme based on this concept is described and tested on some small problems. The results indicate that subgradient optimization is completely capable of solving the dual problem. Moreover it is possible to devise heuristics that construct feasible solutions to the original problem, using the Lagrangean subproblem solution.