一种带梯度惩罚项的离散力学最优控制方法

离散力学最优控制方法(discrete mechanics and optimal control, DMOC) 是最新提出的一种有效的优化控制模型. 由于原始方法在求解优化问题时容易产生控制力的震荡,不利于控制力的稳定输出. 该文首先对产生这种数值现象的原因进行了简单的分析,并提出了可行的解决路径--加入惩罚梯度项. 最后采用数值算例对该方法进行验证,数值算例表明:改进的方法可以在保证力量最小化的前提下,使得控制力连续平滑.     

半空间SH波方程非线性井间双参数反演

以半空间的ＳＨ波方程出发,采用Ｂｏｒｎ迭代法求解半空间弹性介质中密度和剪切模量分布的非线性反演问题。首先,采用矩量法和正则化方法,给出井间反演积分方程的离散形式,然后应用Ｂｒｏｎ迭代法求解非线性反演问题。     

Numerical method for the shape reconstruction of a hard target

IntroductionAninverseproblemofconsiderableimportanceinvariousfieldsofengineeringtechnology ,suchasnondestructivetesting ,medicalimaging ,remotesensingandseismicimaging ,istodeterminetheshapeofascatteringobjectfromitsfar_fieldeffectsontheacousticscatteringwaves.However,thiskindofproblemisparticularlydifficulttosolvesinceitisbothnonlinearandill_posed[1].Fortunately ,therehavebeenseveralmethodsdevelopedforsolvingnumericallytheinverseproblemduringthelastdecade .Ofparticularimportancearenonlinearop…     

基于偶应力模型的连续体结构拓扑优化设计

经典连续介质理论不包含材料尺度参数,因而基于经典理论的结构拓扑优化无法显现尺度效应.本文在偶应力理论的框架下,构造了四节点四边形离散偶应力单元,将传统的SIMP方法推广至偶应力介质.结果表明,在以结构的最大刚度为目标的设计中,偶应力介质的最优结果取决于宏观结构尺寸与材料微结构尺寸(或者特征长度)的比值,最优结果具有明显的尺度效应,具体为,二者比值较大将产生与传统理论相似的结构,而二者比值相当则产生独特的偶应力主导的结构.     

基于蚁群算法的桁架结构布局离散变量优化方法

提出的布局优化方法是将桁架结构的截面变量、拓扑变量及形状变量统一为离散变量.将离散变量转化为适应于蚁群算法求解TSP问题的离散变量,应用MATLAB语言编写求解桁架结构布局优化程序,最终实现对问题的分析与求解.通过对几个经典的平面、空间桁架结构布局优化算例的验算表明:本文设计的基于蚁群算法的桁架结构布局离散变量优化方法较单独处理截面优化、拓扑优化及形状优化问题具有更大的效益,相对于其他布局优化方法也展现出更好的优化效果.“基于蚁群算法的桁架结构布局离散变量优化方法”在程序设计、求解速度、求解空间及其方法通用性等方面都表现出良好的性能,并且简单、实用,适应于实际工程应用.     

面向增材制造的应力最小化连通性拓扑优化

增材制造与拓扑优化的有机结合将极大促进高性能产品的研发, 但现有基于拓扑优化的设计性能和可制造性研究多是独立开展, 或常局限于传统的刚度问题, 缺乏对工程中至关重要的强度问题的考虑. 面向增材制造, 针对协同考虑强度和可制造连通性的结构优化问题, 建立了材料体积和连通性标量场约束下的结构应力最小化拓扑优化模型. 针对求解过程中的不同数值困难问题, 提出了有效的优化求解策略. 引入基于P范数的全局标量场约束度量, 并结合稳定转换误差修正技术来实现对局部标量场的有效控制. 详细推导了相关灵敏度, 然后通过典型数值算例论证了文中模型及方法的合理有效性. 结果表明, 仅考虑连通性约束的刚度最大化设计不一定能避免局部高应力集中, 而该设计也不一定等同于应力最小化连通性设计; 充足的材料许用量和恰当的连通性约束边界条件对提高所研究设计的性能至关重要, 而应力凝聚参数取值并非越大越好, 合理取值才能有助于获取高性能设计. 此外, 优化结果也在一定程度上论证了可制造性拓扑优化中考虑强度问题的必要性和可行性.      

Binary discrete method of topology optimization

The numerical non-stability of a discrete algorithm of topology optimization can result from the inaccurate evaluation of element sensitivities. Especially, when material is added to elements, the estimation of element sensitivities is very inaccurate, even their signs are also estimated wrong. In order to overcome the problem, a new incremental sensitivity analysis formula is constructed based on the perturbation analysis of the elastic equilibrium increment equation, which can provide us a good estimate of the change of the objective function whether material is removed from or added to elements, meanwhile it can also be considered as the conventional sensitivity formula modified by a non-local element stiffness matrix. As a consequence, a binary discrete method of topology optimization is established, in which each element is assigned either a stiffness value of solid material or a small value indicating no material, and the optimization process can remove material from elements or add material to elements so as to make the objective function decrease. And a main advantage of the method is simple and no need of much mathematics, particularly interesting in engineering application.     

大型相控阵天线结构保型设计研究

针对某大型相控阵天线自重大、表面精度要求高、加强筋安装位置受限的特点,本文进行相控阵天线阵面保型的结构方案设计.考虑到加强筋安装位置和型材受限,提出了连续化过滤函数,使得型材变量与连续变量进行映射,将离散变量拓朴优化转换为连续变量拓朴优化求解,提高了求解效率,降低了求解的规模.同时,为降低支腿驱动力,以调整机构条件数为目标进行铰节点的布局优化,并进行了静、动力的计算,确定了支腿最大驱动力.对某大型相控阵雷达进行了案例验证,收到满意的结果,并且该方案将应用到工程实际中.     

Shape Optimization of Body Located in Incompressible Viscous Flow Based on Optimal Control Theory

This paper presents a numerical method of shape optimization of a body located in an incompressible viscous flow described by the Stokes and Oseen equations. The purpose of this study is to find the optimal shape that minimizes the fluid forces subjected to the body. The formulation of the shape optimization is based on the optimal control theory. The first thing that should be carried out in the optimal control theory is to define a performance function, which expresses the optimal shape. In this study, the fluid forces minimization problem is treated, i.e. fluid forces are directly used in the performance function. The performance function must be minimized subject to the basic equation. The optimal shape, which minimizes the fluid force, is pursued in this paper. This problem can be transformed into the minimization problem without constraint conditions by the Lagrange multiplier. As a numerical example, drag force minimization problems of a body located in low Reynolds number flows are carried out.     

Discrete optimal control for Birkhoffian systems

In this paper, we investigate a discrete variational optimal control for mechanical systems that admit a Birkhoffian representation. Instead of discretizing the original equations of motion, our research is based on a direct discretization of the Pfaff–Birkhoff–d’Alembert principle. The resulting discrete forced Birkhoffian equations then serve as constraints for the minimization of the objective functional. In this way, the optimal control problem is transformed into a finite-dimensional optimization problem, which can be solved by standard methods. This approach yields discrete dynamics, which is more faithful to the continuous equations of motion and consequently yields more accurate solutions to the optimal control problem which is to be approximated. We illustrate the method numerically by optimizing the control for the damped oscillator.     

Topology optimization design of continuum structures under stress and displacement constraints

ＩｎｔｒｏｄｕｃｔｉｏｎＴｏｐｏｌｏｇｙｏｐｔｉｍｉｚａｔｉｏｎｏｆｃｏｎｔｉｎｕｕｍｓｔｒｕｃｔｕｒｅｓｄｉｄｎｏｔｄｅｖｅｌｏｐｒａｐｉｄｌｙｕｎｔｉｌｒｅｃｅｎｔｔｅｎｙｅａｒｓｏｗｉｎｇｔｏｔｈｅｓｐｅｃｉａｌｄｉｆｆｉｃｕｌｔｉｅｓｉｎｖｏ...     

Improved global–local simulated annealing formulation for solving non-smooth engineering optimization problems

This paper is concerned with a novel optimization algorithm that implements an enhanced formulation of simulated annealing (SA). The new algorithm is denoted as ISA (improved simulated annealing) in the rest of the paper. ISA includes a two-level random search: “global annealing” where all design variables are perturbed simultaneously and “local annealing” where design variables are perturbed one at a time.The improvement with respect to classical SA is in the fact that trial designs are generated always taking care to choose directions along which the cost function may improve. To this purpose, cost function sensitivities are computed in order to properly choose the size of each random perturbation. In addition, the optimization problem is linearized about the current design point if the optimizer ends up in an infeasible region or there is no significant reduction in cost even though the cost function gradient is not close to zero. The linearization is controlled by a trust region model. The optimization algorithm continuously shifts from global to local annealing based on the current best record at the beginning of each cooling cycle. Finally, the cooling schedule is automatically adjusted within ISA based on the convergence behavior.In this work, the ISA algorithm is successfully utilized to solve complicated optimization problems which exhibit non-smooth/non-convex behavior: (i) the large-scale (200 design variables and 3500 constraints) weight minimization of a 200 bar truss under five independent loading conditions; (ii) the configuration optimization of a cantilevered bar truss with 45 elements and 81 design variables; (iii) an example of reverse engineering where in-plane elastic properties of an eight-ply woven composite laminate are to be determined.The performance of ISA is compared to that of classical SA, gradient based optimization codes recently published in literature and commercial software. The results obtained in this study indicate that ISA is a very efficient optimization code. In fact, ISA was much faster than classical SA. The present code allowed about 300 kg weight saving in the 200 bar truss case and about 80 kg in the cantilevered bar truss case. In addition, the residual error on elastic constants in the material identification problem was less than 3%.     

基于多轮升维策略与改进量子行为粒子群优化算法的热导率函数估计方法

将改进的量子行为粒子群优化算法应用于材料热导率函数估计问题中,并提出了一种多轮升维策略对算法的搜索过程进行优化,形成了一种鲁棒性强且高效的反演方法。通过数值实验测试了该方法在测量误差以及系统误差下的表现,并对不同粒子群优化算法的性能进行了比较研究。结果表明,采用的反演方法能够在较大的搜索范围与反演维度下稳定收敛,对测量误差的敏感度较低;提出的多轮升维策略能够使各类粒子群优化算法在热导率函数估计问题中的搜索效率得到提升。     

双相介质参数反演的混沌搜索方法

混沌运动能在一定的范围内按自身的规律不重复地遍历所有状态。利用这个特点 ,本文将混沌运动引入到双相介质参数反问题的研究中。首先利用边界元方法实现了由介质参数到地表位移的非线性映射 ,然后通过建立合成位移与实测位移的相关函数将参数识别问题归结为优化问题 ,最后利用混沌运动指导优化搜索求得介质参数。算例结果表明了混沌搜索方法用于双相介质参数反演问题的可行性和有效性     

基于凸模型的结构非概率可靠性优化

基于不确定性的凸模型描述，研究考虑非概率可靠性指标约束的结构优化问题. 该优化 模型是一个内层优化为极小极大问题的嵌套优化模型. 为了有效地求解该模型，提出了 一种基于目标性能的优化方法，通过寻找目标性能点来判断约束的满足情况，从而避免直接 计算以极小极大(min-max)问题定义的非概率可靠性指标. 提出的数值方法可处理材 料、几何及载荷等不确定性参数，并且目标性能值的灵敏度计算公式简便，算法稳定. 数值 算例验证了所提出方法的正确性，也表明算法比文献中已有方法更为有效 。     

基于无网格数值求解技术的二维连续体结构拓扑优化设计

将无网格径向点插值法(RPIM)引入到连续体结构拓扑优化设计中。在优化问题中,选取节点的相对密度作为设计变量,以结构的柔度最小化作为目标函数,基于带惩罚的各向同性固体材料模型(SIMP)建立了结构拓扑优化的数学模型,推导了目标函数和体积约束的灵敏度,利用优化准则法进行求解。算例表明了应用无网格径向点插值法进行结构拓扑优化设计的可行性和有效性,同时表明选取节点的相对密度作为设计变量可以有效地克服拓扑优化中的棋盘格现象。     

基于类桁架连续体的结构拓扑优化方法与应用

以各向异性连续体为基结构,采用类桁架连续体材料模型进行结构拓扑优化。以材料在结点位置的密度和方向作为优化设计变量,使材料在设计域内连续分布。并以此建立材料的弹性矩阵和刚度矩阵。优化过程没有抑制中间密度,这从根本上避免了许多拓扑优化方法普遍存在的单元铰接、棋盘格现象以及单元依赖性等数值不稳定问题。采用满应力准则法,借助有限元结构分析,经过少量迭代,建立优化的材料连续分布场,即类桁架连续体结构。由于首先建立的拓扑优化结构是各向异性连续体,从而得到更大优化空间。然后可以结合工程实际需要将其转化为离散的拓扑优化杆系结构。最后,以1个经典Michell桁架和3种形式的拱桥为数值算例,演示了其结构拓扑优化过程。     

Local and Global Injective Solution of the Rotationally Symmetric Sphere Problem

There are problems in the classical linear theory of elasticity whose closed form solutions, while satisfying the governing equations of equilibrium together with well-posed boundary conditions, predict the existence of regions, often quite small, inside the body where material overlaps. Of course, material overlapping is not physically realistic, and one possible way to prevent it combines linear theory with the requirement that the deformation field be injective. A formulation of minimization problems in classical linear elasticity proposed by Fosdick and Royer [3] imposes this requirement through a Lagrange multiplier technique. An existence theorem for minimizers of plane problems is also presented. In general, however, it is not certain that such minimizers exist. Here, the Euler–Lagrange equations corresponding to a family of three-dimensional problems is investigated. In classical linear elasticity, these problems do not have bounded solutions inside a body of anisotropic material for a range of material parameters. For another range of parameters, bounded solutions do exist but yield stresses that are infinite at a point inside the body. In addition, these solutions are not injective in a region surrounding this point, yielding unrealistic behavior such as overlapping of material. Applying the formulation of Fosdick and Royer on this family of problems, it is shown that both the displacements and the constitutive part of the stresses are bounded for all values of the material parameters and that the injectivity constraint is preserved. In addition, a penalty functional formulation of the constrained elastic problems is proposed, which allows to devise a numerical approach to compute the solutions of these problems. The approach consists of finding the displacement field that minimizes an augmented potential energy functional. This augmented functional is composed of the potential energy of linear elasticity theory and of a penalty functional divided by a penalty parameter. A sequence of solutions is then constructed, parameterized by the penalty parameter, that converges to a function that satisfies the first variation conditions for a minimizer of the constrained minimization problem when this parameter tends to infinity. This approach has the advantages of being mathematically appealling and computationally simple to implement.     

Stress energy minimization as a tool in the material layout design of shallow shells

The present research deals with the compliance minimization problem of an elastic thin shallow shell subjected to simultaneous in-plane and bending loads. In this context, our goal is to lay out a given amount of material in the volume of a shell assuming that the distribution in the direction transversal to its middle surface S is homogeneous. The discussion hence reduces to the question of finding the optimal material arrangement on S. Similar problems were solved in the framework of two dimensional elasticity or Kirchhoff plate theory and the present research attempts to generalize these results. Following the pattern emerging from the above mentioned considerations, our research starts from the minimum compliance problem of a structure made of two elastic materials whose volumetric fractions are fixed. The existence of a solution to thus posed optimization task is guaranteed if the fine-scale microstructural composites are admitted in the analysis. Their constitutive tensors can be obtained by certain averaging ensuing from the theory of homogenization for periodic media. Additionally, by the Castigliano Theorem, the compliance minimization problem is equivalent to the one for structural stress energy. In turn, the lower estimation of the energy is achieved in two steps: (i) its modification by a certain energy-like functional, and (ii) utilizing the quasiconvexity property of thus obtained expression. As a result, formulae describing the effective stress energy of one-material shallow shell and the material distribution function are explicitly derived.     

Shape optimization of a body located in low Reynolds number flow

The purpose of this study is to perform a numerical application of the shape optimization formulation of a body located in an incompressible viscous flow field. The formulation is based on an optimal control theory in which a performance function of the fluid force is introduced. The performance function should be minimized satisfying the state equation. This problem can be transformed into the minimization problem without constraint condition by the Lagrange multiplier method and the adjoint equations using adjoint variables corresponding to the state equations. As a numerical study, the drag force minimization problem in the steady Stokes flow, which means approximated equation of the low Reynolds number Navier–Stokes equation is carried out. After that, the unsteady Navier–Stokes flow is analysed. As the minimization algorithm, the steepest descent method is successfully applied. Copyright © 2005 John Wiley & Sons, Ltd.