Unit-4-Optimal-Design-机电专业英语-图文课件

1、Unit 4 Optimal DesignContentsNew Words & Expressions Text & TranslationComplex Sentence AnalysisKey to ExercisesNew Words & Expressions optimization ptimaizein n. 最佳化，最优化Finite Element Analysis (FEA) 有限元分析Computer Aided Design (CAD) 计算机辅助设计burden b:dn n. 担子，负担，责任，义务rigor rig n. 严格，严密，精确mesh me n. 网孔

2、，网格，网状物scenario sin:riu n. (意大利语) 方案，情况seamless si:mlis adj. 无缝的，无伤痕的criterion kraitirin n. 标准，准则，规范New Words & Expressions geometry dimitri n. 几何学，几何图形(形状)，轮廓iteration itrein n.迭代，反复gauge geid v. 判断，测试，测定，测量intensive intensiv adj. 强化的，加强的cast k:st v. 派(角色)，计算, 分类整理assembly sembli n. 组合，装配，部件，汇编warr

3、ant w:rnt v. 成为的证据，保证，证明是正确的yield ji:ld v. 产出，产生，提供，给予，得出expertise eksp:ti:z n. 专家的意见，专门知识，经验；专家New Words & Expressions underlying ndlaii adj. (做) 基础的，根本的，在下面的linear lini adj. 线性的，线的，直线的variable vribl n. 变量，可变物adj. 可变的，变量的function fkn n. (数) 函数，功能，作用，职责constraint knstreint n. 约束，强制，局促impetus impits

4、n. 推动力，促进，刺激，激励scheme ski:m n. 计划，方案，图解Text & TranslationThe integration of optimization techniques with finite element analysis (FEA) and computer aided design（CAD）is having pronounced effects on the product design process. 1This integration has the power to reduce design costs by shifting the burd

5、en from the engineer to the computer. Furthermore, the mathematical rigor of a properly implemented optimization tool can add confidence to the design process. Generally, an optimization method controls a series of applications, including CAD software as well as FEA automatic solid mesh and analysis

6、 processors. This combination allows for shape optimizations on CAD parts or assemblies under a wide range of physical scenarios including mechanical and thermal effects. Text & TranslationModern optimization methods perform shape optimizations on components generated within a choice of CAD packages

7、. Ideally, there is seamless data exchange via direct memory transfer between the CAD and FEA applications without the need for file translation. Furthermore, if associativity between the CAD and FEA software exists, any changes made in the CAD geometry are immediately reflected in the FEA model. In

8、 the approach taken by ALGOR, the design optimization process begins before the FEA model is generated. The user simply selects which dimension in the CAD model needs to be optimized and the design criterion, which may include maximum stresses, temperatures or frequencies. The analysis process appro

9、priate for the design criteria is then performed. Text & TranslationThe results of the analysis are compared with the design criterion, and, if necessary without any human intervention, the CAD geometry is updated. 2Care is taken such that the FEA model is also updated using the principle of associa

10、tivity, which implies that constraints and loads are preserved from the prior analysis. The new FEA model, including a new high-quality solid mesh, is now analyzed, and the results are again compared with the design criterion. This process is repeated until the design criterion is satisfied. Fig.4-1

11、 shows the procedure of shape optimization. Text & TranslationFig. 4-1 Procedure of the Shape OptimizationText & Translation1.Introduction The typical design process involves iterations during which the geometry of the part(s) is (are) altered. In general, each iteration also involves some form of a

12、nalysis in order to obtain viable engineering results. Optimal designs may require a large number of such iterations, each of which is costly, especially if one considers the value of an engineers time. The principle behind design optimization applications is to relieve the engineer of the laborious

13、 task by automatically conducting these iterations. At first glance, it may appear that design optimization is a means to replace the engineer and his or her expertise from the design loop. Text & TranslationThis is certainly not the case because any design optimization application cannot infer what

14、 should be optimized, and what are the design variables, the quantities or parameters that can be changed in order to achieve an optimum design. Thus, design optimization applications are simply another tool available to the engineer. The usefulness of this tool is gauged by its ability to efficient

15、ly identify the optimum. Text & TranslationDesign optimization applications tend to be numerically intensive because they must still perform the geometrical and analysis iterations. 3Fortunately, most design optimization problems can be cast as a mathematical optimization problem for which there exi

16、st many efficient solution methods. The drawback to having many methods is that there usually exists an optimum mathematical optimization method for a given problem. This complexity should be remedied by the design optimization application by giving the engineer not only a choice of methods, but als

17、o a suggestion as to which approach is most appropriate for his or her design problem. Text & TranslationIn this text, we focus on the design optimization of mechanical parts or assemblies. In this case, a typical optimized quantity is the maximum stress experienced. Typical design variables include

18、 geometric quantities, such as the thickness of a particular part. The design of the part or assembly is initiated within a CAD software application. If the component warrants an engineering analysis, the engineer will generally opt to apply finite element analysis (FEA) in order to model or simulat

19、e its mechanical behavior. The FEA results, such as the maximum stress, can be used to ascertain the validity of the design. During the design process, the engineer may alter parameters or characteristics of the CAD and/or FEA models, including some of the physical dimensions, the material or how th

20、e part or assembly is loaded or constrained. Text & TranslationAssociativity between the CAD and FEA software should allow the engineer to alter the model in either application, and have the other automatically reflect these changes. For example, if the thickness of a part is changed or a hole is ad

21、ded in the CAD software, the FEA models mesh should automatically reflect those changes. Under most circumstances, engineers will employ linear static FEA to obtain the stresses. This analysis approach has the benefit of yielding a solution for FEA models with many elements in relatively little time

22、. Obviously, linear static FEA has drawbacks as well. For example, significant engineering expertise may be required when estimating the magnitude and direction of loads that are a consequence of motion. Text & Translation2. Background and Theory In this section, we focus on the theory underlying so

23、me of the mathematical methods employed by design optimization procedures. But, first we describe how the optimization problem arises. Consider a three-step process: (1) generation of geometry of part or assembly in CAD. (2) creation of FEA model of part or assembly. (3) evaluation of results of FEA

24、 models. Text & TranslationFor now, we limit ourselves to the case of linear static FEA. Therefore, the results are comprised of deflections and stresses at one instance. The manual design process involves all three steps, with the results being used to evaluate whether the design is appropriate. If

25、 the design is found inadequate, changes are made to steps (1) or (2) or both. It is clear from this description that the output of the FEA results is what should be optimized, and that any input to the CAD or FEA models can be viewed as a design variable. A design optimization algorithm conducts ma

26、ny FEA runs, each one with a different set of values for the design parameters. Before the manual design approach can be transformed into a design optimization algorithm, there must be associativity between the CAD and FEA applications. Text & TranslationThe rational behind this requirement is best

27、explained using an example. Consider the initial design stage when the engineer applies constraints on a particular surface of the FEA model; it can be safely assumed that this surface coincides with a surface in the CAD model. Now, if the design optimization algorithm decides to alter the geometry

28、of the CAD surface, then the FEA model must automatically reflect these changes, and apply the constraints on the new representation of this surface. Thus, associativity is required in order to achieve this automatic communication between the CAD and FEA models. Having defined the design optimizatio

29、n problem for mechanical systems, we now describe the mathematics used to solve these problems. Text & TranslationMost optimization problems are made up of three basic components. (1) An objective function which we want to minimize (or maximize). For instance, in designing an automobile panel, we mi

30、ght want to minimize the stress in a particular region. (2) A set of design variables that affect the value of the objective function. In the automobile panel design problem, the variables used define the geometry and material of the panel. (3) A set of constraints that allow the design variables to

31、 have certain values but exclude others. In the automobile panel design problem, we would probably want to limit its weight. Text & TranslationIt is possible to develop an optimization problem without constraints. Some may argue that almost all problems have some form of constraints. For instance, t

32、he thickness of the automotive panel cannot be negative. Although in practice, answers that make good sense in terms of the underlying physics, such as a positive thickness, can often be obtained without enforcing constraints on the design variables. Text & Translation3. Benefits and Drawbacks The e

33、limination or reduction of repetitive manual tasks has been the impetus behind many software applications. Automatic design optimization is one of the latest applications used to reduce man-hours at the expense of possibly increasing the computational effort. It is even possible that an automatic de

34、sign optimization scheme may actually require less computational effort than a manual approach. This is because the mathematical rigor on which these schemes are based may be more efficient than a human-based solution. Of course, these schemes do not replace human intuition, which can occasionally s

35、ignificantly shorten the design cycle. Text & Translation4One definite advantage of automated methods over manual approaches is that software applications, if implemented correctly, should consider all viable possibilities. That is, no variable combination of the design parameters is left unconsider

36、ed. Thus, designs obtained using design optimization software should be accurate to within the resolution of the overall method. Text & Translation优化方法与有限元分析和计算机辅助设计的组合正影响着产品的设计过程。这种组合把工作任务从工程师转移给计算机，从而可以降低设计成本。此外，正确地使用优化方法所带来的数学上的严谨也能提高设计过程的可靠性。通常，优化方法决定了包括CAD软件及有限元分析中三维网格自动划分和分析处理器等在内的一系列的应用。这种组合使

37、得在包含机械效应和热效应的各种实际情况下能够对CAD的零件和装配件形状进行优化。Text & Translation现代的优化方法可对CAD软件产生的零件形状进行优化。理论上，通过存储内容的直接转储在CAD和FEA应用间无需文件的转换而实现数据的无缝交换(传输)。此外，如果CAD和FEA 软件间存在关联，CAD几何图形的任何改变会立即在FEA模型中体现出来。在ALGOR所采用的方法中，有限元模型产生之前，优化设计过程就开始了。用户只需要选择CAD模型中要优化的尺寸及设计准则，包括最大应力，温度或频率，然后执行合乎设计准则的分析过程。分析的结果与设计准则进行比较，如果需要的话，无需任何人工干预就

38、可更新CAD图形。必须注意使用关联的原则使FEA模型得到更新，这就意味着要从前面的分析中保存约束和荷载，现在要分析包含新的高质量的立体网格的新的FEA模型，结果要再一次与设计准则进行比较，这一过程反复进行直到满足设计准则。如图4-1所示说明了形状优化设计的过程。Text & Translation图4-1 优化设计过程示意图Text & Translation1.绪论 典型的设计过程在零件几何形状发生改变时会用到迭代法。通常，每一次的迭代也会用到某种形式的分析以获得可行的工程结论。优化设计会用到很多次这样的迭代，每次迭代代价很高，尤其在考虑工程师的时间的价值时。优化设计应用软件的本质就是通过自

39、动进行迭代减少工程师的工作量。乍一看，似乎优化设计是把工程师和专家们从设计循环中替换出来的一种工具。当然情况并非如此，因为任何优化设计软件都不能指明要对什么目标进行优化，哪些是设计变量，哪些量或参数可以改变以获得最优设计。因此优化设计软件只是工程师可以使用的另一种工具。其作用尤其有效地确定最优解的能力来衡量。Text & Translation优化设计软件往往会强化数字化处理，因为他们仍然要执行几何分析的迭代。值得庆幸的是，大多数优化设计问题可以看成是数学优化问题，而数学优化问题就有许多的高效求解方法。但具有许多求解方法的缺陷是对于一个特定的问题总有一种最佳的数学优化方法。这种复杂性可以通过在

40、优化设计软件中不仅给工程师提供优化方法的选择，还给出什么方法最适合其设计问题的建议来得到改善。Text & Translation本文重点在机械零件或装配件的优化设计上。此时，常用的优化目标是能承受最大应力。典型的设计变量包括一些几何量，如特殊零件的厚度。零件或装配件的设计从CAD软件开始。如果(所建)结构能保证工程分析的质量，工程师一般将选择使用有限元分析来模拟分析其机械性能。有限元分析的结果，如最大应力，可以用来验证设计的正确性。设计过程中，工程师可能需要改变CAD和/或FEA模型的参数或特征，包括某些具体尺寸、材料或对零件或装配件的加载或约束方式。CAD和FEA软件间的关联性使得工程师能

41、在其中之一改变模型，而在另一软件中自动体现这些改变。例如，如果在CAD软件中改变了零件的厚度或增加了一个孔，有限元模型的网格能自动反映这种变化。在大多数情况下，工程师将使用线形静态FEA来获得应力。这种分析方法的优点是用较少的时间得到单元数较多的有限元模型的解。显然线形静态FEA也有缺点。例如，在估计由于运动而引起的载荷的大小和方向时需要丰富的工程专业知识。Text & Translation2.基础知识和理论 这部分我们来重点讨论优化设计使用的数学方法的基础理论。但是首先我们描述一下有限元问题是如何提出的。考虑如下3个过程：(1) 在CAD中产生零件或组件的几何图形；(2) 创建零件或组件的

42、FEA 模型；(3) 计算FEA模型的结果。现在，我们只限于讨论线性静态FEA。因此，这种情况下分析结果由变形和应力组成。手工设计过程包括完整的3个步骤，所得结果用于评价该设计是否合适。如果不合适，就要对步骤(1)或(2)或者(1)和(2)均做出修改。从这个描述中可以清楚地看出，FEA输出的是要优化的目标，而CAD或FEA模型的任何输入都可以看做设计变量。优化设计的算法对许多的FEA 运用有指导作用，每一种算法都有一套不同的设计变量值。CAD和FEA应用之间必须建立起关联，才能把手工设计方法转变成优化设计算法。这一要求的合理性可通过一个例子得到最好的解释。在开始设计阶段，工程师在FEA 模型的

43、一个特殊表面施加约束时，我们可以很放心地假设这个表面与CAD模型中的面一致。现在如果优化设计的算法决定要改变CAD模型中面的几何形状，那么FEA 模型必须自动反映这些变化，并在该表面的新模型上施加约束。因此为了实现CAD与FEA模型间自动通讯，就需要二者之间的关联。在明确了机械系统优化设计的问题后，接下来我们来描述解决这些问题的数学方法。Text & Translation大部分的优化问题都由以下3 个部分组成：(1) 一个要使其最小化(或最大化)的目标函数。如在设计汽车的仪表板时，使其在特定区域内的应力最小。(2) 一组影响目标函数值的设计变量。如在汽车仪表板设计中，用变量来确定仪表板的几何

44、形状和材料。(3) 一组约束。这些约束允许设计变量取某些值而排除另一些值。在汽车仪表板设计中，可能会限制其质量。也可以建立无约束优化问题。或许有人会争论说几乎所有问题都应具有某种形式的约束。例如，汽车仪表板的厚度就不能为负。不过实际上，常常无需对设计变量强加约束也可获得从基本物理知识上讲有意义的结果，如正的厚度值。Text & Translation3.优缺点 消除或减少人的重复工作已经成为了许多软件应用的推动力。自动化的优化设计是以可能增加计算量为代价来减少人的工作时间的最新应用之一，甚至也可能实际上所需要的计算量比手工设计方法还少。这是因为数学作为这些方法的基础，其严谨性比人工的解决方法效

45、率更有效。当然这些方法也不能取代人的知识，人的知识有时可以大大缩短设计周期。自动化方法与手工方法相比，一个明显的优点是如果软件的应用正确的话，可以把一切可行的可能性考虑进来。也就是说，设计参数的各种可行的组合均会考虑到。因此，用优化设计软件所获得的设计应该是精确到全面的解决方案。Complex Sentence Analysis1 This integration has the power to reduce design costs by shifting the burden from the engineer to the computer. 这种组合把工作任务从工程师转移给计算机，从而可以降低设计成本。 power：能力，has the power to 翻译成 “能够” .shifting the burden from the engineer to the computer：把任务从工程师转移给计算机Complex Sentence Analysis2 Care is taken such that the FEA model is also updated using the principle of associativity, which implies