【導(dǎo)讀】速，模具行業(yè)產(chǎn)業(yè)結(jié)構(gòu)也有了較大的改善，已經(jīng)成為國民經(jīng)濟(jì)的基礎(chǔ)工業(yè)之一。其發(fā)展趨勢，對于本畢業(yè)設(shè)計無疑具有很大的借鑒作用。我國只有30%左右。國內(nèi)模具制造周期比國外長2-4倍，模具的質(zhì)量穩(wěn)定性也較差，總體水平與國外比尚有較大差距。而塑料模的主要應(yīng)用領(lǐng)域：汽車摩托車行業(yè)，家。而現(xiàn)代模具不同，它不僅形狀與結(jié)構(gòu)十分復(fù)雜，而且技術(shù)。展，采用先進(jìn)制造技術(shù)，才能達(dá)到它的技術(shù)要求。當(dāng)前，整個工業(yè)生產(chǎn)的發(fā)展特點(diǎn)。是產(chǎn)品品種多、更新快、市場競爭劇烈。為了適應(yīng)市場對模具制造的短交貨期，高。日益增多高擋次模具。進(jìn)一步增多氣輔模具及高壓注射成型模具。成本均有著重要意義。術(shù)也日趨成熟，引起工業(yè)界的普遍關(guān)注。此外，在粉末冶金和塑料加工方面，金屬粉末鍛造成形，金屬粉末超塑性。冷卻制品而且不影響其它零件的安排。本次畢業(yè)設(shè)計的水槽設(shè)計和水槽模具的設(shè)計部分，我都是在UG軟件里完成的。選擇基礎(chǔ)特征相當(dāng)于準(zhǔn)備一個毛坯。推薦使用以下特征作為基礎(chǔ)特征：

　　

【正文】 featured brake rotor is illustrated in Fig. 1(b). While the finite element analysis of the fullfeatured model in Fig. 1(a) required over 150,000 degrees of freedom, the defeatured model 33 in Fig. 1(b) required 25,000 DOF, leading to a significant putational speedup. Fig. 1. (a) A brake rotor and (b) its defeatured version. Besides an improvement in speed, there is usually an increased level of automation in that it is easier to automate finite element mesh generation of a defeatured ponent [1,2]. Memory requirements also decrease, while condition number of the discretized system improves。the latter plays an important role in iterative linear system solvers [3]. Defeaturing, however, invariably results in an unknown ‘perturbation’ of the underlying field. The perturbation may be ‘small and localized’ or ‘large and spread out’, depending on various factors. For example, in a thermal problem, suppose one deletes a feature。 the perturbation is localized provided: (1) the heat flux on the boundary of the feature is zero, and (2) no new heat sources are created when the feature is suppressed。 see [4] for exceptions to these rules. Physical features that exhibit this property are called selfequilibrating [5]. Similarly results exist for structural problems. From a defeaturing perspective, such selfequilibrating features are not of concern if the features are far from the region of interest. However, one must be cautious if the features are close to the regions of interest. On the other hand, nonselfequilibrating features are of even higher concern. Their suppression can theoretically be felt everywhere within the system, and can thus pose a major challenge during analysis. Currently, there are no systematic procedures for estimating the potential impact of defeaturing in either of the above two cases. One must rely on engineering judgment and experience. In this paper, we develop a theory to estimate the impact of defeaturing on engineering analysis in an automated fashion. In particular, we focus on problems where the features being suppressed are cutouts of arbitrary （ 560 450 279）塑料水槽及其注塑模具設(shè)計 34 shape and size within the body. Two mathematical concepts, namely adjoint formulation and monotonicity analysis, are bined into a unifying theory to address both selfequilibrating and nonselfequilibrating features. Numerical examples involving 2nd order scalar partial differential equations are provided to substantiate the theory. The remainder of the paper is anized as follows. In Section 2, we summarize prior work on defeaturing. In Section 3, we address defeaturing induced analysis errors, and discuss the proposed methodology. Results from numerical experiments are provided in Section 4. A byproduct of the proposed work on rapid design exploration is discussed in Section 5. Finally, conclusions and open issues are discussed in Section 6. 2. Prior work The defeaturing process can be categorized into three phases: Identification: what features should one suppress? Suppression: how does one suppress the feature in an automated and geometrically consistent manner? Analysis: what is the consequence of the suppression? The first phase has received extensive attention in the literature. For example, the size and relative location of a feature is often used as a metric in identification [2,6]. In addition, physically meaningful ‘mechanical criterion/heuristics’ have also been proposed for identifying such features [1,7]. To automate the geometric process of defeaturing, the authors in [8] develop a set of geometric rules, while the authors in [9] use face clustering strategy and the authors in [10] use plane splitting techniques. Indeed, automated geometric defeaturing has matured to a point where mercial defeaturing /healing packages are now available [11,12]. But note that these mercial packages provide a purely geometric solution to the problem... they must be used with care since there are no guarantees on the ensuing analysis errors. In addition, open geometric issues remain and are being addressed [13]. The focus of this paper is on the third phase, namely, post defeaturing analysis, ., to develop a systematic methodology through which defeaturing induced errors can be puted. We should mention here the related work on reanalysis. The objective of reanalysis is to swiftly pute the response of a modified system by using previous simulations. One of the key developments in reanalysis is the famous Sherman– Morrison and Woodbury formula [14] that allows the swift putation of the inverse of a perturbed stiffness matrix。 other variations of this based on Krylov subspace techniques have been proposed [15– 17]. Such reanalysis techniques are particularly effective when the objective is to analyze two designs that share similar mesh structure, and stiffness matrices. Unfortunately, the process of 幾何分析 can result in a dramatic change in 35 the mesh structure and stiffness matrices, making reanalysis techniques less relevant. A related problem that is not addressed in this paper is that of local– global analysis [13], where the objective is to solve the local field around the defeatured region after the global defeatured problem has been solved. An implicit assumption in local– global analysis is that the feature being suppressed is selfequilibrating. 3. Proposed methodology . Problem statement We restrict our attention in this paper to engineering problems involving a scalar field u governed by a generic 2nd order partial differential equation (PDE): .).( fauuc ????? A large class of engineering problems, such as thermal, fluid and magostatic problems, may be reduced to the above form. As an illustrative example, consider a thermal problem over the 2D heatblock assembl