1、 1 外文原文 A Discussion on Modern Design Optimization The integration of optimization techniques with Finite Element Analysis(FEA) and CAD is having pronounced effects on the product design process.This integration has the power to reduce design costs by shifting the burden from the engineer to the com
2、puter.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 meshers and analysis processors.This combination allo
3、ws for shape optimizations on CAD parts or assemblies under a wide range of physical scenarios including mechanical and thermal effects. Modern optimization methods perform shape optimizations on components generated within a choice of CAD packages.Ideally,there is seamless data exchange via direct
4、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 the approach taken by ALGOR,the design optimization proce
5、ss 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 appropriate for the design criterion,and,if necessary without any hu
6、men intervention,the CAD geometry is updated.Care is taken such that the FEA model is also updated using the principle of associativity,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 res
7、ults are again compared with the design criterion.This process is repeated until the design criterion is satisfied.Fig.7.1 shows the procedure of shape optimization. Introduction The typical design process involves iterations during which the geometry of the part(s) is altered.In general,each iterat
8、ion also involves some from of analysis 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 2 behind design optimization applications is to relieve
9、 the engineer of the laborious 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. Fig.7.1 Procedure of shape Optimization This is certainly not the case because any
10、 design optimization application cannot infer what 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 th
11、is tool is gauged by its ability to efficiently identify the optimum. Design optimization applications tend to be numerically because they must still perform the geometrical and analysis iterations.Fortunately,most design optimization problems can be cast as a mathematical optimization problem for w
12、hich there exist 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 meth
13、ods,but also a suggestion as to which appropriate for his or her design problem. In this paper,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 geometric quantities,such as the thickness of a particular part.The design of Initial Design Preprocessing FE Preprocessor Optimization Preprocessor Optimization Loop FE Solver Optimization Module Optimization design
