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毕业设计外文翻译题 目 曲轴的加工工艺及夹具设计 学 院 航海学院 专 业 轮机工程 学 生 佟宝诚 学 号 10960123 指导教师 彭中波 重庆交通大学 2021年Proceedings of IMECE20212021 ASME International Mechanical Engineering Congress and ExpositionOctober 31-November 6, 2021, Boston, Massachusetts, USAIMECE2021-67447MULTI-OBJECTIVE SYSTEM OPTIMIZATION OF ENGINE CRANKSHAFTS USINGAN INTEGRATION APPROACHAlbert Albers/IPEK Institute of Product DevelopmentUniversity of Karlsruhe GermanyNoel Leon/CIDyT Center for Innovation andDesignMonterrey Institute of Technology,MexicoHumberto Aguayo/CIDyT Center forInnovation and Design, Monterrey Institute ofTechnology, MexicoThomas Maier/IPEK Institute of Product Development University of Karlsruhe GermanyABSTRACTThe ever increasing computer capabilities allow faster analysis in the field of Computer Aided Design and Engineering (CAD & CAE). CAD and CAE systems are currently used in Parametric and Structural Optimization to find optimal topologies and shapes of given parts under certain conditions. This paper describes a general strategy to optimize the balance of a crankshaft, using CAD and CAE software integrated with Genetic Algorithms (GAs) via programming in Java. An introduction to the groundings of this strategy is made among different tools used for its implementation. The analyzed crankshaft is modeled in commercial parametric 3D CAD software. CAD is used for evaluating the fitness function (the balance) and to make geometric modifications. CAE is used for evaluating dynamic restrictions (the eigenfrequencies). A Java interface is programmed to link the CAD model to the CAE software and to the genetic algorithms. In order to make geometry modifications to our case study, it was decided to substitute the profile of the counterweights with splines from its original “arc-shaped design. The variation of the splined profile via control points results in an imbalanceresponse. The imbalance of the crankshaft was defined as an independent objective function during a first approach, followed by a Pareto optimization of the imbalance from both correction planes, plus the curvature of the profile of the counterweights as restrictions for material flow during forging. The natural frequency was considered as an additional objective function during a second approach. The optimization process runs fully automated and the CAD program is on hold waiting for new set of parameters to receive and process, saving computing time, which is otherwise lost during the repeated startup of the cad application.The development of engine crankshafts is subject to a continuous evolution due to market pressures. Fast market developments push the increase of power, fuel economy, durability and reliability of combustion engines, and calls for reduction of size, weight, vibration and noise, cost, etc. Optimized engine components are therefore required if competitive designs must be attained. Due to this conditions, crankshafts, which are one of the most analyzed engine components, are required to be improved 1. One of these improvements relies on material composition, as companies that develop combustion engines have expressed their intentions to change actual nodular steel crankshafts from their engines, to forged steel crankshafts. Another important direction of improvement is the optimization of its geometrical characteristics. In particular for this paper is the imbalance, first Eigen-frequency and the forge-ability. Analytical tools can greatly enhance the understanding of the physical phenomena associated with the mentioned characteristics and can be automated to do programmed tasks that an engineer requires for optimizing a design 2.The goals of the present research are: to construct a strategy for the development of engine crankshafts based on the integration of: CAD and CAE (Computer Aided Design &Engineering) software to model and evaluate functionalparameters, Genetic Algorithms as the optimization method, the use of splines for shape construction and Java language programming for integration of the systems. Structural optimization under these conditions allows computers to work in an automated environment and the designer to speed up and improve the traditional design process. The specific requirements to be satisfied by the strategies are:Approach the target of imbalance of a V6 engine crankshaft, without affecting either its weight or itsmanufacturability.Develop interface programming that allows integration of the different software: CAD for modeling and geometric evaluations, CAE for simulation analysis and evaluation ,Genetic Algorithms for optimization and search for alternatives .Obtain new design concepts for the shape of the counterweights that help the designer to develop a better crankshaft in terms of functionality more rapidly
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