基于BESO的发动机托架臂拓扑优化

S. Srivastava, S. Salunkhe, S. Pande
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引用次数: 0

摘要

发动机支架是发动机最关键的部件之一,用于在车辆中安装和支撑发动机。今天,汽车工业需要轻量化的部件,这将减少汽车的整体重量,当安装到车辆。拓扑优化是一种对零件表面进行优化以达到减轻重量所需形状的技术。通过优化细节表面的材料,减轻了重量。本文所做的工作是拓扑优化在发动机托架臂表面的应用。然后利用实际条件对优化后的模型进行了计算验证。采用双向进化结构优化技术进行拓扑优化。利用BESO法对材料进行了优化,并与原构件进行了权重比较。利用MATLAB编写了一种新的算法。采用von Mises强度作为BESO方法优化的关键参数,考虑了灵敏度比。将优化后的支架模型与部件轮毂进行装配,并在标准条件下对装配过程进行仿真验证。使用拓扑优化对减重进行了比较。
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Topology optimization of engine bracket arm using BESO
An engine bracket is one of the most critical components of the engine used for mounting and supporting the engine in the vehicles. Today, the automobile industry requires lightweight components, which will reduce the car's overall weight when fitted into the vehicle. Topology optimization is a technique with the help of which the surface of a component is optimized to get the required shape for having reduced weight. The weight is reduced by optimizing the material on the surface of the details. In this paper, the work done is the application of topology optimization on the surface of the engine bracket arm. Then the optimized model is tested computationally using realistic conditions. Bi-directional evolutionary structural optimization is used as a technique for topology optimization. With the help of the BESO method, the material optimization is done, and then the weights are compared with the original component. A new algorithm is developed using MATLAB codes. The sensitivity ratio is considered using the von Mises strength as a critical parameter for the BESO method for optimization. The optimized bracket model is then assembled with the hub of the component, and then the assembly is simulated for verification using standard conditions. A comparison of weight reduction is there using topology optimization.
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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
19
审稿时长
16 weeks
期刊介绍: The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).
期刊最新文献
A novel approach for noise prediction using Neural network trained with an efficient optimization technique Topology optimization of engine bracket arm using BESO Integration of digital imagery for topology optimization A comparative analysis of the fuzzy and intuitionistic fuzzy environment for group and individual equipment replacement Models in order to achieve the optimized results Real-time fast learning hardware implementation
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