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Technical Paper

Finite Element Model Generator for Assessment and Optimization of Crankshaft Design

1991-11-01
912494
This paper describes the concept of model generator for structural assessment of crankshaft design, its application and methodology in the design optimisation of crankshaft. The model generator saves to a great extent the time required for iterative design process. It is developed on the ANSYS general purpose finite element programme and makes use of symmetry and repeatability of crankshaft geometry. This model generator software uses 12 parameters which include fillet radius, web thickness and overlap as design iteration parameters. Using these parametric studies of the crankshaft have been carried out. Two stage analysis has been used for computation of fillet stresses. In the first stage 3 dimensional coarse model is analysed to compute stresses and displacements. Next stage uses 3D zoomed model of the critical fillet zone. Zoomed model is refined to give maximum possible accuracy of computation using submodelling techniques.
Technical Paper

Studies on Some Modelling Aspects in the Finite Element Analysis of Small Gasoline Engine Components

1991-11-01
911271
The paper describes some modelling aspects in finite element analysis of a small four stroke air cooled gasoline engine components subjected to thermal and mechanical loading. The authors have developed parametric model generator for connecting rod using isoparametric element. By discribing parameters numericaly the connecting rod finite element mesh is generated very quickly. It has a provision of inclusion of oil hole model also, which itself is parametric in nature. Authors have developed methodology based on ANSYS Finite element package to introduce inertia loading on connecting rod model. The concept of model generator has been extended for analysis of crankshaft for small gasoline engine. Based on results authors suggest that parametric software must have provision for local refining in finite element formulation so that using submodelling techniques stresses can be predicted accurately after convergence of results.
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