Model Analysis of a Diesel Engine Cylinder Block using HEXA8 Finite Elements - Analysis and Experiment The University of Michigan

Format:

Conference/Event

Author/Creator:

Lee, Seungkuh, author.

Conference Name:

SAE International Truck and Bus Meeting and Exposition (1988-11-07 : Indianapolis, Indiana, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1988

Summary:

Analytical and experimental investigations of a diesel engine cylinder block are performed. An attempt is made to reduce modeling and analysis costs in the design process of an engine. Traditionally, the engine has been modeled using either 8-node or 20-node solid elements for stress and thermal analyses and modeled using 4-node plate and shell elements for the dynamic analysis. In this paper, a simpler finite element modeling technique using only 8 node solid elements for both dynamic and static analyses is presented. Based on this integrated modeling technique of finite elements, eigenvalues are calculated and compared with the experimental data obtained from modal testing of an actual engine cylinder block.For problems, in which out-of-plane motion is of prime importance, like cylinder block vibration, there have been difficulties in obtaining an accurate solution of the eigenvalue problem due to the over-estimation of bending stiffness if three-dimensional 8-node solid elements are used. To improve the computational efficiency as well as accuracy for bending dominated problems, the newly developed directional reduced integration method with hourglass control is introduced in the present work. According to the eigenvalue analysis of an engine, the directional reduced integration method with hourglass control provides fairly good agreement with the experimental data obtained from modal testing.Although the directional reduced integration with hourglass control does provide a fairly good finite element approximation, it is impossible to take out all of the approximation errors. To minimize these of error, an adaptive method is presented for the dynamic problem

Notes:

Vendor supplied data

Publisher Number:

881853

Access Restriction:

Restricted for use by site license