Altair India

HYPERWORKS FOR STUDENTS

Projects using HyperStudy

Sensitivity To Support Stiffness





Areas covered:

Construction of an FE Model for thermo-mechanical analysis.

Creation of a Template for Study-construction.

Design Of Experiment.

Design Space Exploration.

Description of the Problem: A design proposal has been received for a subassembly, and the task is to simulate its performance. The screw-shaft subassembly, which fits into a housing, is manufactured to very close tolerances. The dimensional accuracy is measured in 10s of microns. A standard Finite Element approach is to analyze the component assuming the surrounding housing is rigid. How reasonable is this assumption? Can we gain an insight into the impact of the housing's flexibility, without modeling the housing itself? If the behavior of the shaft and plugs is not sensitive to the stiffness of the supports, then the analyst can repose a high degree of confidence in the FE model. If this were not the case, it would be prudent to suggest that the analysis would be more reliable if the housing too were supplied for analysis.

Multi-objective Optimization - Battery Tray





Areas covered:

Construction of FE Models for static and normal-modes analyses.

Creation of a Template for Study-construction.

Design Of Experiment.

Trade-Off Study.

Description of the Problem: A design for the tray to hold the battery of an automobile has been proposed. The basis for the model is a study of earlier designs. The designer's have another query too: can they reduce the maximum deformation as much as possible, while raising the minimum frequency as much as possible? In other words, both the responses - maximum-deformation and base-frequency - are to be treated as objectives. One should be minimized while the other should be maximized. We use two different finite element models - one for static analysis, under the dead-weight of the batteries and the other for the normal-modes calculation. A numerical experiment is constructed to sample the design space, and an approximation built from the results of the DOE. A trade-off study is then used to choose the optimal combination of the design variables for the two objectives.

Next Page.