Altair India

HYPERWORKS FOR STUDENTS

Projects using HyperStudy

Optimization With Load-Redistribution





Areas covered:

Construction of an FE Model with gravity loads.

Design Of Experiment.

Construction of an Approximate Model.

Optimization with change in applied loads.

Description of the Problem: A housing, used to hold an actuator, is the subject of this optimization study. The design assumed that the "internal" weights - of the actuator electronics, etc. - could be taken as "given data". The designers, however, have another query. Since some leeway is available in designing and mounting the "internals" themselves, should they redistribute these weights at the same mounting points? Will it reduce stress? Optimization techniques such as topology optimization cannot change the boundary conditions - loads and restraints. In this case, we explicitly need to study the effect of changing the loads. Going one step further, we need to suggest the best distribution. That is, we need to suggest the "optimum" distribution.

Geneva Mechanism - Effect Of Friction





Areas covered:

Use of a Multi-Body-Dynamics (MBD) Model to simulate a mechanism.

Design Of Experiment.

Construction of an Approximation.

Use of Monte Carlo methods for stochastic analysis.

Description of the Problem: A Geneva Mechanism is a widely used indexing mechanism. It relies on friction between the crank and the slotted-disk for the indexing. Friction is hard to pin down perfectly. At best, we can estimate the range between which the friction coefficient can vary. Further complicating the issue, there is more than one "kind" of friction coefficient the designer has to grapple with. We have static friction at the initiation of motion, dynamic friction when the mechanism is running, and "stiction" or stick-friction, which can be a nightmare for a designer. With this, what is the reliability of the design? There are two areas the designer is interested in. First, the forces on the crank during motion. If these can be evaluated, a stress analysis can be carried out to ensure that the crank is safe for all ranges of expected forces. That is, at the best and worst case friction-coefficient scenarios. Second, which ranges of coefficients are the worst and best case scenarios? We perform a Monte Carlo study to investigate the behavior of the mechanism given the designer's interest.

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