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PERMAS-MLDR Eigenmodes with MLDR

The calculation of eigenvalues with modules DEV and DEVX is complemented by another method. This method can also be used for the calculation of coupled fluid-structure modes.

The application of this method is advantageous in those cases where the elapsed run times are mainly determined by I/O like for large models with a high number of modes to be calculated. The larger the models and the larger the number of modes, the higher is the benefit in elapsed run time through the application of the MLDR method.

This benefit in elapsed run time can be essentially raised more, if there is a subsequent dynamic response analysis calculating the response behavior just at a small number of nodes. Then, the generation of the global mode shapes can be saved resulting in considerable computing time savings.

The MLDR method is based on an automatic partitioning of the model where each part does not exceed a preset quantity. In addition, the coupling between the parts has to be as low as possible. These parts are then groupwise combined as substructures using dynamic condensation and module DEVX. This procedure is hierarchically carried on until the complete model is represented in one component. In this component only a small number of nodes and elements remain and the dynamic behavior is mainly determined by the modes and frequencies taken over from the substructrues and combined following the rules of dynamic condensation. Due to this procedure the method's name is Multi-Level Dynamic Reduction (MLDR)

If certain nodes and elements should be present in the main component, the user can specify them explicitly. So, selected model parts can be pushed to the main component and any subsequent processing of the modes is rather beneficial due to the small size of the remaining matrix system. In this way, dynamic simulation, coupling to MBS, optimization of the remaining system, or the consideration of nonlinearities can be performed with very low computing times.

Additional reductions of computing time are possible using multi-processor systems, because the method has been fully parallelized. Altogether, the use of MLDR is a big step forward to more productivity and allows, for example, dynamic simulation in a higher frequency range as in the past together with a possible increase in model size for more accurate results.

Improved performance with MLDR

Comparison of elapsed run times for Subspace Iteration (red curve) and MLDR (blue curve) with increasing number of modes

157412 Nodes
164301 Elements(QUAD4)
944472 Unknowns