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Optimization with PERMAS

Shaping of a sheet metal
Rolling, blanking, and beading combined in one optimization.

PERMAS offers the following modules for optimization:

PERMAS-OPT - Design Optimization
This module automatically optimizes structures with respect to sizing parameters as well as the shape of the component. Results from a static analysis, an Eigenvalue Analysis, a modal frequency response or inertia relief can be taken into account. Arbitrary conditions can be formulated as the objective function.
PERMAS-TOPO - Layout Optimization
Offers fully integrated topology optimization strategies for the concept development phase. The design space may be defined with respect to a variety of different aspects. Results from static and dynamic as well as contact analyses may be used for optimization. Special constraints are available for casting. A variety of algorithms for smoothing and reduction of results simplify the further processing of the optimized model.
PERMAS-OPT + PERMAS-TOPO - Multi-Modal Optimization (MMO)
A multi-modal optimization combines parametric optimization tasks of topology, size, and shape. Results from a static analysis, an Eigenvalue Analysis, a modal frequency response or inertia relief can be taken into account. Arbitrary conditions can be formulated as the objective function.
PERMAS-RA - Reliability Analysis
The influence of tolerances and scattering parameters from production on the analysis results can be vital, when limits for certain result values are exceeded. Relaibility analysis uses stochastic methods in the FE analysis to get information about keeping the results within the limits. The input consists of distribution functions for the uncertain parameters and the limit values of selected analysis results. The output contains the probability of violating the limits and the influence of the uncertain parameters on this violation.
PERMAS-OPT + PERMAS-RA - Robust Design Optimization (RDO)
A Robust Design Optimization is a combination of optimization and reliability analysis. An additional constraint condition is added to the optimization, which restricts the probability of violating given limit values for selected results. By this way, the optimization can take into account reliability results and one gets a robust optimum, i.e. an optimum which includes robustness conditions.

For more information download the flyer below:

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