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Size Optimization


Size optimization is a different type of optimization which relies on the optimization of material or mesh parameters to improve, maximize or minimize, specified design criteria like stresses or displacements.

For example, the thickness of plate elements can be automatically optimized to minimize the displacement in certain areas of the model through local sensors.

Design sampling is created automatically according to several methods (Latin hypercube design, Taguchi orthogonal array, full factorial design, central composite, parametric study) and results are auto correlated together to generate optimized parameter combinations.

How it works

Demonstration of Size optimization in midas NFX

Result Types

In complex analysis cases, it is difficult to determine the best thickness of plate elements or needed material data by experience.

Size optimization is useful to solve this problem efficiently by providing the best size in function of the defined design criteria (stress for example).

Autocorrelation of optimized parameters also provide the parameters that have the most influence on the actual design.

Application Examples

Size Optimization has been used to determine the appropriate size of 2D plate mesh elements of an airplane셲 wing according to linear static and modal analysis.

Various methods (FFD, CCD, OA, LHD) & 1D parameter study correlation between design variable & response analysis makes size optimization an efficient tool for such concrete problem.

Size optimization models according to Kriging model, Polynomial Regression model have been used and  midas NFX provides  powerful 2D/3D Graphic tools for approximate model analysis.


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