Multi-dimensional maximization method

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SUMMARY

The discussion focuses on optimizing the oswald efficiency factor in an expanded lifting-line problem using interpolation techniques. The user seeks a method to identify the maximum efficiency factor from a dataset of taper and twist combinations, emphasizing that the data does not fit linear models. A recommended solution involves utilizing MATLAB functions to interpolate the data onto a finer grid, enabling the extraction of the maximum efficiency factor from the resulting array of values.

PREREQUISITES
  • Understanding of the lifting-line theory
  • Familiarity with MATLAB programming
  • Knowledge of interpolation methods
  • Basic concepts of efficiency factors in aerodynamics
NEXT STEPS
  • Explore MATLAB's griddata function for data interpolation
  • Research non-linear optimization techniques applicable to aerodynamic efficiency
  • Learn about multi-dimensional optimization algorithms
  • Investigate curve fitting methods for non-linear datasets
USEFUL FOR

Aerodynamic engineers, researchers in fluid dynamics, and anyone involved in optimizing performance factors in aerospace applications will benefit from this discussion.

Ignea_unda
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I'm currently working on an expanded lifting-line problem. I've got plenty of data, but I need to find the maximum oswald efficiency factor. I've got a table of data of efficiency factors for taper and twist combinations and I need to interpolate to find the maximum in 2 directions. I don't know what the maximum is, nor do I know its location. The curve fits to the data I are not linear. Can anyone suggest a scheme? Bonus points for one that is simple (I'll give you extra special thank you or something like that on here!)
 
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There are functions in MATLAB that allow you to interpolate you data onto an arbitrarily small grid. If you did this with your data you would then have an array of values for the efficiency factor and then you could just pick off the max.
 

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