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Structure · dataset · 2023

Results from the paper: A matter of course: Generating optimal manufacturing instructions from a structural layup plan of a wind turbine blade

Listed in Teesside University Research Data Repository

Description

This is the complete results of the journal paper "A matter of course: Generating optimal manufacturing instructions from a structural layup plan of a wind turbine blade" [insert reference when published] which were created by the program KinDrapeMAX (doi.org/10.5281/zenodo.7525530). Please see the paper for details. Each folder contains the output from an optimization run.

The folder name begins with the creation date followed by the following sequence separated by underscores: - Number of layers optimized, i.e. "1layer", "5layer" or "30layer" - (For the multi-layer models, an indication if the sequential layer formulation was used, i.e. "seq") - The optimization criteria used, i.e. "ShearAng" for shear angles, "AngDev" for UD fiber angle deviations, "TrimArea" for trim-off area or "ShearAng+AngDev+TrimArea" / "allcrit" for all three criteria. - The seed used for the random number generator, i.e. "seed0", "seed1" or "seed2". - Indication of the result with the lowest objective function value from the runs with different seeds, i.e. "lowestobj".

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Each folder contains the following files: - ShearFig as .png and MATLAB .fig files: draped courses colored based on shear angle. - FibDevFig as .png and MATLAB .fig files: draped courses colored based on fiber angle deviation. - StackFig as .png and MATLAB .fig files: Flattened stack plot at the root end. - A log file from the command window with optimization progress and evaluation of the criteria and design. - The input file to the program, i.e. a MATLAB script (.m). - Workspace variables stored in the .mat file In addition, the single-layer models with the lowest objective function value has a sub folder with an Abaqus input file with draped fiber angles and the corresponding results.

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Teesside University Research Data Repositoryoai:data.mendeley.com/3mh3ghrz67.18 h agoJSON v1
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