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The stacking sequence optimisation of a filament wound composite bicycle frame using the data-driven evolutionary algorithm EvoDN2

This work focusses on identifying the optimal stacking sequence for composite tubes in mountain bike frames using a data-driven model combined with evolutionary algorithms. The objective is to find a frame that is sufficiently stiff while meeting the requirements of weight, strength, and minimum tub...

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Published in:Philosophical magazine letters 2024-12, Vol.104 (1)
Main Authors: Malá, Anna, Padovec, Zdeněk, Mareš, Tomáš, Chakraborti, Nirupam
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Mareš, Tomáš
Chakraborti, Nirupam
description This work focusses on identifying the optimal stacking sequence for composite tubes in mountain bike frames using a data-driven model combined with evolutionary algorithms. The objective is to find a frame that is sufficiently stiff while meeting the requirements of weight, strength, and minimum tube wall thickness. The decision variables are the ply winding angles and the ply thicknesses of each tube. The study performs designs for two load cases - Starting and Uphill - and explores two types of winding: the gradual winding of individual layers (1ply) and the winding of layers between predefined inner and outer layers with variable thicknesses (TW). Additionally, the design process is applied to frames made of isotropic materials, such as steel, aluminium, and titanium, using the same methodology to allow for comparison of results. The article demonstrates the successful application of this methodology to common sports equipment, suggesting its potential for beneficial use in other common composite frame structures.
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source Taylor and Francis Science and Technology Collection
subjects bicycle
Bicycles
composite
data-driven
evolutionary
Evolutionary algorithms
Filament winding
Frame design
Frame structures
Genetic algorithms
Isotropic material
optimisation
Sporting goods
Stacking sequence (composite materials)
Steel frames
Tubes
Wall thickness
Winding
title The stacking sequence optimisation of a filament wound composite bicycle frame using the data-driven evolutionary algorithm EvoDN2
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