A fascinating study on AWES optimization
For me, the killer takeaway is
The tool has also been used to optimize system parameters, leading to the conclusion that the proper size for an AWE system is the largest size where mass is scaling with wing area or the smallest size where mass is scaling faster than wing area.
Puts me in mind of dymaxion
The Dymaxion car was designed by American inventor Buckminster Fuller during the Great Depression and featured prominently at Chicago’s 1933/1934 World’s Fair. … Fuller associated the word Dymaxion with much of his work, a portmanteau of the words dynamic, maximum, and tension, to summarize his goal to do more with less.
The study begs the question
How do you account for both of those optimisations at the same time?
Arrayed multiple small units all working as 1 large unit.