Back to studying scaling that MaxL and I had moved into network fractal scaling theory, building on Culp Thickness Factor.
[Sommerfeld 2022] neglected AR as a scaling factor by assuming AR10 for all its rigid wing cases.
Fractal Network Scaling helpfully introduces negative scaling exponents to AWES Scaling Theory.
Allometric Laws of Biological Systems inform complex AWES design.
Phase Transitions as Critical Phenomena bound Power Law distrubutions.
Kite scaling phase transitions- polymer molecule, fiber, strand, thread, cloth, panel, sail, network.
Scale-free properties are inherently scalable in linear ranges.
L System production rules and Iterated Function Systems IFS
Power Laws in the linear regions of Normal Distributions.
Sierpiński Triangle and Carpet are usefully kite-like geometry-topology
Self Affine Fractal Tilings for kites
Kleiber’s Law (3/4 Scaling Power Law) applies to kite scaling
One need only calculate the thickness factor between soft and rigid and see what numbers result.
Dave Culp 20yrs ago identified thickness as a critical scaling dimension
In fact, the exponent calculator matches Kiteship real kite mass-scaling data
SS AR is not an a-priori factor “known before scaling” in a numeric model.
If soft kite MSE was 2 or more, Peter Lynn’s wisdom would be wrong. He puts it close to 1.
Mass only exists in 3 dimensions, and thickness is just as vital as span and chord.
1.3 was my calculated result, so I stand by it.
We patiently await third party resolution of objections.
Now happily pondering the Kite Thickness dimension.
In fact, the exponent calculator matches Kiteship real kite mass-scaling data.
SS AR is not an a-priori factor “known before scaling” in a numeric model.
If soft kite MSE was 2 or more, Peter Lynn’s wisdom would be wrong. He puts it close to 1
Its JAL that supplies AR1.5 for SS power kites of NPW and OL proportions
[Sommerfeld] does not try to calculate MSE based on low AR soft kites.
[Sommerfeld et al, 2022] simply assumes AR10 for all the rigid wings.
SS kites like the OL and NPW are about AR1.5
When lower AR is accounted for, MSE for SS kites of 1.3 is good approximation that fits Kiteship data and Lynn on soft kite scaling.
Which “model”? Chord and AR of of SS kites are definitely not modeled.
Ampyx formula does NOT calculate from chord or AR data, but “wing span”
“Aircraft mass m and inertia J are scaled relative to the Ampyx AP2 reference model (Licitra, 2018; Malz et al., 2019; Ampyx, 2020) according to simplified geometric scaling laws relative to wing span bscaled (Eqs. 6 and 7):”
I used the calculator after rechecked kiteship mass-scaling of real kites. This looks right to me-
No, chord is neglected in the Ampyx model because AR >0
MSE of 1.3-1.5 fits the data of KiteShip kite mass-scale and Peter Lynn’s copied soft-kite scaling comment.
Ampyx treated Wing Span as a single Length dimension, while Area is clearly a squared L dimension. In fact, all Wing Spans have a Chord Dimension, or Ampyx’s calculation would not work even for skinny wings.
WS always has A, via >0 AR.
That’s a hidden exponent factor.
kPower has discussed Scaling MSE with Dr Langbein exactly as shared.
MSE ~1.5 for SS scaling as calculated by Area.
[Sommerfeld et al 2022] calculates scaling from WS.
WS is not simple 1D L, but 2D (WS L x Chord L).
kPower has always used A (L-squared) of a low AR kite.
JAL estimate was quite close at MSE 1.3 for SS Wing.
MSE 1.5 is a calculated match to Kiteship OL mass data.
Thanks to Rod for adding Network Scaling in the mix.
Accounting for thickness dimension of real wings, he will not be simply stating “definitely wrong”, but expanding the scientific formulation of MSE to better fit Kiteship data and Peter Lynn expertise.
Kite cloth is as thin as paper, but a large rigid wing is thick as a dictionary.
KiteLab Groups worked out these mass-scaling factors on the old Forum.
They contribute to the amazing MSE of ~1.3, as a function of thinness.
