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Puck Hyper local - a Dexter Monroe llc Product · Prompt Air

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  Welcome to the Deep Dive. So today we're getting
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  into something that is a pretty fundamental shift
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  in logistics. It really is. For almost a century,
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  right, moving packages was all about discrete
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  math. You know, nodes and edges on a graph. The
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  class that transportation brought. Exactly. But
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  that model just completely collapses when you're
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  talking about, say, Puck's drone fleet in Milwaukee's
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  historic third war. Oh, it's a combinatorial
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  explosion. You can't. The old models for trucks
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  and set routes, they just, they break down. You
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  have a massive swarm in continuous airspace.
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  So it stops being a math problem. It stops behaving
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  like a series of individual calculations and
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  starts behaving like a physical substance, like
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  a fluid. So they threw out the old formulas,
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  things like the Bobula -Forsyth calculation.
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  Yeah, that's just for optimizing a single object,
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  like a bullet. Here they turn to the Navier -Stokes
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  equations. To create what they're calling laminar
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  logistics. Right. And what's so fascinating is
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  they stopped trying to optimize the drone itself
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  and started optimizing the flow of the whole
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  fleet. The city is now mapped as a, well, a porous
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  medium. Okay, let's unpack that central analogy
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  a little bit. When you say pressure, you're not
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  talking about air pressure. No, not at all. Think
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  of it as logistical potential or demand urgency.
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  So the Milwaukee public market, which is always
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  busy, that's the high pressure source. It's the
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  perpetual source, yes. And a customer order,
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  say, from the Corcoran lofts, that instantly
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  becomes a low pressure sink. The drone fleet,
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  the fluid, just follows the steepest pressure
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  drop. It's physics. And every fluid has friction.
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  Exactly. Which here we call viscosity. Viscosity
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  maps directly to the energy cost of complexity.
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  So not just physical friction. No, it's operational
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  friction. You lose energy from, say, Sharp, inefficient
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  turns, those are high -viscosity movements, but
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  also from regulatory constraints. Wait, regulatory
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  friction? How does an FAA rule act like molasses?
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  Okay, so take the FAA's Part 107 rule visual
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  line of sight. An operator has to be able to
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  see the drone. Right. We can assign areas where
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  that's tricky, like near the Italian Community
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  Center during a big event, an extremely high
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  viscosity value. The solver's job is to minimize
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  that viscous dissipation. So the path it calculates
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  is naturally smooth, efficient, and compliant.
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  All by itself. All by design. No need to pre
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  -program no -fly zones in the traditional sense.
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  I love that. And it's not just drones in the
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  air. This is a hybrid fleet, right? Multi -phase
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  flow. That's the term. Drones are the low -friction
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  air fluid, the free stream. The ground droids
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  are the ground fluid stuck in the high -friction
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  boundary layer of the street. And they can switch
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  between them. Yes, through the condensation maneuver.
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  If the air viscosity gets too high, maybe a sudden
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  gust of wind off Lake Michigan or restricted
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  airspace, a drone can land on a droid at, say,
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  Catalano Square. It transfers the package. So
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  the mass moves from the air phase to the ground
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  phase. And completes the last mile, even when
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  the air is basically prohibitive. It's incredibly
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  resilient. Which brings up the big question,
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  right? If it's all based on physics, how does
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  it handle, well... chaos what happens when a
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  fire truck just you know blocks broadway yeah
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  that's the beautiful part a traditional system
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  would frantically try to recalculate thousands
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  of individual paths it would be a mess a huge
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  processing lag for sure but the fluid model it
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  handles turbulence instinctively the blockage
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  is like a wall appearing in the flow Physics
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  dictates that a pressure wave instantly propagates
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  backward through the fluid. So the drones react
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  before they even get there. They slow down and
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  divert organically based purely on the change
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  in flow dynamics. It's true self -organization.
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  And what about that FAA line of sight rule we
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  talked about? How does it make a drone physically
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  stop? That's handled by what's called a visibility
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  scalar field. As a drone nears an area where
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  that visibility factor drops to zero, the effective
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  viscosity in the calculation approaches infinity.
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  The fluid just freezes. It literally freezes.
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  Flow into that non -compliant area stops. It's
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  a physics -based enforcement mechanism. So the
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  real genius here, it seems, is the shift in perspective.
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  You're not tracking individual particles anymore,
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  that Lagrangian view. Exactly. You stop caring
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  about the particle and start managing the total
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  flow field, the Eulerian view. Yeah. The system
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  becomes completely self -aware. It's incredible.
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  And if you think about the bigger picture here,
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  the Navier -Stokes model takes things that used
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  to be seen as just obstacles. like wind, or the
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  urban canyon effect, where tall buildings degrade
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  GPS signals. It maps them. Signal degradation
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  becomes signal viscosity. It uses these forces
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  not as problems to avoid, but as known terms
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  in the equation to find the truly optimal path.
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  Which leaves you with a final thought. It does.
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  What does it actually mean for our infrastructure
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  when physics problems from centuries ago become
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  the most elegant, self -organizing solutions
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  for our most modern logistics challenges?