tesla_turbine_structure
plain-language theorem explainer
The theorem shows that the Tesla turbine structure satisfies the ledger-derived energy storage density property. Applied physicists modeling boundary-layer turbines in Recognition Science frameworks would cite it to link geometry to storage constraints. The proof is a direct term-mode application of the energy storage density structure result.
Claim. The Tesla turbine structure satisfies the property that its energy storage density is derived from the ledger.
background
The Engineering.TeslaTurbineStructure module imports EnergyStorageDensityStructure and defines tesla_turbine_from_ledger as the proposition energy_storage_density_from_ledger. This sets the local context for structural implications in Recognition Science engineering models, where turbine properties are constrained by ledger-based density relations rather than free parameters.
proof idea
The proof is a one-line term wrapper that applies energy_storage_density_structure to discharge the goal.
why it matters
This result supplies the structural input needed for engineering applications of the Recognition Science ledger, feeding sibling implications such as tesla_turbine_implies_energy_storage. It connects turbine modeling to the broader T0-T8 forcing chain and phi-ladder mass formulas without introducing new hypotheses.
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