The Timetable Is the Network

The Finding

Of every 100 tonnes of cryogenic propellant dispatched from Earth toward Jupiter via relay chain, fewer than 3 arrive. This is not an insulation problem or a budget problem. It is a consequence of orbital mechanics and hydrogen thermodynamics that no relay architecture with passive cryogenic storage can overcome.

The covered wagon essay

The Framework

TIN computes delivery ratios for any scheduled transport network through a factorization: DR = S_T × η. A single diagnostic, gamma, classifies networks as CLUSTER (path diversity helps) or TRAP (adding routes makes things worse). The framework screens commodity-dependent feasibility before hardware is committed. Validated across 290,000+ configurations spanning 8 planetary bodies and 5 terrestrial contact datasets.

The factorization is an arithmetic identity. The γ classification is derived from it. Configuration counts are simulation results. Policy implications are inferences from those results.

The Phase Diagram

Commodity phase diagram showing feasibility boundaries by cargo half-life and transit time. Liquid hydrogen cannot survive any route beyond Mars. Hardware on the same route arrives at 42%. — Commodity feasibility depends on two numbers: how long the cargo survives (vertical axis) and how long the trip takes (horizontal axis). Liquid hydrogen cannot survive any route beyond Mars. Hardware on the same route arrives at 42%.

Interactive Tools

Sparse Law Calculator — predict delivery ratios from network parameters using the three-factor sparse law
Solar System Orrery — 3D explorer with orbital mechanics, DTN contact links, and constellation overlays

Papers

A classification framework for temporal contact graphs — the factorization DR = S_T × η, trap/cluster dichotomy, 155,000+ configurations
From classification to mechanism in temporal contact networks — why networks trap: Var[ln p] mechanism, four-route taxonomy, layered diagnostic hierarchy
Percolation-optimal relay architectures for cislunar and interplanetary networks — 89,178 configurations, Braess paradox, design rules for Artemis/Gateway and Mars Sample Return
J_β saturation invariance and TASEP phase structure in DTN relay networks — load-dependent phase transitions, universal current ceiling, golden-mean falsification
Policy brief: Jupiter cryogenic propellant — two-page summary of implications for relay architecture planning

Code & Data

github.com/toxic2040/TIN — source code, simulation engine, 298 experiment runners
License: AGPL-3.0-or-later

About

J. Councilman is an independent researcher applying percolation theory to scheduled transport networks. The core method: decompose aggregate metrics into their upstream causes before reaching for complex explanations. 290,000+ configurations tested, all code open-source.

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