LUNAR SURFACE LOGISTICS: From Point Missions to Local Flow Networks

Background Lunar surface mission planning treats mobility and material movement as episodic sorties — rovers, sample returns, single-mission deliveries. As resource extraction, ISRU processing, and sustained habitats scale to continuous operations, this mission-centric framing lacks formal thresholds, capacity specifications, and architectural rules for persistent, resilient surface logistics. No theory specifies when, and by what structural change, a collection of point missions must be replaced by a flow network. Gap The Named Binary distinguishing Sortie-Centric Surface Operations (SCSO) from Network-Centric Surface Logistics (NCSL) does not appear in the literature. No framework specifies the throughput threshold T* at which depot investment becomes economically dominant, the depot spacing rule s* as a function of vehicle range and traversal variance, or the buffer sizing law B* (σₜ) governing inventory requirements under stochastic traversal delays. This silence leaves depot siting, fleet procurement, corridor investment, and risk allocation decisions without formal analytic support. Approach Using network flow theory, queuing theory, and vehicle energy constraints, we derive the mechanistic conditions for surface logistics regime emergence. We formalise spatial network primitives, define the throughput threshold T*, depot spacing s*, and buffer scaling law B* (σₜ), and prove their structural relationships. We ground the framework in the Internal-Geometry Threshold (IGT) theory of self-referentially self-maintaining systems. We present the Strongest Formulation in the four-part programme template, a pre-registerable Collapse Counter-Scenario (CCS), four distinguishing predictions, structural invariance confirmation across three independent engineering domains, and a Weil Protocol practitioner review pack. Results The regime transition from SCSO to NCSL is governed by the interaction of mean throughput α, traversal-time coefficient of variation CV = σₜ/μₜ, vehicle failure rate φᵥ, and infrastructure pre-conditioning. Under moderate traversal variance (CV ≈ 0. 5), T* falls in the range 3–10 t/month for small-payload vehicles (q ≈ 0. 5 t). Under high variance (CV ≈ 1. 0), T* shifts downward to 1–5 t/month because buffer requirements grow superlinearly with variance. Corridor conditioning (reducing CV) shifts T* upward, delaying the required depot investment. Buffer size B* scales as σₜ^β with β > 1, confirming superlinear growth. These results imply that modest early depot investments combined with scheduled courier services materially improve availability once throughput reaches a few tonnes per month. Implications Agencies and commercial operators should treat the T*, s*, and B* thresholds as design-stage investment signals rather than post-hoc observations. Early corridor conditioning, modular fleet procurement, and interface standardisation are high-leverage interventions that shift T* and reduce B* at low capital cost. Practitioner validation of demand projections and mobility failure data is required; a Weil Protocol review pack is provided.