Propellant demand modeling precision for Phase 0-1 operations

Background

The rq-0-14 resolution established propellant production as a core Phase 0 capability, but the current propellant demand range of 100-250 tonnes per year is too wide for infrastructure sizing. This 2.5x uncertainty propagates into electrolysis system sizing, storage tank capacity, power budget allocation, and crew visit frequency. Without a precise demand model tied to specific mission profiles, the station risks either under-building (creating a propellant bottleneck) or over-building (wasting mass and power budget on excess capacity).

Why This Matters

The propellant production system's design point directly determines:

• Electrolysis power allocation (500-750 kW vs. 1+ MW)
• Storage tank sizing and associated thermal management
• Solar array capacity requirements (the 2.5 vs. 3.25 MW decision)
• Number of asteroid retrieval missions supportable per year
• Transport vehicle fleet utilization rates

A 100 t/yr system and a 250 t/yr system are fundamentally different pieces of hardware. The wrong choice could either strand the program with insufficient propellant or consume budget on unused capacity.

Key Considerations

• Asteroid retrieval missions consume the largest propellant budget (trajectory-dependent)
• Transport vehicle stationkeeping and orbital transfers add continuous baseline demand
• Emergency reserves must account for abort scenarios and contingency operations
• Demand grows as Phase 1 operations begin and mission tempo increases
• Propellant type (LH2/LOX vs. storable) affects consumption rates per mission

Research Directions

1. Mission-by-mission propellant budget: Model specific Phase 0-1 missions (asteroid retrieval, material transport, stationkeeping) with detailed delta-V and propellant mass calculations.

2. Fleet utilization modeling: Simulate transport vehicle fleet operations over 5-year periods to establish steady-state propellant consumption under various operational tempos.

3. Sensitivity analysis: Identify which mission parameters (number of retrievals/year, target asteroid distance, transport payload mass) have the largest impact on total demand.

4. Growth trajectory modeling: Project demand evolution from Phase 0 commissioning through Phase 1 ramp-up to establish capacity expansion milestones.

5. Contingency reserve methodology: Define appropriate propellant reserve margins for deep-space operations where resupply from Earth takes months.