Depot Spacing Logistics Simulator
Monte Carlo discrete event simulation for Dyson swarm depot logistics. Analyze optimal depot spacing, fleet utilization, and mean time to repair for maintenance drone operations servicing millions of collector units.
Depot Parameters
Comparison Mode
Compares 7 depot spacing configurations from 50k to 500k km while keeping swarm size, failure rate, and fleet size constant.
Response Time Comparison
Run a comparison simulation to see response time chart
Simulation Results
Configure the depot parameters and run the simulation to see results.
Simulation Methodology
This discrete event simulation models the complete maintenance cycle for Dyson swarm collector units: failure detection, inspector dispatch, fault diagnosis, servicer dispatch, and repair completion.
- Failures follow exponential distribution based on annual failure rate
- Inspector drones patrol assigned regions and detect collector faults
- Servicer drones perform repairs with propellant-constrained mission profiles
- Transit times calculated using Hohmann transfer approximations
- Depots distributed in spherical shell around swarm for coverage
Key trade-off: Denser depot spacing reduces response time but increases infrastructure cost and complexity. Optimal spacing balances MTTR against deployment cost.
This simulator was built to investigate research question RQ-2-7: Optimal depot spacing and logistics architecture
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