Simulation Reveals: Propulsion, Not Fleet Size, Limits NEA Survey Coverage

We built an interactive Monte Carlo simulator to answer a fundamental question for Phase 0: How many prospecting satellites do we actually need? The answer surprised us—and could save Project Dyson $100 million.

The Question

The consensus specification for Prospecting Satellites calls for a 50-satellite constellation at $5M per unit—a $250M investment. But was this number rigorously validated, or just a reasonable planning estimate?

We built a Monte Carlo simulator to find out, running 500+ simulations for each parameter configuration across 11 constellation sizes (20-70 satellites).

The Surprising Finding

High-value NEA coverage plateaus at ~38% regardless of constellation size.

Whether you deploy 20 satellites or 70, with electric propulsion you'll identify roughly the same proportion of high-value mining targets (metallic M-type and carbonaceous C-type asteroids). Adding more satellites only increases coverage of low-value targets.

Constellation Size	Total Coverage	High-Value Coverage
20 satellites	12.8%	38.8%
50 satellites	30.7%	38.2%
70 satellites	41.9%	35.8%

The high-value coverage is essentially flat—even slightly decreasing at larger fleet sizes as resources get spread thinner.

What Does Matter: Propulsion Type

The real determinant of survey effectiveness isn't fleet size—it's propulsion choice:

Propulsion	High-Value Coverage	Delta
Electric (Ion)	38.2%	baseline
Hybrid	36.6%	-4%
Chemical	14.2%	-63%

Chemical propulsion is catastrophic for high-value target identification. The limited delta-V budget means satellites simply cannot reach the orbital families where valuable asteroids reside.

The Physics Explanation

Why does this happen? It comes down to delta-V accessibility:

1. High-value NEAs aren't uniformly distributed—they cluster in orbital families that require specific delta-V to reach
2. Electric propulsion's ~15 km/s budget can access about 38% of these families
3. Additional satellites can survey more targets within those families, but can't reach the 62% of high-value NEAs that remain inaccessible

Think of it like fishing: more boats help you catch more fish in the reachable waters, but no number of boats will catch fish in waters you can't reach. You need a faster boat.

Mission Duration and Reliability

We also tested mission duration (5-10 years) and failure rates (0-10%). Neither significantly affected high-value coverage:

Mission Duration (Electric, 50 sat, 3% failure):

• 5 years: 23% total, 38% high-value
• 7 years: 31% total, 38% high-value
• 10 years: 41% total, 38% high-value

Failure Rate (Electric, 50 sat, 7 years):

• 0% failure: 39% total, 38% high-value
• 3% failure: 31% total, 38% high-value
• 10% failure: 25% total, 38% high-value

The high-value ceiling is consistent across all configurations. Time and reliability affect how many low-value targets you survey, but not the fundamental accessibility constraint.

Implications for Project Dyson

1. Reduce Constellation Size from 50 to 30-35 Satellites

This saves $75-100 million with:

• Zero impact on high-value target identification
• Only 12% reduction in total coverage (low-value targets)
• Sufficient redundancy for the 7-year mission

2. Electric Propulsion is Non-Negotiable

The 63% reduction with chemical propulsion makes it essentially unusable for our primary mission objective. This validates the consensus specification's emphasis on high-Isp systems.

3. Consider Higher Delta-V Systems for Phase 2

To break the 38% ceiling, future prospecting missions would need:

• Higher Isp propulsion (>15 km/s delta-V budget)
• In-space refueling capability
• Or acceptance that 38% coverage is sufficient for Phase 1 mining operations

4. 38% May Be Enough

Even 38% of high-value NEAs represents hundreds of potential mining targets. For Phase 1's production goals, this is likely more than sufficient. The question becomes: is it worth spending $100M+ to survey targets we'll never mine?

Try It Yourself

We've published the interactive simulator so you can explore these trade-offs yourself. Adjust constellation size, mission duration, failure rates, and propulsion type to see how coverage changes.

Methodology

The simulation uses:

• 2,000 synthetic NEAs with realistic orbital element distributions based on known population statistics
• Greedy target assignment prioritizing high-value asteroids (M-type, C-type)
• Simplified Hohmann transfer delta-V calculations
• Bernoulli failure model for satellite reliability
• 500 Monte Carlo runs per configuration for statistical significance

Results should be interpreted as relative comparisons between configurations, not absolute predictions of real-world coverage.

What's Next

This research answers RQ-0-3 and marks the first time we've used simulation to validate a consensus specification. We're now evaluating which other research questions could benefit from similar computational analysis.

The $100M savings identified here could be redirected to:

• Higher-capability propulsion development
• Additional redundancy in processing platforms
• Accelerating Phase 1 collector production

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Research Question: RQ-0-3: Minimum constellation size for survey coverage

Interactive Tool: NEA Constellation Coverage Simulator