Thermoelectric Nanorobot Swarm — Pipeline Energy Harvester

Swarm Controls

Swarm size 120

Exploration noise 0.40

Load resistance 120 Ω

Heat intensity 1.50×

Live Readouts

Harvested power

0.0 mW

Avg ΔT sensed

0.0 K

Shared battery0%

Active bots on gradient (|∇T| > 0.5 K)

0 / 120

How it works

Each nanorobot straddles the hot pipeline surface with two contact legs a small distance apart. Wherever those legs sit across a temperature gradient, the Seebeck effect generates a voltage proportional to the local temperature difference:

ΔT ≈ |∇T(θ,x)| · legSpan
V = S · ΔT                    (Seebeck coefficient S)
P = V² · R_load / (R_int + R_load)²

The pipeline's surface temperature is a sum of moving Gaussian hotspots in the (angle θ, axial x) surface coordinates. Every bot senses the local temperature gradient directly (an analytic ∇T, standing in for on-board thermocouple sensing) and steers itself along it, exactly like stochastic gradient ascent / a simplified particle-swarm search:

v ← v + (gain·∇T + noise·rand) · dt
pos ← pos + v · dt   (θ wraps 2π, x bounces at the pipe ends)

Swarm size — how many nanorobots forage the pipeline simultaneously; more bots cover more of the surface and harvest more total power.
Exploration noise — the random-walk component versus pure gradient-following; too low and bots get stuck on the nearest lukewarm ridge, too high and they never settle on a hotspot.
Load resistance — the external circuit each bot's thermocouple pair drives; power peaks near matched-load (R_load ≈ R_int) as the formula above shows.
Heat intensity — scales the hotspot amplitude, i.e. how hot the pipeline is actually running.

All harvested current is pooled into one shared battery model (charge accumulates from total instantaneous power, minus a small self-discharge leak) — a stand-in for how a real self-powered sensor swarm would trickle-charge a shared energy-storage node while patrolling and monitoring pipeline health.

Harvesting nanorobot Idle / searching

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