Thick concrete pours (footings, dams, mat foundations) generate their own heat as cement hydrates. If the hot core cools much faster at the surface than in the middle, the resulting tensile stress cracks the slab — the classic mass-concrete thermal-cracking problem. Each interior cell gains heat from the exothermic hydration reaction, modelled as a decaying heat pulse:
dT/dt |source = T_ad · k · e^(−k·t) (k ≈ 0.045 h⁻¹, peaks near t = 1/k)
Heat then spreads through the block by 3D diffusion, and the outer shell loses heat to the ambient air at a rate set by the formwork's insulation:
∂T/∂t = D·∇²T + source(t) − h·(T − T_amb) [boundary cells only]
The simulator discretises the pour into a voxel grid and integrates this explicitly every frame (sub-stepped for stability). A swarm of embedded nanorobots continuously ranks every voxel by temperature and re-deploys itself to the hottest cells, each active bot extracting heat locally (a stand-in for a distributed micro-cooling / phase-change actuation mechanism) — visualised as glowing agents converging on the red hot zones.
- Tad — total adiabatic temperature rise of the mix (more cement/high early-strength mix → hotter core).
- Insulation — how well the formwork traps heat; more insulation raises the core temperature and can worsen the gradient if the swarm can't keep up.
- Active cooling agents — swarm size; more agents cool more hot cells simultaneously, flattening the core–surface ΔT.
- Threshold — the ΔT past which real-world guidance (ACI 207-style limits, ~20 °C) calls the gradient a cracking risk.
Real-world relevance: dams and thick foundations already use embedded cooling pipes and insulated blankets to manage this gradient — nanorobot-scale distributed sensing and micro-actuation is a proposed next step for finer, adaptive control without permanent embedded plumbing.