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Reactor Sensor Correlation & Anomaly Stream

Watch two live reactor sensor streams — temperature and pressure — build a 3D correlation trail in real time. Track the rolling Pearson coefficient, the rate of change, and a regression-residual anomaly detector, then trigger a simulated malfunction and see the relationship break.

Data Science3DModerate60 FPS

Two virtual reactor sensors — temperature, held near its setpoint by a proportional thermostat feedback loop, and pressure, physically coupled to it — stream new readings several times a second. Each sample joins a 3D point cloud where the X and Y axes are the two sensor values and depth is recency, so a tight diagonal band of points is a visual readout of correlation strength. A sliding-window Pearson coefficient, a rate-of-change readout, and a regression-residual z-score anomaly detector all update live underneath it. Trigger a simulated malfunction and watch the correlated relationship break in real time, exactly as an operator's dashboard would flag a fault.

⚙ Under the hood

Two live reactor sensor streams — temperature under thermostat feedback control and coupled pressure — build a 3D correlation point cloud in real time, with a rolling Pearson coefficient, rate of change, and a regression-residual anomaly detector that flags a triggered malfunction.

real-time analyticscorrelationanomaly detectionsensor fusionfeedback controldata science

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install