Datasets:

ClarusC64
/

infrastructure-temporal-5node-pressure-buf-lag-cpl-grid-stress-blackout-v0.1

id string	context string	step_unit string	pressure_t0 float64	pressure_t1 float64	pressure_t2 float64	pressure_t3 float64	buffer_t0 float64	buffer_t1 float64	buffer_t2 float64	buffer_t3 float64	lag_t0 float64	lag_t1 float64	lag_t2 float64	lag_t3 float64	coupling_t0 float64	coupling_t1 float64	coupling_t2 float64	coupling_t3 float64	cross_step int64	notes string	label_cascade_state int64
GRID-0001	Normal load. Adequate reserve margin. Fast response dispatch.	hours	0.22	0.26	0.28	0.3	0.86	0.84	0.82	0.8	0.18	0.2	0.22	0.24	0.3	0.34	0.36	0.38	0	stable grid	0
GRID-0002	Peak demand rising. Reserve margin narrowing. Response timely.	hours	0.34	0.4	0.44	0.46	0.78	0.74	0.72	0.7	0.22	0.24	0.26	0.28	0.34	0.38	0.4	0.42	0	recoverable stress	0
GRID-0003	Heatwave spike. Reserve thin. Dispatch delay. Transmission coupling tight.	hours	0.48	0.6	0.72	0.84	0.7	0.6	0.46	0.34	0.28	0.44	0.66	0.84	0.42	0.58	0.74	0.88	2	lock-in forming	1
GRID-0004	Generator outage plus demand surge. Slow frequency response.	hours	0.52	0.64	0.76	0.88	0.66	0.54	0.4	0.28	0.32	0.54	0.74	0.88	0.5	0.66	0.8	0.9	2	frequency instability	1
GRID-0005	Transmission constraint escalates. Reserve depleted. Cascading trips.	hours	0.56	0.7	0.82	0.92	0.62	0.5	0.34	0.22	0.36	0.6	0.82	0.92	0.56	0.72	0.88	0.94	1	early crossing	1
GRID-0006	Load shedding initiated early. Reserve restored. Coupling reduced.	hours	0.44	0.52	0.5	0.48	0.72	0.76	0.78	0.8	0.3	0.26	0.22	0.2	0.46	0.44	0.4	0.38	0	intervention holds	0
GRID-0007	Multiple unit outages. Dispatch backlog. Grid tightly coupled.	hours	0.5	0.62	0.78	0.9	0.68	0.56	0.38	0.26	0.28	0.5	0.76	0.9	0.48	0.64	0.82	0.92	1	system-wide stress	1
GRID-0008	Demand spike managed with fast ramping reserves.	hours	0.46	0.58	0.6	0.56	0.66	0.62	0.68	0.7	0.4	0.34	0.28	0.24	0.52	0.5	0.46	0.42	0	recovery path	0
GRID-0009	Reserve exhausted. Delayed response. High interconnect dependency.	hours	0.58	0.72	0.86	0.94	0.6	0.48	0.32	0.2	0.34	0.62	0.86	0.94	0.58	0.74	0.9	0.96	2	blackout lock-in	1

What this repo does

This dataset tests whether a model can detect a power grid stress cascade forming over time and predict whether blackout lock-in occurs by the final step.

Core quad

pressure
buffer
lag
coupling

Prediction target

label_cascade_state

Row structure

One row represents a short time window (t0–t3) of grid stress conditions including demand pressure, reserve buffer margin, response lag, and interconnect coupling tightness. The label marks whether cascade lock-in (blackout formation) is reached by t3.

Files

data/train.csv
data/tester.csv
scorer.py

Evaluation

Run predictions on tester.csv
Score with scorer.py

License

MIT

Structural Note

This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample demonstrates the geometry.
Production-scale data determines operational exposure.

What Production Deployment Enables

• 50K–1M row datasets calibrated to real operational patterns
• Pair, triadic, and quad coupling analysis
• Real-time coherence monitoring
• Early warning before cascade events
• Collapse surface and recovery window modeling
• Integration and implementation support

Small samples reveal structure.
Scale reveals consequence.

Enterprise & Research Collaboration

Clarus develops production-scale coherence monitoring infrastructure for critical systems across healthcare, finance, infrastructure, and regulatory domains.

For dataset expansion, custom coherence scorers, or deployment architecture:
team@clarusinvariant.com

Instability is detectable.
Governance determines whether it propagates.

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