Datasets:
metadata
language:
- en
license: mit
task_categories:
- text-classification
tags:
- clarus
- f1
- thermal
- latent-instability
- cross-coupling
size_categories:
- 1K<n<10K
pretty_name: F1 Latent Cross-Coupling Thermal Load Instability v0.1
What this repo does
Detects hidden thermal instability before performance loss appears.
Focus: temperature-driven failure across interacting systems.
Core variables
- tyre_temp_load
- brake_temp_load
- power_unit_heat_load
- cooling_efficiency
Prediction target
label_thermal_load_instability
1 → thermal regime will force performance drop
0 → thermal state remains stable
Key idea
Thermal failure is rarely single-source.
It emerges from interaction:
- tyre overheating
- brake heat transfer
- power unit load
- cooling limits
Label logic
label = 1 if:
- latent_instability_score ≥ 0.60
- cross_coupling_intensity ≥ 0.60
- hidden_state_index ≥ 0.60
- activation_threshold_distance ≤ 0.35
- tyre_temp_load ≥ 0.80
- brake_temp_load ≥ 0.78
- power_unit_heat_load ≥ 0.75
- tyre_temp_load > stabilization_buffer
Why this matters
Performance loss is often thermal before it is visible.
This dataset detects:
- overheating before lap time drop
- cooling saturation before failure
- system interaction before degradation
Use cases
- race strategy
- cooling configuration
- stint planning
- simulation
Evaluation
Primary: missed_latent_activation_rate
Secondary: false_activation_rate
Structural Note
This sits in the latent detection layer.
It detects hidden thermal instability before performance collapse appears.
Production Deployment
Used for:
- live telemetry augmentation
- predictive race control
- simulation pipelines
Collaboration
Suitable for:
- F1 teams
- motorsport analytics
- simulation groups
License
MIT