datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PHI-CTRL-F16-Fault-Recovery-Telemetry
PHI-CTRL F-16 Actuator Fault Recovery Dataset
High-Fidelity JSBSim 6-DOF Telemetry for Physics-Hybrid Self-Healing Flight Control
Official verification artifacts of the PHI-CTRL (Physics-Hybrid Integrity Control) architecture — a digital-twin-driven, self-healing flight control framework that actively compensates actuator degradation in real time.
Author: Mohammed Bello Sani (SM-Bello)
Affiliation: Air Force Institute of Technology (AFIT), Kaduna · Penelope Inc. / PHI Lab… See the full description on the dataset page: https://huggingface.co/datasets/SM-Bello/PHI-CTRL-F16-Fault-Recovery-Telemetry.f1_corner_telemetry_2024_2025
Readme Dataset
[!TIP]
This dataset is used in RacingDNA.
[!NOTE]
Dataset Overview
This repository includes:
2024-2025 Curve Dataset: Includes Race and Qualifying sessions.
Normalization: Data is already processed and normalized (see below).
2025 Raw Data: Raw data from the 2025 season is included.
Credits: Raw telemetry data is sourced from TracingInsights on Hugging Face.
Dataset Structure
The dataset is a CSV file where each row represents a specific curve taken… See the full description on the dataset page: https://huggingface.co/datasets/FlorindoDev/f1_corner_telemetry_2024_2025.medical-structure-f19c39
medical-structure-f19c39
Synthetic weather test data: 39 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/jihye54/medical-structure-f19c39.proper-base-f1d00b
proper-base-f1d00b
Synthetic weather test data: 46 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/inoueharuka71/proper-base-f1d00b.both-gear-f15f18
both-gear-f15f18
Synthetic sensors test data: 35 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/Atlas-Theo/both-gear-f15f18.f1-latent-cross-coupling-aero-balance-instability-v0.1
What this repo does
This repository introduces a Clarus dataset for detecting latent instability under cross-coupled conditions in Formula 1 aero-balance systems.
The goal is to identify race states in which aero balance may still appear outwardly stable or only mildly anomalous but already contains hidden internal instability that may activate into sudden balance loss once interacting pressures exceed containment.
Core structure
This dataset models a pre-failure geometry… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-latent-cross-coupling-aero-balance-instability-v0.1.tajik_lemmasF1-tyre-phase-stability-field-mapping-v0.1What this dataset tests
Whether a system can measurethe stability of a tyre operating phasebefore degradation accelerates.
Focus
Thermal gradientslip variancevibration coherenceworking window margin
Required outputs
phase stability score
thermal gradient index
slip variance index
vibration coherence
working window margin
All scores0 to 1
Highermeans stable tyre phase.
cascade-f1-powerunit-cooling-ambient-reliability-v0.1
What this repo does
This repo models a quad coupling pattern linked to thermal reliability collapse.
It supports:
• scoring race states for DNF risk region entry• identifying which variables drive thermal margin loss• testing cooling and load redesign moves
The sample is synthetic.It shows the geometry.
Core quad
• engine_load• cooling_capacity• ambient_temp• component_degradation_rate
Prediction target
label_cascade
• 0 means stable thermal operating… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-f1-powerunit-cooling-ambient-reliability-v0.1.F1-aero-pressure-coherence-mapping-v0.1What this dataset tests
Whether a system can detectlocalized aero coherence lossfrom pressure sensor fields.
Focus
Platform coherencezone asymmetryvortex integritylocalized collapse zonesbalance shift risk
Required outputs
platform coherence score
zone pressure asymmetry index
vortex system integrity flags
localized collapse zones
balance shift risk score
All scores0 to 1
Higher coherencemeans unified platform.
Higher asymmetry and balance riskmean localized collapse is likely.
cascade-f1-teamstrategy-coupling-rival-response-tyre-delta-gap-v0.1
F1 TeamStrategy–Coupling–RivalResponse–TyreDelta–Gap Cascade
A five-node coupling model for team-level strategic collapse in Formula 1.
This repository models how two-car strategy alignment, rival response speed, tyre delta, and track position gap interact to produce non-linear outcome cascades.
It shifts analysis from single-car optimisation to multi-agent interaction geometry.
What This Repo Demonstrates
You can:
• Score a two-car strategic state for cascade risk•… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-f1-teamstrategy-coupling-rival-response-tyre-delta-gap-v0.1.F1-driver-car-harmonic-efficiency-and-energy-waste-mapping-v0.1What this dataset tests
Whether a system can detectharmonic inefficiency in driver-car coupling.
Focus
Overcorrection loopsoscillation signaturesenergy leaksegment efficiency rank
Required outputs
harmonic waste index
correction loop density
oscillation signature type
energy leak score
efficiency rank by segment
All scores0 to 1
Highermeans more waste.
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 drop0 → thermal state remains stable
Key idea
Thermal failure is rarely single-source.
It emerges from interaction:… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-latent-cross-coupling-thermal-load-instability-v0.1.F1-driver-car-input-response-resonance-estimation-v0.1What this dataset tests
Whether a system can estimatedriver-car coupling resonance.
Focus
Phase locklatency matchinput smoothnessresponse gain stability
Required outputs
resonance score
phase lock index
latency match index
control smoothness ratio
response gain stability
All scores0 to 1
Highermeans better coupling.
F1-aero-platform-recovery-and-stability-gradient-v0.1What this dataset tests
Whether a system can maphow an aero platform recovers after localized collapseand identify fragile zones that persist.
Focus
Recovery pathstability gradient across zonespersistent imbalancerecovery latencyfragility hotspotsnext collapse risk
Required outputs
recovery path profile
stability gradient map
persistent imbalance flags
recovery latency score
fragility hotspots
next collapse risk score
All indices0 to 1
Higher latency and next riskmean slower… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/F1-aero-platform-recovery-and-stability-gradient-v0.1.f1-dataF1-cascade-propagation-and-failure-horizon-v0.1What this dataset tests
Whether a system can trace
how decoherence propagates across subsystems
and estimate time-to-failure.
Required outputs
initial_decoupling_pair
propagation_path
affected_components
cascade_velocity
predicted_failure_component
failure_horizon_laps
intervention_window_laps
containment_feasibility_score
Field meanings
cascade_velocity0 to 1higher means faster spread
failure_horizon_lapslaps until failure becomes likely
intervention_window_lapslaps… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/F1-cascade-propagation-and-failure-horizon-v0.1.F1-tyre-phase-collapse-and-recovery-dynamics-v0.1What this dataset tests
Whether a system can diagnosea tyre phase collapseand recommend the recovery or stop strategy.
Focus
Collapse pointrecovery feasibilitytime loss projectioncross-tyre propagation riskoptimal intervention window
Required outputs
phase collapse point
recovery feasibility
lap time loss projection
cross tyre propagation risk
optimal intervention window
All scores0 to 1
Lap time lossin seconds per lap.
Constraints
Telemetry only.Do not assume perfect… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/F1-tyre-phase-collapse-and-recovery-dynamics-v0.1.f1-quad-engine-temp-ambient-temp-fuel-mix-lap-intensity-thermal-failure-risk-v0.1What this repo does
This dataset models engine thermal stress escalation in Formula One. It predicts when the interaction between engine temperature, ambient heat, fuel mix choice, and lap intensity pushes the power unit into a thermal failure risk zone.
Core quad
engine_temp_c
ambient_temp_c
fuel_mix_index
lap_intensity_index
Prediction target
label_thermal_failure_risk
Binary forward label predicting imminent overheating, forced derating, or thermal-triggered retirement risk within the next… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-quad-engine-temp-ambient-temp-fuel-mix-lap-intensity-thermal-failure-risk-v0.1.project_20260813_014200_f15cdb95
Manufacturing Risk Alerts 2026
数据集概述 / Dataset Overview
本项目为巴西与阿根廷中小型制造企业的年度生产安全与供应链风险预警数据集。
This dataset aggregates equipment operation logs, maintenance work orders, supply-chain delivery exceptions, safety reports and quality inspection results collected during the past year from manufacturing plants across South America.
关键元数据 / Key Metadata
覆盖地区 / Coverage Region: 巴西 (Brazil) 与 阿根廷 (Argentina) / South America
行业领域 / Industry: 制造业 /… See the full description on the dataset page: https://huggingface.co/datasets/toolathon123/project_20260813_014200_f15cdb95.F1-driver-car-setup-coupling-optimization-recommendations-v0.1What this dataset tests
Whether a system can propose setup adjustmentsthat increase driver-car coupling resonance.
Focus
Setup candidatespredicted resonance gainstability trade-offcondition sensitivitypersonalized setup profile
Required outputs
setup adjustment candidates
predicted resonance gain
stability trade-off index
track condition sensitivity
personalized setup profile
All indices0 to 1
Higher gainmeans larger coupling improvement.
Constraints
Setup recommendations only.Do… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/F1-driver-car-setup-coupling-optimization-recommendations-v0.1.F1-aero-localized-collapse-trigger-detection-v0.1What this dataset tests
Whether a system can link disturbancesto localized aero collapse events.
Focus
Trigger typecollapse locationonset latencyrecovery timespread riskbalance shift linkage
Required outputs
trigger event type
trigger location zone
collapse onset latency
coherence recovery time
collapse spread risk
disturbance to balance shift score
All indices0 to 1
Timesin seconds
Higher spread riskmeans collapse likely propagates across the platform.
f1-quad-tyre-temp-brake-temp-pack-compression-reaction-delta-restart-position-loss-v0.1What this repo does
This dataset models restart instability in Formula One. It predicts when the interaction between tyre temperature readiness, brake temperature readiness, pack compression intensity, and reaction delay creates a high probability of losing positions at a safety car restart.
Core quad
tyre_temp_index
brake_temp_index
pack_compression_index
reaction_time_delta_s
Prediction target
label_restart_position_loss
Binary forward label predicting position loss across the restart phase… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-quad-tyre-temp-brake-temp-pack-compression-reaction-delta-restart-position-loss-v0.1.cascade-f1-pit-traffic-safetycar-fieldcompression-v0.1
F1 Pit–Traffic–SafetyCar–FieldCompression Cascade
A quad coupling model for position-loss cascades driven by pit timing under dynamic race conditions.
This repository models how pit delta, traffic density, safety car probability, and field compression interact to produce non-linear position collapse.
It shifts analysis from isolated pit loss metrics to interaction-driven strategic instability surfaces.
What This Repo Demonstrates
You can:
• Score a race state for pit… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-f1-pit-traffic-safetycar-fieldcompression-v0.1.cascade-f1-tyre-tracktemp-fuelload-strategy-degradation-v0.1
F1 Tyre–TrackTemp–FuelLoad–Strategy Degradation Cascade
A quad coupling model for strategic collapse driven by tyre degradation dynamics.
This repository models how tyre wear, track temperature, fuel mass, and strategy timing interact to produce undercut vulnerability and late-stint performance failure.
It shifts analysis from single-metric tyre wear tracking to interaction-driven instability surfaces.
What This Repo Demonstrates
You can:
• Score a race state for… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-f1-tyre-tracktemp-fuelload-strategy-degradation-v0.1.f1-quad-tyre-age-track-temp-fuel-load-driving-style-performance-drop-v0.1What this repo does
This dataset models nonlinear tyre degradation collapse in Formula One. It predicts when combined stress from tyre age, track temperature, fuel load, and driving aggression triggers a late-stint performance drop.
Core quad
tyre_age_laps
track_temp_c
fuel_load_kg
driving_style_index
Prediction target
label_performance_drop
Binary forward label predicting whether tyre performance collapse occurs within the next stint window.
Row structure
Each row represents a race-state… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-quad-tyre-age-track-temp-fuel-load-driving-style-performance-drop-v0.1.f1-latent-cross-coupling-tyre-degradation-collapse-v0.1
What this repo does
This repository introduces a Clarus dataset for detecting latent instability under cross-coupled conditions in Formula 1 tyre performance systems.
The goal is to identify race states in which tyre behavior may still appear outwardly stable or only mildly anomalous but already contains hidden internal degradation that may activate into sudden tyre degradation collapse once interacting pressures exceed containment.
Core structure
This dataset models… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-latent-cross-coupling-tyre-degradation-collapse-v0.1.f1-quad-pit-duration-crew-fatigue-race-pressure-weather-variability-pit-error-v0.1What this repo does
This dataset models pit stop failure risk in Formula One. It predicts when the interaction between stop duration strain, cumulative crew fatigue, race pressure intensity, and weather variability produces elevated probability of pit execution error.
Core quad
pit_duration_s
crew_fatigue_index
race_pressure_index
weather_variability_index
Prediction target
label_pit_error
Binary forward label predicting unsafe release, delayed wheel fit, or procedural error during the pit… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-quad-pit-duration-crew-fatigue-race-pressure-weather-variability-pit-error-v0.1.twitter_f1cascade-f1-tire-aero-brake-heat-oscillation-v0.1
F1 Tire–Aero–Brake Heat Oscillation Cascade
A quad coupling model for thermal-driven performance collapse in Formula 1.
This repository models how tire temperature, aerodynamic load, brake heat, and vertical oscillation interact to produce late-race instability.
It shifts analysis from component optimisation to interaction geometry.
What This Repo Demonstrates
You can:
• Score a setup state for cascade risk• Identify which interaction variables drive instability• Compare… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-f1-tire-aero-brake-heat-oscillation-v0.1.