Synthetic Chemical Batch Reactor Operational Logs for RL Agent Training

A mathematically consistent, high-fidelity simulation dataset of an industrial liquid-phase exothermic batch reactor. It contains multivariate time-series operational logs designed for training Reinforcement Learning agents and testing predictive models. The dataset was created by AIMindTeams and was last updated on April 13, 2026.

Use Cases

• Training RL agents for reactor control based on multivariate time-series operational logs.
• Testing predictive maintenance models based on simulated reactor life-cycle data.
• Benchmarking process optimization algorithms using high-fidelity simulation data.

Strengths

• Mathematically consistent, high-fidelity simulation of an industrial process.
• Designed specifically for Reinforcement Learning agent training.
• Contains 269 complete reactor life-cycles in the full 50,000-row version.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for this sample is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

AIMindTeams via Hugging Face.

Collection Method

Mathematically consistent simulation of an industrial batch reactor.

Time Range

Simulated time-series; no real-world temporal coverage specified.

Freshness

Last updated 2026-04-13 20:01:22; freshness should be verified.

Geography

Synthetic data; no real-world spatial coverage.