Featuring experimental measurements from annealing DP980, DP780, and IF steel samples. It includes MATLAB code for predicting steel temperature using a Bayesian Pyrometry model with a conditional emissivity prior. The data collection and analysis procedures are detailed in an accompanying paper.
Use Cases
- Calibrate a Bayesian Pyrometry model using the conditional emissivity prior and annealing measurements for DP980 steel.
- Analyze spectral emissivity data from DP780 and IF steel samples to quantify measurement uncertainty.
- Validate temperature prediction algorithms against experimental annealing data for advanced high strength steels.
Strengths
- Includes data for three distinct steel types: DP980, DP780, and IF steel.
- Provides MATLAB code for implementing the Bayesian Pyrometry model with a conditional emissivity prior.
- Experimental procedures are detailed in an accompanying peer-reviewed paper.
Limitations
- The dataset size, row count, and specific column structure are unknown.
- The file formats for the data and code are unspecified.
- The license terms for use and redistribution are not provided.
Provenance
- Source
- Borealis Harvested Dataverse
- Collection Method
- Experimental measurements from annealing steel samples, as detailed in an accompanying paper.
- Time Range
- null
- Freshness
- null
- Geography
- null