The asphalt test result database
Predict asphalt performance from real test data
AsphaltMine collects laboratory results from European partners in one organized database and uses them to train machine learning prediction models.
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New prediction model: Air voids
A new prediction model is now available on AsphaltMine for estimating asphalt mixture bulk density and air void content. The model uses an uncertainty-weighted neural network that incorporates laboratory measurement uncertainty into training and evaluation. This allows it to account for differences in the reliability…
4000+
Test results
5+
Participating entities
2
Prediction models
What you can do with AsphaltMine
Contribute your results, explore what others have shared, and use the prediction tools.
Contribute data
Enter records with a web form or upload many at once from an Excel template.
Explore and visualize
Search records, download results, and see live statistics across tests, mixtures and years.
Predict performance
Estimate Marshall stability and flow, and bulk density and air voids, from mixture properties.
Developed at the Empa Concrete and Asphalt Laboratory and funded by the Swiss National Science Foundation as part of the WEAVE project No.213163: “Fate of Polymers in Recycled Asphalt: a Multiscale Approach”
Join the AsphaltMine community
We cannot do this alone. Contribute your asphalt test results and get access to all the database functionalities and features.