Software details

Software authors

Christina Schenk, Ignacio Romero

Intellectual Property Rights

Copyright © Fundación IMDEA Materiales and Universidad Politécnica de Madrid. All rights reserved

Opportunity

Software license.

Reference

Publication pending.

Software description

ACBICI is a Python package designed for model calibration with robust uncertainty estimation. Key features include:

• Bayesian calibration for precise model tuning.
• Distribution estimation for the model parameters.
• Quantification of uncertainties from measurement errors and/or model discrepancies.
• Gaussian process surrogate models for accelerated calibration and prediction tasks.
• Integrated visualisation tools for insightful result analysis.

ACBICI includes test examples from various fields of application.

Contact

ACBICI will be released soon, but testers can be provided early access to its beta version upon request. Beta users must be aware that the code may contain bugs, and it is provided as is.

Technology Transfer and Innovation Office, IMDEA Materials Institute

Email: techtransfer.materials@imdea.org

Telephone: +34 91 5493422