Supplementary code for "A metamodel for confined yield stress flows and parameters' estimation"
Supplementary code for "A metamodel for confined yield stress flows and parameters' estimation"
This Zenodo upload is the supplementary material to the article:"A metamodel for confined yield stress flows and parameters' estimation"C. Berger et al. 2023. Submitted October 2023. Then published in Rheologica Acta (27 February 2024): https://doi.org/10.1007/s00397-024-01436-0. This repository contains Python scripts and data built from the methods presented in aforementioned article. The data include in particular precomputed metamodels that can be directly used for the inverse problem. The users can also recompute their metamodels for specific use and customisations. See the README.md for further details. Contact email: clement.berger97@gmail.com
python, lubrication approximation, metamodel, Principal Component Analysis, Herschel-Bulkley, inverse problem, Polynomial Chaos Expansion
python, lubrication approximation, metamodel, Principal Component Analysis, Herschel-Bulkley, inverse problem, Polynomial Chaos Expansion
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!