MELVIS: An open-source web application for computing and modelling the viscosity of volcanic melts
Abstract
The viscosity of volcanic melts governs magma transport, eruption dynamics, and a broad range of magmatic processes, so predicting it as a function of temperature, composition, and dissolved water content is central to physical volcanology. Yet no freely accessible tool integrates global machine-learning predictions, physically motivated viscosity equations, and composition-specific models calibrated to avoid nanocrystallization and water-loss artefacts — experimental biases that can lead conventional viscometry to overestimate melt viscosity. Nor can existing tools show how different assumptions about the dependence of melt fragility on dissolved water propagate into viscosity predictions at eruptive temperatures — a debated question with direct consequences for conduit-flow modelling and eruption-style assessment.,Here we present MELVIS (MELt VIScosity), an open-source web application built with Python and Streamlit. MELVIS comprises three integrated modules: (1) a viscosity calculator based on the artificial neural network of Langhammer et al. (2022), developed using a database of 3,482 measurements spanning basanite to rhyolite including hydrous compositions, with batch processing and TAS-based compositional classification; (2) a hydrous modelling module that parameterises the glass transition temperature Tg(H2O) and melt fragility m(H2O) under three alternative fragility–water relationships, making explicit how model assumptions propagate into viscosity predictions at eruptive temperatures; and (3) a library of seven composition-specific, artefact-free MYEGA models for key volcanic systems. All modules yield closed-form MYEGA parameterisations suitable for direct implementation in numerical eruption models.
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BibTeX
@misc{genova2026melvis,
title = {{MELVIS: An open-source web application for computing and modelling the viscosity of volcanic melts}},
author = {Danilo Di Genova},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x5f806},
url = {https://eartharxiv.org/repository/view/15493/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - MELVIS: An open-source web application for computing and modelling the viscosity of volcanic melts
AU - Danilo Di Genova
PY - 2026
DA - 2026/10/13
PB - EarthArXiv
DO - 10.31223/x5f806
UR - https://eartharxiv.org/repository/view/15493/
AB - The viscosity of volcanic melts governs magma transport, eruption dynamics, and a broad range of magmatic processes, so predicting it as a function of temperature, composition, and dissolved water content is central to physical volcanology. Yet no freely accessible tool integrates global machine-learning predictions, physically motivated viscosity equations, and composition-specific models calibrated to avoid nanocrystallization and water-loss artefacts — experimental biases that can lead conventional viscometry to overestimate melt viscosity. Nor can existing tools show how different assumptions about the dependence of melt fragility on dissolved water propagate into viscosity predictions at eruptive temperatures — a debated question with direct consequences for conduit-flow modelling and eruption-style assessment.,Here we present MELVIS (MELt VIScosity), an open-source web application built with Python and Streamlit. MELVIS comprises three integrated modules: (1) a viscosity calculator based on the artificial neural network of Langhammer et al. (2022), developed using a database of 3,482 measurements spanning basanite to rhyolite including hydrous compositions, with batch processing and TAS-based compositional classification; (2) a hydrous modelling module that parameterises the glass transition temperature Tg(H2O) and melt fragility m(H2O) under three alternative fragility–water relationships, making explicit how model assumptions propagate into viscosity predictions at eruptive temperatures; and (3) a library of seven composition-specific, artefact-free MYEGA models for key volcanic systems. All modules yield closed-form MYEGA parameterisations suitable for direct implementation in numerical eruption models.
ER -