Anisotropy of Mushes (ANIMUSH): Deformation, fabrics, and anisotropy of olivine–melt aggregates at the plutonic–volcanic transition

ANIMUSH (Anisotropy of Mushes; https://animush.eu) provides a comprehensive suite of full-field numerical simulations of dynamic recrystallization and melt distribution in partially molten olivine aggregates, generated using the VPFFT-ELLE approach. The models are designed to investigate stress-driv...

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Detalles Bibliográficos
Autores: González-Esvertit, Eloi, Prieto-Torrell, Claudia, Yu, Yuanchao, Gomez-Rivas, Enrique, Walte, Nicolas, Albert, Helena, Griera Artigas, Albert, Lebensohn, Ricardo, Llorens, Maria-Gema
Tipo de recurso: conjunto de datos
Fecha de publicación:2026
País:España
Institución:Consorci de Serveis Universitaris de Catalunya (CSUC)
Repositorio:CORA.Repositori de Dades de Recerca
OAI Identifier:oai:dnet:cora.rdr____::c09420dbf71b14f035bfb387c2bb152c
Acceso en línea:https://doi.org/10.34810/DATA3320
Access Level:acceso abierto
Palabra clave:Computer and Information Science
Earth and Environmental Sciences
Partial melt
Dynamic recrystallisation
Olivine fabrics
Mush system
Full-field model
Seismic anisotropy
Magmatic systems
Descripción
Sumario:ANIMUSH (Anisotropy of Mushes; https://animush.eu) provides a comprehensive suite of full-field numerical simulations of dynamic recrystallization and melt distribution in partially molten olivine aggregates, generated using the VPFFT-ELLE approach. The models are designed to investigate stress-driven melt connection and segregation at the plutonic-volcanic interface of basaltic magmatic systems, and their role in producing crystal-plastic deformation in olivine crystals. They explore the coupled microstructural, rheological, and melt distribution evolution across a wide range of melt fractions (10–40 vol.%), strain rates (from 3.17e-11 to 6.34e-13 s-1), and deformation kinematics (pure shear and simple shear). In total, the dataset comprises 24 simulations, 12 under pure shear and 12 under simple shear, each resolved over 75 and 200 deformation steps, respectively, yielding more than 3,000 time-resolved model states. For each model state, eight types of output images are provided, including crystallographic orientation (EBSD maps), pole figures and orientation distribution functions, and melt distribution images. This results in ~7,200 images for pure shear simulations and ~19,200 images for simple shear simulations, in addition to crystallographic orientation data and quantitative metrics of melt connectivity, melt-preferred orientation, and crystallographic preferred orientation (CPO) strength. The simulations capture conditions representative of crystal-rich magmas, melt-rich mushes, and melt-poor mushes, allowing systematic evaluation of how deformation geometry, melt fraction, and strain rate control melt segregation and fabric development. Each simulation resolves the coupled evolution of CPO, dynamic recrystallization, and melt topology from initial conditions to high accumulated strain. Results show that progressive deformation and dynamic recrystallization reorganize melt from initially isolated pockets into connected networks and channelized pathways that focus melt extraction, while olivine accommodates deformation by dislocation creep under melt-bearing conditions. By explicitly capturing the coupled evolution of melt migration and mechanical crystal–crystal interactions, these data provide a quantitative framework to investigate the rheological behaviour of magmatic mushes and their transition toward eruptible states. The results also offer a basis for linking microstructural evolution with geophysical observables, including seismic anisotropy in crustal and upper-mantle mush zones.