DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling

Abstract: In order to reconcile petrological and geophysical observations of magmatic processes in the temporal domain, the uncertainties in diffusion timescales need to be rigorously assessed. Here, we present a new diffusion chronometry method: Diffusion chronometry using Finite Elements and Neste...

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Main Authors: Mutch, Euan J. F., Maclennan, John, Shorttle, Oliver, Rudge, John F., Neave, David A.
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://www.repository.cam.ac.uk/handle/1810/321466
https://doi.org/10.17863/CAM.68586
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spelling ftunivcam:oai:www.repository.cam.ac.uk:1810/321466 2023-10-29T02:37:19+01:00 DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling Mutch, Euan J. F. Maclennan, John Shorttle, Oliver Rudge, John F. Neave, David A. 2021-04-22T23:19:36Z application/pdf text/xml https://www.repository.cam.ac.uk/handle/1810/321466 https://doi.org/10.17863/CAM.68586 en eng https://www.repository.cam.ac.uk/handle/1810/321466 doi:10.17863/CAM.68586 Research Article Bárðarbunga Bayesian inversion diffusion modeling finite elements Iceland volcanic and magmatic timescales olivine and plagioclase geospeedometry Skuggafjöll Article 2021 ftunivcam https://doi.org/10.17863/CAM.68586 2023-10-05T22:20:35Z Abstract: In order to reconcile petrological and geophysical observations of magmatic processes in the temporal domain, the uncertainties in diffusion timescales need to be rigorously assessed. Here, we present a new diffusion chronometry method: Diffusion chronometry using Finite Elements and Nested Sampling (DFENS). This method combines a finite element numerical model with a nested sampling Bayesian inversion, meaning that uncertainties in the parameters contributing to diffusion timescale estimates can be obtained and that observations from multiple elements can be used to better constrain individual timescales. Uncertainties associated with diffusion timescales can be reduced by accounting for covariance in the uncertainty structure of diffusion parameters rather than assuming that they are independent of each other. We applied the DFENS method to the products of the Skuggafjöll eruption from the Bárðarbunga volcanic system in Iceland, which contains zoned macrocrysts of olivine and plagioclase that record a shared magmatic history. Olivine and plagioclase provide consistent pre‐eruptive mixing and mush disaggregation timescales of less than 1 year. The DFENS method goes some way toward improving our ability to rigorously address the uncertainties of diffusion timescales, but efforts still need to be made to understand other systematic sources of uncertainty such as crystal morphology, appropriate choice of diffusion coefficients, initial conditions, crystal growth, and the petrological context of diffusion timescales. Article in Journal/Newspaper Iceland Apollo - University of Cambridge Repository
institution Open Polar
collection Apollo - University of Cambridge Repository
op_collection_id ftunivcam
language English
topic Research Article
Bárðarbunga
Bayesian inversion
diffusion modeling
finite elements
Iceland
volcanic and magmatic timescales
olivine and plagioclase geospeedometry
Skuggafjöll
spellingShingle Research Article
Bárðarbunga
Bayesian inversion
diffusion modeling
finite elements
Iceland
volcanic and magmatic timescales
olivine and plagioclase geospeedometry
Skuggafjöll
Mutch, Euan J. F.
Maclennan, John
Shorttle, Oliver
Rudge, John F.
Neave, David A.
DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
topic_facet Research Article
Bárðarbunga
Bayesian inversion
diffusion modeling
finite elements
Iceland
volcanic and magmatic timescales
olivine and plagioclase geospeedometry
Skuggafjöll
description Abstract: In order to reconcile petrological and geophysical observations of magmatic processes in the temporal domain, the uncertainties in diffusion timescales need to be rigorously assessed. Here, we present a new diffusion chronometry method: Diffusion chronometry using Finite Elements and Nested Sampling (DFENS). This method combines a finite element numerical model with a nested sampling Bayesian inversion, meaning that uncertainties in the parameters contributing to diffusion timescale estimates can be obtained and that observations from multiple elements can be used to better constrain individual timescales. Uncertainties associated with diffusion timescales can be reduced by accounting for covariance in the uncertainty structure of diffusion parameters rather than assuming that they are independent of each other. We applied the DFENS method to the products of the Skuggafjöll eruption from the Bárðarbunga volcanic system in Iceland, which contains zoned macrocrysts of olivine and plagioclase that record a shared magmatic history. Olivine and plagioclase provide consistent pre‐eruptive mixing and mush disaggregation timescales of less than 1 year. The DFENS method goes some way toward improving our ability to rigorously address the uncertainties of diffusion timescales, but efforts still need to be made to understand other systematic sources of uncertainty such as crystal morphology, appropriate choice of diffusion coefficients, initial conditions, crystal growth, and the petrological context of diffusion timescales.
format Article in Journal/Newspaper
author Mutch, Euan J. F.
Maclennan, John
Shorttle, Oliver
Rudge, John F.
Neave, David A.
author_facet Mutch, Euan J. F.
Maclennan, John
Shorttle, Oliver
Rudge, John F.
Neave, David A.
author_sort Mutch, Euan J. F.
title DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
title_short DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
title_full DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
title_fullStr DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
title_full_unstemmed DFENS: Diffusion Chronometry Using Finite Elements and Nested Sampling
title_sort dfens: diffusion chronometry using finite elements and nested sampling
publishDate 2021
url https://www.repository.cam.ac.uk/handle/1810/321466
https://doi.org/10.17863/CAM.68586
genre Iceland
genre_facet Iceland
op_relation https://www.repository.cam.ac.uk/handle/1810/321466
doi:10.17863/CAM.68586
op_doi https://doi.org/10.17863/CAM.68586
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