Global Analysis of Experimental Data on the Rheology of Olivine Aggregates
Global Analysis of Experimental Data on the Rheology of Olivine Aggregates
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橄榄石聚集体流变学实验数据的全局分析
DOI：
10.1029/2018jb016558
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Karato, Shun‐ichiro
中科院分区：
文献类型：
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作者：
Jain, Chhavi;Korenaga, Jun;Karato, Shun‐ichiro
在重新分析一些广泛引用的研究（Jain等人，2018年，https：//doi.org/10.1002/2017JB 014847），我们重新审视了Korenaga和Karato（2008年，https：//doi.org/10.1029/2007JB 005100）的全球数据分析，并对其马尔可夫链蒙特卡罗反演进行了显着改进。他们的算法，以前修正Mullet等人。（），以尽量减少潜在的参数偏差，在这里进一步修改，以更有效地估计全球数据集的运行间偏差。使用改进的马尔可夫链蒙特卡罗反演技术，我们同时分析了从不同的研究汇编的橄榄石聚集体的变形的实验数据。采用了包括扩散和位错蠕变的复合流变模型，并研究了位错调节晶界滑动的作用。此外，使用实验和合成数据研究了运行间偏差对反演结果的影响。我们的分析表明，现有的数据可以严格限制扩散蠕变的晶粒尺寸指数为102，这与通常假设的值（p= 3）不同。然而，不同的数据集和模型假设产生了对其他流动律参数的非重叠估计，并且在大多数情况下，晶界滑动的流动律参数解决得很差。因此，我们提供了几个合理的候选流动律模型的橄榄石流变学，以促进未来的地球动力学建模。获得更多的数据，探索更广泛的实验条件，特别是更高的压力，是必不可少的，以提高我们对上地幔流变学的理解。
Following the reanalysis of individual experimental runs of some widely cited studies (Jain et al., 2018, https://doi.org/10.1002/2017JB014847), we revisit the global data analysis of Korenaga and Karato (2008, https://doi.org/10.1029/2007JB005100) with a significantly improved version of their Markov chain Monte Carlo inversion. Their algorithm, previously corrected by Mullet et al. () to minimize potential parameter bias, is further modified here to estimate more efficiently interrun biases in global data sets. Using the refined Markov chain Monte Carlo inversion technique, we simultaneously analyze experimental data on the deformation of olivine aggregates compiled from different studies. Realistic composite rheological models, including both diffusion and dislocation creep, are adopted, and the role of dislocation‐accommodated grain boundary sliding is also investigated. Furthermore, the influence of interrun biases on inversion results is studied using experimental and synthetic data. Our analysis shows that existing data can tightly constrain the grain‐size exponent for diffusion creep at ∼2, which is different from the value commonly assumed (p= 3). Different data sets and model assumptions, however, yield nonoverlapping estimates on other flow‐law parameters, and the flow‐law parameters for grain boundary sliding are poorly resolved in most cases. We thus provide a few plausible candidate flow‐law models for olivine rheology to facilitate future geodynamic modeling. The availability of more data that explore a wider range of experimental conditions, especially higher pressures, is essential to improve our understanding of upper mantle rheology.