On the Grain Size Sensitivity of Olivine Rheology
On the Grain Size Sensitivity of Olivine Rheology
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DOI：
10.1002/2017jb014847
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发表时间：
2018-01-01
影响因子：
3.9
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
使用 Mullet 等人的马尔可夫链蒙特卡罗 (MCMC) 反演技术。 (2015)，我们重新评估了橄榄石聚集体中扩散蠕变粒度指数的传统接受值的有效性。对三项广泛引用的研究中的各个实验进行的系统和全面的分析表明，这些数据并没有严格限制晶粒尺寸指数或扩散和位错蠕变的任何其他流动定律参数。我们的分析表明，由于晶粒尺寸和应力指数之间的协方差，大的数据不确定性可能会导致反演结果与真实值显着偏离，甚至从 3 中解析出 2 的晶粒尺寸指数也很困难。然而，我们可以利用 MCMC 反演技术的多功能性，通过确定未来实验研究的最佳条件来改善这种情况。例如，由于晶粒尺寸和应力指数的不确定性高度相关，因此增加晶粒尺寸变化范围有助于更好地同时约束两个指数。
Using the Markov chain Monte Carlo (MCMC) inversion technique of Mullet et al. (2015), we reassess the validity of the conventionally accepted values of the grain size exponent of diffusion creep in olivine aggregates. A systematic and comprehensive analysis of individual experimental runs taken from three widely cited studies reveals that these data do not tightly constrain the grain size exponent or any other flow law parameter for diffusion and dislocation creep. Our analysis indicates that large data uncertainties can cause inversion results to deviate significantly from true values because of the covariance between the grain size and stress exponents, and that even resolving a grain size exponent of 2 from 3 is difficult. The versatility of our MCMC inversion technique can, however, be exploited to improve this situation by identifying optimal conditions for future experimental studies. Because the uncertainties of the grain size and stress exponents are highly correlated, for example, increasing the range of grain size variation can help better constrain both exponents simultaneously.