An accurate determination of water content in garnet is critical to quantify the transport of water to the deep mantle by the subducted oceanic crust beyond the breakdown of hydrous phases. Fourier transform infrared spectroscopy (FTIR) is the most widely used approach to determine the species and contents of water in garnet. Accurate quantification of OH in garnet requires independent calibration using an external method, as OH absorbance is mineral and composition specific. To obtain the infrared absorption coefficients of structural hydroxyl in garnet, a combined study of spectrometric analyses by FTIR and a method combining a thermal conversion elemental analyser with isotope ratio mass spectrometry (TC/EA-MS) was carried out for fourteen gem-quality natural garnet crystals with variable compositions. The obtained molar absorption coefficients were 9322 ± 338 and 240 ± 26 l mol−1 cm−2 for grossular- and spessartine-rich garnet and pyrope-almandine garnet, respectively. These results are within the range of previous studies. A new molar absorption coefficient of 689 ± 177 l mol−1 cm−2 was obtained for pyrope-spessartine garnet. The large variation in the absorption coefficient indicates it is controlled by both garnet composition and OH-absorption bands. The obtained absorption coefficients are only appropriate for certain types of eclogitic garnet, and more studies should be carried out on eclogitic garnets. 相似文献
Mathematical Geosciences - Quantitative evaluation of fracability is essential for hydraulic fracturing design, with the distribution of in situ stress being a key parameter. This study focused on... 相似文献
It is known that a lot of uncertainties are involved in geotechnical design of energy piles. In this paper, a Bayesian updating framework is presented to characterize those uncertainties. The load-transfer model is developed to predict the thermomechanical response of energy piles. Considering the cross-case variability of the uncertainty in the axial strains of pile, the global model bias is firstly calibrated by establishing a comprehensive database consisting of 12 energy pile cases. Furthermore, the uncertainty in input parameters is considered in the Bayesian updating of model bias in a specific case. The variability of the uncertain parameters is effectively reduced after updating. The coefficient of variation of prediction is decreased from 0.34 to 0.13. The present framework can well quantify uncertain factors and improve the accuracy and reliability of the prediction model.
Natural Hazards - The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual... 相似文献