The alkali element K is moderately volatile and fluid mobile; thus, it can be influenced by both primary processes (evaporation and recondensation) in the solar nebula and secondary processes (thermal and aqueous alteration) in the parent body. Since these primary and secondary processes would induce different isotopic fractionations, K isotopes could become a potential tracer to distinguish them. Using recently developed methods with improved precision (0.05‰, 95% confidence interval), we systematically measured the K isotopic compositions and major/trace elemental compositions of chondritic components (18 chondrules, 3 CAIs, 2 matrices, and 5 bulks) in the carbonaceous chondrite fall Allende. Among all the components analyzed in this study, CAIs, which formed initially under high‐temperature conditions in the solar nebula and were dominated by nominally K‐free refractory minerals, have the highest K2O content (average 0.53 wt%) and have K isotope compositions most enriched in heavy isotopes (δ41K: ?0.30 to ?0.25‰). Such an observation is consistent with previous petrologic studies that show CAIs in Allende have undergone alkali enrichment during metasomatism. In contrast, chondrules contain lower K2O content (0.003–0.17 wt%) and generally lighter K isotope compositions (δ41K: ?0.87‰ to ?0.24‰). The matrix and bulks are nearly identical in K2O content and K isotope compositions (0.02–0.05 wt%; δ41K: ?0.62 to ? 0.46‰), which are, as expected, right in the middle of CAIs and chondrules. This strongly indicates that most of the chondritic components of Allende suffered aqueous alteration and their K isotopic compositions are the ramification of Allende parent‐body processing instead of primary nebular signatures. Nevertheless, we propose the small K isotope fractionations observed (< 1‰) among Allende components are likely similar to the overall range of K isotopic fractionation that occurred in nebular environment. Furthermore, the K isotope compositions seen in the components of Allende in this study are consistent with MC‐ICP‐MS analyses of the components in ordinary chondrites, which also show an absence of large (10‰) isotope fractionations. This is not expected as evaporation experiments in nebular conditions suggest there should be large K isotopic fractionations. Nevertheless, possible nebular processes such as chondrules back exchanging with ambient gas when they formed could explain this lack of large K isotopic variation. 相似文献
ABSTRACT High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning. 相似文献
Methane content in coal seam is an essential parameter for the assessment of coalbed gas reserves and is a threat to underground coal mining activities. Compared with the adsorption-isotherm-based indirect method, the direct method by sampling methane-bearing coal seams is apparently more accurate for predicting coalbed methane content. However, the traditional sampling method by using an opened sample tube or collecting drill cuttings with air drilling operation would lead to serious loss of coalbed methane in the sampling process. The pressurized sampling method by employing mechanical-valve-based pressure corer is expected to reduce the loss of coalbed methane, whereas it usually results in failure due to the wear of the mechanical valve. Sampling of methane-bearing coal seams by freezing was proposed in this study, and the coalbed gas desorption characteristics under freezing temperature were studied to verify the feasibility of this method. Results show that low temperature does not only improve the adsorption velocity of the coalbed gas, but also extend the adsorption process and increase the total adsorbed gas. The total adsorbed methane gas increased linearly with decreasing temperature, which was considered to be attributed to the decreased Gibbs free energy and molecular average free path of the coalbed gas molecular caused by low temperature. In contrast, the desorption velocity and total desorbed gas are significantly deceased under lower temperatures. The process of desorption can be divided into three phases. Desorption velocity decreases linearly at the first phase, and then, it shows a slow decreases at the second phase. Finally, the velocity of desorption levels off to a constant value at the third phase. The desorbed coalbed gas shows a parabolic relation to temperature at each phase, and it increases with increasing temperature at the first phase, and then, it poses a declining trend with increasing temperature at the rest phases. The experimental results show that decreasing the system temperature can restrain desorption of coalbed methane effectively, and it is proven to be a feasible way of sampling methane-bearing coal seams.
The factors affecting permeability change under repeated mining of coal seams are important study aspects that need to be explored. This study combined various stress variation characteristics of protective seam mining and simplified the stress path of repeated mining in protective seam mines. Based on the results from the bespoke gas flow and displacement testing apparatus, seepage tests for simulated repetitive mining were carried out. The results simulated the actual behavior very well. With any drastic increase in the mining influence, the axial deviation stress in the stress path increased, and the greater the difference in coal permeability during the unloading and stress recovery stage, the more substantial the increase in permeability. The change in coal permeability was significantly influenced by the severity of simulated repeated mining cycles. When the mining stress exceeded a critical value, the permeability of the coal sample increased with the increase in the number of loading and unloading cycles, but the reverse was true when the mining stress was lower than the critical value. The effective sensitivity of seepage to the applied stress decreased with an increase in the number of stress cycles. With a decrease in the deviation stress, that is, with lower severity of mining influence, the effective sensitivity of coal seepage to stress gradually decreased.
