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High-temperature initial oxidation behavior at 1000 C in LDX 2101 oxidized in a closed element is studied. The samples are investigated using optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, glow discharge optical emission spectroscopy, and Raman spectra. Results show differences in morphology and development of oxides on the two phases. In the initial stage, the oxide on austenite is granular, whereas that on the ferrite region is homogeneous. However, the entire surface is full of chromium oxide. In the austenite phase, oxide gradually changes from Fe 2 O 3 to Cr 2 O 3 . By contrast, oxide transforms from Mn 2 O 3 to Fe 2 O 3 and then to Cr 2 O 3 in the ferrite phase. In addition, manganese enrichment is observed in the entire oxidation process.

As a response to climate changes, permafrost has deteriorated and the hydrologic process has undergone significant alterations in high-cold regions. The response mechanism still remains unknown. The characteristic contribution was calculated using the random forest (RF) algorithm, AdaBoost algorithm, and gradient-boosted decision tree (GBDT) algorithm. A comprehensive evaluation model was constructed to evaluate the contribution of climate changes to the headwaters of the Yellow River and the influence of permafrost degradation as well as climate-permafrost cooperation on runoff changes. The selected characteristic vectors were chosen as datasets for the support vector machine (SVM) and RF algorithms. A model was constructed for the prediction of permafrost degradation and runoff changes based on climate data. Results demonstrated that climate variables influencing the mean depth-to-permafrost table (DPT) were ranked according to their contributions: air temperature > evapotranspiration > wind speed > relative humidity (RHU) > sunshine duration > precipitation. The descending rank of climate and permafrost variables according to their contributions to runoff was the following: precipitation > sunshine duration > permafrost coverage > evapotranspiration > relative humidity (RHU) > mean DPT > wind speed > maximum DPT > air temperature. The model demonstrated good prediction results. The outputs can provide scientific references in applications related to water resources and the protection of ecologically vulnerable areas in high-cold regions.

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