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High temperature oxidation of duplex stainless steel 2205 was carried out in the simulated combustion atmosphere of natural gas (i.e. 3%O2-10%CO2-18%H2O-N2) from 1100 to 1260°C by means of weight gain, X-ray diffraction and scanning electron microscope. The results show that the initial oxidation kinetics submits to parabolic law and nodules are formed at about 1180°C. The oxidation rate increases slowly from 1100 to 1220°C but dramatically at 1260°C because of the fast growth of nodules. The nodules consist of three thin oxide layers, i.e. the external Fe-rich oxides, the mid-Fe-Cr spinels and the internal Cr-rich oxides. It is suggested that the reheating temperature should be below 1180°C for removing the oxide scales in pickling. [ABSTRACT FROM AUTHOR]

According to simulation analysis of the advanced integral equation model (AIEM), there is a good linear relationship between emissivity and soil moisture under conditions of given roughness. The normalized difference of emissivities at 19.35 GHz and 10.65 GHz with vertical polarization can partly eliminate the influence of roughness and the squared correlation coefficient is about 0.985. This paper uses the normalized brightness temperature for retrieving soil moisture in Tibet from TRMM/TMI data. This method avoids parametrizing the land surface temperature which is a key parameter for the computation of emissivity. We make some sensitivity analysis for the atmosphere which is the main influence factor for our method. The analysis results indicate that our method is very good for clear days but is not very good when there is rainfall. We evaluate our algorithm by using the ground truth data obtained from GAME-Tibet and the retrieval error of soil moisture is about 0.04m3 m-3 relative to experimental data. The analysis indicates that the relationship obtained from the theoretical model should be revised through the local ground measurement data because the method is still influenced by roughness and vegetation. After making a regression revision, the retrieval error of soil moisture is under 0.02m3 m-3. Finally, we retrieve the soil moisture in Tibet from TRMM/TMI data, and the distribution trend of retrieval results is consistent with the real world. [ABSTRACT FROM AUTHOR]