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Precipitate Stability in Creep Resistant Ferritic Steels-Experimental Investigations and Modelling

机译:抗蠕变铁素体钢中的析出稳定性-实验研究与建模

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Predictions of long-term microstructure stability of creep resistant ferritic 9-12% Cr steels up to 200000-300000 h at temperatures up to 600-650℃ are highly interesting for safe power plant operation. At technically interesting creep conditions the microstructure stability is mainly controlled by the stability of precipitate particles. Predictions of precipitate stability have to rely on ⅰ) Microstructure characterisation methods to measure volume fractions and mean particle sizes of individual precipitate types, and ⅱ) Microstructure models to predict the evolution of precipitate volume fractions and mean sizes as functions of temperature, time and applied stress. Characterisation methods, which allow on-line particle type discrimination in 9-12% Cr steels include energy filtered transmission electron microscopy (EFTEM) and scanning electron microscopy (SEM) with atomic number contrast. Modelling of precipitate stability based on thermodynamic equilibrium calculations and multicomponent diffusion databases is demonstrated. A multi-component coarsening model gives accurate predictions of coarsening rates for MX and Laves phase precipitates in steel P92 with fit values for the interfacial energy in the expected range. For M_(23)C_6 carbides in steel P92 the model results in unexpectedly low apparent values for the interfacial energy. Modelling of published data for steel P91 indicate much higher coarsening rates for M_(23)C_6 carbides, and the fit value for the interfacial energy is as expected. A possible explanation for the low apparent value of the interfacial energy for M_(23)C_6 carbides in steel P92 is the content of boron in the steel.
机译:预测蠕变铁素体9-12%Cr钢在600-650℃的温度下长达200000-300000 h的长期组织稳定性是非常有趣的。在技​​术上令人关注的蠕变条件下,微结构稳定性主要由沉淀颗粒的稳定性控制。沉淀物稳定性的预测必须依靠ⅰ)微观结构表征方法来测量各个沉淀物类型的体积分数和平均粒径,以及ⅱ)微观模型来预测沉淀物体积分数和平均粒径随温度,时间和应用的变化强调。允许在线鉴别9-12%Cr钢中颗粒类型的表征方法包括具有原子序数对比的能量过滤透射电子显微镜(EFTEM)和扫描电子显微镜(SEM)。演示了基于热力学平衡计算和多组分扩散数据库的沉淀物稳定性模型。多组分粗化模型可以准确预测P92钢中MX和Laves相沉淀物的粗化率,并且界面能的拟合值在预期范围内。对于P92钢中的M_(23)C_6碳化物,该模型得出的界面能的表观值出乎意料的低。对P91钢的公开数据进行建模表明,M_(23)C_6碳化物的粗化率高得多,并且界面能的拟合值符合预期。 P92钢中M_(23)C_6碳化物的界面能表观值低的可能解释是钢中硼的含量。

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