Alloy Design for Paticle Strengthened Materials for High Temperature Use

颗粒强化是提高蠕变强度的最有效途径。本研究旨在为颗粒强化（PS）材料的合金设计提供基础知识.许多PS材料是由热不稳定的沉淀物强化的。析出相的粗化强烈影响PS材料的蠕变性能。PS材料的蠕变数据已通过以下基于非稳态蠕变概念的蠕变方程进行分析：ε =A {1-exp（-ε at）} + β {exp（ε at）-1} ε：应变，t：时间（1）该方程具有表征蠕变变形的三个参数，A、B和α。这些参数为合金的组织退化、蠕变机制和合金设计提供了有用的信息. PS材料通常具有通过热挤出制成的细长颗粒形状。晶粒形状对蠕变强度有显著影响。由于相容性要求，蠕变变形被限制在晶界处。晶界滑移释放了约束，从而增强了蠕变变形。这是晶粒形状相关蠕变强度的原因.以α_2-Ti_3Al/γ-TiAl层状金属间化合物为例，研究了其蠕变行为。菌落尺寸的粗化和γ体积分数的增加导致更高的抗蠕变性。片层间距对蠕变强度没有影响.在合金设计中，我们必须了解材料在使用条件下的蠕变性能。通过从短期数据外推来评估长期性质，并且外推引入误差。讨论了外推误差产生的原因，并提出了消除外推误差的方法。

Particle strengthening is the most effective way for improving creep strength. This study aims at providing basic knowledge of alloy design for particle strengthened (PS) materials.1. Many of PS materials are strengthened by thermally unstable precipitates. The coarsening of the precipitates strongly affects creep properties of PS materials. Creep data of PS materials have been analyzed by the following creep equation based on non-steady-state creep concept :epsilon=A {1-exp(-alphat)} +beta {exp(alphat)-1} epsilon : strain, t : time (1)This equation has three parameters, A,B and alpha, that characterize creep deformation. These parameters provide useful information about microstructural degradation, creep mechanism and alloy design.2. PS materials often have an elongated grain shape made by hot extrusion. The grain shape has a significant effect on creep strength. Creep deformation is constrained at grain boundaries due to the compatibility requirement. Grain boundary sliding releases the constraint, and consequently enhances creep deformation. This is the cause of the grain shape dependent creep strength.3. Creep of alpha_2-Ti_3Al/gamma-TiAl lamellar intermetallics has been studied as an example of composite materials. Coarsening of colony size and increase in gamma volume fraction result in higher creep resistance. Lamellar spacing, however, has no effect on creep strength.4. In the alloy design, we must know creep properties under a service condition of the material. The long term properties are evaluated by extrapolation from short term data, and the extrapolation introduces an error. The cause of the extrapolation error has been discussed, and it has been proposed how to eliminate the extrapolation error.