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。本研究旨在为颗粒增强(PS)材料的合金设计提供基础知识。许多PS材料被热不稳定的沉淀物强化。析出物的粗化对PS材料的蠕变性能有很大影响。采用基于非稳态蠕变概念的蠕变方程：Epsilon=A{1-exp(-Alphat)}+beta{exp(Alphat)-1}epsilon：应变，t：时间(1)该方程有三个参数A、B和α，描述了材料的蠕变变形。这些参数为组织退化、蠕变机理和合金设计提供了有用的信息。PS材料通常具有通过热挤压制成的细长的颗粒形状。颗粒形状对蠕变强度有显著影响。由于相容要求，蠕变变形被限制在晶界。晶界滑动释放了约束，从而提高了蠕变变形。这是蠕变强度随晶形变化的原因。以α2-Ti3Al/γ-TiAl层状金属间化合物为例，对其蠕变行为进行了研究。团聚体尺寸的粗化和伽马体积分数的增加导致了更高的蠕变抗力。然而，片层间距对蠕变强度没有影响。在合金设计中，我们必须知道材料在使用条件下的蠕变性能。长期属性是通过从短期数据外推来评估的，而外推引入了误差。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.