P91 steel has been a highly researched material because of its applicability for high-temperature applications. Considerable efforts have been made to produce experimental creep data and develop models for creep life prediction. As creep tests are expensive and difficult to conduct, it is vital to develop authenticated empirical methods from experimental results that can be utilized for better understanding of creep behavior and can be incorporated into computational models for reliable prediction of creep life. In this research, a series of creep rupture tests are performed on the P91 specimens within a stress range of 155 MPa to 200 MPa and temperature range of 640 oC (913 K) to 675 oC (948 K). The microstructure, hardness, and fracture surfaces of the specimens are investigated. To analyze the results of the creep rupture tests at a macro level, a parameter called creep work density is derived. Then, the relationships between various creep parameters such as strain, strain rate, time to rupture, creep damage tolerance factor, and creep work density are investigated, and various empirical equations are obtained.

The type, volume fraction, size, shape and arrangement of embedded particles influence the mechanical properties of the particle reinforced metal matrix composites. This presents the investigation of the SiC particle and porosity distributions in various aluminum matrix composites produced by cold- and hot-pressing. The microstructures were characterized by optical microscopy and stereological parameters. SiC and porosity volume fractions, and the anisotropy distribution function were measured to establish the influence of the consolidation method.

This paper presents a new approach for analyzing the microstructure of -reinforced aluminum matrix composites from digital images. Various samples of aluminum matrix composite were fabricated by hot pressing the powder mixtures with certain volume and size combinations of pure Al and SiC particles. Microstructures of the samples were analyzed by computer-based image processing methods. Since the conventional methods are not suitable for separating phases of such complex microstructures, some new algorithms have been developed for the improved recognition and characterization of the particles in the metal matrix composites.