No abstract

Continuous parallel alumina fiber-reinforced metals produced by pressure infiltration are tested in tension/compression along the fiber axis with a goal of measuring the influence exerted by long fibers on the flow stress of their matrix. In this configuration, the equistrain rule of mixtures, modified to take into account stresses due to differential lateral contraction, can be used to back-calculate the matrix flow stress from that of the composite. This method provides the least physically ambiguous measurement of matrix flow stress in the composite; however, experimental uncertainty can be high. This uncertainty is evaluated in detail for the present experiments, in which matrix in situ stressstrain curves are measured for cast 3M NEXTEL 610 and DUPONT FIBER FP reinforced pure and alloyed aluminum-and copper-based matrices of varying propensity for recovery and cross-slip. Within experimental uncertainty, data show no enhanced matrix work-hardening rates such as those those that have been measured with tungsten fiber-reinforced copper. It is found that the fibers alter the matrix plastic flow behavior by increasing the flow-stress amplitude of the matrix, and by rendering initial yield in compression more progressive than in initial tension. Essentially, all observed features of matrix/fiber interaction can be rationalized as attributable to dislocation emission in the matrix caused by thermal mismatch strains within the material during composite cooldown from processing temperatures.

While conventional structures are usually designed to fulfill a single primary purpose, smart structures add the ability to sense changes in their environment and use that information in a timely manner in ways that augment their functionality. Smart structures today are increasingly found in applications as diverse as analysis and reporting of damage (health monitoring), in situ repair of structural damage (self‐healing), and physical adaptability and active response to various operating conditions (morphing structures). In this article, we start with a review of the main classes of smart materials that make building smart structures possible. We review the fundamental principles that give these materials “smart” functionality, allowing them to sense external stimuli, adapt, and respond in various ways. We also provide a detailed example of implementation of a smart structure in the real world. The ever‐increasing variety of smart materials, each with very different capabilities and requirements, gives the designer of smart structures multiple options as well as challenges in this still maturing field. Smart materials, when combined with sophisticated signal processing and control hardware made possible by modern electronics, open the door for new generations of smart structures with advanced capabilities—such as the ability to “learn” and respond accordingly—that may one day blur the line between inanimate and living systems.

No abstract

No abstract