Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs) with statistical equivalent fiber distribution against the actual material microstructure. The realistic statistical data is utilized as inputs of the new method, which is archived through implementation of the probability equations. Extensive statistical analysis is conducted to examine the capability of the proposed method and to compare it with existing methods. It is found that the proposed method presents a good match with experimental results in all aspects including the nearest neighbor distance, nearest neighbor orientation, Ripley’s K function, and the radial distribution function. Finite element analysis is presented to predict the effective elastic properties of a carbon/epoxy composite, to validate the generated random representative volume elements, and to provide insights of the effect of fiber distribution on the elastic properties. The present algorithm is shown to be highly accurate and can be used to generate statistically equivalent RVEs for not only fiber-reinforced composites but also other materials such as foam materials and particle-reinforced composites.

Composite materials have been widely used in recent years due to an attractive combination of superior physical properties. Since the macroscopic properties of a composite material are determined by the microscopic structure of the bottom layers, it is critical to calculate the macroscopic elastic modulus of single-layer plates using the elastic modulus of the component material(s) in a scientific and effective manner. The traditional Halpin–Tsai model only considers two materials when calculating the macroscopic elastic modulus. This paper proposes an improved model considering three-phase components (fiber, matrix, and interface). A finite element representative volume element is created to determine the empirical parameter ξ, and its overall validity is established by comparing it with the experimental results. This improved model offers more convenience in predicting the macroscopic elastic modulus of a composite material and can even predict the overall mechanical properties based solely on the mechanical properties of the component material.

This article presents a comprehensive experimental and numerical study to investigate the effects of strain rate and temperature on flow stress and ductile failure strain of three aluminum alloys. The test matrix includes smooth and notched round tensile specimens tested at room temperature (24 ℃) and two elevated temperatures (66 ℃ and 149 ℃), and under different strain rates. For 5083-H116, three loading rates are considered at 24 ℃ and it is found that the flow stress and failure strain are lowest at the intermediate strain rate. At high strain rate, the flow stresses of 5083-H116 and 6082-T6 are higher than the quasi-static loading while the flow stress of the 5183 weld metal remains unchanged; the ductility of the 5XXX alloys shows a significant increase compared to the quasi-static loading while the ductility of 6082-T6 does not change much. The study indicates that the Johnson–Cook plasticity and fracture models can be used to describe the temperature dependencies of the flow stress and the failure strain for 6082-T6 but not the 5XXX alloys. At 66 ℃ the 5XXX alloys do not display temperature softening compared to 24 ℃ while their ductility is reduced. As temperature is elevated to 149 ℃, the flow stress of the 5XXX alloys decreases while the ductility increases. The unconventional behavior of the 5XXX alloys in certain temperature and strain rate ranges has been attributed to the dynamic strain aging effect. The study also suggests that the dependency of the failure strain on stress triaxiality can be described by the Johnson–Cook fracture model for all three materials under quasi-static loading at room temperature and the model parameters are calibrated using an inverse method combining experimental results with finite element analysis.

Since the first successful on-orbit repair mission in 1984 to the Solar Maximum Mission (SMM) satellite, considerable progress has been made in the field of On-orbit Servicing, Assembly, and Manufacturing (OSAM) of spacecraft using either human-guided or autonomous robots. This article aims to provide a review of state-of-the-art efforts in this field and the necessary technologies to achieve the ultimate objective of autonomous spacecraft repairs while in orbit. The article covers the literature relevant to OSAM, including a brief overview of OSAM, inspection technologies, manufacturing and repair technologies, state-of-the-art robotic technologies capable of performing the required tasks, and intelligent path planning of robots. The article also highlights the research’s location, timeframe, and public versus private sector efforts, and outlines future directions in this field. This article aims to foster a community of researchers and public-private partnerships working towards the common objective of autonomous robotic inspection and repair of on-orbit spacecraft.