A concise state-of-the-art survey of fiber-reinforced polymer ͑also known as fiber-reinforced plastic͒ composites for construction applications in civil engineering is presented. The paper is organized into separate sections on structural shapes, bridge decks, internal reinforcements, externally bonded reinforcements, and standards and codes. Each section includes a historical review, the current state of the art, and future challenges.

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Various methods have been developed to perform atomistic-scale simulations for the cross-linking of polymers. Most of these methods involve connecting the reactive sites of the monomers, but these typically do not capture the entire reaction process from the reactants to final products through transition states. Experimental time scales for cross-linking reactions in polymers range from minutes to hours, which are time scales that are inaccessible to atomistic-scale simulations. Because simulating reactions on realistic time scales is computationally expensive, in this investigation, an accelerated simulation method was developed within the ReaxFF reactive force field framework. In this method, the reactants are tracked until they reach a nonreactive configuration that provides a good starting point for a reactive event. Subsequently, the reactants are provided with a sufficient amount of energy-equivalent or slightly larger than their lowest-energy reaction barrier-to overcome the barrier for the cross-linking process and form desired products. This allows simulation of cross-linking at realistic, low temperatures, which helps to mimic chemical reactions and avoids unwanted high-temperature side reactions and still allows us to reject high-barrier events. It should be noted that not all accelerated events are successful as high local strain can lead to reaction rejections. The validity of the ReaxFF force field was tested for three different types of transition state, possibly for polymerization of epoxides, and good agreement with quantum mechanical methods was observed. The accelerated method was further implemented to study the cross-linking of diglycidyl ether of bisphenol F (bis F) and diethyltoluenediamine (DETDA), and a reasonably high percentage (82%) of cross-linking was obtained. The simulated cross-linked polymer was then tested for density, glass transition temperature, and modulus and found to be in good agreement with experiments. Results indicate that this newly developed accelerated simulation method in ReaxFF can be a useful tool to perform atomistic-scale simulations on polymerization processes that have a relatively high reaction barrier at a realistic, low temperature.

Utilizing electrically conductive nanocomposites for integrated self-sensing and health monitoring is a promising area of structural health monitoring (SHM) research wherein local changes in conductivity coincide with damage. In this research we conduct proof of concept investigations using electrical impedance tomography (EIT) for damage detection by identifying conductivity changes and by imaging conductivity evolution in a carbon nanofiber (CNF) filled epoxy composite. CNF/epoxy is examined because fibrous composites can be manufactured with a CNF/epoxy matrix thereby enabling the entire matrix to become self-sensing. We also study the mechanisms of conductivity evolution in CNF/epoxy through electrical impedance spectroscopy (EIS) testing. The results of these tests indicate that thermal expansion is responsible for conductivity evolution in a CNF/epoxy composite.

The objective of this paper is to define a rigorous numerical method to calibrate parameters of a given local bond-slip relationship using experimental results of pullout tests, taking into account the distribution of the slip and bond shear stress throughout the bar. The proposed method involves finding parameters of a given bond-slip relationship, such that results of pullout tests can be predicted in terms of applied pullout force and consequent slip at the loaded end and slip at the free end. The method is applied to some experimental data, and the results are discussed. For the application of the proposed method, two analytical expressions of the bond-slip relationship are selected, even though it could be applied to any analytical expression. An example of determination of anchorage length starting from the knowledge of the local bond-slip relationship is given.

The conductivity of glass fiber reinforced polymers with nanocomposite matrices can be leveraged for structural health monitoring. Since nanocomposite matrices depend on well-connected networks of conductive nanofillers for electrical conductivity, matrix damage will sever the connection between fillers and result in a local conductivity loss. Monitoring composite conductivity changes can therefore give insight into the state of the matrix. Existing conductivity-based structural health monitoring methods are either insensitive to matrix damage or employ large electrode arrays. This research advances the state of the art by combining the superior imaging capabilities of electrical impedance tomography with conductive networks of nanofillers in the composite matrix. Electrical impedance tomography for damage detection in glass fiber/epoxy laminates with carbon black nanocomposite matrices is characterized by identifying a lower threshold of through-hole detection, demonstrating the capability of electrical impedance tomography to accurately resolve multiple through holes, and locating impact damage. It is found that through holes as small as 3.18 mm in diameter can be detected, and electrical impedance tomography can detect multiple through holes. However, sensitivity to new through holes is diminished in the presence of existing through holes unless a damaged baseline is used. Finally, it is shown that electrical impedance tomography is also able to accurately locate impact damage. These research findings demonstrate the considerable potential of conductivity-based health monitoring for glass fiber reinforced polymer laminates with conductive networks of nanoparticles in the matrix.

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