This paper describes an experimental investigation on mono steel and polypropylene (PP) fiber-reinforced concrete beams. The main aim of this present study is to evaluate undamaged and damaged reinforced concrete (RC) beams incorporated with mono fibers such as steel and PP fibers under free-free constraints. In this experimental work, a total of nine RC beams were cast and analyzed in order to study the dynamic behavior as well as the static load behavior of steel fiber-reinforced concrete (SFRCs) and polypropylene fiber-reinforced concrete (PPFRCs). Damage to the SFRC and PPFRC beams was obtained by cracking the concrete for one of the beams in each set under four-point bending tests with different percentage variations of the damage levels such as 50%, 70% and 90% of the maximum ultimate load. The fundamental natural frequency and damping values obtained through the dynamic tests for the SFRC and PPFRC beams were compared with a control RC beam at each level of damage that had been acquired through static tests. The static experimental test results emphasize that the SFRC beam has attained a higher ultimate load compared with the control RC beam.
Fibers are raw materials used for manufacturing yarns and fabrics, and their properties are closely related to the performances of their derivatives. It is indispensable to implement fiber identification in analyzing textile raw materials. In this paper, seven common fibers, including cotton, tencel, wool, cashmere, polyethylene terephthalate (PET), polylactic acid (PLA), and polypropylene (PP), were prepared. After analyzing the merits and demerits of the current methods used to identify fibers, near-infrared (NIR) spectroscopy was used owing to its significant superiorities, the foremost of which is it can capture the tiny information differences in chemical compositions and morphological features to display the characteristic spectral curve of each fiber. First, the fibers’ spectra were collected, and then, the relationships between the vibrations of characteristic chemical groups and the corresponding wavelengths were researched to organize a spectral information library that would be beneficial to achieve quick identification and classification. Finally, to achieve intelligent detection, pattern recognition approaches, including principal component analysis (PCA) (used to extract information of interest), soft independent modeling of class analogy (SIMCA), and linear discrimination analysis (LDA) (defined using two classifiers), assisted in accomplishing fiber identification. The experimental results – obtained by combining PCA and SIMCA – displayed that five of seven target fibers, namely, cotton, tencel, PP, PLA, and PET, were distributed with 100% recognition rate and 100% rejection rate, but wool and cashmere fibers yielded confusing results and led to relatively low recognition rate because of the high proportion of similarities between these two fibers. Therefore, the six spectral bands of interest unique to wool and cashmere fibers were selected, and the absorbance intensities were imported into the classifier LDA, where wool and cashmere were group-distributed in two different regions with 100% recognition rate. Consequently, the seven target fibers were accurately and quickly distinguished by the NIR method to guide the fiber identification of textile materials.
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Nanocomposites of multiwalled carbon nanotubes (MWCNTs) in epoxy resin and polypropylene (PP) are studied. The effect of matrix viscosity on the degree of dispersion of nanotubes is determined by rheological methods. Rheology and microwave properties are correlated to estimate the optimal limits of nanofiller content required for improving the performance of nanocomposites. Rheological percolation threshold is determined for both types nanocomposites, ϕp=0.27% for the epoxy/MWCNT and; ϕp=1.5% for the PP/MWCNT, as found critical for achieving a network structure of interacting nanotubes in the matrix polymer. Good electromagnetic shielding efficiency was obtained for nanocomposites at nanotube contents above the rheological percolation. Low viscosity matrix facilitates contacts between MWCNTs, resulting in appearance of electromagnetic shielding at very low percolation threshold.
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