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Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed ( ), plunge force ( ), and welding speed ( ) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables ( , , ,) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

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The effects of surface modification of jute fibers and nanoclay on jute–biopol green composites are evaluated by the thermal and interlaminar shear strength (ILSS) characterizations. Four subsequent chemical treatments including detergent washing, dewaxing, alkali treatment, and acetic acid treatment were performed to facilitate better bonding between the fiber and matrix. The scanning electron microscopy and Fourier transform infrared spectroscopy study confirmed improved fiber surfaces for better adhesion with matrix after final treatment. Enhanced thermal performance and tensile properties were obtained due to chemical treatments. Montmorillonite K10 nanoclay (2–4 wt.%) was dispersed into a biodegradable polymer, biopol, using solution intercalation technique and magnetic stirring. Nanoclay-infused biopol resulted in 7% improvement in the degree of crystallinity over the neat biopol. Jute fiber-reinforced biopol biocomposites with and without nanoclay were produced using treated and untreated jute fibers by the compression molding process. Treated jute fiber-reinforced biopol composites (TJBC) without nanoclay showed 5% and 9% increases in decomposition temperature and storage modulus, respectively, and 19% decrease in coefficient of thermal expansion compared to untreated jute fiber-reinforced biopol composites (UTJBC). The respective values were 5%, 100%, and 45% for 4% nanoclay-infused TJBC compared to UTJBC without nanoclay. ILSS evaluated by the short-beam shear tests, improved by 20% in the TJBC compared to the UTJBC. Incorporation of 4 wt.% nanoclay in TJBC further improved the ILSS by 22% compared to that of TJBC without nanoclay.

Friction stir welding (FSW) is a solid-state joining process, where joint properties largely depend on the amount of heat generation during the welding process. The objective of this paper was to develop a numerical thermomechanical model for FSW of aluminum-copper alloy AA2219 and analyze heat generation during the welding process. The thermomechanical model has been developed utilizing ANSYS Ò APDL. The model was verified by comparing simulated temperature profile of three different weld schedules (i.e., different combinations of weld parameters in real weld situations) from simulation with experimental results. Furthermore, the verified model was used to analyze the effect of different weld parameters on heat generation. Among all the weld parameters, the effect of rotational speed on heat generation is the highest.