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Fused Filament Fabrication (FFF), a process parameters-dependent manufacturing method, currently dominates the additive manufacturing (AM) sector because of its prominent ability to produce parts with intricate profiles, customise products, and minimise waste. Though the effects of FFF process parameters were investigated experimentally, recent research highlighted the importance of developing numerical modelling and computational methods on optimising the FFF printing process and FFF-printed materials. This study aims to investigate the tensile strength (TS) of FFF-printed high-impact polystyrene (HIPS) via devising a systematic testing and analysis framework, which combines experimental testing, representative volume element (RVE)-finite element method (FEM), rule of mixture (ROM), and artificial neural networks (ANN). HIPS samples are fabricated using FFF considering the variations of infill density, layer thickness, nozzle temperature, raster angle, and build orientation, and tested with standard tensile testing. The rule of mixtures (ROM) and its modified version (MROM) are employed to calculate the TS of longitudinally and transversely built samples at various infill densities, respectively, while an ANN model is constructed to investigate the effect of material anisotropy precisely. The optimal ANN architecture is built with five hidden layers with the number of neurons in each layer as 44, 82, 169, 362, and 50. Although both MROM and ANN perform well on the validation set, ANN exhibits superior accuracy with only a maximum error of 0.13% for training set and 11% for validation set. The combination of the RVE-FEM, MROM, and ANN approaches can significantly improve the FFF printing process of polymers for optimisation.

This paper investigates the flow of blood through a slanted stenosed artery beneath the impact of a magnetism field. The equations that control the behavior of blood use a type of derivative called Caputo Fabrizio time fractional derivatives. These equations explain that blood acts like a non-Newtonian Casson fluid. The objective of this study is to explore the governing equations of blood flow in a narrow artery by utilizing Caputo Fabrizio fractional derivatives. Using the Laplace and limited Hankel changes of arrange zero, expository arrangements for the overseeing conditions have been inferred. Using the Akbari Ganji method, simple math problems have been solved and transformed into simpler forms. Answers have been found using this method. This article introduces a new approach by applying the AGM analytical and numerical method to address dimensionless fractional equations related to velocity and pressure, in conjunction with the Capato method, marking a significant innovation. Generally, the velocity of the particles is slower than the velocity of the blood. Anyway, the Reynolds number and Casson's liquid parameters are incrementing in both blood and molecule velocities. However, blood velocity diminishes with an increment within the Hartmann number. These discoveries hold noteworthy suggestions for the progress of atherosclerosis treatment. The narrowing of the diameter of the blood vessel with a radius of 45° and a relative percentage of 35 increases the flow resistance and height of the stenosis.