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Due to its biodegradability, biocompatibility, and mechanical properties, poly‐lactic acid (PLA) is a leading biomaterial for numerous applications, especially for fused deposition modeling and fused filament fabrication. Nonetheless, the absence of a comprehensive recycling strategy may emerge as a significant source of plastic pollution in the future. Indeed, the polymer undergoes deterioration during melt recycling, resulting in a decrease in some mechanical properties that can compromise recyclability. To improve the properties of recycled PLA, the utilization of organic fillers coming from renewable materials can be considered as a sustainable solution. The objective of this work is then to evaluate the effect of recycling (reprocessing) on a virgin raw material as well as on biocomposites based on spent coffee grounds (incorporating 5% of spend coffee grounds in weight). The different types of filaments are extruded and re‐extruded and characterized under tensile, melt flow index, and hardness tests. The results show that the increase in the number of extrusions whether for virgin PLA or the composite contributes to the diameter fluctuation. Regarding the tensile properties, the rise in the frequency of recycling shows a weakness in the tensile strength and the elongation at break. On the other hand, Young's modulus values exhibit fluctuations. Concerning the addition of the spent coffee grounds filler, no major enhancement is observed in the tensile strength and the elongation at break, which is attributed to the poor adhesion between the matrix and the filler. The recycling process affects the hardness values of PLA, leading to an increase in these values, as well as those of the composite, which can be associated with the increased crystallinity caused by the recycling process and the SCG incorporation. Highlights: Recycling and reusability strategy for poly‐lactic acid (PLA) and PLA/spent coffee grounds (SCG) filaments.Assessment of recycling effects on PLA and PLA/SCG.Mechanical characterization through tensile and hardness testing. [ABSTRACT FROM AUTHOR]

Directed energy deposition (DED), a form of additive manufacturing (AM), is gaining traction for its ability to produce complex metal parts with precise geometries. However, defects like distortion, residual stresses, and porosity can compromise part quality, leading to rejection. This research addresses this challenge by emphasizing the importance of monitoring process parameters (overlayer distance, powder feed rate, and laser path/power/spot size) to achieve desired mechanical properties. To improve DED quality and reliability, a numerical approach is presented and compared with an experimental work. The parametric finite element model and predictive methods are used to quantify and control material behavior, focusing on minimizing residual stresses and distortions. Numerical simulations using the Abaqus software 2022 are validated against experimental results to predict distortion and residual stresses. A coupled thermomechanical analysis model is employed to understand the impact of thermal distribution on the mechanical responses of the parts. Finally, new strategies based on laser scan trajectory and power are proposed to reduce residual stresses and distortions, ultimately enhancing the quality and reliability of DED-manufactured parts. [ABSTRACT FROM AUTHOR]

A high percentage of failure in pump elements originates from fatigue. This study focuses on the discharge section behavior, made of ductile iron, under dynamic load. An experimental protocol is established to collect the strain under pressurization and depressurization tests at specific locations. These experimental results are used to formulate the ultimate pressure expression function of the strain and the lateral surface of the discharge section and to validate finite element modeling. Fe-Safe is then used to assess the fatigue life cycle using different types of fatigue criteria (Coffin-Manson, Morrow, Goodman, and Soderberg). When the pressure is under 3000 PSI, pumps have an unlimited service life of 107 cycles, regardless of the criterion. However, for a pressure of 3555 PSI, only the Morrow criterion denotes a significant decrease in fatigue life cycles, as it considers the average stress. The topological optimization is then applied to the most critical pump model (with the lowest fatigue life cycle) to increase its fatigue life. Using the solid isotropic material with a penalization approach, the Abaqus Topology Optimization Module is employed. The goal is to reduce the strain energy density while keeping the volume within bounds. According to the findings, a 5% volume reduction causes the strain energy density to decrease from 1.06 to 0.66 106 J/m³. According to Morrow, the fatigue life cycle at 3,555 PSI is 782,425 longer than the initial 309,742 cycles. [ABSTRACT FROM AUTHOR]

The paper addresses the importance of incorporating material behavior models, such as plasticity and fatigue models, into the academic curricula of mechanical engineering, materials science, and structural engineering. It highlights the challenges encountered by students due to the complexity of these models and the necessary mathematical background. The primary objective is to present a systematic implementation of the Chaboche model, which integrates isotropic and kinematic hardening to simulate material behavior under cyclic loading conditions. The implementation involves employing numerical methods like the Newton–Raphson method and solving ordinary differential equations using the implicit Euler method or asymptotic approximations. The paper aims to support and inspire students, engineers, and researchers to master the implementation of material behavior models. It specifically examines the case of isotropic elastoplastic material with mixed hardening subjected to a 1-D tensile-compression test. The provided MATLAB code allows users to customize cyclic loading scenarios and analyze material responses. The article structure encompasses sections introducing the Chaboche model, detailing numerical implementation methods, integrating the model, discussing the MATLAB code (included in the appendix) and results, and concluding remarks. [ABSTRACT FROM AUTHOR]

The study of optimization methods for reliability-redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability-redundancy allocation problems. Results from a literature survey show the best results found for series, series-parallel, bridge, and applied case problems (e.g., over-speeding gas turbine benchmark). Review of literature from recent years indicates an extensive improvement in the algorithm reliability performance. However, this improvement has been difficult to achieve for high-reliability applications. Insights and future challenges in reliability-redundancy allocation problems optimization are also discussed in this paper. [ABSTRACT FROM AUTHOR]