LM26 is a cast aluminum-silicon alloy that exhibits superior castability, moderate strength, and high corrosion resistance. Silicon is typically the primary alloying agent in aluminium alloy LM26. The present study investigates the development of hybrid composites and the machining of aluminium alloy LM26 reinforced with varying weight percentages (0.25%, 0.5%, and 0.75%) of multi-wall carbon nanotubes (MWCNTs), with a focus on sustainable machining. The casting was performed by stir casting at 700°C and 650 rpm. In this study, the Central Composite design is used to design the experiment, and Response Surface Methodology (RSM) is employed to develop a quadratic (polynomial) equation using Design-Expert software V13. The milling experiment was conducted on MWCNT-reinforced LM26 material using a milling machine, with spindle speed, feed rate, depth of cut, and MWCNT percentage as parameters, to measure surface roughness (Ra) and temperature (T). Microstructural characterization of the composite was performed. The performance characteristics were analyzed using ANOVA. This result shows that wt.% of MWCNT is an influential factor in minimizing Ra, while spindle speed affects Ra, and feed rate affects temperature. Based on the results, it has been concluded that adding 0.25% wt. of MWCNTs has improved machinability; however, increasing the MWCNT content increases Ra and temperature. To achieve better machining performance that meets sustainability criteria, a Multi-Objective Genetic Algorithm was employed to optimize the objectives. The MOGA was adopted to solve the optimization problem, yielding 21 non-dominated Pareto-optimal solutions. This study has identified several alternatives to help academics and industry develop environmentally friendly, sustainable machining techniques.

Fused Deposition Modeling (FDM), the preferred additive manufacturing technology used for creating plastic-based parts, due to its affordability and simplicity of use. A well-known material used in FDM is Polylactic acid (PLA); however, its mechanical properties limit its use as a functional part for many applications. This research investigates the effect Copper-reinforcement has on PLA material's ultimate tensile strength (UTS) during production with a FDM process. The max tensile strength measured during this study was produced using a combination of low layer thickness (0.14 mm), high infill (90%), and high printing speed (100 mm/s). The wall thickness had a point of maximum tensile strength which was found at approximately 1.2 mm before strength began to decrease. Surface finish results were achieved with a combination of 0.14 mm layer thickness, 95 mm/s printing speed, 85% infill, and 1.0 mm wall thickness, and deviations from these settings led to increased roughness due to thermal and structural factors. Multi-objective evolutionary algorithm-based optimization MOEA/D method produced a combined "knee" point for tensile strength that was greater than all the highest experimental tensile strength measures while maintaining surface roughness identical to established through experimental means, demonstrating the effectiveness of multi-objective FDM parameter optimization utilizing it.

Laser Powder Bed Fusion (L-PBF) of nickel superalloy Inconel 625 (IN625) is widely adopted for fatigue-critical aerospace and energy applications. The accuracy of finite element method (FEM) fatigue predictions depends critically on the Basquin fatigue constants used, yet most FEM studies apply generic material library values without calibration to the actual process-specific material state. This study presents a systematic FEM-based fatigue assessment of L-PBF IN625 specimens (ASTM E466) under constant amplitude axial loading (20–60 kN, R = 0.1) and quantifies the effect of Basquin constant calibration on fatigue life, damage, and safe load predictions. Stress-life (S-N) analysis was performed in ANSYS Workbench 2021 R2 using SOLID187 tetrahedral elements (148,563 nodes; 35,532 elements). The Basquin fatigue strength coefficient was calibrated from published fatigue failure data for L-PBF IN625 (Poulin et al., ≤0.1% porosity, R = 0.1), yielding σ'f = 2050 MPa with b = −0.134 fixed at the literature consensus value. Compared to the ANSYS library constants (σ'f = 2282 MPa, b = −0.134), the calibrated constants reduce predicted fatigue life by 55% across all load levels. The critical safe load threshold (safety factor SF = 1.0) shifts from 23.6 kN (library) to 21.2 kN (calibrated), a 10.2% reduction with direct design implications. The calibrated model is validated against three independent published experimental datasets for L-PBF IN625, showing improved agreement in the finite-life regime. These results establish that uncalibrated material library constants systematically overestimate L-PBF IN625 fatigue performance and provide quantitative guidance for safe load determination in fatigue-critical AM components.

In the present work, a statistical modeling of the % increase in von-Mises and Tresca stress was done for a structural steel pipe containing a quarter-ellipsoidal internal corrosion defect subjected to internal hydrostatic pressure. An analytical solution was developed considering the internal corrosion defect length (z), width (x), depth (y), and internal hydrostatic pressure (P) as independent variables. The finite element analysis (FEA) simulated dataset was used for modeling. The analytical equations demonstrated high predictive accuracy, with coefficients of determination (R²) of 98.64% for von Mises stress and 98.38% for Tresca stress. The stress distribution from FEA was nearly similar quantitatively for both stresses; however, their patterns exhibited noticeable differences in their respective profiles inside and outside of the curvature of the internal corrosion defect. The contour plots for the percentage increase in von-Mises and Tresca stresses revealed both elastic and plastic regimes. The maximum percentage increase in von Mises stress remained slightly below the ultimate tensile strength of the specimen. In contrast, the contour plots for Tresca stress indicated a limited region in which the stress exceeded the ultimate tensile strength. For the linear effect, the geometrical variable x (width of the internal corrosion defect) exhibited a negative T-value, indicating that an increase in x reduces the percentage increase in both von Mises and Tresca stresses. The significance of standardized effects for von-Mises stress was in the order of P > y > z > x > zy> yp> zz> xy> xP> zP> xx. However, for the Tresca stress, the order was P > y > x > z > zy> yp> xy> zz> xP> zP> xx. The steel pipe with an internal corrosion defect of minimum length (z = 30 mm), maximum width (x = 134 mm), and minimum depth (y = 0.5 mm) exhibited the lowest von Mises and Tresca stresses. However, the maximum stresses were observed for a defect with maximum length (z = 454 mm), minimum width (x = 26 mm), and maximum depth (y = 1.5 mm).

In the present work, a statistical modeling of the % increase in von-Mises and Tresca stress was done for a structural steel pipe containing a quarter-ellipsoidal internal corrosion defect subjected to internal hydrostatic pressure. An analytical solution was developed considering the internal corrosion defect length (z), width (x), depth (y), and internal hydrostatic pressure (P) as independent variables. The finite element analysis (FEA) simulated dataset was used for modeling. The analytical equations demonstrated high predictive accuracy, with coefficients of determination (R²) of 98.64% for von Mises stress and 98.38% for Tresca stress. The stress distribution from FEA was nearly similar quantitatively for both stresses; however, their patterns exhibited noticeable differences in their respective profiles inside and outside of the curvature of the internal corrosion defect. The contour plots for the percentage increase in von-Mises and Tresca stresses revealed both elastic and plastic regimes. The maximum percentage increase in von Mises stress remained slightly below the ultimate tensile strength of the specimen. In contrast, the contour plots for Tresca stress indicated a limited region in which the stress exceeded the ultimate tensile strength. For the linear effect, the geometrical variable x (width of the internal corrosion defect) exhibited a negative T-value, indicating that an increase in x reduces the percentage increase in both von Mises and Tresca stresses. The significance of standardized effects for von-Mises stress was in the order of P > y > z > x > zy> yp> zz> xy> xP> zP> xx. However, for the Tresca stress, the order was P > y > x > z > zy> yp> xy> zz> xP> zP> xx. The steel pipe with an internal corrosion defect of minimum length (z = 30 mm), maximum width (x = 134 mm), and minimum depth (y = 0.5 mm) exhibited the lowest von Mises and Tresca stresses. However, the maximum stresses were observed for a defect with maximum length (z = 454 mm), minimum width (x = 26 mm), and maximum depth (y = 1.5 mm).

Predicting drilling parameters accurately to guarantee the creation of high-quality holes is a critical task in the field of precision machining. The optimisation of drilling parameters for excellent hole quality is the main subject of this scientific study paper, which explores the field of predictive modelling. In order to predict thrust force, delamination, and surface roughness, the research presents a unique method that utilizes the Gated Recurrent Unit (GRU) and recurrent neural network (RNN) architecture. The main goal is to use an Adaptive Fire Hawk Optimiser (AFHO) to guide the GRU model towards ideal hyperparameters. Through systematic experimentation and meticulous analysis, the study showcases the model's capability to forecast drilling outcomes with unprecedented precision, thereby streamlining the machining process and contributing to the advancement of quality hole production.

Fracture toughness is a key engineering design parameter. Fracture of engineering materials and components may occur under 3 basic deformations or modes namely pure mode I (opening), pure mode II (shearing) and pure mode III (tearing). However, in practice the possibility of fracturing under mixed mode I/II, I/III and general mixed mode I/II/III case are more than the pure modes. Several experimental methods and testing specimens have been employed by the fracture mechanics researcher to determine the fracture toughness of engineering materials under different mode mixities. Among them, a recently designed and proposed test configuration named Edge-Notched-Disc-Bend (ENDB) is a suitable and favorite testing method for conducting general mixed-mode I/II/III fracture toughness experiments. In this research following a brief description of the ENDB specimen, a review of some recently published papers for investigating the mixed mode fracture problem is presented. According to such a review, it can be concluded that the ENDB method is a suitable candidate specimen for studying general mixed-mode I/II/III fracture problems in materials with brittle or quasi-brittle nature.

Aluminum 1100 is a commercially pure aluminum alloy with properties suitable for applications requiring ductility and workability. It is soft, weldable, and corrosion-resistant. This study attempts to determine the influence of machining on high-speed turning operations. The experiment is designed using the Design of Experiments of Response Surface Methodology, using input parameters such as cutting speed, feed rate, and cutting depth, to estimate surface roughness, temperature, and machining time of aluminum1100 as the workpiece material, with a carbide tool used for operation. The Analysis of Variance technique has been used to test the material's performance. In contrast, the Design Expert software has been used to study the impact of cutting parameters on the workpiece. A Backpropagation ANN model is developed in MATLAB to optimize cutting parameters and reduce Ra, T, and Tm values. The ANN indicates that the lowest expected value is in this case. The Multi-Objective Genetic Algorithms are employed to forecast turning parameters, and it is observed that, for an input parameter grouping of 16 Pareto-optimal solution sets, the ideal Ra ranges from 1.37 to 1.62 µm, and the temperature ranges from 34.10 to 34.08 °C. The machining time ranges from 1.27 to 1.34 min. Among all, cutting speed has the greatest influence on the parameter. The confirmatory analysis shows that the experimental and predicted values differ by less than ±2% and agree admirably with the experimental values.

This study investigates the ballistic response of multilayer jute/epoxy laminates subjected to 9 mm projectile impact through a combined experimental and numerical approach. Experimental results show that, at an impact velocity of 356 m/s, the projectile penetrates only 7-8 layers of a 39-layer laminate and rebounds without back-face deformation. A finite element model is developed and validated against experimental observations, showing good agreement in terms of penetration depth and damage mechanisms. A parametric analysis is conducted by varying the laminate thickness (number of layers) to determine the ballistic limit and the minimum thickness required for projectile arrest. The results identify a transition region between 23 and 26 layers, where the response changes from complete perforation to full projectile arrest, highlighting the strong influence of laminate thickness on ballistic performance.

Rapid advances in 3D printing enable the automotive sector to shorten the design cycles, improve flexibility and support customised manufacturing, overcoming the limitations of conventional methods. However, direct comparisons of impact performance particularly those employing instrumented techniques to analyse strain–time signals between SLM-produced SS 316L specimens of varying thicknesses and these specific conventional reference materials remain limited, leading to uncertainty regarding the use of Additive Manufacturing (AM) parts in safety-critical applications. This study aims to assess the strength of additive manufacturing Stainless Steel 316L (SS 316L) powder at various specimen thicknesses and to compare it against the conventional SS 304 and Al 6061-T6. To capture the strain signal, a Charpy machine, a data acquisition system and strain gauges were used in the experiment. Specimen preparation followed the ASTM E8 for tensile test and ASTM E23 for the Charpy impact. Charpy specimens with thicknesses 5, 7.5 and 10 mm were fabricated using an Ermaksan Enavision 120 Selective Laser Melting (SLM) 3D printer under controlled parameters. Results show that increase in specimen thicknesses proportionally increase the absorbed energy and the area under the curve. Compared to reference material, SS 304 exhibited highest impact resistance, followed by AM SS 316L and Al 6061-T6. These findings demonstrate that AM materials can closely match the performance of conventional material. Furthermore, optimising SLM parameters and applying post-processing can improve impact toughness.