In this research work, an attempt has been carried out to examine (investigate) and study the dry, wet and cryogenic boring of AA 7075 alloy, which is predominantly used in transport applications in defense (aeronautical parts), oceanic and automaker industries. To ensure direct supply of the coolant, and real-time measurement of cutting temperature a modified boring bar is used (modification is carried out using EDM to accommodate placement of a thermocouple to obtain real-time measurement of temperature readings during the boring cycle). It is observed that during cryogenic boring of AA 7075 alloy there is a considerable reduction in the cutting force (F_c), cutting temperature (T_c) and surface roughness (R_a) by 56.16%, 84.70%, 58.98% compared to dry boring and 48.43%, 80.70%, 34.70% compared to wet boring, respectively. Decrease in F_c and T_c leads to a reduction in high stresses at localized points during machining and in turn curtail wear in workpiece and tool. Lubrication provided by cryogenic fluids also plays a sizable role in reduction of F_c and T_c. Reduction in lower F_c and T_c has a glaring effect on the surface characteristics of the hole produced during the boring process. Tool wear is reduced in cryogenic boring by 36.96% and 17.57% compared to dry and wet boring, respectively. Taguchi and ANOVA was carried out which helped in determining feed as an important parameter with respect to F_c and R_a during boring of AA 7075 under dry, wet and cryogenic conditions whereas speed as an important parameter in determining T_c in dry and wet conditions and feed for T_c in cryogenic boring condition. TOPSIS analysis highlighted speed of 770 rpm and feed of 0.055 mm/min as the most closest to ideal solution for all three different cutting conditions. Surface morphology study after boring of AA 7075 highlighted better surface characteristics in cryogenic bored surface compared to dry and wet boring. Roughness measured in AFM for tool used in boring highlighted a decrease in 86.79% and 66.01% in cryogenic boring in juxtaposition with dry and wet boring, respectively. A surge in compressive residual stress is observed in cryogenic bored surface by 10.41% and 3.5% in juxtaposition with dry and wet boring, respectively, highlighting an abatement in tensile residual stress and better workpiece integrity as compared to dry and wet boring conditions.

An endeavor has been made to bailiwick cryogenic, wet, and dry boring of HSLA ASTM A36 steel, which is predominantly used in armor material and oil and gas pipelines. To ensure a direct coolant supply (controlled flow rate) at the cutting zone and palpable ciphering of cutting temperature, a transmogrified boring bar is exercised. Electrical discharge machining (EDM) was availed to create for the accommodation of a thermocouple slot, in an axial hole boring bar. Reduction of 16.1–59.8% and 4.3–16.7% in cutting force, 53.38–78.36% and 25.31–64.89% in cutting temperature, and 27.76–70.23% and 4.22–28.30% in surface roughness is ascertained in cryogenic milieu boring in correlation to dry and wet milieu boring, respectively. It is discerned for cutting force, speed of 88.59 m/min and 0.055 mm/min is the ideal cutting parameter for cryogenic, wet and dry boring conditions. For cutting temperature, ideal cutting parameter is speed of 88.59 m/min and 0.048 mm/min for dry and wet, respectively, and speed of 88.59 m/min and 0.055 mm/min for cryogenic boring. Additionally, speed of 88.59 m/min and 0.055 mm/min is the ideal cutting parameter for surface roughness in all three different cutting environments. From ANOVA, it is determined that speed plays a vital role in all three conditions of boring. For dry and wet boring, speed personates a notable semblance in ascertaining the cutting temperature, but in the case of cryogenic boring, feed plays an imperative part. Additionally, for surface roughness, feed is the most prominent parameter in cryogenic, wet, and dry boring. Furthermore, cryogenic machining surges the hardness of ferrite culminating in curtailed chip lengths and deficient built-up edge evolution on the cutting tool. An abatement in flank wear by 36.58% and 53.65% is ascertained in the cryogenic boring of ASTM A36 HSLA steel correlated to wet and dry boring, respectively. Boring under cryogenic condition, the crater wear reduces by 88.30% and 90.10% with respect to wet and dry boring, respectively. Scanning electron microscopy observations of bored surfaces in wet and dry boring show a network of microcracks which is absent in cryogenic boring of ASTM A36 HSLA steel. Compressive residual stress has increased by 9.5% and 31.83% in boring under cryogenic medium with respect to wet and dry boring of ASTM A36 HSLA steel. There is an overall increase in hardness value in bored surface in cryogenic medium over wet and dry bored surface by 22.26%–30.06% and 21.06–39.43%, respectively. The corrosion resistance in cryogenic boring increases by 65.26% and 29.33% with respect to wet and dry boring of ASTM A36 HSLA steel, respectively. High repercussions of geometrical features are ascertained in abatement of circularity and cylindricity of hole profile bestowing cryogenic medium of boring.

This study investigates the blast mitigation capabilities of A286 steel micro-lattice structures produced through additive manufacturing. The research explores the effects of different manufacturing conditions, such as stress relief and heat treatment, on the mechanical properties and blast resistance of honeycomb and gyroid lattice structures in correlation with armour steel structures. Comprehensive evaluations, including surface morphology, corrosion resistance, and compressive residual stress analysis, reveal notable findings for micro-lattice structures. Micro-lattice structures demonstrated 57.23% higher corrosion resistance compared to conventional materials, presently available in the form of rolled homogeneous armour, medium hardness armour, and high-nitrogen steel. Additionally, honeycomb lattice structures exhibit compressive residual stresses of up to 581.90 MPa, providing significant advantages in blast mitigation potential. These results underscore the significance of lattice geometry, material microstructure, and residual stress in enhancing blast resistance. The research offers valuable insights into optimizing additive manufactured structures as an alternative modular solution for defence applications.

The development of lightweight, corrosion-resistant metallic lattice structures has gained significant attention in aerospace, defense, and structural applications, where material durability and weight optimization are critical. This study investigates the corrosion behavior of Laser Powder Bed Fusion (LPBF)-fabricated A286 steel honeycomb, Body-Centered Cubic (BCC), and gyroid lattices, comparing their performance against conventional materials such as Rolled Homogeneous Armor (RHA), Maraging High Strength Steel (MHA), and High-Nitrogen Steel (HNS). Corrosion testing was conducted using accelerated salt spray exposure, and the results were validated through computed tomography (CT)-based structural integrity analysis and machine learning-based predictive modeling. The experimental findings revealed that lattice structures exhibited significantly lower corrosion rates than conventional bulk materials, with the honeycomb lattice demonstrating the highest corrosion resistance (1.218 mm/year), followed by BCC (1.311 mm/year) and gyroid (1.671 mm/year). Compared to RHA, the honeycomb lattice exhibited a 57.23% reduction in corrosion rate, confirming its superior electrochemical stability. CT scan evaluations further highlighted differences in density distribution and geometric fidelity, with honeycomb lattices showing the most uniform porosity, while BCC structures displayed localized density variations at nodal intersections. To enhance predictive capabilities, various machine learning (ML) algorithms were employed to model corrosion behavior based on weight-loss measurements and lattice topology. Bayesian Ridge regression outperformed other models, achieving an R² of 0.99849 and RMSE of 0.00049, confirming its robustness in capturing corrosion trends. Linear Regression also performed well, while ensemble models such as Random Forest and XGBoost exhibited higher error margins due to dataset linearity constraints. Residual analysis and graphical interpretations further validated the stability and predictive reliability of ML-based corrosion assessments, demonstrating their feasibility as an alternative to traditional experimental methods. This study presents a comprehensive framework for integrating experimental corrosion testing, computational modeling, and CT-based defect analysis, offering a scalable approach to optimizing micro-lattice designs for corrosion-sensitive applications. The findings highlight the potential of LPBF-fabricated metallic lattices for aerospace, defense, and marine structures, where enhanced corrosion resistance, reduced material degradation, and predictive maintenance strategies are essential for long-term operational performance.