Additive manufacturing has revolutionized the manufacturing industry, particularly in aerospace. This paper provides an overview of the advancements, state-of-the-art, challenges, and future of additive manufacturing in the aerospace industry. It begins by discussing the workflow of additive manufacturing and the comparison of software required for modeling and slicing the designed models. Various types of additive manufacturing processes used in the aerospace industry with their postprocessing challenges and solutions are also presented in detail. Besides, the challenges and limitations that come with the use of additive manufacturing in aerospace are also outlined. The paper investigated that the use of additive manufacturing in aerospace has given several advantages such as the ability to produce complex geometries, reduce material waste, and improve design flexibility. The future of additive manufacturing in aerospace looks promising, with the potential for even more cost-effective and efficient production. The paper concludes that additive manufacturing has proven to be a game-changer in aerospace presenting different advanced aerospace components in detail, with continued research and development shaping the future of manufacturing and production. With advancements in technology and processes, additive manufacturing for aerospace can overcome the challenges and become a reliable and cost-effective alternative to traditional manufacturing methods.

Coal is a major fuel source but raises environmental concerns. This study investigated the feasibility of utilizing a composite briquette sustainable fuel produced from subbituminous coal and Jatropha curcas biomass. Briquettes were prepared with varying weight ratios of coal to J. curcas biomass (90:0–0:90) using corn starch as a binder. The influence of this ratio on the briquettes’ properties was comprehensively evaluated through proximate analysis, ultimate analysis, scanning electron microscopy (SEM), and X‐ray fluorescence (XRF) analysis. The results revealed that increasing the J. curcas content in the briquettes gradually decreased the moisture content, ash content, and fixed carbon content while increasing the volatile matter content. The elemental composition analysis showed a decreasing trend in carbon and sulfur content with increasing J. curcas , while nitrogen and oxygen content increased. The gross calorific value (GCV) exhibited a significant positive correlation with the coal content, reaching a maximum value of 28.29 MJ/kg for briquettes specially composed of J. curcas biomass. These findings suggest that coal– J. curcas briquettes offer a promising alternative fuel source with tailorable properties depending on the desired balance between burning characteristics and calorific value. Further research could explore the combustion behavior and emission profiles of these briquettes to assess their environmental impact.

The drilling process plays a crucial role in the assembly process of modern‐day manufactories. One of the major causes of component rejection during drilling operations is the incorrect selection of spindle speed and feed rate. Therefore, this study aimed to investigate the impact of process factors such as spindle speed and feed rate on torque, thrust force, temperature surface roughness, and chip formation during the drilling of AISI 1020 mild steel. A combination of finite element modeling and experimental investigation was employed to achieve the process. Specifically, the commercially available finite element software, Deform 3D, was used for simulation. The modeling results were then compared and validated with the experimental data. A high‐speed steel drill bit was utilized during the modeling and experimentation. The spindle speed was varied at 330, 410, and 510 rpm, while the feed rates were set at 0.12, 0.2, and 0.3 mm/rev. The study’s findings suggest that the spindle speed has an inverse relationship with thrust force, torque, and surface roughness, whereas it has a direct relationship with temperature. Conversely, the feed rate directly correlates with thrust force, torque, temperature, and surface roughness. Additionally, an analysis of the chips produced during the experiments revealed the impact of the cutting conditions on chip formation. The study results showed a 2–10% discrepancy between the experimental and simulation data. The ANOVA results indicated that the feed rate contributes the most to thrust force and torque, with a percentage contribution of 61.73% and 59.87%, respectively, followed by spindle speed, with a percentage contribution of 37.09% and 38.89%, respectively. Furthermore, temperature influences spindle speed the most, followed by feed rate, with percentage contributions of 67.75% and 31.11%, respectively. Moreover, the feed rate’s percentage contribution to surface roughness is higher than the spindle speed, with a contribution of 66.20% and 32.18%, respectively.

Cavitation in hydro turbines causes component deterioration that requires continuous and costly maintenance in the hydroelectric power generation stations. The Tarbela Dam Hydel Project (TDHP) in Pakistan is facing a cavitation problem in the Francis Turbine components, such as the runner and draft tube. Simulation work has been performed to examine and quantify the cavitation rate as a function of the suction head (SH) and flow velocity (FV) by utilizing a homogeneous cavitation model. The result shows that pressure fluctuation is maximum for overcrowded conditions and minimum for rated load conditions. Moreover, a higher cavitation rate is found for the part and overcrowded conditions compared to the rated load condition. Additionally, the cavitation rate becomes 50% higher when the SH increases from 5.54 to 12.34 m. Moreover, SEM results have verified the CFD results that higher FV and SH enhance the cavitation rate. Furthermore, the numerical work is validated by simplified hydrofoil geometry. The computational fluid dynamics results presented a good arrangement with the experimental data.

This research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton’s second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 s, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller’s simulation on MATLAB Simulink demonstrates the controller’s ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.