Open Access

Article

Article ID: 2534

Effect of inverse-square heat absorption on MHD natural convection flow in a vertical concentric annulus with radial and induced magnetic fields

by Muhammad Yusuf Muhammad, Yusuf Ya’u Gambo, Muhammad Auwal Lawan

Mechanical Engineering Advances, Vol.3, No.2, 2025;

This study investigates the impact of inverse-square heat absorption on steady, fully developed laminar MHD natural convection flow within an infinite vertical concentric annulus under the influence of applied radial and induced magnetic fields. The governing transport equations in the model were transformed into a non-dimensional form, allowing for the derivation of unified analytical solutions for the velocity, temperature, magnetic field, and induced current density distributions for both isothermal and iso-flux on the inner cylinder of concentric annuli. The influence of key physical parameters in the model is illustrated through a comprehensive analysis of graphs and tables. The findings reveal that increasing the heat absorption parameter intensifies thermal gradients near the inner cylinder, while stronger magnetic fields suppress fluid motion, reducing mass flux and enhancing flow resistance. Mass flux and induced current density decrease as Hartmann number and heat absorption parameter increase, demonstrating the combined influence of thermal and electromagnetic forces. The magnetic field distributions and associated current densities exhibit pronounced attenuation near the inner cylinder under a higher Hartmann number. These findings highlight the intricate interaction between thermal and electromagnetic forces, offering valuable insights for applications in nuclear reactors, MHD power generation, and advanced cooling technologies. This study contributes to refining MHD-driven thermal management approaches for Advanced  engineering systems.

Open Access

Article

Article ID: 2145

Traffic-based methodology to develop peak Heat Release Rate probability distributions for sizing road tunnels ventilation systems when using a probabilistic approach

by Sonia Fernandez, Charles Fleischmann, Daniel Nilsson, Alberto Fraile

Mechanical Engineering Advances, Vol.3, No.2, 2025;

Road tunnels are a crucial part of today’s transport infrastructures worldwide. Among the installed systems, the tunnel ventilation is key, as in the case of fire, it establishes and keeps appropriate conditions for self-evacuation and emergency services operations. Recent works propose using a probabilistic approach to assess road tunnels ventilation systems’ capacity for fire scenarios. Under this approach, key design variables are defined based on probability distributions. From these distributions, the analysis uses the different possible values of the variables, including lower and upper limits as well as mean and characteristic values. The results obtained with this proposed probabilistic approach allow not only designers, but also tunnel operators and administrations, to quantify the reliability of the capacity of the ventilation system, assess its probability of failure, and define safety levels. This paper illustrates a methodology to define the design fire as a probability distribution for sizing road tunnels ventilation systems when applying the above-mentioned probabilistic approach. The methodology uses traffic information (crucial in road tunnels) and correlates it to peak Heat Release Rate (HRR) values from published reports by PIARC to obtain the design fire variable in terms of peak HRR probability distributions. The methodology is applied to two case study tunnels with different characteristics. The obtained results for the two tunnels are then compared and analyzed to peak HRR values normally recommended and used when sizing road tunnels ventilation systems to understand the uncertainty and sensitivity of the results.

Open Access

Article

Article ID: 2150

Design and implementation of a cleaning robot

by Yung-Hsiang Chen, Sheng-Yan Pan

Mechanical Engineering Advances, Vol.3, No.1, 2025;

This study focuses on the development of a cleaning robot, covering the three main aspects of mechanical design, circuit design, and software design. First, in the area of mechanical design, we created a structure capable of agile movement and efficient cleaning to ensure the robot can operate smoothly in various environments. Second, for circuit design, we developed a microcontroller-based control system to coordinate the operation of various components, including drive motors, sensors, and image recognition modules. Furthermore, in the software design aspect, we utilized YOLO (You Only Look Once) and OpenCV technologies to enable the robot to accurately identify and classify waste during the automatic cleaning process. Finally, we conducted practical cleaning experiments to verify the robot’s ability to recognize waste and the accuracy of waste classification. The experimental results show that the cleaning robot not only possesses the ability to recognize waste but also accurately classify it, demonstrating its potential for practical applications.

Open Access

Article

Article ID: 2511

Modeling penetration depth in submerged arc welding using artificial neural networks: A comprehensive approach

by Farhad Rahmati, Ali Shafipour, Masood Aghakhani, Farhad Kolahan

Mechanical Engineering Advances, Vol.3, No.1, 2025;

Penetration depth, defined as the distance from the surface of the base material to the deepest point of the molten zone, is a critical factor influencing the strength and mechanical properties of welds. This study investigates the effects of process parameters in submerged arc welding (SAW) on penetration depth, utilizing a two-hidden-layer artificial neural network (ANN) for modeling. The input parameters include arc voltage, welding current, electrode stick-out, welding speed, and the thickness of a manganese-enriched nanoparticle layer, with penetration depth as the output variable. The results demonstrate that increasing the welding current to 700 amps enhances heat transfer to the molten pool, thereby improving base material melting and penetration depth. Similarly, raising the arc voltage from 24 to 32 volts results in a moderate increase in penetration depth due to higher heat input while maintaining a relatively stable electrode melting rate. These findings highlight the potential of optimizing SAW parameters to achieve consistent weld quality and desirable mechanical properties.

Open Access

Article

Article ID: 2469

Deep neural network enhanced modeling and adaptive control of a malfunctional spacecraft under unknown accessory breakage

by Krzysztof Zalewski, Aliaksei Zakrevsky, Mikko Virtanen, Johan Svensson, Anders Joe, James Wilson

Mechanical Engineering Advances, Vol.3, No.1, 2025;

This manuscript presents a sophisticated deep neural networks (DNNs)-driven adaptive control paradigm for concurrently regulating the attitude and suppressing structural oscillations of a flexible spacecraft in a fully three-dimensional domain. By leveraging Hamilton’s principle, the spacecraft’s motion is formulated as an infinite-dimensional dynamic model described by partial differential equations, capturing the subtle interactions between rigid-body rotational maneuvers and flexible panel deformations. In contrast to traditional schemes, the proposed control methodology integrates a DNNs module to compensate for uncertain actuator anomalies and external input disturbances in real time, thereby ensuring fault tolerance under arbitrary, potentially unbounded actuator malfunctions. A rigorously constructed Lyapunov-based stability analysis corroborates that the system’s energy, angular rates, and transverse deflections remain uniformly bounded and asymptotically converge to zero, even in the face of multiple actuator failures. This theoretical guarantee stems from the synergistic interplay between the network’s representational power and the adaptive control law’s robust learning capabilities. Extensive computational experiments demonstrate the efficacy of the developed framework in orchestrating high-precision attitude stabilization while simultaneously mitigating detrimental vibrations, showcasing the superior performance and resiliency of the proposed DNNs-infused control architecture.

Open Access

Article

Article ID: 2098

Research progress on thermal comfort evaluation in vehicle cab

by Yuanyuan Fu, Bin Zhao

Mechanical Engineering Advances, Vol.3, No.1, 2025;

In order to improve thermal comfort of vehicle cab, reduce driver fatigue and further improve work efficiency, researches on thermal comfort of vehicle cab are summarized. Research background of thermal comfort for vehicle cab is analyzed. And then related research progress on thermal environment in vehicle cab is studied from aspect of time and space, and thermal environment inside and outside vehicle are compared. Affecting factors of thermal comfort in vehicle cab are discussed in depth, which conclude thermophysical parameters, human physiological factors, clothing thermal resistance and other secondary factors. And thermal comfort evaluation indexes are analyzed in depth. Evaluation methods of thermal comfort in uniform environment are analyzed, related experimental research and theoretical analysis are summarized, and it also points out some problems in thermal comfort of vehicle at this stage, and also gives corresponding solutions. The future trend of thermal comfort of vehicle cab is predicted. Analysis results can provide theoretical guidance for optimization design of air conditioning supply parameters and structural parameters, and has significant meaning of improving thermal comfort of vehicle cab.