Current Issue : April-June Volume : 2026 Issue Number : 2 Articles : 5 Articles
This work presents a study on the fabrication of polymethyl methacrylate (PMMA) coatings on NiTi alloys using the spin-coating technique, combining numerical simulation with COMSOL Multiphysics 6.3 and experimental validation. This study provides a numerical framework and parametric study of a COMSOL-based simulation framework for estimating the PMMA coating thickness during the spin-coating process. We present an axisymmetric numerical framework, consistent with classical analytical trends; we provide parametric maps (viscosity, rpm, volume) to delimit thickness ranges (e.g., 100–300 μm). Limitations with no experimental validation are included and evaporation is not modeled; therefore, the figures are indicative estimates. The spin-coating parameters, such as the rotation speed, internal pressure, viscosity of the PMMA solution, and initial volume of the polymer solution, are considered important factors for the simulation process. The coating parameters determine the thickness of the coating layer achieved during the process of spin coating. The 2D axisymmetric flow considers internal factors of a surface tension of 0.07 N·m, a contact angle of 90◦, and a density of 1150 kg/m3 for the coating process without evaporation effects. The moving mesh (coating layer) is considered a free surface without any slip boundary with the substrate surface. The coating thickness was determined by various rotations and dynamic viscosities, using a simulation method. The experimental findings and simulation output of the coating thickness as a function of various dynamic viscosities and rotations match well. The final coating thickness ranged from 100 to 300 μm, depending on a viscosity of 11 mPa·s and 100, 500 rpm....
This paper introduces a novel framework that integrates reinforcement learning with declarative modeling and mathematical optimization for dynamic resource allocation during mass casualty incidents. Our approach leverages Mesa as an agent-based modeling library to develop a flexible and scalable simulation environment as a decision support system for emergency response. This paper addresses the challenge of efficiently allocating casualties to hospitals by combining mixed-integer linear and constraint programming while enabling a central decision-making component to adapt allocation strategies based on experience. The two-layer architecture ensures that casualty-to-hospital assignments satisfy geographical and medical constraints while optimizing resource usage. The reinforcement learning component receives feedback through agent-based simulation outcomes, using survival rates as the reward signal to guide future allocation decisions. Our experimental evaluation, using simulated emergency scenarios, shows a significant improvement in survival rates compared to traditional optimization approaches. The results indicate that the hybrid approach successfully combines the robustness of declarative modeling and the adaptability required for smart decision making in complex and dynamic emergency scenarios....
This study investigates hydrogen storage enhancement through adsorption in porous materials by coupling the Dubinin–Astakhov (D-A) adsorption model with H2 conservation equations (mass, momentum, and energy). The resulting system of partial differential equations (PDEs) was solved numerically using the finite element method (FEM). Experimental work using activated carbon as an adsorbent was carried out to validate the model. The comparison showed good agreement in terms of temperature distribution, average pressure of the system, and the amount of adsorbed hydrogen (H2). Further simulations with different adsorbents indicated that compact metal–organic framework 5 (MOF-5) is the most effective material in terms of H2 adsorption. Additionally, the pair (273 K, 800 s) remains the optimal combination of injection temperature and time. The findings underscore the prospective advantages of optimized MOF-5-based systems for enhanced hydrogen storage. These systems offer increased capacity and safety compared to traditional adsorbents. Subsequent research should investigate multi-objective optimization of material properties and system geometry, along with evaluating dynamic cycling performance in practical operating conditions. Additionally, experimental validation on MOF-5-based storage prototypes would further reinforce the model’s predictive capabilities for industrial applications....
Recent advances in bionic intelligence are reshaping humanoid-robot design, demonstrating unprecedented agility, dexterity and task versatility. These breakthroughs drive an increasing need for large scale and high-quality data. Current data generation methods, however, are often expensive and time-consuming. To address this, we introduce Digital Twin Loong (DT-Loong), a digital twin system that combines a high-fidelity simulation environment with a full-scale virtual replica of the humanoid robot Loong, a bionic robot encompassing biomimetic joint design and movement mechanism. By integrating optical motion capture and human-to-humanoid motion re-targeting technologies, DT-Loong generates data for training and refining embodied AI models. We showcase the data collected from the system is of high quality. DT-Loong also proposes a Priority-Guided Quadratic Optimization algorithm for action retargeting, which achieves lower time delay and enhanced mapping accuracy. This approach enables real-time environmental feedback and anomaly detection, making it well-suited for monitoring and patrol applications. Our comprehensive framework establishes a foundation for humanoid robot training and further digital twin applications in humanoid robots to enhance their human-like behaviors through the emulation of biological systems and learning processes....
During the machining of nickel-based superalloys using coated tools, a significant amount of cutting heat is generated. This study employs ABAQUS finite element analysis software to establish two-dimensional orthogonal cutting simulation models for three types of coated tools: single-layer AlTiN, double-layer AlTiN/AlCrN, and AlCrN/AlTiN. The research focuses on simulating the cutting temperature and cutting stress of carbide tools with these three different coating types and thicknesses when machining nickel-based superalloy GH4169. The simulation results indicate that the double-layer AlCrN/AlTiN-coated tool exhibits lower maximum cutting temperature and cutting stress on the tool rake face and tool substrate during the cutting process. Compared to the other two coated tools, the cutting temperature and cutting stress on the rake face are reduced by up to 13.2% and 13.3%, respectively. When the AlCrN/AlTiN coating thickness is 2.5 μm with a ratio of 1.5:1, the maximum cutting temperature and cutting stress are minimized. During the cutting process with coated tools, the cutting speed, coating type, and coating thickness significantly influence the maximum cutting temperature and cutting stress. Therefore, investigating the effects of cutting speed, coating type, and coating thickness on carbide-coated tools can reduce tool wear, extend tool life, and thereby improve machining efficiency....
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