The rapid growth of semiconductor and display manufacturing highlights the demand for fast, precise motion stages. Advanced systems such as lithography and bio-stages require accuracy at the μm and nm levels, but linear motor stages face challenges from disturbances, model uncertainties, and measurement noise. Disturbances and uncertainties cause deviations from models, while noise limits control gains and performance. Disturbance Observers (DOBs) enhance performance by compensating for these effects using input–output data and a nominal inverse model. However, widening the disturbance estimation bandwidth increases noise sensitivity. Conversely, the Kalman Filter (KF) estimates system states from noisy measurements, reducing noise in position feedback, but it does not treat disturbances as states, limiting compensation. To address this, we propose an Augmented Kalman Filter (AKF)–based position control for linear motor stages. The system was modeled and identified through frequency response analysis, and DOB and AKF were implemented with a PIV servo filter. Experimental validation showed reduced following error, jitter, and control effort, demonstrating the improved control performance of the AKF approach over conventional methods.

Propulsion motors are vital components in marine propulsion systems and industrial machinery, where high torque and operational reliability are paramount. During operation, high-power propulsion motors generate considerable heat, which can adversely affect efficiency, durability, and stability. Therefore, an effective thermal management system is necessary to maintain optimal performance and ensure long-term reliability. Cooling technologies, such as water jackets, are commonly employed to regulate temperature distribution, prevent localized overheating, and preserve insulation integrity under high-power conditions. This paper examines the cooling performance of water jackets for high-power propulsion motors through numerical analysis. We evaluated the effects of three different cooling pipe locations and varying coolant flow rates on thermal balance and cooling efficiency. Additionally, we analyzed temperature variations in the windings and key heat-generating components to determine if a specific cooling flow rate and pipe configuration can effectively keep the winding insulation (Class H) within its 180^oC limit. The findings of this study highlight the significance of optimized cooling system design and contribute to the development of efficient thermal management technologies, ultimately enhancing motor reliability, operational stability, and energy efficiency.

The polymer electrolyte membrane fuel cell (PEMFC) generates electrical energy through electrochemical reactions and is a key technology for sustainable energy. The electrolyte membrane significantly affects performance under varying conditions. This study examines the impact of membrane thickness and relative humidity (RH) on PEMFC performance using j-V curves and electrochemical impedance spectroscopy (EIS). Experiments were conducted with membrane thicknesses of 30, 15, and 5 μm under RH conditions of 100%-100% and 100%-0%. Under RH 100%-100%, performance improved as the membrane thickness decreased, with values of 954, 1050, and 1235 mW/cm² for the 30, 15, and 5 μm membranes, respectively. The 5 μm membrane demonstrated a 23% performance improvement over the 30 μm membrane. Under RH 100%-0%, performances were 422, 642, and 852 mW/cm², with degradation rates of 55.8%, 39.0%, and 32.1%. The 5 μm membrane exhibited the lowest degradation rate, indicating superior performance under low humidity. These results suggest that thinner membranes generally enhance performance and maintain efficiency even in dry conditions.

This study presents a self-wearable smart personal protective respirator featuring a color-signaling triage system designed to facilitate rapid assessment during large-scale physical disasters. The device enables individuals to wear the respirator, allowing responders to quickly identify critically ill patients through real-time biometric signal acquisition and intuitive LED-based visualization. Clinical triage criteria, developed with input from emergency medicine experts, informed a severity classification algorithm based on heart rate, respiratory rate, body temperature, and posture. To implement this system, an ergonomic head-type respirator prototype was created, integrated with a compact sensor module that includes a photoplethysmography (PPG) sensor, a barometric pressure and temperature sensor, and a combined accelerometer and gyroscope sensor. Additionally, custom sensors were developed: a respiration sensor utilizing nickel oxide nanoparticles patterned by laser, and an ECG sensor made by spraying silver nanoparticles onto a flexible polyimide film and then laser-patterning it into a serpentine shape. The system effectively detects vital signs and visualizes severity levels using color signals. Although field deployment was not part of this study, the prototype demonstrated potential to reduce triage time and enhance disaster response efficiency. Further validation in real-world settings is recommended.

This study details the development of a semi-active suspension wheel module for small mobile robots and assesses its dynamic characteristics under various driving conditions through simulation. The wheel module features a low-degree-of-freedom mechanical design and includes a semi-active damper to improve adaptability to different environments. To validate the simulation model, a prototype robot equipped with the wheel module was created, and obstacle-crossing experiments were conducted to measure vertical acceleration responses. The model was then refined based on these experimental results. By employing design of experiments and optimization techniques, the effective range of damping coefficients was estimated. Additionally, simulations were carried out at different speeds, payloads, and obstacle heights to identify optimal damping values and examine their trends. The results indicate that the proposed module significantly enhances driving stability and can serve as a foundation for future control strategies in robotic mobility systems.

Currently, advanced countries such as the US and the UK are researching laser-based weapons and communication systems. The application of Fast Steering Mirror (FSM) is crucial in laser systems to control internal optical paths and compensate for disturbances, including atmospheric fluctuations and mechanical vibrations. Additionally, research is underway to enhance image clarity in surveillance and reconnaissance systems, such as Electro-Optical/Infrared (EO/IR) systems, by applying FSM technology. Consequently, the demand for FSMs is rising, necessitating the development of small, lightweight, and high-performance solutions. In this study, we designed a compact and lightweight FSM with a diameter of 25 mm, and its performance was validated through rigorous testing. Furthermore, we developed a piezoelectric actuator using single crystal piezoelectric material to ensure a wide operating bandwidth and rapid response speed for the FSM. Before manufacturing the designed FSM, we conducted modeling and simulation (M&S) to analyze its performance and confirm that it met the required specifications. Subsequently, a prototype of the FSM was produced, and its operating range, bandwidth, and accuracy were evaluated through performance tests.

In this study, we developed a composite anode support composed of La-doped SrTiO₃ (LST) and Gd-doped CeO₂ (GDC) using a tape casting process for solid oxide fuel cells (SOFCs). By adjusting the pore former content in the slurry, we constructed a bilayered structure consisting of a porous anode support layer (ASL) and a dense anode functional layer (AFL) with the same material composition. The number of tape-cast sheets was controlled to tailor the overall thickness, and lamination followed by co-sintering at 1250^oC resulted in a mechanically robust bilayer. We characterized the microstructural evolution concerning sintering temperature and pore former content using SEM, while XRD confirmed the phase stability of LST and GDC. The measured electrical conductivity at 750^oC ensured sufficient electron transport. To enhance interfacial adhesion and suppress secondary phase formation, we introduced a GDC buffer layer and a pre-sintering treatment prior to electrolyte deposition. A full cell with a YSZ electrolyte and LSCF cathode achieved a stable open circuit voltage of approximately 0.7 V and demonstrated continuous operation at 750^oC. These findings highlight the suitability of LST-GDC composite anodes as thermochemically stable supports, potentially enabling direct hydrocarbon utilization in intermediate-temperature SOFCs.

In this study, we employed an infiltration technique to create a nanostructured functional layer, enhancing the electrochemically active area in solid oxide fuel cells (SOFCs). We infiltrated Pr₂NiO_4+δ (PNO) into a porous GDC electrolyte, resulting in a nanostructured catalytic layer. We characterized its microstructure and cross-sectional morphology using field-emission scanning electron microscopy (FE-SEM). The electrochemical performance was assessed at 750°C with a NiO-YSZ/YSZ/GDC half-cell configuration. The reference cell without PNO infiltration achieved a maximum power density of 2.07 W/cm², while the cell with 0.05 M PNO infiltration reached an improved value of 2.55 W/cm². These results demonstrate that by optimizing the infiltration concentration of PNO, we can fabricate a high-performance nanostructured functional layer without adding extra thickness, confirming infiltration as an effective strategy for enhancing SOFC performance.

Materials such as titanium alloys, nickel alloys, and stainless steels are difficult to machine due to low thermal conductivity, work hardening, and built-up edge formation, which accelerate tool wear. Frequent tool changes are required, often relying on operator experience, leading to inefficient tool use. While modern machine tools include intelligent tool replacement systems, many legacy machines remain in service, creating a need for practical alternatives. This study proposes a method to autonomously determine tool replacement timing by monitoring machining process signals in real time, enabling automatic tool changes even on conventional machines. Tool wear is evaluated using current and vibration sensors, with the replacement threshold estimated from the maximum current observed in an initial user-defined interval. When real-time signals exceed this threshold, the system updates controller variables to trigger tool changes. Results show vibration data are more sensitive to wear, whereas current data provide greater stability. These findings indicate that a hybrid strategy combining both sensors can enhance accuracy and reliability of tool change decisions, improving machining efficiency for difficult-to-cut materials.

This study outlines a structural design process for a cylindrical superelastic shape memory alloy (SMA) ligation clip. Although polymer-based clips are widely used, they face challenges related to long-term stability and limited radiopacity, highlighting the necessity for metal clips. By systematically modifying two key design variables—the hole offset ratio and the cut-off ratio—the proposed clip effectively reduces excessive stress concentration and enhances superelastic behavior. Finite element analyses indicate that the stress deviation in the two cross-sectional deformation regions decreased by 83.9%, and the martensitic transformation remained confined to a small area, demonstrating robust strain recovery within the superelastic range. In conclusion, the improved SMA clip successfully withstood internal pressures exceeding 15 psi without leakage, showcasing its superior ligation performance and potential for durable, reliable use in minimally invasive surgical procedures.

Identifying the impeller type is essential for enabling torque sensing in conventional agitators. Previous studies have demonstrated that using arrays of permanent magnets with like poles facing each other allows for cost-effective, non-contact sensors. However, these configurations create strong repulsive forces, complicating assembly during sensor fabrication. This study addresses the issue of poor assemblability by introducing a high-permeability ferromagnetic ball between the magnets. This ball not only reduces repulsive forces but can also induce attractive forces, making assembly easier. We analyzed the effects of ball diameter, magnet thickness, and the number of magnets on the inter-magnetic force using ANSYS Maxwell. To validate the finite element method (FEM) results, we conducted experiments, which showed that the measured values closely matched the simulation results. This confirmed that the ferromagnetic ball significantly mitigates the repulsion between magnets, and in some cases, reverses the force to attraction. These findings are important for enhancing assemblability in automated mass production. Additionally, the study identified an optimal steel ball size that minimizes repulsion while facilitating sensor miniaturization, providing a practical solution for compact sensor design.