In this paper, we develop a cylindrical triboelectric nanogenerator (TENG) for omnidirectional wind energy harvesting, by designing a slanted slit structure along the outer surface of the cylinder. The TENG consists of an inner cylinder based on Al film and a 3D printed outer structure. Wind blowing through the slits of the outer structure causes the inner cylinder to rotate in the slanted direction, and the contact-separation between the Al cylinder and polytetrafluoroethylene attached to the inner surface of the outer structure generates an output voltage. The performance of the harvester with different inner cylinder diameters under various wind speeds is experimentally studied. The results indicate that the TENG with a smaller Al cylinder is suitable for a self-powered wind speed sensor while that with a larger cylinder is optimal for efficient energy harvesting. In addition, the TENG is capable of harvesting wind energy in all directions. Its potential utility to be used as a supplementary power source for small electronic devices is verified through various experiments. Based on its compact size, simple design, and ease of manufacturing, the proposed TENG can be used as a low-cost, portable harvester.

Climbing stairs places a greater load on lower limb joints compared to walking on level ground. Variations in anatomical structures and muscle characteristics between genders suggest potential differences in the distribution of required mechanical work among the three lower limb joints. This study aimed to identify gender disparities in the allocation of mechanical work to lower limb joints during stair climbing. A total of thirty-six adults (equally divided between men and women) participated in the study. Participants ascended stairs equipped with force plates at their comfortable speeds, while motion was captured using nine cameras. Inverse dynamics analysis was employed to calculate the mechanical work performed by each joint during four phases of stance: weight acceptance, pull-up, forward continuation, and push-up. Male participants exhibited significantly higher mechanical work than females at the hip and ankle joints (p < 0.05) from the 1st- 3rd phases and the 2nd phase, respectively. Conversely, female subjects displayed greater knee joint work during the 2nd- 3rd phases (p < 0.05). Notably, a pronounced gender difference was observed during the 2nd pull-up phase, where body mass is lifted by a single leg. These findings suggest that men and women employ distinct strategies in distributing mechanical work across lower limb joints.

The Electrochemical Hydrogen Compressor is an optimal device for compressing low-pressure hydrogen to high-pressure hydrogen. It has a similar structure to the Proton Exchange Membrane Fuel Cell but operates at extremely high pressures, requiring multiple cells sealed with End Plates. The End Plate design must provide initial cell activation support, withstand maximum operating pressure within the stack, and prevent internal gas leakage. This study applies a multi-objective optimization method and grey relation analysis to determine the optimal design parameters for the End Plate based on the activation area of Dummy Cells. Finite Element Method (FEM) analysis is conducted to verify the effectiveness of the optimized End Plate design, considering the uniform pressure distribution with stacked Dummy Cells (1, 3, 6, 12). The analysis reveals that the parameters affecting the uniform pressure distribution include the End Plate design, stack sealing pressure, individual Cell design parameters, and the number of Cell stack layers.

This study investigated the Laser-Induced Plasma Backward Deposition (LIPBD) process for transparent glass-copper composite film production. LIPBD was compared with Laser-Induced Backward Transfer (LIBT). Controlling laser parameters and the z-axis position of Depth of focus (DOF) resulted in various post-deposition outcomes. The optimal deposition depth was 10 μm to 90 μm, ensuring good glass-copper adhesion. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping confirmed copper and copper oxide (CuO) particles. X-ray diffraction confirmed Cu and CuO peaks. The adhesive test showed a strong binding between glass and deposition, but the parts of the cracks caused by heat accumulation were delaminated during the test. LIPBD offers controlled deposition potential for glass-copper composites. Optimizing laser parameters leads to high-quality films. This study provides valuable insights into nanotechnology and the semiconductor industry, with potential applications across diverse fields.

Exteriors of structures (apartments, buildings, bridges, dams, power plants, etc.) are subject to deterioration and damage (cracks, rust, etc.), mainly due to thermal expansion/contraction and environmental humidity. The damages shorten the lifespan of structures and cause unnecessary reconstruction, increasing social costs. The existing damage maintenance methods, which are directly constructed by the workers, have problems such as reduced work efficiency, increased work cost, lack of timely maintenance, and high work risks. In this paper, a spraying device attached to a drone for active and flexible maintenance of structures is developed. To simplify maintenance, the device consists of a solenoid motor, detachable parts for maintenance agent, and a lightweight-designed frame, manufactured with a 3D printer. In particular, the lever mechanism that amplifies the pushing force of the solenoid motor is designed to spray the maintenance agent when a switch comes into contact with the exterior of the structure. The prototype of a spraying device is attached to a commercial drone (Mavic3, DJI) and tested for effectiveness in structure maintenance. It demonstrates successful, cost-effective maintenance of structural damages in less than 10 minutes.

It is challenging to automate the shoe upper adhesive spraying process using a robot due to the three-dimensional curved shape of the shoe upper. This paper proposes a method to automate the shoe upper adhesive spraying process with a 3-D measuring device and an industrial robot. The adhesive spraying automation process consists of the following steps, First, a transformation matrix calibration is performed to make the points measured by the 3-D measuring device and the robot end-effector points the same. Second, the shoe gauge line that connects the shoe adhesive spaying line measured by the 3D measurement device is smoothed. Lastly, the target points of the robot end-effector to quantitatively spray the adhesive are selected and the robot end-effector position/orientation to operate the robot is generated. The proposed method was validated on the test bed of a shoe upper spray system. With the method proposed in this paper, even non-robot experts can measure shoe gauge line data with a 3-D measuring device and the shoe upper adhesive spraying process can be automated without manually operating a robot.

This paper presents the development of a design optimization module for achieving the best performance of hydrostatic bearings. The design optimization module consists of two components: a bearing performance analysis module and an optimization module that utilizes optimization algorithms. Widely recognized global search methods, genetic algorithm (GA), and particle swarm optimization (PSO) algorithm, were employed as the optimization algorithms. The design optimization problem was defined for hydrostatic bearings. Optimization design processes were carried out to improve load capacity, stiffness, and flow rate. Subsequent experimental validation was conducted through the fabrication of a practical experimental setup. The design optimization model demonstrated superior performance compared to the initial model while satisfying design conditions and constraints. This confirms the practical applicability of the design optimization module developed in this study.

In this study, we aim to develop a self-humidifying polymer electrolyte membrane fuel cell (PEMFC) by depositing platinum (Pt) on a membrane using sputtering. After we coated it with a Nafion^® ionomer solution. This is considered a solution that can prevent membrane degradation in low humidity conditions. By introducing this self-humidifying concept, we can expect improved performance compared to conventional PEMFCs. By managing the water content of Nafion^®, we aim to improve both the stability and performance of the PEMFCs. This research contributes to the development of more efficient and reliable PEMFC systems, showing promise for advances in this field.

Predicting fall risk is necessary for rescue and accident prevention in the elderly. In this study, deep learning regression models were used to predict the acceleration sum vector magnitude (SVM) peak value, which represents the risk of a fall. Twenty healthy adults (aged 22.0±1.9 years, height 164.9±5.9 cm, weight 61.4±17.1 kg) provided data for 14 common daily life activities (ADL) and 11 falls using IMU (Inertial Measurement Unit) sensors (Movella Dot, Netherlands) at the S2. The input data includes information from 0.7 to 0.2 seconds before the acceleration SVM peak, encompassing 6-axis IMU data, as well as acceleration SVM and angular velocity SVM, resulting in a total of 8 feature vectors used to model training. Data augmentations were applied to solve data imbalances. The data was split into a 4 : 1 ratio for training and testing. The models were trained using Mean Squared Error (MSE) and Mean Absolute Error (MAE). The deep learning model utilized 1D-CNN and LSTM. The model with data augmentation exhibited lower error values in both MAE (1.19 g) and MSE (2.93g²). Low-height falls showed lower predicted acceleration peak values, while ADLs like jumping and sitting showed higher predicted values, indicating higher risks.

The quality and quantity of heat treatment in mold processing can vary depending on the skill level of the equipment operator. Therefore, study on ways to overcome these disadvantages are essential. This study aimed to increase the antiwear properties of molds through high-frequency induction heat treatment and laser heat treatment processes. The heat treatment was applied to the surfaces of molds used in car body production using an articulated robot, to achieve long-term use and quality maintenance. Additionally, an articulated robot system based on redundant degrees of freedom suitable for mold heat treatment processes was designed, and its operational efficiency was verified through virtual environment simulations. Furthermore, heat treatment was validated through on-site testing of the robot system. Its effects were analyzed according to mold materials and shape conditions, ultimately deriving the optimal robot heat treatment conditions. Finally, off-line programming (OLP) in virtual processes was proposed to minimize robot setup time and maximize production efficiency. The conditions for articulated robot automated heat treatment obtained in this study can be preapplied in simulation environments when generating heat treatment robot programs based on OLP. They can be utilized for optimizing the quality of mold heat treatment in car body production.