A strut tower brace is one of the components that can improve the driving stability of a vehicle. This component has received steady attention for a long time due to its affordable price and easy installation. However, strut tower braces sold in the market have different structures. Moreover, most of them do not contain sufficient information related to safety or stability. Thus, this study aimed to analyze and compare structural behaviors of strut tower braces having various body shapes under bending and compressive scenarios. For this purpose, this study selected six representative models in the market and calculated structural behaviors (stress and deformation) using finite element analysis. Results revealed the body shape had a decisive effect not only on the durability of the strut tower brace, but also on the safety and stability of the vehicle. Among the six models tested, the model having a body shape with a single-axis form utilizing a wide rectangular cross-sectional showed the best bending and compressive performances. This study also confirmed that bending and compressive performances could be simultaneously improved depending on body shape.

In the field of robotics and automation, path planning holds significant potential for optimizing field operations. These operations must cover the work area comprehensively and efficiently with minimal movement. To achieve these goals, coverage path planning (CPP) utilizing the Boustrophedon method is essential. However, in an experimental environment, CPP often results in missed work areas due to cumulative sensor errors and structural inconsistencies. This paper aimed to improve CPP by employing the Douglas-Peucker algorithm to simplify the work path and minimizing missed areas. Additionally, Edge Zone Path method was used to generate edge paths, enhancing safety of the trajectory. For experimental purposes, data were acquired from an actual barn. The work area was divided using three segmentation algorithms. Among these, the Voronoi Segmentation, which demonstrated superior performance, was used to extract the data. Experimental results indicated that the proposed optimized CPP improved path safety by maintaining a safe distance from obstacles during frequent turns. Additionally, the Coverage Ratio increased the coverage area of the autonomous robot by an average of 17% compared to the original CPP. These findings suggest that the proposed method can generate more efficient and safe work paths.

Excavators are crucial heavy equipment on construction sites, performing diverse earthwork tasks. The construction worksite is experiencing a labor shortage due to an aging workforce. Training new operators requires significant time and resources. Furthermore, the construction environment is hazardous, with a higher rate of excavator-related accidents. Autonomous excavators offer an effective solution by reducing the need for operators in risky environments and substituting skilled workers. Trajectory planning algorithms are vital for autonomous excavators, with skilled operators’ paths serving as important references. However, many studies do not adequately consider skilled operators’ methods or the actual excavation environment. This paper introduced a rule-based algorithm for excavation trajectory planning using terrain data. Based on analysis results of skilled operators’ paths, the proposed algorithm categorizes the excavation process into three stages, depending on the usage rate of the excavator"s joints. Terrain data were derived by projecting point clouds from a stereo depth camera onto a side plane. The path was modified if the excavation volume exceeded a set limit to avoid excessive load. The algorithm was tested with a 30-ton excavator, demonstrating validation of operability and efficiency similar to that of skilled operators.

In this study, we investigated characteristics and mechanical properties of SKD61 repaired using the direct energy deposition (DED) process. Mechanical properties of the repaired product can vary depending on the base material and powder used in the DED process. To prepare for DED repairing for a damaged part, we conducted experiments using two different powders (H13 and P21). Experimental results showed that both powders were deposited without defects in the surface or interface between the deposited zone and the substrate. Hardness measurements indicated that the repaired region of the Repaired-H13 sample exhibited higher hardness than the base material, while the Repaired-P21 sample showed a sharp increase in hardness in the heat-affected zone (HAZ). Additionally, tensile test results revealed that the Repaired-H13 sample had lower tensile strength and elongation than the base material, whereas the Repaired-P21 sample demonstrated higher tensile strength and yield strength with a higher elongation than the Repaired-H13 sample. In case of Repaired-H13, it was confirmed that interfacial crack occurred due to a high hardness difference between the repaired part and the substrate.

This study proposed a method for simultaneously reducing mass imbalance and vibration in gimbal systems utilizing a tuned mass damper (TMD) as a balancing weight. Finite element analysis (FEA) and experiments were used for testing the method. Mass imbalance in gimbal systems generally causes external disturbance torque. To reduce this, a balancing weight can be used. However, weight increase due to balancing weight causes resonance in the gimbal system, which generates bias error in the gyroscope sensor. This study demonstrated that both mass imbalance reduction and vibration reduction effects could be achieved by utilizing a TMD as a balancing weight. FEA results showed that the mass imbalance reduction effect of the gimbal was not affected by TMD. The magnitude of vibration response at the resonance point was reduced by about 98% with TMD. When a TMD was applied, the magnitude of the vibration response at the resonance point was reduced by 98% to the same level as that of the gimbal. Bias error of the gyroscope sensor was reduced by about 95% or more. These results show that a TMD is useful for effectively reducing mass imbalance and vibration in gimbal systems while improving gyroscope sensor performance.

CNN is one of the deep learning technologies useful for image-based pattern recognition and classification. For machining processes, this technique can be used to predict machining parameters and surface roughness. In electrical discharge machining (EDM), the machined surface is covered with many craters, the shape of which depends on the workpiece material and pulse parameters. In this study, CNN was applied to predict EDM parameters including capacitor, workpiece material, and surface roughness. After machining three metals (brass, stainless steel, and cemented carbide) with different discharge energies, images of machined surfaces were collected using a scanning electron microscope (SEM) and a digital microscope. Surface roughness of each surface was then measured. The CNN model was used to predict machining parameters and surface roughness.

In the 4^th Industrial Revolution, advancements in semiconductor technology demand high performance, efficiency, and precision, highlighting the importance of high-speed and ultra-precise motion stages. To improve positioning performance of a motion stage, robust torque generation by current controllers alongside position control is crucial. This paper explored a custom current control for linear motor motion stages. We built a linear motor motion stage with a 560 mm stroke, 5 m/s speed, and 280 N continuous thrust supported by air bearings and equipped with a passive reaction force compensation. Custom user code for position and current controls of PowerPMAC motion controller was developed for the motion stage. The position control code included frequency domain system identification, disturbance observer, and repetitive learning control while the current control code featured vector or d/q-axis current controllers and disturbance observer. We developed a current control tuning GUI to adjust the current control gain by injecting an excitation signal into the motion controller and measuring the frequency response of the open-loop transfer function. Experimental results confirmed the effectiveness of the custom current controller for evaluating static and dynamic performance.

To accurately assess mechanical properties of micro- and nano-sized specimens, a reliable material testing system is indispensable. However, due to small sizes of these test specimens, in-situ measurement of their mechanical behavior necessitates installing the tester within high-magnification microscopes such as SEM. Traditionally, researchers have used wired methods by placing the tester inside the SEM chamber and connecting it to an external controller via electrical feedthrough. Unfortunately, this approach is cumbersome. In addition, it limits its compatibility with other SEMs. In this study, we developed a compact controller capable of driving 3-axis piezoelectric actuators with nanometer-level displacement control resolution via Bluetooth communication. This innovative setup enables wireless control and data acquisition from outside the closed confines of an SEM chamber. To validate the versatility of our tester, we conducted both a nanoindentation test on a fused silica specimen using a Berkovich indenter in a wired configuration and a copper micropillar compression test wirelessly using a flat punch indenter within an SEM. By installing this tester in various measurement systems, researchers could observe deformation patterns in real time, making it a valuable tool for investigating deformation mechanisms of diverse micro- and nano-sized specimens.

Recent advancements in science and technology have enabled even microsatellites to perform various high-level tasks. As the range of missions that satellites undertake expands, even microsatellites now require thrust systems for orbit adjustment and collision avoidance. In such satellite applications, sizes and weights of all electrical components and propulsion systems are restricted, emphasizing the importance of miniaturization and weight reduction. Research is ongoing in various methods to address these needs. To solve these challenges, this study proposed a design model for miniaturizing and lightening both Anode Power Module (APM) and gas supply system. The APM utilizing an LLC resonant converter achieved an efficiency of up to 86%. An evaluation of flow control characteristics of the proposed gas supply device showed that the flow control error was less than 2.3%, indicating effective results. A thermal mass flow sensor was developed to measure the flow of gas. Temperature characteristics derived from experiments were analyzed to assess their applicability to electric thruster systems for satellites.

Predicting elastic modulus of a porous structure is essential for applications in aerospace, biomedical, and structural engineering. Traditional methods often struggle to capture complex relationships between material properties, design variables, and mechanical behavior. This study employed artificial neural networks (ANNs) to predict the elastic modulus of a porous structure based on various material and design parameters. An ANN model was trained on a dataset generated via finite element analysis (FEA) simulations, covering diverse combinations of material properties and design variables (e.g., porosity, structure types). The model demonstrated high accuracy in predicting the elastic modulus on a separate test dataset. Key findings included identification of significant design variables influencing the elastic modulus and the ANN model"s ability to generalize predictions to new data. This approach showcases that ANN is a powerful tool for designing and optimizing porous structures, providing reliable mechanical property predictions without extensive experimental testing or complex simulations. The proposed method can enhance design efficiency and pave the way for developing advanced materials with tailored mechanical properties. Future research will extend the model to predict other mechanical properties and incorporate experimental validation to verify ANN predictions.

Recently, X-ray images through chest radiography (CXR) can distinguish gas, fat, soft tissue, bone, and metal based on their densities. It is the most basic chest imaging technique. With advancement of technology, CXR is becoming safer by lowering the radiation dose. It has become the first examination performed on patients with thoracic abnormality syndrome for early diagnosis of various chest diseases worldwide, accounting for up to 26% of all diagnostic radiology examinations. Despite its various advantages, CXR can distinguish only a few densities. Various thoracic anatomical structures can overlap in a single 2D image and various pathologies can show the same density, making accurate interpretation at various densities difficult. Errors in CXR interpretation have been present since the mid-20th century, with 10-20% of tuberculosis cases being interpreted differently by various radiologists and 19% of lung cancer cases being misinterpreted. To address these issues in interpreting chest CXR and to increase its usability in emergency situations and various environments, the quality of CXR images needs to be improved. In order to improve the quality of these images, this study aimed to establish a portable multi-energy X-ray field technique using MCNP with dual energies of 40 and 70 keV.

Nonlinear hysteresis effects in piezoelectric fast steering mirrors (FSMs) are major culprits of deteriorating the servo performance and reducing the robustness of a control system. In order to compensate for such nonlinearities, this paper presents an identification and compensation method of piezoelectric hysteresis using frequency response measurements. The relationship between hysteresis curves and frequency response was analyzed using various amplitudes of input voltage and measured output displacements. Results proved that hysteresis curves could be reconstructed based on frequency response measurements. By utilizing an inverse function from reconstructed hysteresis curves, parameters for the compensation model were identified. Experimental results showed that the maximum range of output displacement at the nominal position due to hysteresis was significantly decreased by 76% when the hysteresis model identified by the proposed frequency-domain method was used. In addition, the compensated frequency response showed consistent results regardless of input amplitudes, implying that linear dynamics of the piezoelectric FSM could be separately measured.