In dissimilar joints between Si₃N₄ and Ti-6Al-4V, insertion of a ductile Nb interlayer is effective for stress relaxation under bonding and loading. In this study, elastoplastic analysis using the finite element method (FEM) was applied to determine the optimum thickness of the Nb interlayer in Si₃N₄/Nb/Ti-6Al-4V joints needed to maximize the bending strength, and the analytical results were compared to experimental results to validate the proposed method. The joining process involved transient liquid phase bonding using Ni and Cu fillers on the Nb/Ti-6Al-4V side to suppress brittle intermetallic compounds, and brazing with Ag-Cu-Ti filler on the Si₃N₄/Nb side to promote wettability and interfacial bonding with Si₃N₄. The average bending strength was maximized at 366 MPa when the cross-sectional area was 3 × 4 mm² and the thickness of Nb interlayer was 0.25 mm. Joints fractured near the Si₃N₄/Nb interface brazed with Ag-Cu-Ti filler. According to FEM analysis, stress singularity fields were found near the interfaces at free surfaces after cooling and bending owing to the discontinuity of stiffness in each material. The stress singularity field in Si₃N₄ after bending was minimum when the cross-sectional area was 3 × 4 mm², and the thickness of Nb interlayer was 0.25 mm because the stress singularity fields near Si₃N₄/Nb and Nb/Ti-6Al-4V interfaces separated and the deformation constraint of Nb from Si₃N₄ and Ti-6Al-4V was relatively effective. Therefore, the results from experiments and the proposed analytical method were in qualitative agreement. The optimum thickness of the Nb interlayer in Si₃N₄/Nb/Ti-6Al-4V joint was 0.25 mm for a cross-sectional area of 3 × 4 mm² and 0.75 mm for a cross-sectional area of 10 × 10 mm²; therefore, the optimum interlayer-thickness-to-joint-height ratio was approximately 0.08.

In the initial stages of railway vehicle design, finite element analyses are often repeated while adjusting design variables such as plate thickness, window dimensions, and under-floor equipment installation positions to achieve the desired performance. However, this repetitive process of finite element analysis, which involves the detailed modeling of large and complex vehicle structures, is highly computationally demanding. Therefore, it is necessary to improve the efficiency and speed of analysis. In this paper, we propose a machine-learning-based surrogate model to replace finite element analysis in railway vehicle design. To address the complexity resulting from the vast number of nodal values, this model utilizes dimensionality reduction through principal component analysis (PCA) and a multilayer perceptron architecture. It enables the prediction of critical parameters for railway vehicle designs including maximum deflection, deformation, stress distribution, eigenfrequencies, and eigenmodes, directly from design parameters such as plate thickness, window dimensions, and under-floor equipment loading positions. The model demonstrates high accuracy, with predicted maximum deflection and eigenfrequencies within 0.2% and 1% deviation, respectively, across all input variables. Additionally, nodal displacements, stress distributions, and eigenmodes are also predicted with accuracies of 4.2%, 13%, and 2.5%, respectively. Slightly lower accuracy is observed particularly when inputting loading positions of point loads. This is attributed to the limitation of capturing locally steep changes in shape and stress caused by dimensionality reduction using PCA. The results for any input-output combinations are obtained in approximately 0.005 seconds per case, potentially eliminating the need for setup and conducting finite element analysis, which may take enormous time and effort.

The two-dimensional pressure field around a hydrofoil is estimated from the pressure values of sparse sensors flush-mounted on the hydrofoil. The sparse data is expanded to pressure field data using a combination of multi-layer perceptron (MLP) and super-resolution convolutional neural network (SRCNN) techniques, where MLP is employed to temporarily increase the size of the sparse data to that of the output two-dimensional field data. The training dataset for these neural networks (NNs) is CFD data of the cavitating flow field computed using a transport-equation-based cavitation model. Therefore, the prediction accuracy depends on the accuracy of the CFD of the training dataset. The input is the pressure values at 25 points on the hydrofoil surface in a certain spanwise section, and the NNs are trained with the corresponding pressure fields in the spanwise section as the label data. As a result of the training, the pressure field for one cycle of sheet/cloud cavitation is qualitatively estimated. However, the accuracy is relatively low in the vicinity of the trailing edge of the hydrofoil, where cavitation grows rapidly. When the pressure wave causes due to the disappearance of the cloud cavitation, the accuracy is also poor for most of the wake. The homogeneous fluid density field is predicted from the estimated pressure field and the barotropic cavitation model. The boundary of the cavitation region and liquid phase region are blurred. This may be due to the use of estimated pressure based on the transport equation model, which considers non-equilibrium effect and advection.

The novel posture analysis system for a user's whole body while walking with a walker was developed by using a deep learning method based on the image data of only one camera. The original walker equipped with the system was proposed in this paper. The fisheye-camera enables us to capture the posture of the user's whole body using only one camera equipped on the walker, which is conventionally difficult. (1) The 3-dimensional pose of the user while walking with the walker is estimated from the obtained data using deep learning. (2) The 3-dimensional pose is estimated from the 2-dimensional pose estimation of the user's pose which is obtained from the image data for each of the two cameras. (3) The user's pose is measured using the 3-dimensional position measurement device in order to evaluate the estimation results of (1) and (2). The walking speed and stride-length are estimated using the multilayer perceptron in the multimodal method in which the input data is the estimated results of the user's pose and the moving distances obtained from the encoder equipped in the walker wheel. The estimated results are also evaluated on the measurement results of the 3-dimensional position measurement device. The present system is useful in a practical walker for the rehabilitation of walking, because it is equipped with only one camera, and it enables us to estimate not only the user's posture, but also the user's walking-speed and stride-length during walking with the walker.

DC magnetic suspension operated by transmitted power is introduced to AC magnetic suspension system using magnetic resonant coupling for dynamic stabilization. The target AC magnetic suspension system has a self-stabilization property. Although restoring force is produced without active control in this system, damping is necessary for dynamic stabilization. To generate damping force, a DC magnetic suspension mechanism, which is operated by the power transmitted to the floator through magnetic resonant coupling, is installed in parallel with the AC magnetic suspension mechanism. The newly developed system has a pair of AC electromagnets and another pair of DC electromagnets. The former pair generates positive stiffness according to the self-stabilization property. The latter pair is expected to produce positive damping by shortening the coil of the electromagnet on the stator. However, it is experimentally shown that negative damping is produced because the latter pair also has the self-stabilization property. Therefore, a bias voltage is applied to the DC electromagnet on the stator to make the stiffness negative. As a result, stable suspension is achieved without active control in the developed system. However, the overall stiffness decreases and the stability range is small because the latter pair has negative stiffness. To solve such a problem, a phase-lead compensation is applied to the latter pair instead of the bias voltage. This method can produce positive damping and positive stiffness at the same time so that the suspension characteristics are improved.

We investigated a damping switching control law with simplicity and high performance for semi-active suspension with time delay. The present law simply switches damping according to the sign of the condition function of ( + ₀) using target and base velocity and ₀, respectively, whereas a skyhook-based law does it by ( − ₀). We conducted the simulations and experiments of vibration suppression for a single degree-of-freedom system with a semi-active magnetorheological damper to compare both the law. The key findings of this study are as follows: (1) In the time delay of 10–100 ms, the ON–OFF control using the present law maintains the vibration suppression performance under sine excitations although that using a skyhook-based law degrades it increasing with time delay. At least, over the time delay of 50 ms, the present law has the vibration suppression performance higher than a skyhook-based law in the overall range of frequency ratio of 0–4. (2) The velocity-proportional damping control using the present law shows the vibration suppression performance higher than or equal to the ON–OFF control using the present law under sine excitations. (3) Under a road surface excitation, the velocity-proportional damping control using the present law shows the ideal vibration suppression performance that the response displacement in the control is equal to that in the ON state around the natural frequency and close to that in the OFF state over the frequency ratio of √2.

Modeling methods of a robot dynamics include (i) obtaining the equations of motion and identifying the dynamics parameters, and (ii) system identification of the robot dynamical characteristics. However, the parameters obtained in (i) are approximate solutions whose accuracy depends on the motion and environment in which the robot is operated, because the actual robot is finer and includes un-modeled dynamics. Therefore, an appropriate evaluation index is required for identification. In (ii), the accuracy is low in the high-frequency domain due to the S/N ratio problem, which often causes spillover. In addition, in closed-loop identification, the inverse function of the controller is identified due to noises. In this paper, we focus on the periodic motion of the end-effector of a planar 3-link manipulator and derive an error equation that exploits the periodicity of the motion to simultaneously identify the dynamics parameters and spillover. In particular, by selecting the identification object to realize an open-loop identification, the identification of spillover has high accuracy. Based on the obtained dynamic model, a control system is designed to suppress the error, and experiments show to verify that the proposed method achieves sub-millimeter order accuracy control.

During the cutting process, it is crucial to replace cutting tools at the right time to meet machining accuracy requirements. However, determining tool life relies on the unsystematic tacit knowledge of skilled engineers. Moreover, the increasing variety of cutting tools needed to accommodate the trend towards small quantities of various products has made it even more challenging to determine tool life. This study aimed to address this issue by developing a system that could accurately determine when to replace ball end-mills without requiring the judgment of skilled engineers. The results of the study showed that anomaly detection methods can be applied to images of worn tools to determine tool life accurately. By converting current value data during cutting into images and using image classification methods, it is possible to classify tools according to their wear conditions, such as new, early wear, end stage of wear, and end of tool life. The study also showed that constructing a multimodal judgment system using both tool appearance image abnormality detection and current value data image classification resulted in a 98% judgment accuracy rate for tools that had reached the end of their service life, with a correct answer rate of over 90%.

Carbody elastic vibration of a railway vehicle negatively affects the ride comfort of passengers. One of the sources of the vibration is excitation force induced by the longitudinal vibration of the bogies. The excitation force transmits to the carbody through longitudinal coupling devices between the bogie and the carbody, such as traction links and yaw dampers. Since the longitudinal coupling devices can affect running stability of the vehicle, it is necessary to develop a device which copes with both vibration reduction and running stability. The purpose of this study is to develop a device which achieves both vibration reduction and the running stability. To confirm the vibration isolation performance and also to evaluate the running stability, using multi-body dynamics software, we construct a simulation model of a test vehicle equipped with traction links and yaw dampers with rubber bushes. The simulation reveals that the elastic vibration can be reduced by the traction links equipped with soften rubber bushes. On the other hand, running stability decreases under the condition that the rubber bush of the traction link is soft, especially under the condition when another damper fails. In the simulation, we investigate the desirable displacement-load characteristics of a rubber bush for the traction link in order to reduce the carbody elastic vibration and to secure the running stability. As a result, we confirm that it is possible to cope with both vibration reduction and the running stability by configuring parameters on displacement-load characteristics of rubber bush so that the rubber bushes vibrate in small stiffness at micro amplitude and in large stiffness at large amplitude. Furthermore, we propose a design method of the vibration isolator considering running resistance, and confirm the effectiveness of the method on both vibration reduction and security of the running stability.