We developed an automatic tagging system for design documents based on BOM (Bill of Materials) information. The purpose of the development is to facilitate efficient information retrieval during the design process and to support sharing expert knowledge in railway vehicle design. The system integrates two key natural language processing techniques. First, a BERT + CRF-based Named Entity Recognition (NER) model is utilized to accurately extract specialized railway component names from design documents. Second, an LDA(Latent Dirichlet Allocation)-based model is developed to infer potential tags by learning the latent structural relationships among component names from BOM data. A novel corpus construction method is proposed where BOM information, including hierarchical assembly structures, is converted into a Bag of Words (BoW) vector, enabling LDA to capture co-occurrence patterns and produce meaningful topic distributions. We conducted verification using 69 railway design documents manually tagged with reference component names. The evaluation, based on precision, recall, and F1 score, confirmed that the proposed LDA-based tag estimation model significantly outperforms the traditional TF-IDF approach with an F1 score approximately three times higher than that obtained by TF-IDF. These results demonstrate the effectiveness of leveraging BOM information to model latent structural relationships among component names. In conclusion, this technology can enhance the accessibility of relevant design information, contributing to a more efficient DX(Digital Transformation)-driven production environment.

It is well known that rubber suspensions, which are used in railway vehicles, change the characteristics in vibration transmission such as stiffness over time. This ageing property affects the vehicle running performance. However, the method for predicting such ageing property of railway rubber suspension is not well established. This paper describes the modeling method to calculate the change in stiffness of rubber suspension in the long-time usage for improving the long-term reliability of the vehicle. In this paper, the thermal oxidative degradation, which is one of the major degradation factors in rubber, is discussed. Firstly, heat accelerated ageing test of the rubber block is carried out to obtain the heat ageing properties of the rubber material used in railway suspension. The ageing test results show that the change in strain energy of rubber is dependent on heating time, distance from the surface of rubber block, and strain amount of rubber. Secondly, these heat ageing properties are modeled as the mathematical equations based on the heat ageing test results. The change in stiffness of rubber block due to thermal oxidative degradation is predicted with FEM simulation using the material constants generated by these mathematical equations. By comparing calculation and test results of increase in stiffness after heat ageing, the calculation results with the proposed method are in good agreement with the heat ageing test results. And finally, rubber stiffness change under the thermal oxidative degradation at the operating ambient temperature is evaluated using a formula for the temperature dependence of reaction rates. The results show that the increase of rubber stiffness is large at high operating temperature. Moreover, the results also show that the amount of stiffness increase is affected by the size and shape of rubber suspension.

The maintenance standard values for track irregularity at high-speed type turnouts where trains pass through the main line of turnout at a speed of 120 km/h are managed with stricter values compared to general turnouts. The target track irregularities are longitudinal level irregularity, alignment irregularity, and cross level irregularity. The maintenance standard values for these irregularities of high-speed type turnouts are approximately half of those for general turnouts. This resulted in significant labor and maintenance costs. These values have been empirically determined from running tests conducted in the 1980s. However, since these values were determined empirically, the quantitative validity of these values has not been verified. Therefore, in order to optimize maintenance, it has been necessary to clarify the adequacy of standard maintenance values for track irregularity at high-speed type turnouts on the basis of quantitative technical evidence. This study developed a vehicle running simulation model on turnout using 3D dynamic finite element method (FEM) to quantitatively evaluate the effect of track irregularity on the damage to turnout components. Furthermore, using the developed simulation models, we carried out various studies on track irregularity. As a result, it was found that when alignment irregularity exceeds the current maintenance standard value, it has a significant impact on the damage to track and signal components. Therefore, it is desirable to manage alignment irregularity within the current maintenance standard value. On the other hand, it was found that longitudinal level and cross level irregularity have a small impact on the damage to these components, even when the track irregularities exceed the current maintenance standard value. From these results, it was clarified that the maintenance standard value for longitudinal level and cross level irregularity can be tolerated up to 23 mm, which is the same value as that for general turnouts.

We investigate the deformation behavior of the ballast layer under a grid-type sleeper, using the elastoplastic FEM with the extended subloading surface model. In the elastoplastic FE analysis, we have to utilize the time history of the sleeper reaction as the external force in the FE-based simulation. The time history of the sleeper reaction is evaluated using a wheel-track vibration analysis. Through numerical tests on the jointed track with a suspended joint, the use of the grid-type sleeper leads to the reduction of the ballast settlement.

On railway vehicles, when passengers get on or off, their luggage and other objects can get caught in the doors. If the object caught is large, the pinching of the object is detected by the current door pinching detection device (DPDD). In such a case, the vehicle will not be able to move. On the other hand, it is difficult to detect the pinching of narrow inclusions with the current DPDD. As a result, there is a possibility that the vehicle moves with the inclusion pinched in, or that the inclusion will cause the passenger to be dragged. Therefore, in order to detect these events, we have developed a door pinching detection system (DPDS) using a door rubber with a built-in pressure-sensitive sensor (DRBPS). The DRBPS can detect the pinching of inclusions with a diameter of 8 mm or larger, and can detect dragging that occurs outside the vehicle with a load of approximately 150 N or less. The DPDS can easily transmit the detection information obtained by the DRBPS to security equipment using a non-contact power supply, and can be easily installed in existing vehicles. The results of one year of operation with DPDS installed in real vehicles showed that no missed detections or false detections occurred, although some detections were caused by contact with the low-risk rubber end of the door.

An aliasing type reducer, which fulfils both a high reduction ratio and low vibration in a thin and small body, had been proposed to cope with the further downsizing of DC motors. This reducer consists of two disks with sinusoidal grooves of the same amplitude but different periods, bearing balls rolling in grooves, and a disk with oval holes formed at equal intervals around the circumference through which the bearing balls can move radially. The two grooved disks sandwich the disk with bearing balls in its oval holes, and the bearing balls are held at the intersections of the two types of grooves. The disk with the groove of larger period works as the input plate, the disk with the oval holes as the output plate, and the other grooved disk as the stator, respectively. The reduction mechanism is inspired by the "sampling theorem." As the input plate rotates, the bearing balls engaged with each groove reciprocate radially within the oval holes, decelerating the output plate and rotating it in the same direction as the input plate. It is confirmed that the prototype has extremely small output torque fluctuation during power transmission, and that the idling torque is as small as that of a planetary gear reducer. However, the torque transmission efficiency is only 70%, which is significantly lower than that of a planetary gear reducer. This is thought to be due to the slip friction between the bearing balls and the grooves, and is a forthcoming challenge.

This study focused on the piston system and targeted vehicle interior noise caused by combustion, which is mainly due to vibration transmission in the high-speed, high-load region. Vehicle interior noise is defined as having both a combustion excitation force, which causes the piston to move due to combustion, and a structural excitation force, which causes the engine block to vibrate due to piston movement. The purpose of this study was to index these forces to develop noise and vibration suppression technologies and adapt them to design concepts. Conventionally, the relationship between combustion and noise and vibration is discussed in terms of ensemble averages. However, due to the nonstationary properties of noise and vibration, this paper analyzed both excitation force characteristics for vibration on a cycle-by-cycle basis. Engine vibration is affected by heat release characteristics, even with the same engine structure specifications. As heat release characteristics, combustion speed: the maximum second derivative of heat release value and combustion phase: CA50 were identified as indicators of the excitation force of combustion. Engine vibration is also affected by piston specifications, even when heat release characteristics are the same. The maximum piston tilt angle, maximum piston tilt speed, and maximum piston translation speed were identified as indicators of the structural excitation force. Based on these indicators, various means have been devised to suppress noise and vibration caused by combustion.

Heat exchangers for air conditioners are generally composed of aluminum fins and copper tubes, and their performance has been improved over the years since 1970. On the other hand, microchannel heat exchangers achieve significant performance improvements by increasing refrigerant-side heat transfer performance and reducing airflow resistance through the application of microchannel tubes, and by reducing the contact thermal resistance between the fins and tubes through aluminum furnace brazing. It is also possible to reduce material costs by making it all aluminum, and in recent years, this technology has attracted attention as it can be applied to air conditioners to improve system efficiency, make products more compact, and reduce the amount of refrigerant. This paper summarizes the development trends that have been conducted to date in applying microchannel heat exchangers to air conditioners, and presents current challenges and future prospects.

In this study, the effectiveness of the electrical impedance method (EIM) for monitoring lubrication conditions in helical gear systems during actual operation was investigated. A custom-built gear tester equipped with helical gears, and an alternating current circuit was used to monitor the lubrication conditions through EI signals. The temporal changes in EI signals were analyzed to estimate the dimension less thickness and breakdown ratio of the lubricant film at the gear mesh. The results revealed that the EIM effectively monitors the temporal changes in the lubricated conditions at the gear mesh of the helical gear. The technique also demonstrated the ability to monitor lubrication regimes through evaluating the dimension less thickness and breakdown ratio simultaneously. Thus, the EIM presents a promising tool for real-time monitoring of the lubricated conditions in helical gear systems.

The contact characteristic of a tire is fundamental property that significantly influences handling stability, ride comfort, and environmental performance such as rolling resistance and wear. Although it has been experimentally confirmed that the rolling contact pressure distribution of a tire exhibits circumferential asymmetry, a theoretical interpretation of this asymmetry is not self-evident. This study proposes a new tire mechanical model that calculates contact pressure distribution during tire rolling. The proposed model is a tire model that integrates a three-dimensional elastic ring model and brush elements of tread. The brush elements representing the tread exhibit variable stiffness, designed to emulate the hysteresis behavior of tires as confirmed through experimental observations. The validity of the proposed model was verified using an inner-drum tire testing machine equipped with road surface segments embedded with force sensors. In this model validation, the model parameters for sidewall and belt stiffness were theoretically calculated from tire design parameters, while the tread stiffness parameters were identified based on experimental results. The validation showed that the proposed model qualitatively reproduced the measured rolling contact pressure distribution with circumferential asymmetry in the contact plane. The proposed model is expected to be utilized in design studies aimed at achieving the desired tire contact pressure characteristics.

Prestressed concrete sleepers (PC sleepers) are an important component of railway tracks. The dynamic response of PC sleepers to passing trains is influenced by various factors relating to the vehicles and tracks. However, few studies have quantitatively evaluated the relationship between wheel surface roughness and the bending moment of PC sleepers. In this study, we measured the wheel surface roughness of the target vehicles under normal use conditions and the bending moment of PC sleepers when the vehicles passed over them on the commercial line. Additionally, we quantitatively evaluated the relationship between wheel surface roughness and the bending moment of PC sleepers using numerical analysis, the validity of which was varied through comparison with field measurement results. The results were as follows: 1) A wheel flat with a dip of about 0.5 mm was measured. 2) Compared to the roughness spectrum of a wheel without a wheel flat, the wheel flat increased the roughness level at spatial frequencies of between 10 and 100 m^-1. 3) No significant difference was observed in the measured bending moments between vehicles with and without wheel flats. 4) This is because the influence of the measured wheel surface roughness on the bending moment was smaller than that of the rail roughness. 5) Numerical analysis showed that when wheel flat length is 75 mm or more, the bending moments peak at low vehicle running speeds of around 15 km/h. At a wheel flat length of 75 mm, the bending moments are up to 3.7 times greater than when there is no wheel flat. 6) The rounded wheel flat shifted the speeds at which the bending moment peaks to higher speeds, but had little effect on the maximum value. 7) Of all the track parameters, the spring constant of the rail pad had the greatest influence on the bending moment.

This study deals with a tilt control pattern design for a tilting train using air springs. When a railway vehicle travels on a curve, the tilting system tilts the car body by supplying compressed air to the air springs on the outer rail, causing them to expand. However, when the vehicle runs on a railway track with continuous curves, there is a possibility that the vehicle may run out of compressed air. Therefore, in this study, based on the compressed air consumption estimated from the internal pressure of the supply air reservoir, a tilt control pattern that reduces the car body tilt angle was generated. The tilt control pattern for continuous operation of the tilting system was calculated using dynamic programming. To calculate the tilt control pattern, a four degrees of freedom model combining a simplified vehicle model and a supply air reservoir model was used. For simplicity, a condition for continuous operation of the tilting system was that the internal pressure of the supply air reservoir did not fall below the internal pressure of the air spring. Under this constraint, we generated the tilt control patterns for a route with continuous curves with the same curvature. As a result, by selecting curves with shorter circular sections and generating tilt control patterns with reduced tilt angles on those curves, continuous operation was enabled, although ride comfort deteriorated.

In recent years, the proportion of elderly individuals in Japan has been increasing, accompanied by a rise in the number of patients with osteoarthritis. In particular, artificial joints, which are effective in treating knee osteoarthritis, commonly use Co-Cr-Mo alloys (CCM alloys) for their sliding surfaces due to their ability to suppress uneven wear. However, conventional CCM alloys pose a problem during sliding use, as they generate biotoxic metallic wear debris. To address this, high-carbon Co-Cr-Mo alloys (HC-CCM alloys) with improved wear resistance have been developed. Nevertheless, there have been few studies on the machining of HC-CCM alloy with end mills. This study investigates the high-speed machining of HC-CCM alloy using radius end mills, focusing on the influence of tool material and cutting speed on cutting performance. The results showed that both carbide and CBN tools reached their tool life limit within a short cutting length. In contrast, the binderless nano-polycrystalline cubic boron nitride (RcBN) tool exhibited excellent wear resistance, achieving a machining length of up to 7.0 km. These findings indicate that the RcBN tool is highly effective for machining HC-CCM alloy. Furthermore, excessive tool damage was observed at cutting speeds exceeding 15 m/s, suggesting that an optimal cutting speed is approximately 10 m/s.

This paper presents the results of a validation study assessing the adequacy of a method proposed in a previous study, which continuously measures the lateral contact position between the wheels and rails of a railway vehicle. A series of tests were conducted at speeds of up to 30 km/h using a railway vehicle equipped with an instrumented wheelset specifically designed to measure the contact position. This wheelset had been fabricated as part of the earlier study. Consequently, it was confirmed that the proposed method is capable of continuously measuring the contact position, even during wheel climb events. However, there were instances in which the contact position could not be determined. Periodic fluctuations caused by computational errors were also observed; however, these were effectively mitigated through a moving average processing. The inability to determine the contact position was primarily attributed to high-frequency fluctuations (approximately 300 Hz) in the bridge output and computational errors inherent in the proposed method. The former is considered to have minimal impact when the contact position is measured at approximately 100 Hz. The latter affects the filtered contact position at 100 Hz, but its influence can be reduced through moving average processing. To further verify the adequacy of the proposed method, the authors conducted a direct measurement of the contact position using paint. This was achieved by photographing the areas of the wheel tread where the paint had been removed due to contact with the rail. A comparison with the moving-averaged contact positions revealed a discrepancy of approximately ±2 mm, thereby confirming the sufficient accuracy of the proposed method.

This study describes the development of a microcurrent supporter powered by a triboelectric nanogenerator (TENG), designed to be integrated into an ankle supporter. Microcurrent therapy (MCT) is known for promoting tissue repair, reducing pain, and enhancing muscle recovery. However, conventional MCT devices are not suitable for use during exercise due to size and power source constraints. To address this, the authors developed a self-powered, wearable TENG system that harvests biomechanical energy during walking and delivers microcurrent stimulation through the skin via water-soaked conductive sponge electrodes. The TENG structure employs stacked layers of triboelectric films with conductive nonwoven electrodes, achieving peak voltages exceeding 200 V. A tribotronic energy extractor (TEE) was incorporated to regulate and enhance current output to a biologically effective range (50–500 μA), overcoming impedance mismatch between TENG and human skin. Experimental results demonstrated that when the supporter was used with water-soaked sponge electrodes, contact resistance dropped to 0.1–0.5 MΩ, enabling effective current delivery. Muscle stiffness measurements in the gastrocnemius and soleus muscles showed that applying microcurrents via the TENG-supporter system significantly suppressed post-exercise muscle stiffness compared to no current condition, particularly in the gastrocnemius muscle within the first 45 minutes post-exercise. These findings suggest that triboelectric-powered microcurrent delivery systems can be effectively used during physical activity, offering a novel approach to real-time muscle care and recovery.

This study examines Operational Transfer Path Analysis (OTPA) for vibration-acoustic dynamics in complex vehicle systems. OTPA simplifies data collection by avoiding structural transfer function pre-measurement, overcoming traditional method limitations on complex paths. It uses multivariate regression for transfer function estimation but faces noise and multicollinearity. Conventional PCR-based OTPA for vibration-acoustic coupling often misidentifies dominant sound contributors by prioritizing high-energy vibrations, potentially overlooking critical low-energy components or the low radiation efficiency of high-energy ones. To address this, a Partial Least Squares (PLS) regression-based OTPA is proposed. PLS extracts 'acoustic latent modes' by maximizing covariance between reference vibrations and response sound, better linking vibrations to acoustics. The PLS-OTPA is verified to extract key sound-constituting vibration modes and shows improved accuracy over PCR methods in analyzing an air-conditioning outdoor unit's piping. This approach significantly refines transfer path analysis accuracy, advancing vibration and acoustic analysis.

This study evaluates the effectiveness and risks of using AR goggles in a hands-free standing-type Personal Mobility Vehicle (PMV). AR goggles, which overlay digital information onto the real world, have significant potential for enhancing efficient information access and entertainment experiences during travel. In the experiment, Apple Vision Pro was utilized to compare conditions with and without AR goggles, as well as to evaluate the effects of different screen positions. Foot pressure data and questionnaire were collected. The results showed that wearing AR goggles increased the maximum displacement of foot pressure during turns, indicating a higher risk of falling. Increased COP (Center of Pressure) oscillation was also observed, suggesting potential instability. Survey responses indicated that wearing AR goggles led to increased fatigue and instability, negatively affecting ride comfort. However, the visual entertainment aspect of AR goggles was highly appreciated. In conclusion, AR goggles are effective for enhancing information access and entertainment during travel, but they pose risks of falling and reduced ride comfort in a hands-free standing-type PMV.

Classical ballet and other forms of dance have both aspects of sports competition and artistic performance. Dancers require not only the technical skill to control body movements but also the expressive ability to effectively and impressively convey emotions and narratives to an audience. While physical movements can be measured and quantitatively evaluated, it is challenging to quantitatively assess people's subjective impressions of dance. Addressing this challenge, research aimed to quantify and objectively evaluate ambiguous Kansei information, handle nonlinear relationships, and specifically analyze skeletal movements in dance. To investigate the impressions ballet, a questionnaire survey was conducted. This involved using 18 pairs of Kansei words to evaluate nine sample videos, which allowed for the definition of decision classes. Subsequently, rough set theory was applied to analyze the relationship between ballet body movements and these impressions. Analysis focused solely on skeletal movements, deliberately excluding elements like background, music, and costumes that significantly influence overall impressions. OpenPose was utilized to detect human joint points and generate a BODY_25 Model. Dance characteristics were then defined using 8 attributes, each with two possible values to thoroughly analyze the correlation between body movement features and the impressions perceived by viewers. By utilizing rough set theory, the ability to extract patterns and regularities from data containing subjective human judgments is demonstrated. This enables an objective evaluation of the relationship between body movements and Kansei information such as "beautiful" or "elegant" derived from ballet's physical expressions. This approach proves that rough set theory's robust analytical capabilities can effectively analyze the nonlinear relationship between body movements and viewer impressions.

Finite elements analysis (FEA) has been widely used for evaluating the performance of products in practical engineering design processes. In the FEA of industrial equipment, such as large-scale motors and transformers, the accurate identification of material constants for iron core components is essential. This identification is formulated as an inverse problem based on mechanical properties. Surrogate multi-objective optimization has been widely employed to solve this problem, demonstrating high accuracy. However, the identified material constants are not always uniquely determined and may result in physically unrealistic values. From a practical perspective, it is crucial to obtain physically realistic material constants. To address this issue, this paper presents two key ideas: (1) the introduction of an in-plane isotropy constraint that reflects the structural characteristics of the iron core, and (2) the consideration of the sensitivity of objective functions with respect to material constants. The former effectively confines the search space to a physically plausible region, thereby enhancing both the physical realism of the identified constants and the accuracy of the FEA results. The latter contributes to improving the uniqueness of the identified values. These ideas are validated through a case study of an iron core component. The results of this study show the effectiveness in improving identification accuracy and ensuring the physical plausibility of the estimated material constants.

To reduce energy consumption in production systems, it is effective to evaluate energy-saving measures through simulations in advance. However, conventional methods require significant time and effort to construct and analyze multiple simulation models for different energy-saving measures configurations. Automating this process improves efficiency, but existing methods struggle with model complexity and reliance on human experience, risking the omission of effective measures. To address this challenge, we propose an automated approach using 1D-CAE models to systematically explore energy-saving configurations. Our method integrates engineering constraints in Alloy with Modelica-based simulation models to automatically generate and evaluate feasible system configurations. A key feature is a hierarchical constraint structure, where Modelica-dependent constraints are extended to define system-specific constraints, ensuring both syntactic validity in Modelica and physical relevance. We demonstrate this method using a 1D-CAE model of an injection molding machine, demonstrating a systematic exploration of energy-saving technologies.

Adaptive cruise control (ACC) is one of the critical elements of vehicle performance in the market. To ensure the quality of ACC performance, comprehensive evaluations that control both complex test scenarios that reproduce market driving conditions and vehicle behavior is required. However, it is difficult to evaluate all combinations of test scenarios using real test vehicles within limited development resources. Furthermore, it is necessary to determine complex Electrical Control Unit (ECU) parameters while considering multiple performance trade-offs. This paper proposes a new automatic screening and exploration system for ACC, incorporating Bayesian active learning (BAL). The proposed system automatically explores the worst conditions of ACC and the design space of ECU parameters for the improvement of vehicle ACC performance. This system consists of two automated elements: an automatic evaluation system and an automatic exploration system. In the automatic evaluation system, the behavior of ACC is automatically evaluated in real-time simulation using Real Car Simulation Bench (RC-S). Additionally, ACC sensor simulation is used to simulate various driving scenarios that may occur in the market. In the automatic exploration system, the worst condition screening evaluation of ACC performance and the exploration of the feasible region of design space for ECU parameters using BAL are conducted. As a result, it becomes possible to make the evaluation process more efficient through closed-loop evaluation, thereby improving ACC performance. In BAL, a Gaussian process model of ACC performance evaluated by RC-S is trained. Based on the posterior distribution of the trained Gaussian process model, the acquisition function is evaluated and maximized to generate new sampling points. In this study, an example of data comparison between RC-S and a real vehicle driving on a test course is demonstrated to show the effectiveness of the proposed system.

Shape design optimization of 3-dimensional solid structures must satisfy two key objectives: high mechanical performance and light weight. For machines in motion, time-response problems in design optimization are crucial for machine life and reliability, requiring optimal time-response characteristics depending on the given objective function. Time-response problems (e.g. the dynamic compliance minimization problem) arise not only in solid structures made of single materials but also in composite structures composed of heterogeneous materials. Heterogeneous composite structures can exhibit excellent mechanical behavior that is unattainable with single-material structures. For example, by using dissimilar materials with different thermal expansion coefficients, it is possible to control thermal displacement through interface shape design optimization between the two different materials. Shape design optimization is also beneficial for reducing the dynamic compliance of solid structures within a limited volume. Bimetals are a type of heterogeneous composite structure consisting of two different adhered metals. In recent years, metal additive manufacturing technology has rapidly advanced, allowing for precise fabrication of metal parts. This study aims to develop a gradient-based interface shape design optimization method for minimizing the dynamic compliance of 3D bimetal composites. First, we formulate the design problem, where the time-dependent dynamic compliance is set as the objective function to be minimized, with the time-response governing equation and the volume constraint serving as the constraint conditions. Then, we theoretically derive the shape gradient function (i.e., the sensitivity function) and perform the velocity analysis to obtain the optimal interface shape between the adhered metals. Furthermore, the effectiveness and feasibility of the proposed interface shape design optimization method are validated through design examples.

Plastic injection molding (PIM) is a major manufacturing technology to produce plastic products for high product quality and high productivity. The process parameters such as the melt temperature, the packing pressure and the cooling time affect the product quality and productivity, and thus it is important to determine the optimal process parameters. Recently, the pressure vibration injection molding (PVIM), which vibrates the pressure during the filling and packing phases, has attracted attention. The mechanical properties, the viscosity and the shear stress are mainly discussed through the experiment in the literature, but the period and amplitude of pressure vibration are rarely discussed. In this paper, the process parameters optimization in PVIM is performed for a thin-plate product. The warpage and the cycle time are simultaneously minimized for high product quality and high productivity. The numerical simulation in PIM is so intensive that sequential approximate optimization using radial basis function network is adopted. It is clarified though that numerical result that the PVIM makes the distribution of shear stress and pressure uniform, and thus the warpage is well reduced. Thus, the PVIM is an effective approach for warpage reduction and short cycle time.

This paper proposes a novel inspection system for seismic isolation and vibration control devices using unsupervised deep learning to enhance evaluation reliability and objectivity. Conventional force and stiffness assessments through loading tests require human inspectors, creating potential subjective bias and necessitating impartial third-party evaluation. The proposed deep learning system minimizes human intervention, significantly improving test result consistency while eliminating operator bias. The unsupervised learning approach enables the model to learn exclusively from normal operational data, facilitating detection of anomalies in previously unseen patterns with high sensitivity. This paper presents a comprehensive framework encompassing data generation, preprocessing, and model inference. Experimental validation using oil dampers and laminated rubber bearings, representative components in seismic isolation technology, demonstrates the method's effectiveness with approximately 98% classification accuracy for oil dampers and 100% for rubber bearings in distinguishing normal from anomaly conditions. These results confirm the system's viability for large-scale manufacturing deployment. Furthermore, anomaly visualization capabilities provide valuable insights for manufacturers and regulatory bodies, reinforcing the importance of objective and transparent evaluation. This inspection system establishes a robust foundation for quality control in seismic isolation and vibration control technologies, with significant potential for broader adoption toward ensuring safer and more reliable infrastructure.

This study discusses the concept of resilient multi-agent systems and algorithms for their realization. Specifically, we focus on improving the optimization algorithm for task assignments and applying it to a mid-air retrieval mission. In particular, this study highlights the mid-air retrieval of a low-speed descending object, supported by a parachute, by one of three unmanned aerial vehicles (UAVs) that constitute a multi-agent system as a representative case. The results demonstrate that the optimal task assignments can be achieved within practical computation times. This capability enables prompt and appropriate adjustments to task assignments in response to dynamic changes in situations and environments, marking a significant step toward realizing practical resilient multi-agent systems. Different from the conventional methods such that they pursue mathematically rigorous optimal solutions, this study aims to obtain solutions suitable for practical applications within shorter time frames. Therefore, we propose a method to derive optimal task assignments based on approximate trajectory planning, as verified through numerical simulations. These simulations demonstrate that, in the case study, one of the UAVs can successfully capture a low-speed descending object with feasible maneuvers. In this paper, the issue of deriving exact optimal trajectories using the obtained approximate trajectories as initial solutions still remains. This issue is one of the important subjects in this study and we will discuss it in another paper.

In order to understand rocking vibration characteristics of a small structure installed on the seismic isolation system using sliding mechanical system under various condition, we have performed vibration test and proposed a numerical analysis model using 2-DOF. From results of vibration test using sine waves and observed seismic ground motions as inputs, it was indicated that the rocking vibration and overturning behavior of a structure can be suppressed by setting the dynamic friction coefficient. The rocking vibration and overturning behavior of the structure could be suppressed by the dynamic friction coefficient on the small seismic isolation system in which the small friction coefficient that could not reach the overturning limit acceleration amplitude of the structure was set. In case of input as sine waves and seismic ground motions, it was good agreement between response wave forms in vibration test and numerical analysis. Therefore, the numerical model using 2-DOF proposed in the study is effective to evaluate vibration behavior of small structure installed on the seismic isolation systems with sliding mechanical system.

This paper proposes the fluorescence response-based optical probing (FROP) method for the 3-dimensional measurement of precise products. Several 3-dimensional measurement methods exist, such as micro-coordinate measuring machines, confocal microscopy, and point autofocus microscopy. However, measuring precise products with small, smooth, and steep (3S) structures—such as die molds and optical lenses—remains challenging. In this study, we propose a new surface detection scheme that utilizes autofluorescence from the sample surface. Unlike reflected light, fluorescence is emitted over a wide angle. Therefore, the optical response from the surfaces of 3S structures can be obtained by exciting fluorescence at the measured surfaces. This paper first explained the principle of FROP. Next, the fundamental FROP signal was examined on surfaces tilted at different angles. The FROP successfully detected vertical and even overhanging surfaces, demonstrating its strong potential for 3-dimensional measurement. The principle of surface position determination was then verified through comparisons with conventional confocal microscopy for 2.5D measurements, and thickness measurement results were compared with micrometer results. These results revealed that the peak position of the differentiation signal in FROP coincided with the sample surface. Finally, a 3-dimensional 3S structure was measured. The results confirmed that vertical surfaces could be successfully measured using the FROP method, whereas conventional confocal microscopy could not measure them. Consequently, the performance of FROP for 3-dimensional measurement of precise products was validated.

Active control of flow separation on a bluff body model utilizing dielectric barrier discharge plasma actuators (DBD-PAs) was experimentally demonstrated at Re = 28,000. The model consisting of a flat side plate and a quarter cylinder with a radius of 84.5 mm was placed 200 mm downstream from the exit of the blowing-type wind tunnel and fixed at a yaw angle of 10 degrees relative to the main flow. In the conventional spanwise arrangement of exposed electrode utilizing a string-array-type plasma actuator consisting of six Cu wires coated with silicone rubber and exposed electrodes, the control effect significantly decreased as the distance from the separation point increases. Therefore, blowing-type and suction-type vortex generating plasma actuators (VG-PAs) with exposed electrodes arranged in the streamwise direction were prototyped by combining the string- array-type DBD-PAs, and the effects of suppressing flow separation were verified by generating blowing and suction jets. Both blowing-type and suction-type VG-PAs were effective in suppressing flow separation, with the blowing jet reducing the displacement thickness by 64% and the suction one reducing it by 85% compared to the no control case. Strain rate analysis of the Y-Z cross section revealed that the control effect of the suction-type VG-PA can be obtained over a wider range in the spanwise direction than that of the blowing type VG-PA.

Tensegrity structures are lightweight structures, often deployable, consisting of axial members (rods and cables). One of their design problems is to determine the minimum member mass to support an external force under the buckling and yielding conditions. In the previous work, the deformation of the structure is not considered, and the equilibrium position is assumed to be known in advance. However, when the structure is subjected to an asymmetric force, for example, the equilibrium position is not obvious and is typically unknown. As a more realistic problem setting, this study discusses a minimal mass design considering the deformation by an asymmetric external force. The self-equilibrated configuration is chosen as the initial configuration for the optimization. The internal force at this configuration is called the prestress, and is often utilized to improve structural stability and stiffness. The problem setting in this paper also allows us to introduce the prestress in the design. Mechanical formulae considering the deformation without the prestress are first derived. A minimal mass design problem allowing the deformation can be formulated by using these formulae. The problem is a nonlinear problem with many variables, and requires proper initial estimates. The paper also addresses this issue by employing dynamical simulation. The prestress can be introduced by modifying the member force calculation in the above formulae. Numerical examples are conducted to show the efficiency of the proposed method.

The damping performance of a rolling-ball damper was examined experimentally and numerically. The damper consists of multiple rolling balls on a circular track attached to the main vibration body. Since, unlike mass-spring-tuned mass dampers, it does not use a spring, it is far superior in durability. Moreover, the cover of the damper ensures that the rolling balls will not jump out from the track. However, determining the combination of parameters that maximize performance remains challenging. In this study, we used a novel evolutionary algorithm and the discrete element method. In terms of convergence and calculation time, we compared the particle swarm optimization (PSO) and cuckoo search algorithms and chose PSO as the evolutionary algorithm. To verify the validity of the numerical method, an experimental apparatus that acts as an equivalent horizontal single-degree-of-freedom system was used. The main vibration body is excited sinusoidally at the support using a motor and a slider-crank mechanism. Steel balls were used as rolling balls. The displacement of the support and the main vibration body was measured using two laser displacement sensors. The numerical results were compared with the experimental results for the relationship between amplitude and frequency to verify the validity of the numerical method.

This paper deals with an advanced version of eMDVA (embedded Mass Dynamic Vibration Absorber), which is a passive multi-modal damping device that was proposed by the authors. The eMDVA consists of a mass embedded in a viscoelastic material, and the mass can vibrate freely in all directions. The authors showed in their former works that the eMDVA consisting of a single mass sphere embedded in a spherical or elliptical viscoelastic material with a constrained outer shape is valid for multiple vibration control target frequencies. Considering practical use, the authors are developing another configuration of the eMDVA where many masses are dispersed and embedded in a sheet-like viscoelastic material. While the original eMDVA utilizes the multi-directional vibrations of the embedded mass as a multi-modal dynamic vibration absorber, the sheet-like configuration achieves multi-modal vibration damping by using different sizes of masses. In this work, we take up an eMDVA in which a mass sphere is embedded in a cuboid viscoelastic material, assuming a partial element of the sheet-like eMDVA and the influence of the external shape of the viscoelastic material on the vibration of the embedded mass is investigated using finite element analysis. It is shown that the peak frequencies of the frequency response function (corresponding to natural frequencies of the embedded masses) can be adjusted by changing the diameter of the mass sphere and the thickness of the viscoelastic material, and this means the sheet-like eMDVA can be designed by the size of the embedded mass sphere. The numerical and experimental results are described in this paper, including the configuration of multiple masses embedded in the viscoelastic material side by side. In addition, a series of excitation tests are conducted using a plate-like structure, a 1:10 scale model of a railway vehicle’s underframe, and the multi-modal vibration reduction effect by the eMDVA has been confirmed.

This paper proposes a simple passive device with an adjustment mechanism for spring constant and damping coefficient to realize a dynamic vibration absorber (DVA) that can be used for various vibration control target frequencies. The proposed device consists of a coil spring and an air spring with an auxiliary reservoir and orifice. The active coil of the device's coil spring can be varied to adjust the spring constant. The main tank and reservoir tank are separated by an "orifice disk" with several orifices of different diameters, and the damping coefficient can be changed by selecting one of these orifices. A numerical model was constructed to design the spring constant and damping coefficient, and a DVA equipped with the proposed adjustment mechanism was developed. The results of stand-alone vibration tests showed that the changing trend of vibration response property agreed well with the numerical results, and the proposed adjustment mechanism worked well. Then, vibration control tests were conducted by mounting a dynamic vibration absorber on a plate-like structure that simulates the underframe of a railroad car at approximately 1/10 scale. As a result, a significant vibration reduction was successfully achieved for the bending mode of elastic vibration, and the usefulness of the proposed spring constant and damping coefficient adjustment mechanism was confirmed by adjusting the optimum spring constant and damping coefficient values, which varied at each measurement point.