Recent advancements in two-photon micro stereolithography have enabled the fabrication of complex micro optics with freeform surfaces. However, the design of freeform microlenses for optical MEMS (Micro Electro Mechanical System) applications remains underexplored. This paper presents a rotary focus-tunable freeform microlens, fabricated using two-photon micro stereolithography, capable of adjusting its focal length through rotational motion. The freeform microlens has a quasi-cylindrical freeform surface, and its curvature in the one axis direction of the incident light continuously changes with the rotational motion. A ray tracing simulation was employed to design a quasi-cylindrical freeform microlens with a diameter of 700 μm, achieving a focal length variation with a magnification ratio of more than 4 times. The quasi-cylindrical freeform microlens was fabricated using two-photon micro stereolithography, and its focal length tuning capability was experimentally tested using a bulk rotation stage. The focal length varied from 0.85 mm to 3.47 mm through the rotational motion, achieving a focal length variation ratio of 4.1 times. This experimentally demonstrated the validity of the proposed design of the quasi-cylindrical freeform microlens. Future integration of this freeform microlens with a MEMS rotary actuator is expected to enable the development of a MEMS-driven focus-tunable cylindrical microlens revolver at the microscale.

In public transportation systems such as trains and buses, where passengers frequently travel in a standing position, the risk of falling due to sudden deceleration—such as during Autonomous Emergency Braking (AEB)—poses a significant safety concern. However, conducting physical experiments under conditions with a high risk of injury is ethically and practically challenging. To address this issue, we developed a full-body human finite element (FE) model incorporating a muscle control system to simulate postural maintenance and physical load during emergency braking. The FE model replicates the human body's ability to maintain an upright posture through muscle activation during deceleration. When the model fails to sustain posture, it enables estimation of potential injuries such as fractures. This study aims to evaluate the effect of nearby standing passengers on the biomechanical load experienced by an individual during AEB events. Two simulation conditions were considered: (1) a single standing passenger holding a strap, and (2) the same passenger accompanied by other nearby passengers standing to the left and the rear, assumed to be a drowsy state, or to maintain an upright position. The braking deceleration was set at approximately 7 m/s². Simulation results indicated that the presence of nearby passengers led to increased contact reaction forces on the passenger, compared to the single-passenger scenario. These increases were attributed to collisions caused by the surrounding individuals. Furthermore, muscle activity prevented passengers from falling; however, it concurrently increased compressive stress in the intervertebral discs. These findings suggest that the presence of nearby passengers and their muscle activity significantly influence the biomechanical load of standing individuals during emergency braking, and should be carefully considered in safety evaluations of public transportation systems.

The performance of Air Drag Brake (ADB) units for Shinkansen trains was predicted using wind tunnel experiments and numerical analysis, and running tests were carried out using a test car equipped with a number of ADB units. First, A large scale wind tunnel experiment was carried out with 20 ADB models. The models were 1/4 scale and placed in a staggered pattern on both sides of a car. The drag reduction ratio k at the downstream ADB models was investigated. It was found that k increased logarithmically as the non-dimensional flow distance increased, and then converged to a constant value of K=0.5. Secondly, computational fluid analysis was carried out using a LES method, with 56 ADB models arranged on the roofs of the middle four cars of a six-car train. As a result, the drag reduction ratio k for ADB models 1st to 14th on the leading car were generally the same as in the analysis and experiment. The total drag force obtained in ADB models with eight cars was estimated to be D_sum = 48.3D₁ (where D₁ is the drag force of the leading ADB model). Finally, the total drag force of the ADB units was verified by running the test car equipped with 92 ADB units. As a result, the total drag force of the ADB units was 106.7 kN at a speed of 360 km/h in a tunnel section, and the ratio D_sum /D₁ = 49.5 was approximately the same as that of the numerical analysis. Therefore, it was confirmed that the total drag force of the ADB units predicted by CFD could be achieved in a real train.

This study presents a variable-sensitivity force sensor utilizing a shape-memory polymer (SMP) sheet embedded with an electric heating wire, whose stiffness fluctuates with temperature changes. Therefore, replacing the force sensor is also pointless, as both the measurement range and sensitivity can be adjusted according to the target of measurement. SMP is frequently characterized as a reversible biphasic structure including a low-temperature "glassy" hard phase and a high-temperature "rubbery" soft phase. This work illustrates a sensor that measures applied force using a strain gauge affixed to a beam of SMP. Consequently, the sensitivity and measuring range of the force can be adjusted based on temperature. In our prior investigation, we assessed an arrangement where a beam is fixed at both ends. However, due to the discrepancy between the measured and predicted values, we have enhanced the design of the force sensor considered in this study to broaden its applicability. Furthermore, we have utilized this improved version to measure the compressive elastic modulus and grip force to assess its superiority. In addition, we compared the calculation method of force with or without the consideration of the viscoelasticity for the grip force measurement. The results validate that the improved sensor can also change the range of the measured force depending on the temperature. Moreover, the results confirm that the compressive elastic modulus and the grip force can be measured by the proposed sensor. The application of a transfer function model in conjunction with a viscoelastic model demonstrated that a more precise measurement of grip force could be achieved by accounting for the viscoelasticity of the SMP.

In this paper, necessity and usefulness of analyzing intensity of singular stress filed (ISSF) at 3D interface corner are discussed to evaluate adhesive strength of scarf joint. Previous studies showed that the adhesive strength of scarf joints can be expressed as a constant critical 2D ISSF at the interface edge when a tensile singular stress appears. In this paper, first, the special bad pair condition when a compressive singular stress occurs at the 2D interface edge in the scarf joint is described in terms of the scarf angle and the material combination of the adherend and the adhesive. Second, under this special condition, the detail analysis method is described for the 3D corner singularity index and the 3D corner ISSF. Third, under this special condition, the adhesive strength of the scarf joint is newly investigated in terms of the 3D corner ISSF. It is found that the adhesive failure criterion can be expressed as a constant critical intensity of singular stress field at the interface corner. This new finding shows that the 3D corner ISSF is especially useful for evaluating the adhesive strength of the scarf joints which have the compressive singular stress at the interface edge.

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.

A knocking control system based on a zero-dimensional heat balance model was implemented on a 1.6L conventional turbocharged gasoline engine to improve the thermal efficiency of internal combustion engines. The zero-dimensional model has been used to predict the exhaust port temperature, with its parameters already identified based on experimental measurements obtained from a test bench in a previous study. Some transient experiments were conducted to assess the effectiveness of the proposed control system. The results demonstrated that the application of the proposed system successfully suppressed knocking and allowed for more advanced ignition timing compared to the conventional coolant control system that maintained a constant coolant water temperature, ultimately leading to improved thermal efficiency. It is found that the present model-based knocking control system and zero-dimensional heat balance model are applicable as pragmatic engine control.

Bicycles are regarded as one of the major risk factors for vehicles. In particular, the behavior prediction of bicycle would be a critical issue for design of autonomous driving system. The utilization of simulation is increasingly expected to efficiently and safely evaluate bicycle-related safety functions. For effective simulations incorporating bicycles, it is necessary to construct a model capable of representing cyclist behavior. Construction of accurate cyclist behavior models requires the measurement and analysis of a sufficient amount of riding data. However, acquiring extensive ride data from actual bicycles is very difficult. Consequently, there has been growing interest in employing bicycle simulators for data acquisition. In this paper, to enhance the reproducibility of bicycle behavior in a simulator while employing a simplified bicycle model, first of all, the parameter estimation is performed based on actual riding data captured using a motion capture system. In the bicycle-cyclist system, since the weight ratio of the cyclist is dominant, the parameter estimation is carried out for each cyclist individually. Second, to replicate the behavior that more closely reflects the real behavior, a model designed to reproduce the wobbling phenomenon is developed and implemented. Finally, several evaluations are performed in order to demonstrate the validity of the proposed model.

This study systematically evaluates the effects of surface treatment methods and adhesive types on the bonding strength between carbon fiber reinforced polymer (CFRP) and two commonly used metals: stainless steel (SUS304) and aluminum alloy (A5052). Three surface conditions—untreated, sanded, and atmospheric pressure plasma treated (APPJ)—were applied, and five adhesives (four epoxy-based and one acrylic-based) were assessed using lap shear tests in accordance with JIS K6850. To elucidate the mechanisms underlying strength improvement, the chemical states of the bonding interfaces were analyzed using X-ray photoelectron spectroscopy (XPS). The results showed that SUS304 achieved high bonding strength even without surface treatment, whereas A5052 required surface modification to ensure adequate adhesion. Sanding enhanced bonding via physical roughening and contaminant removal, while APPJ treatment introduced oxygen-containing functional groups (e.g., C=O, O=C–O) and eliminated surface-adsorbed water, thereby chemically activating the surface. Notably, the combination of sanding and APPJ treatment exhibited a synergistic effect, resulting in further strength improvement. Furthermore, three-point bending tests on CFRP-metal sandwich structures revealed that appropriate surface treatment of the metal layer suppressed interfacial delamination and provided bending strength and stiffness comparable to or exceeding those of monolithic CFRP. In particular, the A5052–CFRP combination demonstrated a favorable balance between weight reduction and mechanical performance. Overall, this work presents a comprehensive evaluation of dissimilar material bonding strategies, offering practical insights for lightweight structural design in automotive, aerospace, and renewable energy applications.

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.