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.

The Pure Pursuit method has been widely used as a standard approach in many autonomous vehicles due to its ease of implementation and low computational cost. However, there is a trade-off between responsiveness and preview distance: while a longer preview distance is necessary to accommodate sudden changes in the reference trajectory, increasing this distance reduces the responsiveness of trajectory tracking. This trade-off arises from the dynamic characteristics of the trajectory tracking system when using the Pure Pursuit method. However, no prior studies have attempted to improve these dynamic characteristics by interpreting the system as a vibratory system. In this study, we aim to resolve the fundamental issues of the Pure Pursuit method while retaining its advantages, such as ease of implementation and low computational cost. Specifically, we propose adding an additional preview point ahead of the vehicle, enabling control over both the natural frequency and damping ratio. We provide a detailed explanation of this method and its practical application.

As part of a study to improve the efficiency of two-phase flow systems using HFO refrigerants, a correlating equation for predicting heat transfer coefficient has been proposed. In particular, the separation angle, which is the boundary between the liquid and gas phases, is an important parameter in the equation for separated flow in a horizontal tube, and it is expected that a more accurate prediction model for the wetting boundary angle can be verified by measuring the temperature distribution using an infrared camera. In this study, a horizontal tube heating apparatus was constructed with a heating test section and a transparent heating apparatus as visible sections to conduct the temperature measurement of the boiling flow of refrigerant R1336mzz(E) by a high-speed infrared camera and visualize the boiling flow pattern by high-speed camera. In the experiments, heat transfer coefficient and frictional pressure drop were measured using horizontal circular tube with an inner diameter of 10.0 mm and the flow pattern was observed at mass fluxes of 100 to 300 kg/(m²∙s) and inlet heat fluxes of 2.1 to 19.3 kW/m². Wavy flow and transition flow to dry-out were observed at low mass fluxes, and slug-wavy, intermittent, and annular flow were observed at high mass fluxes. The heat transfer coefficient and frictional pressure drop gradient were close to the values of the previously correlated equations for the flow pattern stabilized with increasing quality, and these results were reasonable. In the spatial-temporal temperature fluctuation measured by a high-speed infrared camera, the maximum value of the temperature fluctuation was confirmed in the circumferential direction. The temperature fluctuation measurement using a high-speed infrared camera is considered to be a new method to evaluate the separation angle with high accuracy.

To ensure the strength and safety of shafts, which are basic components of machines, it is important to accurately evaluate the stress concentration factor (SCF) of stepped round bar fillets. Noda et al. analyzed the SCF of stepped round bar with fillet under tension and bending by using the body force method and proposed SCF formulas valid for all dimensional ranges. These formulas are very useful in design practice. Since shafts generally transmit power, the SCF of torsion is also important, but there is no solution for the torsional SCF that is valid for all dimensional ranges. In this study, therefore, the stepped round bar subjected to torsion is investigated for all dimensional ranges. The finite element method for an axisymmetric body subjected to a non-axisymmetric load is applied to torsional problems by confirming the coincidence with the SCF solution by the body force method for a round bar with a semicircular notch under torsion. The SCF formula proposed for all dimensional range under torsion shows that SCF charts in literature commonly used in design practice have large errors about 10% because they are based on old research results. Peterson's SCF equation is simple and useful, but the application range of the equation for torsion is extremely narrow and inconvenient to be used in machine design.

This paper presents a topology optimization method for minimizing power dissipation while constraining the maximum temperature in thermal-fluid systems. The advantage of the proposed optimization is its ability to accurately approximate the maximum temperature constraint as a continuous function. It is necessary to solve the complex interaction between thermal and fluid dynamics multiphysics problems in the fixed design domain. The p-norm measure to approximate the maximum temperature constraint is employed to address these challenges, and the coupled Navier-Stokes and energy conservation equations for incompressible viscous flow are solved in forced convection. The proposed method employs a density-based approach, with design sensitivities computed via the adjoint variable method. The finite volume method (FVM) is used to solve both the state and adjoint equations, while the method of moving asymptotes (MMA) updates the design variables. Through several numerical examples, the effectiveness of the proposed method in handling complex thermal-fluid optimization problems is demonstrated. Compared to existing approaches, our method contributes to the optimization of thermal-fluid systems, making it a promising tool for industrial engineering applications.

In recent years, low back pain(LBP) among manufacturers has become a problem. One causes of LBP is the lifting of loads. It has been confirmed that the stoop lifting, where the object is lifted by bending forward with extended knees, puts more strain on the lower back than squat lifting, where the back is straight and the knees and hips are flexed. In addition, it is recommended that men over 18 handle loads of about 40% or less of their body weight, so knowing the object’s weight is important. In this study, we propose a method to determine if the weight of the grasped object is 10 kg or 20 kg immediately after lifting, using a 9-axis sensor attached to the chest and the stoop lifting, which is considered to have a large load on the lower back. A linear approximation was made based on the most recent 0.2s data of the forward tilting angle calculated from the 9-axis sensor measurements, and the change in the tilt was obtained by repeating this process. The difference and maximum of the extreme values at the start of lifting were calculated from the change in inclination, and the amount of grasped material was discriminated against by k-fold cross-validation using a nonlinear Support Vector Machine (SVM) with these two as the feature values. The discrimination accuracy was 82.3%, 7% higher than that of the conventional method calculated under the same conditions. It is necessary to conduct further validation using different lifting methods, known masses, and smaller mass differences in the future.

Due to rapid changes in the market and various customer values, it is necessary to shorten the development period of automobiles. Vehicle performance has been improved mainly through experimental analysis and CAE (computer aided engineering). In the increasingly rapid development of vehicles, machine learning is taking the lead. Vehicle performance prediction usually involves constructing surrogate models using design parameters and CAE results. However, three-dimensionally complex vehicle shapes cannot be fully represented by design parameters. Additionally, reducing vehicle drag has become even more important with the rise of battery electric vehicles. While balancing design and vehicle performance, complex three-dimensional shapes are explored to find optimal solutions, which requires a substantial amount of effort. For predicting vehicle drag performance, a method using variational autoencoder (VAE) is proposed to predict the shape of the vehicle front bumper side, drag coefficient, and flow field on the side and rear of the vehicle. With the proposed method, the drag coefficient was predicted with a maximum error of 0.012, an average error of 0.002, and an R² value of 0.88, demonstrating good agreement with CFD (computational fluid dynamics). Additionally, the predicted velocity magnitude distribution on the side and rear of the vehicle is similar to CFD results. By creating a scatter plot (map) of the latent variables of the proposed method using principal component analysis results, it was found that the direction of increase in the first and second principal components corresponded with the increasing trend of the drag coefficient. Using this map, it becomes possible to predict the drag coefficient, velocity magnitude distribution on the side and rear of the vehicle, and vehicle shape derived from the proposed method. By using the proposed method, it is possible to suggest three-dimensional shapes that were not represented by traditional design parameters, making it easier to balance design and performance and thereby facilitating the search for optimal solutions.

In order to improve the accuracy of fatigue life predictions for power modules under future operating conditions, fully-reversed cyclic bending test method was developed for aluminum wires with a diameter of 0.4 mm. The tests were conducted at a temperature of 175 degrees with frequencies of f = 10, 4, 1, 0.4 and 0.1 Hz, and the fatigue life increases with increasing f. When f was converted to the operating time of the power module, t_on, it was observed that the slope α of t_on and fatigue life on a double-logarithmic scale decreases with increasing t_on, approaching 0. For power modules operating at 175 degrees, α is a function of t_on, and incorporating this relationship enables accurate fatigue life prediction.

An aerodynamic brake is a device that is aimed for increasing air drag to obtain brake force by expanding plates. As proposed by Takami (2013), multiple plates are distributed on the train roof. In this arrangement, many devices are installed in the wake of the most upstream device. In the wake, where the flow is slow, the devices are difficult to gain drag force. Thus, to obtain efficient drag force in this method, it is desirable to rearrange all the devices so that they are subjected to a higher velocity flow. For this purpose, it is important to understand the influence of the device arrangement on the obtained drag, and this drove us to perform a computational flow analysis on flat-plate-modeled aerodynamic braking devices. Specifically, the flat plates are placed in the staggered layout and the clearance between the flat plates (in the crossflow direction) was parametrically varied. Then, their impact on the magnitude of drag force and the flow field were investigated. As a result, by decreasing the clearance between the flat plates from 50 % to 0 % of its width, drag force increased by 11 % because the flow velocity behind the plates easily recovered so that faster flow hits the plates located downstream.

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.