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.

When a copper foil is adhered to a machine element subjected to repeated loads, grains grow in the foil. It has already been revealed that the maximum shear stress and principal stresses, which are important in evaluating the fatigue strength of the element, can be measured from density and crystal orientation of grown grains. EBSD or XRD method was used to analyze the crystal orientation. However, both methods require measurement of the foil inside each equipment, meaning that the principal stress measurement is not convenient. The portable X-ray residual stress analyzer can obtain the crystallographic features of the grown grains in situ as Debye ring. In this study, therefore, we proposed a method for measuring the principal stresses using Debye ring of grown grains. First, a plate-type specimen with a copper foil was subjected to cyclic loading under various biaxial stress conditions to grow the grains in the foil. The copper foil was then measured using a portable X-ray residual stress analyzer to obtain the Debye ring. As a result of various biaxial stress tests, the intensity peak of the Debye ring shifts from 0° to 180° as the biaxial stress ratio increases. This tendency can be explained by the out-of-plane shear stress and is in good agreement with the EBSD method, suggesting that the Debye ring can be used for principal stress measurement. A calibration equation was derived to measure the principal stresses by quantifying this tendency and the measurement accuracy was also examined.

Fracture analysis using damage mechanics models such as the GTN (Gurson-Tvergaard-Needleman) model is applied for the purpose of limit load or limit strain evaluation of structures. It has been pointed out that failure analysis using a damage mechanics model is affected by element size. In general, the material parameters of the GTN model are determined by fracture analysis for tensile test by smooth round bar specimens, but very small element size of 0.5 mm or less are used for fracture analysis. However, it is difficult to adopt such small element size for fracture analysis in large-scale models such as actual structures due to the high computational load. In this study, to establish a fracture analysis technique that can be applied to the evaluation of actual structures, a method for determining the material parameters of the GTN model considering the influence of element size in fracture analysis is proposed. Tensile and compression tests were performed using smooth round bar specimens and the circular–arc notched specimens made of the rolled steel for welded structure SM400A to obtain the basic data necessary for studying a procedure to determine the material parameters of GTN model. The accuracy of reproducing deformation behavior of the tensile test specimens were simulated by the GTN model based on the stress-strain relationship obtained from compression tests that theoretically do not result in void nucleation. Asensitivity analysis using the Monte Carlo method was conducted to investigate the influence of material parameters on the accuracy of reproducing deformation behavior. Based on these results, a method for determining material parameters in the GTN model was proposed. Furthermore, the influence of element size on the results of fracture analysis using the GTN model was investigated. Finally, it was confirmed that by determining the material parameter f_F related to element fracture based on the number of element divisions, a unified evaluation of fracture behavior could be achieved regardless of the shape and size of the specimens.

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.

The effect of elongational flows during molding processes on the tensile strength of polymeric liquid crystal (PLC) plastics has been experimentally investigated. It is known that the molecular orientation profile in PLC plastics exhibits the skin-core structure, characterized by a high molecular orientation near the surface of the moldings and a low molecular orientation in center region of the moldings. The presence of the core region results in a decrease in the tensile strength of PLC plastics. Preliminary simulations of the molecular orientation dynamics suggest that elongational flows have a potential to eliminate or reduce the core regime. PLC moldings are then produced using dies with several different taper angles: 0°, 28°, 60°, and 90°. The elongational rate of PLC flows during molding process increases with a larger taper angle. The elongational rate of PLC flows during the molding process increases with a larger taper angle. The load-displacement curves for moldings made with tapered dies exhibit characteristics similar to those of mild steel, while the curves for moldings made with a straight die show characteristic typical of ductile materials. The fracture stress for moldings made with tapered dies is higher than for those made with the straight die, reaching a maximum for the die with a 60° taper angle. The maximum fracture stresses for extrusion pressures of 2 MPa and 3 MPa are approximately 2.5 and 1.8 times higher than the fracture stress of the moldings produced with a die with a straight hole.

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.

The characteristics of resin multi hole regenerators (R-MHR) and stainless steel mesh regenerators (SMR) were compared in a low temperature difference Stirling engine. Comparing equalized regenerators in the engine with a swept volume of 5 cc and the temperature difference of 80 K, the measured shaft power of the engine with R-MHR was 25% higher than that with SMR, and the thermal efficiency of the engine with R-MHR was 17% higher than that with SMR. These results were mainly caused by the difference in pressure loss and regenerator loss between them. The friction coefficient of SMR is more than 2.92 times that of R-MHR. Nusselt number of R-MHR is higher than that of SMR under the condition that Reynolds number is less than 43, and the practical regenerator loss of SMR is higher due to the effect of the working fluid flow passing through the gap between displacer and regenerator. Through these analyses, it was shown that R-MHR is a better regenerator than SMR in low temperature difference Stirling engine.

A robot motion tracking control system consists of feedback and feedforward controller. The former is realized by state feedback such as PD controller or a dynamic controller such as PID controller, while the latter is obtained by inverse dynamics analysis based on a robot dynamics model. To obtain the robot dynamics model, an approximate solution of minimum set of dynamics parameters is identified from experimental data using the least-squares method, etc. The accuracy of the approximation, i.e., which parameters have priority, is highly dependent on the robot motion and feedback controller used. We have proposed a stochastic parameter identification method using sensitivity analysis to determine the priority of the parameters. However, a state feedback controller is assumed to be used for this approach. In this paper, we derive a stochastic parameter identification method for small periodic motions of the end-effector, such as weaving motion of a welding robot, using a dynamic controller, and verify the effectiveness of the proposed method through experiments using a planar three-link manipulator. Based on the error ellipsoid of the parameters, we show that the priority of the parameters to be identified changes as the controller changes, and that the priority of the parameters that the controller will compensate decreases.

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.

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.

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.

This study proposes a regularization method for high-accuracy prediction by machine learning under small data conditions by combining Physics-Informed Neural Networks (PINNs) and data augmentation based on equation discovery using Sparse Identification of Nonlinear Dynamical Systems (SINDy). PINNs incorporate governing equations into the loss function to enforce physical consistency, while SINDy extracts mathematical models from data, enabling interpolation with continuity and physical interpretability. Validation using crack propagation data (25 points) demonstrated that the combination of SINDy- based augmentation and PINNs reduced the sum of squared errors (SSE) by approximately 28% compared to linear interpolation. The effectiveness of the proposed method was also confirmed for different datasets (59 points). These results indicate that the method is particularly effective in improving learning accuracy for engineering problems where only small amounts of data are available.

In human rehabilitation, the measurement of joint range of motion (ROM) is essential in evaluating the degree of disability and recovery of patients. In clinical practice, ROM is typically measured with an angle meter, but its accuracy depends on the skill level of the measurer, and the task is burdensome. Recently, measurement methods using image analysis have been proposed for ROM; however, their cost is high because of the requirements of vast space and a large number of cameras. Therefore, this study proposes a wearable device for measuring shoulder joint motion targeting the shoulder joint which has many types of ROM measurements. This device, which uses a parallel wire-driven mechanism and can be worn by humans, is expected to facilitate the measurement of shoulder joint ROM. The mechanism consists of a base, output link, and three wires connecting them. This study proposed a method of measuring shoulder joint motion using the kinematics of the mechanism, and designed and fabricated the device. The validity of the device was confirmed through basic experiments, and its practicality for ROM measurement was verified in clinical practice by having humans wear the device.

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 paper refines the ambulance travel model, which is used to determine the optimal route from an emergency site to a hospital, to enhance the accuracy of travel time estimation. The model provides driving rules regarding the acceleration and velocity of the ambulance under the assumption that it moves along a route within a road network consisting of nodes and links. The conventional model, proposed in 2019, has a drawback: it cannot accurately estimate travel time in two specific situations - when the route includes road sections where traffic signals are synchronously controlled, and when there are significant hourly variations in traffic volume. To address this drawback, two new rules are incorporated into the conventional model, resulting in a modified version. To account for hourly variations in traffic volume, the Directions API of Google Maps Platform is utilized to adjust the maximum speed of the ambulance. Based on 90 ambulance transport records collected in Hiroshima City, the model parameters are optimized using the genetic algorithm by minimizing three objective functions related to travel time, a patient’s blood pressure fluctuations, and the compressive force exerted on the patient’s back, in terms of Pareto optimality. As a result of the modification, the estimation accuracy of travel time improved by an average of 4.2%. Especially for the transport route with road sections where traffic signals are placed at short intervals, which the conventional model struggled to handle effectively, the accuracy improved by 97.8%.