Automobile bodies are assembled by resistance spot welding of 3,000 to 6,000 points per car, mainly on pressed thin plate components. In this study, a low-power, high-strength joint was investigated by inserting a low boiling point compound into the joint interface and using the vaporization and volume expansion of the compound caused by heat during resistance welding to break down the oxide film and increase the area of strong joint. As a result，higher tensile strength was obtained than that of the non-inserted joint.

In this study, a novel tomographic system of stress visualization (OCSE) is proposed on the basis of PS-OCT, which can provide stress tomography from photo elastic interference fringe pattern at a cross-section, even when sample is turbid material under anisotropic stress distribution (not plane stress condition).In this experiment, OCSE was applied to laser welded material of PAR and PBT/PC alloy material．As a result, this system can offer the proposed method can non-destructively visualize the internal stress distribution at the micrometer resolution. Consequently, it was concluded that there is a correlation between internal stress and laser conditions.

Using non-combustible magnesium alloys for structural materials contributes to weight reduction in transportation equipment. Therefore, appropriate joining method for non-combustible magnesium alloy with high reliability is necessary. Self-Piercing Rivet (SPR) joint has been widely applied to joining aluminum alloys and is suitable for joining of dissimilar metals. In this study, SPR joint was applied to a non-combustible magnesium alloy AX41, and fatigue strength properties of AX41 similar material joint and dissimilar materials joints with AA6061 and SPCC were evaluated. The dissimilar material joints exhibited higher fatigue strength compared to AX41 similar material joint. Depending on the combination of the upper and lower plate materials, cracks may occur during the joining process, and fatigue properties may be affected. Regardless of the plate materials combination, stiffness of a plate is considered to have a significant effect on fatigue strength of SPR joint because deformation of upper and lower plates has an effect on fatigue mechanism.

Against the background of growing needs for super engineering plastics in CFRTP molding, we verified the effect of Si-DLC on reducing the peel-off strength between molded resin and mold surface. In particular, we focused on whether or not a sufficiently low peel-off strength could be achieved without using a mold release agent by applying Si-DLC to the surface where PEEK material is melted and solidified. The PEEK specimen is given a melting-solidification temperature history on three types of metals or DLC films (SUJ2, Si-DLC, ta-C), and the adhesion interface is peeled off at a peeling temperature after solidification. In SUJ2, the peel-off strength increased monotonically from 8.10 to 21.09 MPa as the peeling temperature increased from 30 °C to 130 °C, which is near the glass transition temperature of PEEK. When Si-DLC was applied, the peeloff strength was not smaller than that of SUJ2.

In this study, Suspension Plasma Spraying (SPS) and Atmospheric Plasma Spraying (APS) thermal barrier coatings were used. After solid solution treatment, heat exposure tests were conducted at a temperature of 1000 ° C for a holding time of up to 1000h. The oxide layer (TGO layer) morphology, residual stress, In oxide layer (TGO layer) and interfacial fracture toughness were investigated. It was confirmed that the structure of the top coat layer of the SPS test piece has a crack suppressing effect. In addition, it was confirmed that, the residual stress and the interfacial fracture toughness decreased in the SPS test piece with an increase in exposure time.

Equations of fluid dynamics, for example Navier-Stokes’ equation are based on continuum model of fluid. These days, miniaturization of the machines have been progressed. MEMS and μTAS are the examples. Actualization of the true nano size machine is desired in future days. In nano size, the liquid should be treated as discrete model. In present study, flow of LJ liquid around nano-size body is simulated by pseudo 3-dimensional molecular dynamics (MD) method. The purpose of this study is to analyze and visualize the behavior of nano scale flow.

In this study, we demonstrate that thermally induced Knudsen forces in a rarefied gas can be exploited to achieve a tweezer-like mechanism to trap and grasp a micro-object without physical contact. Using the direct simulation Monte Carlo (DSMC) method, we showed that a heated thin plate, mounted perpendicularly on a flat substrate, can act as the tweezer-like mechanism. Specifically, it is found that the pressure differences induced by the thermal edge flows around the corners of the beam and the tip of the thin plate, generate a force that attracts the beam to the plate horizontally and vertically.

In modern society where the words such as SDGs and carbon neutralization have become keywords, it is essential to study how to successfully reuse the unused heat energy, such as the factory heat removal, in the circular society. Therefore, we focused on studying the Leidenfrost phenomenon of liquid in order to convert the unused heat into energy that can be used again. When a liquid approaches the object whose temperature is much higher than the liquid's boiling point, the liquid droplets produce an insulating vapor layer that makes the droplets hover over the hot object. It is called Leidenfrost phenomenon. This non-contact state between the droplet and hot object hinders the heat transfer and increases the evaporation time dramatically. In general, temperature and object surface state will affect the evaporation time of the liquid in Leidenfrost state. In this research, we studied the relationship between the evaporation time and the releasability of object surface. The experimental results shown that the evaporation time was extended by subjecting the substrate to a releasable and non-adhesive treatment. Moreover, it is also necessary to investigate the effect of the change in the releasability of the substrate surface on the characteristic of droplets in the Leidenfrost state, which self-moves on a substrate having a serrated structure.

In recent years, hydrogen energy, which does not emit carbon dioxide when used, has been attracting attention as a candidate solution to environmental issues. Hydrogen is produced as a mixture of hydrogen and carbon dioxide or other gases, mainly using fossil fuel reforming. Therefore, in order to use hydrogen as an energy source, the gas mixture must be separated and purified to a high-purity hydrogen. The methods currently used require advanced technology, leading to increased costs. This research has developed a gas separation system utilizing the Soret effect, a thermal diffusion phenomenon caused by a temperature gradient, as a simple and low-cost method to extract hydrogen from a hydrogen and carbon dioxide mixture. Since the separation caused by the Soret effect is very small at one time, previous studies have employed network separation structures to achieve high efficiency. This time, we succeeded in improving the separation performance by optimizing the size of the partition structure inserted at the gas branching area.

Coarse-grained molecular simulations based on non-Markovian dissipative particle dynamics can reproduce the dynamic properties of fluids, whereas they cannot reproduce the static properties with sufficient accuracy. This is because many-body effects are not considered. To overcome this drawback, we need an interaction model that considers neighborhood particle configurations near coarse-grained particles. In this study, as a method of modeling the conservative force term in the governing equation of non-Markovian dissipative particle dynamics, we define a density function to evaluate the particle configuration around coarse-grained particles and show the way to calculate the force acting on the coarse-grained particles based on this density function by conducting modal decomposition.

In recent years, water shortage has been getting worse in the world. To solve the water shortage, research on desalination, which is the process of obtaining fresh water from seawater that accounts for 97.5% of the earth's water, is attracting attention. Various desalination methods, such as reverse osmosis (RO), have now been established. However, the electricity to operate these systems is generated from fossil fuels, which are anxious about being depleted and emit CO₂. In recent years, membrane distillation technology has been attracting attention because of its low environmental loading and the ability to utilize waste energy. In this study, a prototype of a laboratory-scale seawater desalination system was developed, and desalination was attempted. In the analysis of flow pattern inside the device, vertical and horizontal inflow patterns were compared. After the device was fabricated successfully, experiments of distillation from 1 wt% NaCl aqueous solution with membrane has nano scale pores were conducted and freshwater generation was experimentally confirmed.

The Leidenfrost phenomenon is a unique behavior of droplets, in which a liquid, close to a surface with hotter temperature than the liquid's boiling point, produces an insulating vapor layer that makes the droplets hover over the surface, rather than making physical contact with it. This non-contact state between the droplet and hot surface leads to the decrease in heat transfer and the increase in evaporation time. Due to its characteristics, this Leidenfrost phenomenon has been involved in various industrial technologies, such as liquid cooling methods, precision machinery and semiconductor fabrication. In this study, we conducted the basic research using different solvents for innovating an industrial technology by controlling the behavior of droplet in the Leidenfrost state. As a result, we found that the behavior of the mixed solvents exhibit different compared with that of each solvents, and the droplet behavior can be controlled by adjusting the mixing ratio of the solvents. In the future, it is necessary to investigate the behavior on the diffrent surface state and to observe the Leidenfrost phenomenon in the smaller droplets.

Leidenfrost phenomenon is one of the unique behaviors of droplets. In Leidenfrost phenomenon, liquid closing to a surface that is significantly hotter than the liquid's boiling point, produces an insulating vapor layer that keeps the liquid from boiling rapidly. This non-contact state between the droplet and the hot surface leads to the decrease in heat transfer and the increase in evaporation time. This phenomenon occurs for the micro-order droplets. For example, it is influence the combustion efficiency of the engine in which fuel sprayed. For another example, the mist CVD, which is one of the functional thin film fabrication methods, also makes a good use of the Leidenfrost phenomenon to make high quality thin films. This has been indirectly proven by the previous experiments, but there was no direct observation, which needs to be verified. In recent years, the evaporation behavior of microdroplets is also involved in the removal of bacteria from the air due to the spread of infectious diseases. In this study, we developed an observation device for checking the evaporation behavior of micro droplets and a program for measuring the droplet diameter, analyzed the evaporation behavior of droplets by optical observation. The experimental results shown that the range of observation conditions was improved and the accuracy of droplet measurement was enhanced. In the future, we will continue to enhance the accuracy of machine and study the observation methods to further improve the measurement accuracy.

We propose a method for creating a reduced-order model (ROM) for temperature prediction that is applicable to nonlinear time-variant systems, able to be created using a very small amount of data, and easy to interpret. Our nonlinear time-variant ROM is an extension of sparse identification of nonlinear dynamical systems, which was first proposed in 2016. Three machine learning methods are developed for automatically deriving a thermal network model from time-series data. Link relationships between temperature nodes and parameter settings, such as thermal resistance and heat capacity, are automatically inferred by machine learning. The effectiveness of the proposed method is demonstrated using the results of thermo-fluid analysis for a natural air-cooled power module in which thermal resistance is a function of temperature. The ROM was created using the results of 15 thermo-fluid analyses, with is fewer than the 25 independent variables in the ROM. The computational efficiency of the created ROM is very high, and unknown data, including extrapolated data, were predicted with error of less than 1 K. By using the proposed method, it is expected that design parameters can be fine-tuned and actual loads can be taken into account, and also that condition-based maintenance can be realized through real-time simulation.

Fluids under supercritical conditions exhibit unique physical properties that differ from those under subcritical conditions or standard temperature and pressure conditions. For this reason, when performing numerical simulations of fluids under supercritical conditions, the fluid cannot be treated as an ideal gas, and it is necessary to consider the non-ideal property of the fluid. However, if a simulation is performed considering the non-ideal property of the fluid, more computation time is required compared to the case where the fluid is treated as an ideal gas. To reduce the computational cost if non-ideal properties, we developed a mathematical model that can estimate fluid properties considering non-idealities using deep learning, and by replacing it with a conventional method, we confirmed that the calculation speed can be accelerated while maintaining the calculation accuracy of the conventional method in a multi-component flow field under supercritical conditions.

Molecule generation is crucial for developing materials and drugs while exploring the huge and discrete chemical space. Targeted at the electret material design, 53000 amines are sampled from the PubChem for training deep generative models. It is found that sequence-based model struggles to comprehend the syntax of SMILES strings and the sensitivity to slight change of strings limits the zoom-in search of electret molecules with similar substructures. Besides, although early stopping is used, GAN-based likelihood-free molecule generation suffers from mode collapse with less stable training process. In comparison, the variational auto-encoder (VAE) framework renders better and smoother generative results where discrete representation of a molecule is encoded into a real-valued multidimensional continuous vector.

In the design of Francis turbine runner, improvement of variable flow characteristics is one of the problems. Conventionally, performances at not only the design point but also non-design points were optimized using various optimization methods such as multi-objective genetic algorithm. However, since general Pareto ranking technique treats all objective function with the same priority, the solutions with high efficiency at non-design point but low efficiency at design point might be obtained. The highest efficiency point of such solutions would deviate from the design point, therefore, a technique to match those points is needed. In this study, we developed the Bayesian optimization system for Francis turbine runner design using computational fluid dynamics (CFD), Gaussian process regression (Kriging) model, and multi-objective genetic algorithm. To match the highest efficiency point and design point, non-swirling discharge of each solution was evaluated from CFD results, and a constraint was considered using the discharge predicted by Kriging model. Finally, it was confirmed that the solutions obtained by Bayesian optimization with the constraint of non-swirling discharge is superior to the one without the constraint.

Real-time micrometeorology predictions are important for heat-stroke risk reduction and safe drone logistics in urban streets. However, the extensive calculation cost hinders operational real-time predictions of micrometeorology. In order to solve this, it is proposed to use a super-resolution simulation system that can provide high-resolution (HR) predictions at the low cost for low-resolution (LR) simulations. The system utilizes the super-resolution that converts LR maps into HR ones by means of machine-learning technologies. The super-resolution technology has been advancing rapidly and its neural networks can now learn physics to some extent. It has, however, the room for improvement. We propose the Pixel Attention Super-Resolution Network (PA-SRN), which gives attention weights to features and space at the same time. The training and test data for the deep neural networks were generated from the building-resolving urban micrometeorology simulations with a multi-scale atmosphere-ocean coupled model named the Multi-Scale Simulator for the Geoenvironment (MSSG). The proposed PA-SRN model has improved learning accuracy compared to a conventional algebraic interpolation and other existing neural network models. In addition, the analysis of attention weight distributions has clarified how the proposed neural network learns the physics in the micrometeorology data.

Particle size distribution of soil is often evaluated by “the method for particle size distribution of soils (JIS A 1204)”. This method requires long sieving time and accurate mass measurement of sieved soils, resulting rapid evaluation of in-situ soil characteristics and admission decision of soil classification difficult. Image analysis using an image analyzer, developed by Marui Co. and named “Sand measure”, has been applied for rapid evaluation. The method holds the error generated by the overlaps of soil particles. We have applied machine learning with expanding the input data to image analyzer for reducing the error. The machine learning is installed in the model composed of Convolution Neural Network. The machine learning reduces the error by about 40 % of the results evaluated by test data. Maximum reduction in error is about 78 % in test data. The image analyzer with machine learning can be applicable for rapid evaluation of particle size distribution.

Investigating the permeability and porosity of rocks is essential for petroleum production, CO₂ geological storage and etc. The permeability is one of the most basic physical properties that evaluate the ease of flow of fluid in a porous object for understanding the behavior of fluids such as water, oil, and CO₂ in rocks. Laboratory experiments using excavated rock for permeability estimation is very time and cost-consuming. In recent years, estimation of physical properties of rock using the deep learning technology has received a lot of attention. In this study, we have developed a method for efficiently predicting the physical properties of permeability using the convolutional neural networks (CNN). Four types of convolutional neural networks have been tested: basic CNN, VGG, GoogLeNet, and Resnet. These networks are trained using the dataset of directly calculated permeability values based on flow simulation and the corresponding raw CT images. By comparing the prediction accuracy of each network, we found that the Resnet model showed the best performance.

This research focuses on the feature of human dynamic motion during the use of seated personal mobility vehicles (PMV). Ten motion conditions were set up from different speed, direction, and motive methods. Two pressure sensors were used to measure the pressure and changes of center of pressure in back and hip with different speeds and directions under the autonomous conditions and manual conditions. To find out the feature of in different conditions, a deep learning program based on the ResNet were used to classify and plan to extract the feature map to show the feature of human dynamic motion. While, the poor classification result obtained is not so good because the vehicle motive in relative low speed both autonomous and manual conditions, displacement of center of pressure may not show significant difference. For this point T-test is used, and shows that both autonomous and manual conditions average displacement of centers of pressure after the vehicle braked 1 second are similar while in the beginning of vehicle starting moving are different.

This study concerns a method for evaluating the structural anomaly of F type support information board from acceleration measurements. Acceleration of the top of supports columns were measure about three years. The evaluation f structural anomaly is performed by the autoencoder method．In the method training of the autoencoder is conducted from the normal conditions, and diagnosis of the structural is conducted by estimation error from the data neural network． The diagnoses are performed to the information board at two sites．Data of site B，which has unstable boundary，has high fluctuation to the natural frequency and constant fluctuation to the average of the natural frequency．Data of site A has stable natural frequency．Additionally site B shows a large change in condition after the typhoon passed, and the autoencoder was able to show a significant change in error value. At site A, the values were stable, and although there were temporary fluctuations, the results were not problematic in the long term. Therefore, the method of structural variation detection using the autoencoder is a practical method.

This research is about the diagnostic method of anomaly of bridge measurement using machine learning. In this study, diagnostic method of the condition of bridges via convolutional neural network (CNN) based on the acceleration responses is proposed. Spectrogram images of acceleration response are applied to image classification using a CNN. The condition of bridges is identified or detected by classifying spectrograms for each condition of the bridge. The number of learning generations is able to increased by employing a CNN model that incorporates a dropout layer. The optimal number of learning generations is determined from the learning curve using the loss function. Result of the damage detection for both of the bearing section (damage level high) and slab section (damage level low) shows high accuracy. Above identification accuracy, bearing section shows higher accuracy. Therefore, it be able to say that proposed damage diagnostic method using CNN is effective for condition diagnosis of bridges.

This study focused on the effect of ignition position in the pre-chamber on front chamber jet combustion. To investigate the effect of ignition position, we designed a pre-chamber visualized cylinder head with multiple ignition positions that can capture the pre-chamber combustion. From the visualized images, it was found that two different jet morphologies, a pre-existing jet and a pre-existing unburned mixed gas jet, are produced depending on the ignition position. In the case of the pre-existing jet, it was confirmed that the combustion pattern of the sub-chamber affects the main chamber flame spread velocity.

In this study, PM exhausted from unsteady pool flame of iso-octane on a shallow dish under various furnace temperature conditions (25 – 700 °C) was investigated as fundamental study of fuel film combustion. Flame appearance during from ignition to combustion end under various furnace temperature conditions was observed. And relationship between maximum flame length and furnace temperature was obtained. Moreover, total masses of CO, CO₂ and PM emitted during flame formation period were measured. As the result, it was also found that total mass of PM exhausted during flame formation period increased with furnace temperature raise.

In this study, three types of gasoline surrogate fuels were used to investigate the effect of fuel chemical composition on combustion and auto-ignition characteristics. For the study, an optically accessible engine capable of velocity analysis was used to observe the combustion and auto-ignition behavior. The results showed that the knock intensity of TRF with high toluene content was lower than that of S5R due to the OH consumption effect during combustion, but the knock suppression effect of toluene weakened at higher temperature and pressure conditions. Next, as the reason why auto-ignition did not occur only for PRF 82.6, the combustion rate analysis and chemical reaction numerical analysis indicate that the cold flame reaction and H₂O₂ reaction loop are more active in PRF 82.6 than in the other fuels, resulting in a shorter ignition delay and faster flame spread speed, and thus no auto-ignition occurred. Conversely, in TRF and S5R, the OH consumption effect by toluene and the suppression of the cold flame reaction and H₂O₂ reaction loop resulted in a slower flame spread velocity than in PRF 82.6, which created a time delay before auto-ignition and thus auto-ignition occurred. In addition, it can be inferred that the main reason for the frequent occurrence of wall auto-ignition in S5R is that, unlike PRF 82.6, this fuel does not have an NTC region.

Nano meter size particulate matter (PM) formed by the combustion process of hydrocarbon fuel has harmful effects on human health. Fundamental research works for investigation of formation behavior of PM precursor such as polycyclic aromatic hydrocarbons (PAHs) in combustion process were required for the reduction of nano-PM emission. In this study, PM and PAH formed by low temperature (less than 1350K) pyrolysis and oxidation of hydrocarbon fuel using a flow reactor were investigated. The mass concentration of PM was obtained by the filter sampling method with a glass-fiber filter, while the mass concentration of PAH was analyzed by a Gas Chromatography. In addition, numerical simulation for PAH formation was performed using a CHEMKIN-Pro software. As a result, it was found that the mass concentration of PM increased with temperature raise under various equivalent ratio conditions (φ = ∞, 6.2 and 2.8). Therefore, it was also found that the mass concentration of PM without oxidation condition was higher than that with oxidation condition.

Combustion origin particulate matter (PM) has different characteristics such as hydrophilicity and hydrophobicity depending on the combustion method, however it is difficult to separate each PM characteristics. In this study, to develop real-time selective PM sensing system using a quartz crystal microbalance (QCM), PM adsorption characteristics on the QCM surface was investigated. PM emitted from a pool flame of hydrocarbon fuel such as cyclohexane and toluene was supplied to the QCM, and the frequency shift of the QCM was measured. In addition, polystyrene coated QCM with hydrophobic and acetylcellulose coated QCM with hydrophilic characteristics were also investigated.

Nitrous oxide (N₂O) is a greenhouse gas and contributes to ozone depletion, and ammonia (NH₃) contributes to the formation of secondary particulate matter. To reduce global warming and particulate matter, the real-world levels of N₂O and NH₃ emitted from automobiles is required to be examined. However, there are a few studies on the measurements of N₂O and NH₃ in automobile exhaust under the real-world conditions. In this study, we have measured the real-world emissions of N₂O and NH₃ from the latest diesel vehicle equipped with an urea-SCR system. N₂O was measured by an on-board system using mid-IR laser spectroscopy and NH₃ was measured using a sensor-based measurement technique. As a result, NH₃ was not emitted, while N₂O was emitted intermittently when vehicle was running.

We conducted an experimental study of effects of dispersed oil droplet diameter on micro-explosion of oil-in-water (O/W) emulsion droplet during spheroid-type evaporation on a heated surface. The base fuel was n-dodecane, the surfactant was polyoxyethylene (6) lauryl ether. O/W emulsion was made with Shirasu Porous Glass (SPG) membrane, which is hydrophilic and has numerous and continuous pores, and then degassed. Also, the emulsion was stirred at low speed during the experiment. The hot surface temperature was 700 K, the initial droplet diameter was 1.95 mm, and the water content was 0.4. The pore diameter of the membrane was varied from 5 μm to 50 μm. The experiment of dropping the emulsion was conducted more than 30 times for each condition. The particle size distribution showed that the dispersed oil droplet diameter and its Sauter mean diameter decreased with the decrease of the membrane’s pore diameter. And as the pore diameter became smaller, the start time of phase separation was delayed. Total waiting time for disruptive microexplosion and its Weibull average increased with the decrease of the pore diameter. These results are considered to be due to the delay in the start time of phase separation as the dispersed oil droplet diameter decreases.

Engine deposits in exhaust gas passages cause the increase of the pumping loss and the failing of the valve action. Deposits also affect EGR gas temperature in cooled EGR system because their thermal conductivity is low. Therefore, it is necessary to reduce engine deposits in order to improve engine performance. In this study, the influences of the inner surfaces of pipe on deposit formation are investigated by comparing the deposition on SUS304 and two kinds of fluorocarbon polymer, PTFE(polytetrafluoroethylene) and PFA(copolymer of tetrafluoroethylene and perfluoroalkyl vinyl ether). Deposits are experimentally formed by smoke produced when diesel fuel is burning in an alcohol lamp or actual exhaust gas emitted from a gasoline engine. The results indicate that different surfaces make difference to the amount and shape of deposits. In addition, it is suggested that small Van der waals force and non-wettability contribute to deposit reduction.

The purpose of this study is to clarify the seismic response reduction effect of the piping system by a dynamic vibration absorber. The piping system with a dynamic vibration absorber was modeled into a two-degree-of-freedom system composed of a simple modal mass and a dynamic vibration absorber. Using this model, the floor response spectrum for the observed seismic waves was calculated. By comparing the changes in the two floor response spectra of the piping system with the dynamic vibration absorber and the piping system without the dynamic vibration absorber, the response reduction effect of the dynamic vibration absorber and the magnitude of the added damping ratio were discussed. When a dynamic vibration absorber was installed, the peak height of the floor response spectrum of the piping system decreased, and the effect was useful for the piping system with a smaller damping ratio. Dynamic vibration absorbers are suggested to be an effective method for reducing the seismic response of small-bore piping systems with a small damping ratio.

Elasto-plastic response analysis of pipe systems including the pipe supports is necessary to evaluate the seismic fragility for input seismic motions exceeding the design assumptions. However, the elasto-plastic response analysis method for pipe supports has not been developed yet. In this study, we aim to develop the elasto-plastic response analysis method for pipe supports by focusing on the non-linearity of the load-displacement characteristics. We also conduct parametric analyses on the material properties, etc., for existing loading tests. This paper reports the quantitative computing for energy dissipation with the load-displacement characteristic curves obtained via the analyses, and the comparison between the analytic results and experimental results.

In previous reports, a new seismic fatigue evaluation method based on the vibration velocity was proposed. In this study, the cumulative fatigue damage was evaluated by the rain flow method as well as the new method for the case where the seismic input acts on the cantilever pipe with the concentrated mass at the tip. When the cumurative fatigue damage was relatively large, both results were shown to be in good agreement, especially at the peak values of the response spectra. It was shown that quantitative fatigue evaluation is possible using the new method.

To collect the actual material strength of carbon steel tee pipe, a tensile test by cut-out test pieces was conducted. In addition, inelastic FEM analysis on a simple configuration of pipe specimen including a tee pipe was conducted. In the inelastic analysis, four kinds of yield stress settings were used, and the effect of yield stress setting was examined for out-of-plane static loading and for sinusoidal excitation. From the results of the tensile test, it was found that the yield shelf did not appear in the tensile test, and that the yield stress was approximately 1.6 times higher than the minimum yield stress determined by the JIS standard. This is considered due to the work hardening effect during the manufacture process of tee pipe. In the dynamic analysis under sinusoidal input, it was confirmed that the higher setting of yield stress brought the larger response acceleration and larger plastic strain accumulation.

This is a follow-up article to a talk given a week ago at the D&D 2022 conference. At that time, we discussed the rate of deterioration of vibration suppression performance of the DVA optimized based on the H_∞ criterion that occurs when the two absorber masses of a parallel-type double-mass dynamic vibration absorber (DVA) are set to equal. There are five dimensionless parameters necessary for optimal design of the double-mass DVA. One of them is the mass ratio of two absorbers arranged in parallel. Depending on a given system condition, the optimum mass ratio of the two absorbers becomes as small as 0.75(75%), but even when this mass ratio is set to 100%, the degradation rate of the DVA performance was only 0.43%. Now, in addition to the H_∞ criterion, which aims to minimize the height of the resonance point of the primary system, there is the H₂ criterion, which minimizes the area (called the H₂ norm, which represents the energy of the vibration) under the curve obtained by squaring the frequency response function. In this presentation, we investigate how much the performance of a DVA designed with this H₂ criterion deteriorates when the two absorber masses are equal.

Mechatronic damper, that is an electromagnetic damper, has a damping force in general. The damper complies with ball screw mechanism and generator. The damping force is depended on terminal resistance of the generator, and it is controllable. However, Dr. Zhu’s group researched about the mechatronic damper based on active control, it was called mechatronic inerter, which could get an inertia force by using a force feedback PID active control, and reported in simulation. In this paper, to confirm it and moreover get switchable inertia effect, vibration tests are carried out by using the mechatronic damper and another simple control method. Finally, it is clear from the experiments that inertia effect can be varied when current goes to the generator will be controlled.

A new weldable ferrous-based Fe-Mn-Si (FMS) seismic damping alloy with excellent fatigue durability was developed by optimizing the phase transformation behaviors in both fatigue deformation and solidification. Fatigue and welding tests were performed on prototype alloys with nominal compositions of Fe-15Mn-(10+2X)Cr-(8-X)Ni-4Si, (X=0, 0.5, 1, 2). The fatigue lives of these alloys were superior to those of general steels, and the fatigue lives of the alloys with X=0.5 were comparable to those of the previously developed FMS alloy, X=0. However, the fatigue lives decreased with increasing X (increase in Cr and decrease in Ni). The analysis on the microstructure after fatigue fracture suggests that the decrease in fatigue life was due to the deformation-induced formation of α’-martensite that might have inhibited the fatigue damage mitigation mechanism through the bidirectional transformation between γ-austenite and ε-martensite (BTRIP). On the other hand, increasing X resulted in a change in solidification mode and improved solidification cracking susceptibility: significant segregation and solidification cracking were observed for X=0, while segregation was eliminated and no cracking occurred in X=0.5. These results indicate the Fe-15Mn-11Cr-7.5Ni-4Si corresponding to X=0.5 has excellent properties as a second-generation FMS alloy that can realize a welded assembly damper with excellent fatigue durability.

The development of a SFR(:Sodium-cooled Fast Reactor) is carried out by Japan Atomic Energy Agency and others. Not only the decrease of horizontal seismic loads, but also the decrease of vertical seismic loads is important in SFR which has thin wall structures. Accordingly, the three-dimensional isolation system is developed for the seismic design of the components. This isolation device consists of a thick rubber bearing, four coned disc spring units, four vertical oil dampers, eight sliding functions and a supporting function. Furthermore, horizontal oil dampers are installed for damping force. This isolation device has few critical development elements and no additional function such as the rocking suppression device. In this isolation system, the natural frequency in the horizontal direction is 0.29Hz, the natural frequency in the vertical direction is 3.0 Hz. This isolation device is premeditatedly developed from 2017. This project has carried out load tests with full and half scale coned disc springs. The design method of coned disc spring units has been confirmed. Furthermore, this project has developed the horizontal oil damper of high allowable velocity and the vertical oil damper. This project is carrying out load tests of the half scale three-dimensional seismic isolation device, which consist of the thick rubber bearing, the coned disc spring units, the supporting function and so on. The development of this isolation device will be continued sequentially. The fundamental design method of this isolation device is confirmed in this project.

The purpose of this study is to investigate the applicability of proportional damping to reduce the computational load, which is a common issue for seamless structural integrity evaluation with a 3D-FEM model. When the proportional damping is applied, it is necessary to compare this method with current design method (strain energy proportional damping) regarding on the seismic response calculation precision. Therefore, the research target is to construct a modeling method of proportional damping that realizes the same calculation precision as current design method. The ratios of the maximum stresses in strain energy proportional damping and proportional damping were confirmed using the 3D-FEM model with multiple damping properties, and the applicability of the proportional coefficients setting method based on the magnitude of the effective mass ratio was examined. As a result, it was confirmed that the proportional damping method can calculate the same stress distribution as current design method by setting the proportional coefficients for vibration modes with large effective mass ratios and for the upper limit frequency of the target frequency range.

The various vibration tests have been conducted, depending on the specification and shape of the structure. However, the data, which was obtained from these vibration tests, are underutilized in the failure evaluation caused by vibration. In this study, the failure probability evaluation method of the similar structure is investigated based on these test data. In previous studies, cabinets and underfloor equipment on railroad vehicles were investigated based on the PRA (Probabilistic Risk Assessment) method used in nuclear facilities. As a result, the failure probability could be evaluated at classifying these sample appropriately before the vibration test. Furthermore, in order to adapt this method to more structures and equipment, an evaluation indicator, which can be evaluated regardless of differences in input waves, is necessary. Accordingly, in this report, the vibration tests with the simple examination specimens were carried out in order to investigate the vibration energy which input to the equipment and accumulated. The natural frequency of the simple examination specimen is 112Hz. The sine wave test was carried out at the resonant frequency. The accumulated energy to failure, was investigated for each vibration test. As a result, the accumulated energy increased with increasing input acceleration, furthermore, the average value of the accumulated energy to failure was approximately 3750 [J] on this test condition.

A ouble-slit breakwater has two water columns, one at the sea side and the other at the land side. an oscillating water column type wave energy converter has been proposed to utilize these chambers. In this presentation, the performance of a wave generator installed in both or one of the two chambers was evaluated in a water tank experiment. In the experiment, a 1/25 scale model of the actual system was used to evaluate the performance in regular waves. The regular waves ranged from 0.6 to 2.4 seconds with a wave height of 5 cm. Air chambers were installed on both the sea and land sides, and it was found that the water level amplitude of the seaward air chamber was larger at the short periods of 0.6 and 0.8 seconds, while the amplitude of the land side air chamber increased as the period increased. In other words, more energy is absorbed in the seaward air chamber in waves with short periods, and more energy is absorbed by the land-side air chamber in waves with long periods. The phase difference between the two air chambers was found to decrease as the period becomes longer. It was also confirmed that when air chambers were installed only on the seaward side or only on the landward side, the air chambers exhibited characteristics similar to a dynamic damper.

Simple support structures such as U-bolts and clamps are used for the low-seismic-class piping designed using the constant pitch span method. Recently, the safety of the piping is required during the earthquake, and the demand for safety in nuclear power plants has increased. As a result, the high seismic resistance has also been required for the low-seismic-class piping. In the response analysis, the support structure constrains the displacement in two translational directions, but not the axial displacement of the pipe. Depending on the routing of the piping, a large axial response displacement may occur, and the structural integrity of the piping and the support structure may not be ensured. Therefore, measures have been taken to add or reinforce support structures. In practice, pipes are subjected to the axial friction resistance by the support structure, which reduces the response displacement. A static element test was conducted to understand this axial resistance. In this test, the friction resistance force was measured with no tightening force. Specimens were G28 (about 3 kg) and G54 (about 6.5 kg) pipe elements. The resistance force about 3.5 to 7 N for G28 and about 7 to 15 N for G54, and the friction coefficient about 0.18 were observed. By taking this into consideration, it is expected that the response displacement during the earthquake will decrease. The development of a rational seismic evaluation method considering the frictional resistance in the axial direction will be continued.

This paper deals with the response behavior of the multi connected vehicles subjected to seismic excitation. The multi connected vehicles are modeled by a set of vehicle models that have 21 degree of freedom. The running road is modeled by mass, spring and damper system that have 1 degree of freedom in three directions. One of the problems with multi connected vehicles is that they have a large degree of freedom, and the calculation cost considerably increase. Therefore, we made the reduced order model by using sparse estimation. We investigated the influence of vehicle characteristics on reduced order model. As a result, the number of modes required for the reduced order model to reproduce the original model is less when the motor car is not considered than when it is considered. In addition, when considering a model that includes motor car, the reproducibility car by car of the original model is affected by the number of motor cars and their positions.

It is important to analyze responses of a high-speed-moving vehicle when it receives a seismic wave, because such vehicle has risks of leaving the rail and overturning. It needs much simulation cost to analyze them because of complexities of the car models. So, we investigated about the reduced-order-model which includes some vibration modes chosen by sparse estimation. Especially we studied effects of types of seismic waves and with/without running roads. We used three types of earthquakes, and made the reduced-order-model which is suitable for each seismic wave to estimate risks of overturning. In conclusion, it was possible to estimate risks of overturning by using about 10% vibration modes of the original model. And it needs more vibration modes when we considered the running road than when not considering it. Also, we found that we could estimate risks of them by using one common model for three types of earthquakes.

This paper deals with vibration response of connected cabinets and electronics inside subjected to seismic wave by using the elasto-plastic dampers which is installed between cabinets. We consider the behavior of the adjacent cabinets with the electronics connecting by two elasto-plastic dampers. The cabinets are modelled by the rigid bodies rotating around their lower corners. The electronics in cabinets are modelled as masses moving in the translational direction in the cabinets. The elasto-plastic damper has bilinear hysteretic characteristics and can absorb the energy of the earthquake inputs. We compare the responses by changing lower connecting positions and mass of electronics. When we connect the dampers near the bottom and the top of cabinets, the maximum rocking angle increased. This may be because the moment around the center of rocking motion is small at the bottom, while the moment is too large at the top. When we change the mass of electronics, the maximum rocking angle decreased when the mass of electronics is about 80~155kg. This may be because the moment acting on the cabinets become smaller in that range.

Piezoelectric NC-shunt damping is a technique for vibration suppression by connecting an external circuit called the NC-shunt circuit (Negative capacitor shunt circuit) to a piezoelectric element attached to a mechanical structure. In this paper, we develop the multimodal NC-piezoelectric shunt-damping by proposing a new cost function, which enables to evaluate the decreases in multiple resonance peaks equally. The proposed method takes the difference between the gain peak when uncontrolled and the gain peak when the selected NC-shunt circuit is used. It then selects the smallest of the multiple vibration modes and optimizes it to be larger. Numerical examples are demonstrated to evaluate the effectiveness of the proposed cost function. In addition, we investigate the gain diagrams of the open-loop transfer functions to clarify the key issues in the broad-band vibration control performance of the NC-shunt circuit. It is shown that the vibration control is effective if the anti-resonance and resonance frequencies of the open-loop transfer function are located between the bending points of the admittance.

In this paper, we designed a generator and power conversion circuit for battery-free real-time wireless sensing powered by magnetostrictive vibration power generation, and demonstrated it on a bulldozer blade vibration. We attached the generator device to the blade and measured the open circuit voltage, and confirmed that a power equivalent to 29.8 mW was obtained. In addition, by supplying power from the generator through a power conversion circuit to a wireless sensor with a power consumption of 10 mW, it was confirmed that sensing could be performed without interruption. Thus, we demonstrated that battery-less real-time wireless sensing by magnetostrictive vibration power generation is feasible.

In the steel plate manufacturing process, deterioration of surface quality due to contact between the roller and the steel plate has become a problem. Our research group is continuously researching a system that levitate a flexible steel plate while bending it. It has been confirmed that when a flexible steel plate is magnetically levitated, it bends in a range where electromagnetic force does not apply, but the levitation is stabilized by bending the steel plate. In this study, dynamic analysis was performed using the finite difference method, and the vibration characteristics of the levitating steel plate were examined.

"Flying cars", which are being developed in Japan and overseas, are expected to be a new means of transportation for people and things. But noise reduction is essential to use them in residential areas because they may not be able to meet the noise regulations. In this study, we investigated the directivity of a drone propeller’s noise using multiple microphones in order to understand the noise characteristics of a fan for vertical take-off and landing aircraft(VTOL). In addition, a target plate simulating the ground effect was installed downstream of the propeller, and changes in the sound field due to the difference in distance between the target plate and the propeller were investigated. Furthermore, we also grasped the noise reduction effect when the propeller blade has a tip anhedral.