Stability of tall rectangular and horseshoe shaped tunnels in cohesive-frictional soils subjected to surcharge loading has been investigated numerically assuming plane strain conditions. In this study, continuous loading is applied to the ground surface, and both smooth and rough interface conditions are modelled. For a series of tunnel diameter-to-depth and tunnel width-to-diameter ratios and material properties, rigorous lower- and upper-bound solutions for the ultimate surcharge loading are obtained by applying numerical limit analysis. The results are presented in the form of dimensionless stability charts with the actual tunnel stability numbers being closely bracketed from above and below. Finally, an expression that approximates the ultimate surcharge load has been applied.

The selection of covariance function significantly affects spatial distributions estimated by Gaussian Process Regression (GPR). Gaussian and Markovian models have been used for the covariance function in many studies. Special covariance functions, which assign a correlation of 0 when the distance exceeds a certain value, are proposed also. In this paper these functions are called as sparse covariance functions. The covariance function M-R proposed by Melkumyan and Ramos is one of the sparse covariance functions, and is formulated to have a shape similar to the Gaussian model. This study examined the spatial distribution and computation cost by GPR with the sparse covariance function, using synthesized data. The spatial distribution by GPR with Gaussian and M-R were in good agreement with the true distribution. The contour map of the negative log-likelihood about hyperparameters shows a unique minimum point. When dealing with large-scale data, GPR requires a lot of matrix computations, so reduction of computation cost and computer memory are important research topics. By utilizing the sparsity of the covariance matrix, the computational cost may be reduced. Matrix sparsity is a feature in which the components are mostly composed of zeros. We confirmed that the sparse covariance function M-R can reduce the computation cost depending on the sparsity.

Concrete float is known to be caused by corrosion and expansion of reinforcing bars. However, many cases of re-deterioration after repair have been confirmed. It is speculated it is mainly due to impromptu repairs that ignore the float generation mechanism. The purpose of this study is to estimate the internal defect shape of concrete and to clarify the mechanism of float generation by using the infrared method and three-dimensional unsteady heat transfer analysis, which are one of the non-destructive inspection techniques. In this paper, a method for estimating the defined position of the sound part, the shape, range and depth of the float was clarified for concrete with defects.

Road roughness is a widely used index for evaluating pavement serviceability and determining maintenance needs. However, road roughness estimation methods utilizing GPS information encounter difficulties in GPS-blocked environments; existing non-GPS vehicle mapping techniques utilizing only inertial measurement unit (IMU), have a limited accuracy when IMU is not of high precision. To address this problem, this study introduces a vehicle mapping approach that relies solely on an IMU at GPS-blocked road sections. The proposed method consists of five steps utilizing GPS data at GPS-accessible sections and IMU data for all sections. The data are transformed into Universal Transverse Mercator (UTM) and body coordinate systems. The initial positions, velocities and accelerations at both ends of the GPS-blocked section are estimated by optimization based on kinematic information outside the GPS-blocked section. Then the drive speed is estimated by the inverse analysis of vehicle body dynamic responses. Finally, the vehicle states within the GPS-blocked section are estimated using the IMU data as well as the estimated drive speed through a bidirectional Kalman filter. The effectiveness of the method is evaluated at linear and curved road sections. The results show the high accuracy of the method.

Reducing computational cost in the reliability analysis or Bayesian updating process, especially for complex models, remains one of the key challenges. Adaptive surrogate models have attracted attention for the efficiency since active learning reliability method combining Kriging and MCS (AK-MCS) was proposed. The adaptive surrogate model approach can reduce the computation cost by appropriately replacing, possibly adaptively, the evaluation of the original computationally costly models with approximate ones that are much less costly. One of key points in this approach is how to construct the surrogated model based on the limited number of function calls such as estimation by finite element method, which needs large computation cost. AK-MCS uses Kriging for the construction of the surrogated model. This paper compares Gaussian Process Regression (GPR) with single random field and two random fields for the surrogated model. Single random field GPR is better in a simple reliability analysis benchmark example, though two random fields GPR is better in a Bayesian updating benchmark example. It seems the optimal number of the random field for the surrogated model depends on the complexity of the shape of limit state function or posterior probability density function. This paper also discusses the initial sampling placement for the surrogated model construction, and reliability analysis with ordinary random number, Latin Hypercube sampling, or low discrepancy sequence for the estimation of limit state probability.

In recent years, the amount of rainfall has tended to rise due to climate change, and in the past few years alone, many floods have occurred, such as the 2019 Boso Peninsula Typhoon, the 2019 East Japan Typhoon, and the heavy rain in July 2020. Based on such an increase in flood risk, the importance of measures against flood damage is increasing. However, conventional flood countermeasures are implemented for assumed scenarios based on assumed inundation areas. Based on these, the Ministry of Land, Infrastructure, Transport and Tourism is developing probabilistic flood hazard assessment methods and flood risk assessment methods for the purpose of flood control measures such as river improvement according to the scale of flood damage. Therefore, in this paper, we evaluate the flood hazard of the Kuma River flooded by the heavy rain in July 2020.

The degradation of repainting systems was examined according to the pre-coating substrate's preparation grades by performing various accelerated weathering tests. The coating degradation was measured by the total area of rust, color and gloss variations, and blistering of the coating surface under accelerated weathering tests. The scanning electron microscope was used to investigate the mechanisms of corrosion underneath the coating film. During this study, it was discovered that substrate's preparation influences the degradation mechanism of repainting systems on corroded steel specimen. Results of current research indicate that pre-coating substrate's level has greatly affected to the parameters of repainting resistance.

Bridges are critical infrastructure that enable safe and efficient transportation for people, goods, and services. However, the frequent and cyclical loads that bridges endure on a daily basis can lead to fatigue damage. Measuring the displacement responses due to cyclic loading is a key approach to determine the fatigue environment of bridge structures. In this study, a 4K video camera was utilized as a means of measuring displacement response. The determined displacement response was then compared to those measured using contact displacement gauge. Furthermore, the determined displacement response was compared to strain response measured using strain gauge to confirm the suitability of the displacement responses for fatigue environment evaluation. Finally, rain-flow analysis was conducted using the determined displacement response to assess the fatigue environment.

One of the typical examples of bridge deterioration is bearing restraint due to corrosion or other forms of damage. When bearings are subjected to unexpected restraint, fatigue cracks occur around the sole plate. Therefore, it is very important to quantitatively evaluate the condition of bridge bearings. The authors estimated the rotational spring constants of the bearings based on the influence lines in a previous study. An index Ir for the rotational resistance of bearings calculated from the deflection angle at supports was also proposed. In the above study by the authors, it was confirmed that the shape of the influence line was distorted by Low-pass filtering for removing the noise contained in the influence line. In this study, the effect of the distortion of the influence line due to the filtering on the estimation results of the rotational spring constants is examined. In the numerical simulation, it is confirmed that the filtering reduces the deflection angle of the influence line at the support, resulting in a deviation of Ir. It is also confirmed that filtering reduces variability. In applying this to the experimental data, it is confirmed that the effect of filtering is similar to that of the numerical simulations.

We developed a string shoot impactor with a small stainless ball attached to the string of a string shooter for generating impacts. This impactor can remotely inspect walls. We applied the impactor to 70 mm × 70 mm and 70 mm × 145 mm tiles, and successfully detected tile delamination, as well as raised tiles due to mortar failure. The test conditions were as follows: the distance between the specimen and the impactor was about 50 cm, the diameter of the ball used for the impact was 4 mm, the ejection velocity of the ball was 10 m/s, and the movement speed of the impact point on the inspection surface was 50 mm/s.

Infrastructure safety inspections rely on visual inspections and hammering inspections by inspectors. However, an important difficulty is that inspection results vary because of differences in the technical expertise of inspectors. An inspection method and preventive work using a coating type resin sensor and an infrared camera are proposed to overcome that difficulty. A nondestructive evaluation technique using thermography is used increasingly as a tool to maintain concrete structures. Most inspections only evaluate the defect locations and shapes on planes. No method has been developed for evaluating defect depths. After applying infrared reactive resin, thermographic images of a target area are taken sequentially. Then, temperature curves obtained at each pixel during cooling defect states in different parts of the temperature distribution are analyzed using Fourier transform. The temperature change is related to the defect size. Approximately 10% of aluminum powder mixed into the applied gel resin, because of its specific gravity, has the property of concentrating in areas damaged by compression failure or floating.

Currently, the number of aging bridges is rapidly increasing in Japan, and there is a need to establish a more efficient and quantitative bridge inspection method. The authors focused on the impact vibration test using a portable FWD (falling weight deflectometer). The target bridge is a small bridge used in Kaminoyama City, Yamagata Prefecture, and deck slab replacement work was performed in 2019. We measured response acceleration before and after deck replacement, and further applied the MTS (Mahalanobis Taguchi System) method to determine local damage and deterioration of the deck slabs. In addition, we created a 3D FEM model and performed a dynamic analysis by degrading a portion of the deck. Also applied the MTS method to this data and compared with the experimental data to estimate localized areas of deterioration.

The Kumamoto earthquake in 2016 caused damage to many water tanks. Sloshing caused by slightly longer-period seismic motion and bulging caused by shorter-period seismic motion are possible causes of damage to water tanks due to earthquakes. Since the periodic characteristics of seismic motions are greatly affected by the amplification characteristics of the surface soil, the damage to the water tanks is expected to be greatly affected by the ground characteristics. Therefore, this study evaluated the relationship between water tank damage and ground characteristics, and assessed the risk of damage to water tanks for earthquakes that are expected to occur in the future. The results showed that there is some relationship between water tank damage and ground characteristics, and that analysis of ground characteristics may be used to assess the risk of water tank damage.

There is a concern that the liquefaction hazard assessment in the Specification for Highway Bridges is subject to fluctuations due to uncertainties that affect the presence or absence of liquefaction. In this study, we evaluated the uncertainty of various conditions included in liquefaction risk assessment in a 250m square area and its effect on the accuracy of the liquefaction risk assessment. As a result, it was shown that the liquefaction hazard level may differ depending on the location even within the area. The calculation of the probability of exceeding the level based on the reliability theory confirmed that the reliability of the risk assessment is ensured because the probability converges to some extent even when the information on the liquefaction resistance of the ground is uncertain. On the other hand, if the information on the stress resultant and resistance is not appropriate, the accuracy of the judgment will be reduced.

Losses due to hazards are expected. A study estimating the damages and losses was conducted, however, the damages per mesh were estimated as independent to one another. Spatially distributed lifeline systems, such as water supply pipelines, are interconnected, and seismic spatial variability affects the damages across the region; thus, spatial correlation of damage spots is an important factor to account for uncertainty in the target area for portfolio loss estimation. Researchers opt for simulations to predict and estimate possible losses; however, these simulations assume each damage behaves independently and is uncorrelated. The researchers assumed the damages behave in a Poisson Distribution, to avoid over-dispersion and eliminate negative losses in estimations. There are limited ways to Simulate Correlated Poisson Distributed values, thus NORTA (NORmal To Anything) is used. Including NORTA accounts for the correlation for Poisson Distributions. From the simulated losses at different scenarios and correlations, a probabilistic model based on the generalized linear model and central limit theory was produced to estimate the losses without simulations. d. Once the probabilistic model is obtained, the seismic risk index of a spatially distributed water supply pipeline system, such as the PML or NEL can be easily estimated. The proposed model can also be used in other lifeline systems; though additional investigation is needed for confirmation. The proposed method is then tested using an artificial field and a location-based scenario. This would aid in pre-disaster planning and would require only a few steps and time.

Renewable energy, which has been increasingly introduced in recent years, not only emits less carbon dioxide, but can also be expected to have the effect of reducing the risk of power supply in the event of a natural disaster as a distributed power source. In this study, after estimating the damage probability of power facilities in the event of a natural disaster, a simulation of the power supply risk in the event of a disaster was performed for the power system in the Tohoku region. As a result of the simulation, the risk for Miyako City in Iwate Prefecture was high, so we assumed that Miyako City would introduce solar power generation and wind power generation as renewable energy, and calculated the risk reduction effect according to the amount of introduction. In addition to the risk reduction effect, we also considered the cost of introducing power sources, conducted an economic evaluation, and calculated the optimal amount of renewable energy to be introduced. As a result of the calculation, the economic evaluation was the highest when 70 MW of solar power generation and 20 MW of wind power generation were introduced.

The safety index and a partial safety factor play an important role in structural reliability design. According to the AFOSM method, when the performance function given as a nonlinear function, the safety index obtained from the mean and standard deviation of the linearized performance function around the failure point. On the other hand, the calculation of the partial safety factor by the first-order Gaussian approximation method interpreted as obtaining the failure point that satisfies the target safety index. In this study, the extended Kalman filter used to estimate the failure point of performance function, and then evaluate the partial safety factor that satisfies the target safety index.

A numerical approach is developed for analysis on random stress field of FRP strengthened CFRP plate under uniaxial tensile load, where the multiple precision arithmetic is applied to reduce instability of numerical scheme. First, a system of differential equations is formulated for describing axial force, shear force and bending moment of CFRP plate, which is directly applied to formulate normal and shear stress of adhesive material between CFRP plate and FRP material. Next, the system of equations is extended to a system of spatially random differential equations by taking into account spatially random variation of thickness of the adhesive material. Finally, numerical simulations are executed for generating sample functions of normal stress as well as shear stress of the adhesive material, where multiple precision arithmetic is applied to numerical simulations. It is clarified that the numerical scheme for calculating stress field of the adhesive material shows significant instability under widely used double precision arithmetic, which indicates that application of the multiple precision arithmetic is undoubtedly needed.

Hydrogen and natural gas blending can be considered an important energy technology in terms of utilization of the existing infrastructure, which has a significant cost impact on the deployment of hydrogen infrastructures, and the smooth transition of energy systems. In this study, fatigue crack growth tests were carried out in air, hydrogen (H₂), 20% H₂ mixed methane (CH₄) and 20% H₂ mixed natural gases. Three kinds of natural gases with different oxygen (O₂) impurity concentrations were used in order to characterize the effect of hydrogen on the fatigue crack growth behavior in natural gas in conjunction with the effect of the O₂ impurity. The pressure of the gases except for air was 1 MPa. The test material was JIS SCM435 low-alloy steel. In the H₂ and the 20% H₂ mixed CH₄, the fatigue crack growth rates were accelerated. The acceleration was less in the 20% H₂ mixed CH₄ compared to that in the H₂. It is presumed that the lower hydrogen effect was due to reduced partial H₂ pressure in the mixture. This was confirmed by the crack growth test in 0.2 MPa H₂ resulting in the same crack growth rate as in the mixture. Regarding the fatigue crack growth tests in the 20% H₂ mixed natural gases, acceleration of the fatigue crack growth rate and suppression of the acceleration due to oxygen were observed. The oxygen effect increased with the increase in the oxygen concentration and was well-evaluated by the predictive model of hydrogen-assisted crack growth in the presence of oxygen proposed by Somerday et al.

Horizontal seismic isolation systems have been studied for Sodium-Cooled Fast Reactors to improve their seismic resistance. However, challenges arise in reducing seismic forces not only in the horizontal direction but also in the vertical direction. The authors have developed a new three-dimensional seismic isolation system to address this issue. A 1/2-scale test specimen was fabricated, and the force-displacement relationships were examined using static loading tests with a maximum axial force of 8000 kN to evaluate the feasibility of this design. Moreover, a horizontal oil damper was fabricated as a horizontal damping element, and its damping force was assessed through excitation tests with a maximum velocity of 2.7 m/s. This paper reports the findings of these tests.

In 2019, the JSME Code Case for seismic design of nuclear power plant piping systems was published. The Code Case provides the strain-based fatigue criteria and detailed inelastic response analysis procedure as an alternative design rule to the current seismic design, which is based on the stress evaluation by elastic response analysis. In 2022, it was approved to revise the Code Case with improving the cycle counting method for fatigue evaluation to the Rain flow method. In addition, the discussion to incorporate the elastic-plastic behavior of support structures is now in progress for the next revision of the Code Case. This paper discusses the contents and background of the 2022 revision, the progress of the next revision, and future tasks.

In order to develop analytical model to simulate failure behavior and nonlinear load–displacement characteristic of piping support subjected to excessive seismic loading with high accuracy, case studies were performed focusing on two types of piping support showing different failure behaviors such as buckling and low cycle fatigue. Analytical failure behaviors and nonlinear load–displacement characteristics reasonably agree with the experimental data. The possible reasons for some differences between experimental data and analytical results were discussed. Finally, points for improvement of analytical models were extracted.

In the structural design of buildings, the occurrence of earthquakes must be treated as uncertain phenomena. It is undesirable to design structures so that safety is maintained only against a few specific types of seismic motion. Thus, uncertainty must be considered in the design. The seismic robustness of a structure can be defined by the little variation in the seismic response when subjected to uncertain disturbances and/or changes in structural parameters. Order statistics can be used as an index of seismic robustness. In this study, a robust design method using order statistics is applied to evaluate the seismic robustness of the displacement restraint PC steel bar brace in response to uncertain variation of the initial gap length.

In Japan, a lot of structural damage occurred due to great earthquakes, so a necessity to establish resilience-oriented restoration design method has been discussed. Some repair methods for damaged steel structures proposed in the Japanese restoration technical guideline, but few studies have investigated the seismic performance of the whole repaired frame. In the restoration design for the damaged structures, it is desirable to ensure the formation of collapse mechanisms that have high energy absorption capacity. Therefore, the previous study has proposed a new restoration concept and a repair method by reducing the yield strength of the steel member to control the portion where plastic hinges form in the steel frame. This research aims to evaluate the relationship between the dominant plastic failure mode and the energy absorption capacity of repaired steel frames, and aims to establish the restoration design method considering these factors. This paper investigates the energy absorption capacity of each plastic failure mode of the steel frame, which repaired using the proposed method in a previous study, in relation to reliability indicators of each plastic failure mode. Based on the results of plastic hinge analysis and the energy absorption capacity of steel members, the energy absorption capacity of the repaired frame was calculated for each failure mode. And the reliability indexes of each failure mode were evaluated by reliability analysis FOSM. Furthermore, by comparing these analysis results, the effectiveness of the evaluation of energy absorption capacity of repaired frame using the proposed method have been confirmed.

To reduce delays in roof repair work after natural disasters caused by typhoons or earthquakes, automatic classification of roofing materials by remote sensing is one of the key technologies for estimating roof repair demand. This paper investigates a technology for classifying roofing materials using ortho image obtained based on UAV photos. An initial investigation shows that the detection accuracy varies with the resolution of the images to be trained. Therefore, two trained models with different resolutions are used under the same conditions to validate the accuracy. As a result, it is found that detection accuracy is lower when automatic detection is performed using images with a lower resolution than that used in training.

In many foreign countries, the intensities of seismic loads are determined by the target seismic performance level. On the other hand, the seismic performance level of buildings is not explicitly taken into consideration in the Japanese Building Standards Act and most general buildings are designed according to seismic loads which is determined by the Standards Act without seismic performance level. This paper aim to implement seismic performance-based design in Japan and examine the seismic performance level of buildings designed on the basis of the Standards Act. Therefore, calibration against the Standards Act is conducted. In Part 2, probabilistic seismic performance evaluation is conducted for calibration of the Standards Act.

In overseas seismic design, the seismic loads are determined in response to the target seismic performance. However, the seismic loads based on the Japanese Building Standards Act are determined without considering the required seismic performance of each building. Since the buildings must be designed based on the Building Standards Act, those target seismic performance is not considered in the seismic load. This paper aims to evaluate the seismic performance level of two buildings designed based on the Building Standards Act based on Reliability Evaluation Method and Capacity Spectrum Method. As a result of this paper, return periods of Uniform Hazard Spectra which are corresponded to the serviceability and safety limit state are evaluated.

In November 2022, the Headquarters for Earthquake Research Promotion (HERP) released “Probabilistic Seismic Hazard Analysis of Response Spectra.” The Probabilistic Seismic Hazard Analysis (PSHA) is important for seismic performance-based design of buildings. However, sites for which the seismic hazard released are limited to only the Tokyo Metropolitan Government Office, the Osaka City Hall, and the Nagoya City Hall in the form of figures rather than functions. For this reason, results of the PSHA cannot be directly used for seismic performance-based design. Therefore, the PSHA of Response Spectra by HERP are quantified with approximating lognormal distribution in this paper.

In the seismic PRA used for risk assessment of nuclear power plants, simplifying the evaluation of seismic fragility curves of components that exist in large numbers in a power plant is an important issue to reduce the evaluation cost. In this study, we proposed a method for estimating the median value of fragility curves of structures, systems, and components (SSCs) in nuclear power plant buildings by applying a non-iterative equivalent linearization method and examined its effectiveness by comparing it with nonlinear time history analysis. The results showed that stable solutions were obtained for SSCs installed on the ground surface. For equipment installed in a building, the median value of the seismic fragility curve was found to be accurately evaluated if the period of the equipment is sufficiently smaller than the period of the building.

In this research, we propose a simple method to estimate the cumulative plastic deformation, 𝜂, of a Multi-spring (MS) model equivalent to the 1st mode of a response control structure with hysteretic dampers.　The logarithm of the ratio of 𝜂 of each elasto-plastic spring in the MS model is first modeled as a linear function of the yield displacement of the damper to the minimum yield displacement among the dampers.　Then the slope of the linear relationship is modeled as a linear function of the logarithm of the ratio of the maximum yield displacement among the springs to the minimum one.　Using these models, the 𝜂 of each spring can be simply estimated.　The accuracy and applicability of the proposed method are investigated using numerical examples.

In this paper, the performance of evaluation methods and proposed new evaluation methods for the use of limit strength calculations in traditional wooden houses with large floor openings or extremely low story heights, and have confirmed the trends. The zoning method used for buildings with large floor openings was found to result in smaller restoring forces at the zone boundaries and larger deformation angles. For buildings with extremely low story heights, the deformation angles of the second story were not different from those of the conventional method but the deformation angle of the first story was different when the atrium was treated as a one-story house and the tsushi as a two-story building.

This study focuses on space debris impact risk of pressurized vessels installed in spacecrafts.　Wall perforation conditions are necessary to assess the debris impact risk of the pressurized vessel.　Ballistic limit equations are generally used to know the debris impact conditions causing perforation of the structure wall.　However, these equations have almost been developed for flat plates.　The purpose of this study is to investigate effects of curvature of the structure wall to debris impact damage.　Hypervelocity impact experiments were conducted to both of flat and curved plates.　Titanium alloy plates of 1.2 mm in thickness and aluminum alloy plates of 3.0 mm in thickness were tested.　The radiuses of curvature were approximately 210 mm of titanium and approximately 50 mm of aluminum.　The experimental results were compared with NASA’s ballistic limit equation for metallic flat plates.　As a result, the equation was able to predict not only flat plate results but also curved plate results.　The peeling fracture by spalling was only observed on the backside of the titanium curved plate. In aluminum plate results, the differences of damage were not seen by the curvature.　It seems that the effect of the curvature is difficult to appear for ductile material.　The numerical simulations were also performed with the same condition as the impact experiments.　The simulation results showed in good agreements with the experimental results.　To investigate distributions of fragments generated by the perforated experiments, the numerical simulations with the SPH method were performed.　The spray angle of the fragment cloud became smaller by the curvature.　In the experiments, the fragment distributions were obtained from crater examination of witness plates installed behind the targets.　The spray angle decreased by approximately 10 degrees due to the curvature of the target.

This study concerned with a risk evaluation method and a risk reduction method for maintenance activity using the identification results of damage identification using inverse problem analysis. Regression analysis is the most commonly used method for damage identification by inverse problem analysis. Linear regression analysis is easy to compute, but the output is a fixed value, and the predicted mean value is given as the solution. However, when evaluating the reliability of a structure, it is necessary to consider the distribution of diagnostic error because the failure of the structure is caused by low-probability events. Therefore, the author's research group is proposing a method to estimate the distribution of occurrence rates of damage parameters and calculate probability of failure by deriving regression coefficients as a distribution using Bayesian estimation as the damage identification results. In addition, in order to construct a method for quantitative maintenance decision making, a risk quantification method as the result of damage identification is proposed. Overestimating damage that is sufficiently smaller than the expected failure size will not cause failure, and underestimating damage that is sufficiently large will not cause failure. In other words, these areas do not require very high accuracy when maintenance is performed using damage identification results. In this study, a method to reduce risk and probability of failure by controlling the estimation accuracy in arbitrary regions using a generalized linear mixed model (GLMM), which is one of the hierarchical Bayesian models, is investigated.

To contribute to shortening the design and development period of the Type 4 hydrogen pressure vessel, three-dimensional finite element analysis was performed to evaluate the effect on the mechanical properties based on the design parameters of the Type 4 (the length of the cylinder, the inner diameter of the cylinder, the hoop layer and helical layer thickness). Moreover, based on these FEA results and a modified Goodman diagram, a design map in which the design parameters of the hoop layer and the helical layer thickness considering to the weight and fatigue life as a designable area was proposed. As results, it was found that the helical layer and the hoop layer thickness affected the fiber direction stress, and that the stress concentration changed from the hoop layer to the helical layer in the dome part as the hoop layer thickness increases. In a design map, there was a gap in thickness between the theoretical layer and the optimal layer which was calculated from the design map, and it was revealed that importance of considering metal boss in determine the optimal ratio of hoop and helical layer thickness at the design process.

Fiber-reinforced thermoplastic composites that use thermoplastic resin as the matrix are highly recyclable and suitable for mass production. By using spread yarns treated in a wide and thin state for the woven structure, the occurrence of voids during impregnation can be minimized, leading to improved mechanical properties and shortened impregnation time. However, evaluating damage in woven composite materials using spread yarns is challenging due to their extremely thin thickness and complex woven structure, which result in various damage modes. In this study, numerical analyses were conducted to investigate the damage propagation behavior of thermoplastic woven composites, by varying the fiber volume fraction in the numerical analyses of models with ply thickness changed from the conventional yarn thickness to the thickness of the spread yarns. As a result, changes in the damage development behavior were observed when the fiber volume fraction changed.

Injection conditions in injection molding with FRP and thermoplastic resin have a great influence on molded products, however, it is inefficient to evaluate the effect of injection conditions in terms of time and money. Therefore, a numerical simulation that can take account of the interaction between resin and fibers is required. In this study, a multiscale approach is applied to injection simulation based on MPS method. In the global analysis, the effect of viscosity on resin flow was evaluated. At low viscosities, the shape of the flow front and temperature distribution were affected, but the resin velocity converged when the viscosity exceeded a certain level. In the local analysis, the effect of fiber aspect ratio on fiber orientation varies with the velocity distribution occurring in space. It was also confirmed that the effect of viscosity varied depending on the location of fiber flow. And the fiber was observed converging to certain position. This is considered to express the aggregation of fibers seen in the experiment.

In order to o prevent deterioration of coating paint on a steel bridge member, it is very important to well adjust the surface of the member before repainting A major method of surface adjustment is the blast cleaning. But there is a problem in using the blast cleaning method because it spread out a great amount of dust and it have to be properly disposed. Then, a laser cleaning method is now getting attention, because it can instantaneously sublimate the paint and absorb it into the container of the machine. However, there is possibility that the heat of laser might damage the steel. Therefore this paper researches the effect of laser to the material, and confirm the safety and the efficiency of the laser cleaning method.

In this study, fatigue tests using a one-side notched specimen of SNCM439 were conducted to investigate the validity of probabilistic fatigue strength assessment of mechanical structural materials via structural reliability analysis. First, the probability density functions were defined as statistical variations of fatigue strength and fatigue loading to perform structural reliability analysis for fatigue failure of the specimen using Monte Carlo simulation. The result of the structural reliability analysis was then compared with the probability of fatigue failure obtained from fatigue tests with fatigue loading, which was by the probability density function of the fatigue loading in the structural reliability analysis. The result showed that the probability of fatigue failure calculated via structural reliability analysis agree with the likelihood of fatigue failure obtained from fatigue tests. This study provides substantial evidence for the validity of probabilistic fatigue strength assessment via structural reliability analysis.

A new probabilistic model is developed for descibing random fatigue crack growth reflecting spatial inhomogeniety of materials, where (i) mean behavior of fatigue crack growth is assumed to obey the well known Paris’s law, (ii) the randomness associated with materials property is modeled as a spatially homogeneous random field, (iii) a random differential equation driven by a random field is transformed into a random differential equation driven by a random process and (iv) the transformed system of random differential equations is of diffusive type so that it is compatible with computer simulations. The proposed model consists of a bivariate diffusion process given as a solution of the system of random differential equations driven by a Wiener process, which leads to a simple algorithm for generating sample functions of fatigue crack growth. Simulation analyses indicate that (i) the proposed model can well reproduce probabilistic properties associated with residual life of fatigue crack gorwth and (ii) a transformed random process descrbing fatigue crack growth resistance can well reproduce a gradual reduction of a correlation time which is caused by a gradual acceleration of fatigue crack growth rate.

Industrial robots in the automotive and precision equipment industries have been dramatically increasing in recent years, and the industrial robot arms have structures of composite cables made by twisted strands. There are many design parameters for composite cables such as total number and diameter of a strand, the number and diameter of filaments in a strand, a twisting direction and a pitch length of a strand, etc. It is time-consuming to estimate the fatigue life of composite cables based on experiments considering effects of design parameters on mechanical behaviors. Therefore, a numerical modeling method for composite cables with various twist patterns and pitches was proposed by using Python code in this study. Furthermore, a hybrid model of a strand was developed with beam and solid elements of the finite element method. The fatigue life of composite cables was estimated based on numerical analysis with hybrid models and fatigue test of a single filament. The numerical results showed that the mechanical characterization of the rung twist pattern was inferior to that of the normal twist pattern, and the fatigue life was inferior as the twist pitch became shorter. The proposed numerical modeling and evaluation method of the fatigue life are useful for the design and development of composite cables in robotic arms.

To reduce risk in chemical plants, preventive measures must be incorporated into the design. In the case of a leak of a highly toxic substance, detection and isolation, prevention of spread, and suppression of effects are possible methods. In the previous studies, the diffusion behavior of substances with small specific gravity and water solubility has been studied, while that of substances with large specific gravity and non-water solubility has not been sufficiently studied. In this study, numerical fluid dynamics analysis was conducted to evaluate the diffusion behavior of bromine in the case of a leak and to study disaster mitigation measures, and the effects of dike dimensions and installation method on diffusion behavior were evaluated. It was found that the size of the embankment affects the distance that bromine can reach in a certain time, and that the distance of diffusion can be controlled by installing a barrier on the downwind side or by installing the embankment underground.

An optimal control of an urban health index quantifying an integrity of urban performance is theoretically investigated by the use of the stochastic control theory, where three factors – recovery of the index, prevention of disasters and alternative risk transfer – are controlled. First, a probabilistic model is constructed for describing temporal variation of the urban health index with random occurrence of disasters. Next, based upon a budget structure depending on the current state of the index, optimal strategy is mathematically formulated by introducing costs associated with a recovery process, loss due to disasters and transferring risk. The HJB equation to give an optimum solution is then derived. Finally, the optimal strategy is numerically derived from the HJB equation, where a probability measure transformation technique is applied to accelerate a Monte Carlo method for estimating the cost required for the risk transfer. The results indicate that (i) optimal valance among three kinds of cost – recovery delay cost, disaster occurrence cost and a cost caused by degradation of the health index – can be realized and (ii) the importance sampling technique can improve accuracy in deriving the optimal solution.

The prevention of occupational accidents in the construction industry in Japan is based on a safety and health management system. Safety patrol inspections conducted at construction sites are one of the most important tasks and are carried out using a list of inspection items required for each site. This time, this inspection table is performed using the FRAM (Functional Resonance Analysis Method). Various work items in the field are represented as system functions, and are not a list of items, but rather interrelated functions. The existence or non-existence of functional variability is observed during the inspection, and corrective instructions are given to prevent accidents from occurring, thereby preventing disasters.

This study examines the status and issues in the Community Disaster Management Planning system from the perspectives of documents, systems, and approaches. The results revealed that the process of creating documents that differentiate the Community Disaster Management Planning system from conventional voluntary disaster prevention activities produces various effects. Specifically, it facilitated the handover of members in areas where activities had been suspended due to the spread of the COVID-19 and had a positive impact on reconstruction in areas that had experienced the disaster.

In this study, through a workshop adopting Future Design and Business Model Canvas, we investigated changes in the perceptions of workshop participants from the standpoints of the current generation and the Imaginary Future Generations (IFGs). The results suggested that the introduction of the IFGs led to an emphasis on sustainability and long-term perspectives, and a relative decline in short-term perspectives such as value propositions and profitability. In addition, the analysis by Business Model Canvas indicated that while most of the discussions by the current generation were considered in terms of improving or extending existing businesses, discussions as IFGs tended to yield results that could not be obtained in the conventional way. These results suggested that it was possible for participants to develop sustainable business models and business successions that had a long-term perspective and could respond flexibly to changes in the environment and society.

In this study, the author extends the method of the previous paper to shell elements and propose a practical method for calculating the extreme value distribution of von-Mises stresses that can be applied to solid elements in addition to shell elements. The proposed method can be applied to structures subjected to stationary Gaussian load and can be easily calculated from the response functions of the stress components and the external force spectra without relying on numerical integration. To verify the validity of the proposed method for solid elements, a structural analysis in waves was conducted using a solid FEM model of a box-type ship, and the extreme value distribution of von-Mises stress obtained by the time series data as well as the direct integration of the original quadruple integral was compared with the proposed formula. It is confirmed that the proposed formula has very good accuracy for both 1/10 and 1/1000 maximum expected values, independent of the stochastic parameters. The proposed formula is derived on the assumption that the standard deviation ratio is small, and the solid element tends to have a larger standard deviation ratio than the shell element presented in the previous paper, but it is confirmed that it can still be applied without significant error.

In this paper, we describe simulation of the dynamic response of a 2-MW spar type floating offshore wind turbine (FOWT) during power production in actual sea area. Accurate estimation of the dynamic response of FOWTs are essential for the design and development of FOWTs to ensure their safety and reliability. Therefore, this paper compares and validates the simulated and measured dynamic response of FOWTs during power production using Adams with SparDyn, which has already shown good agreement with measured values under a typhoon environment. Five simulation cases were selected from low to high wind speed range during power production. Numerical simulations were performed using time series data of wind speed, wind direction, wave height, wave direction, current speed and current direction obtained during power production. Comparisons have shown reasonably good agreement between the simulated and the measured values except yaw motion.

In recent years, heavy rainfall has been increasing in all regions of Japan due to rising temperatures caused by climate change. In addition, many reservoirs throughout Japan are aging and have weak management systems. Against this background, the risk of reservoir failure due to heavy rainfall is expected to increase in all regions of Japan in the future. These factors make it important to assess the risk of reservoir breaches assuming future temperature increases. In this study, for the purpose of contributing Rational decision making for reservoir renovation, using the Database for Policy Decision making for Future climate change (d4PDF), predict the heavy rainfall with rising temperatures and use the data of rainfall to calculate the probability.

The asphalt mixture plant receives construction waste, crushes it, and reuses it as a raw material for recycled asphalt mixture. Currently, workers identify the type and measure the weight of construction waste on each dump truck, resulting in queues and traffic jams during busy periods. In this research, a basic study was conducted for estimating the type and weight of construction waste by image recognition of deep learning using image data taken from above a dump truck. Although the number of data used was not large, the model was built with some estimation accuracy.

This study concerns a method for diagnosing bridge anomalies using machine learning. In this study, bridge abnormality diagnosis method using convolutional neural network (CNN) from acceleration responses is proposed. Spectrogram images of acceleration responses are applied to image classification by CNN. By classifying spectrograms for each bridge condition, bridge anomalies are detected and the condition is identified. In order to improve the accuracy of damage classification, a two-step classification method is used: first, a classification is performed in the major damage category, and then the sub-categories are identified within the major category. The two-step classification improved the accuracy of damage identification in the sub-category of girder damage, indicating that the two-step classification is effective in improving the identification accuracy of this method.