Methods for improving the accuracy of second order derivative calculations using the complex first-order derivative approximation (CSDA method) is proposed. In this paper, the following two approaches are investigated: (1) perturbation direction on the complex number plane, (2) use of double and quadruple precision floating point arithmetics. The above approaches were applied to several numerical examples to discuss the accuracy and computational costs. As the results, the perturbation of CSDA on θ = 45° had the best accuracy and stability throughout all the examples. Moreover, it was also found that when combined with perturbation on θ = 45° and quadruple precision floating point arithmetics, the second-order derivatives could be computed with more than accuracy of the double precision arithmetic in the examples.

An efficient and robust method for deriving the stress-strain relationship of hyperelastic material model (HM-model) was proposed via complex-step derivative approximation. This method has a capability to calculate the stress-strain relationship with the same accuracy as the analytical solution by coding only the strain energy density function, being applied for the implementation of an identification program of material constants for HM-model using a Microsoft/Excel. The performance evaluation of HM-models (Yeoh and Ogden models) using this method revealed that all models could reproduce the results of the three types of material tests (uniaxial tensile (UT), pure shear (PS) and equibiaxial tensile (BT) tests) of carbon-black-filled SBR. Moreover, only the hyperelastic model composed of the first invariant of the right Cauchy-Green tensor could predict the PS and BT test results from the UT data. As a future prospect, we would like to proceed with studies on other rubber materials and HM models.

It is important to select appropriate material model for non-linear CAE. However, the models provided in commercial software are limited. In addition, it is not efficient to implement the specific material models to many commercial FEM codes individually. In the activity of sub committees in the Nonlinear CAE Association (JANCAE), we have developed hyperelastic, damage, and viscoelastic constitutive laws using user subroutines to be incorporated into commercial FEM codes. The developed subroutines, called Unified Material Model Driver for rubber (UMMDr), have recently been released to the public. This paper presents an overview of the subroutines and examples of their use.

Since the velocity of the P-wave may be much larger than that of the S-wave in nearly incompressible materials, explicit time integrators are hardly applied to such problems. This paper presents a novel time integration scheme for transient finite element analysis of nearly incompressible elasticity. The proposed time integrator is derived by extending the Rattle algorithm for constrained Hamiltonian systems. The proposed approach works as an implicit scheme for the P-wave propagation while it works as an explicit one for the S-wave. Thus its numerical stability depends on only the Swave velocity.

A novel finite element formulation using 4-node tetrahedral elements is presented for large deformation analysis of nearly incompressible solids. The present method is a straightforward extension of the strain smoothing element (SSE) or the edge center-based SSE (EC-SSE) using selective reduced integration (SRI) to avoid volumetric locking. The deviatoric strain distribution of the present method is piecewise linear, whereas the volumetric one is piecewise constant. The suppression effect of spurious low-energy modes and pressure checkerboarding with the present method will be discussed at the conference.

A new data-driven multi-scale material modeling method called Deep Material Network (DMN), based on the Representative Volume Element (RVE) method and machine learning techniques, has been developed to predict physical properties with high accuracy and speed. DMN represents the response of RVE by forming a network using a mechanical building block that avoids the loss of intrinsic physics that occurs in common neural networks. The network can be constructed based on the analysis of linear elastic RVEs and can predict the nonlinear characteristics of various RVEs. In this paper, the basic concept of DMN is explained and its application to short-fiber reinforced composites is verified. The results confirm that DMN can reproduce the nonlinear response of the RVE with the same accuracy and orders of magnitude faster than the results of direct numerical simulations.

The use of short fiber reinforced plastic (SFRP), which can be injection molded, is expanding. However, it is difficult to obtain the material parameters which is necessary for structural analysis at the design stage. In this paper, we present a case study of a fracture law considering stress triaxiality, which has been the focus of attention in recent years. The parameters of the accumulated plastic strain fracture law, a fracture law considering stress triaxiality, are identified based on the results of conventional fracture laws.

Ceramic matrix composites (CMCs) are expected to be applied to high-temperature parts of jet engines because they are lighter and have higher heat resistance than Ni-based alloys which have been conventionally applied to turbines. One of the challenges in applying CMCs to engine parts is the difficulty of design due to the difference in material strength due to the microstructure composed of fiber bundles and matrix. The two types of microstructure models were prepared. The one is "unit cell model" which is a simplified shape model with a rectangular three-dimensional orthogonal weave structure. The other one is "CT model" which is a complex detailed shape model created by image recognition technology based on image data acquired by X-ray Computed Tomography (CT). Structural analyses of these models were conducted using a damage model based on continuum damage mechanics including a nonlocal damage theory proposed by the authors. It was confirmed that the fracture strength varies depending on the microstructures which are narrow area of yarns and void in matrix. On the other hand, it was unclear how the parameters related to the damage model affected the material behavior. Thus, the effect of damage model on material behavior was investigated by changing the parameters in this study. As a result, it was found that there was an appropriate parameter for nonlocal damage theory to avoid the mesh dependence of nonlinear behavior and fracture strength.

Computational engineering has made great progress in terms of both numerical meshods and numerical computing environment. COMSOL Multiphysics®, as a mathematical modeling tool, can automate general-purpose multiphysics finite-element analysis, not only modeling process but also can create and distribute applications, that is, it can provide a ubiquitous CAE environment (U-CAE) that enables analysis for "anyone,anytime, anywhere". In this paper, we apply the U-CAE environment to the design of acoustic metasurface and demonstrate the effectiveness of the application in understanding the generalized Snell's law, which is the basis of the metasurface, and achieved quick implementation of the latest theory including numerical study to U-CAE. As a result, one of the difficult problems in computational engineering is the work of interpretation from theory to numerical model in the process of implementing the latest theory to CAE environment. It is recommended for theorist to write papers with consideration of numerical computation.

In AM, hot deformation during manufacturing makes it difficult to receive the full benefit of the performance improvement by AM, because output shape deviates from the design shape. In order to cancel the deformation, the designed shape can be deformed beforehand in the opposite direction to the deformation, which is called the pre-deformation correction in this paper. The pre-deformation correction requires numerical calculation with both high-accuracy and low calculation cost to obtain the deformation on entire product surface beforehand by simulating the complicated process in which the material melts and solidifies ununiformly. In this paper, we propose a method to improve the AM simulation accuracy using inherent strain method, which has low calculation cost. The characteristic of this method is that the complex inherent strain distribution, which is simulation input, is estimated by Ridge regression from the trial manufacturing result. The effectiveness of the proposal method is shown using some specimens with different deformation modes.

The research subject is to develop a finite element modeling method to reproduce the bending stiffness of IWRC 6×Fi(29) wire ropes for cranes. Since IWRC 6×Fi(29) is made of steel wire instead of fiber in the center of the rope, there are many contact points between wires. Therefore, a high level of reproducibility of contact conditions between wires is required. In this study, Fi(29) strands, IWRC and IWRC 6×Fi(29), which consists of these strands, are the object of analysis. A rope model eliminated initial penetrations between wires by the dynamic relaxation analysis and modeling of a three-point bending test was conducted. For validation, the experimental and analytical results were compared, and the slope and hysteresis of the load-displacement curves were well represented in the analysis. Furthermore, it was confirmed that the analytical values of the rope flexibility obtained by the load-displacement curve approximately matched the experimental values and that the bending deformations of the rope can be expressed in the analysis.

The friction coefficient between tire tread rubber and road surface is an important property for tire performances and the prediction of the friction coefficient is also important．In this study, the general purpose finite element analysis software “Abaqus” is used to obtain the hysteresis friction behavior between periodic rigid surfaces and rubber models in which hyperelastic and viscoelastic properties are taken into account．A multi-scale analysis is used to calculate the friction coefficients of each scale．The contact load between a road surface and a rubber model is determined by the average contact pressure calculated by a larger scale model analysis．As the model scale is smaller, the deformation of the rubber model and the friction coefficient become larger. The maximum friction coefficient is about 0.8 in λ = 1×10^-4 mm scale model.

Automobile millimeter-wave corner radars are mounted behind plastic bumpers, and it is known that bumper shape and color affect millimeter-wave propagation characteristics. Numerical simulation is an effective means of predicting these effects, but explicitly meshing the bumper coating is not practical in terms of modeling man-hours and computational load. We have verified that the Multi-layered Thin Sheet function, which equivalently models the structure of multi-layered coating layers, provides results equivalent to those obtained by explicitly representing multi-layered coating layers while reducing the computational load.

EVs are about 30% heavier on average than similar-sized engine vehicles due to the weight of their batteries. Therefore, it is crucial to reduce the weight of the components. In this paper, we focused on the impact energy absorption member, and the possibility to use the cylindrical honeycomb structure as an impact energy absorption member was investigated. First, an impact analysis of the cylindrical honeycomb was performed to compare the impact energy absorption performance with the box beam and the conventional tubular honeycomb structure. As a result, it was shown that the cylindrical honeycomb has a high impact on energy absorption performance. Next, the coating method of the cylindrical honeycomb core was investigated. It was shown that spray painting, which influences less environmental load, could be available to paint the cylindrical honeycomb core with complex geometry.

We developed the CFD analysis code BAROC for the reactor containment vessel and reactor building in a situation of severe accident. BAROC can analyze the three-dimensional thermal-hydraulics of multi-component gas and FP (fission product) aerosol in detail. By applying the implicit method and partially parallel processing, high-speed calculation is possible even for large-scale systems. The physical model and numerical solution method used in BAROC, as well as the results of analysis of the leakage and diffusion behavior of hydrogen and FP in the reactor building at the time of the accident of the Fukushima Daiichi Nuclear Power Plant are introduced.

Print circuit board (PCB) mounted on transportation equipment receive various random loads from the outside as vibrations during running. We sometimes experience that fatigue failure of electrical component leads under random loading and so it is very important to evaluate the fatigue life in the design of PCB. In general, we calculate the response power spectrum density (PSD) for random loads with FEM, and fatigue life is predicted in the frequency domain. However, fatigue fracture occurs in localized stress areas due to shape change, so handling of localized stress is an issue for improving the accuracy of predicting fatigue life. In this paper, we research the predicted life using Dirlik’s method with Hot Spot stress and the S-N curve considering the stress concentration factor. And we compare the predicted life with the rupture life obtained from random vibration tests on the PCB. As a result, we can confirmed that these predicted lives are close to the experimental results, and the life estimation considering the stress concentration is effective for the fatigue life evaluation of the bent portion of the terminal of electronic parts.

In recent years, demands for robustness in products have increased. Airbags are essential restraint devices that are indispensable for crash safety in automobiles. However, various factors, such as friction, affect their deployment, and deployment repeatability is still an issue, especially in the out-of-position case where contact with the occupant occurs during deployment. In this paper, the results of several Out-of-Position cases with slightly different friction and dummy position are processed using the robustness analysis software DIFFCRASH. As a result, the relationship between input scatters and the modes of behavior are visualized as well as the temporal evolution of the scatter.

The catalytic reactions converting carbon into reusable fuel materials is one of the key technologies in carbon recycling. Numerical simulations have been conducted to study the catalytic reactors including multi-step chemical reactions, flow, reaction heat, heat transfer, and diffusion. In most models, however, the microstructure of the catalyst bed are often treated as a homogeneous body, making it difficult to evaluate the effects of the differences in pellet shapes. In this study, we have developed the macroscopic homogenization model combined with the three-dimensional microstructure in the catalyst bed in order to predict complex phenomena in the reactor. The model validation has been also performed with the actual experiments of catalytic reactions. Furthermore, the effects of different pellet shapes on the temperature, flow field, and reaction field in the reactor were compared.

In recent years, topology optimizations have attracted attention as advanced optimization methods with higher degree of freedom to represent various topologies. These methods can automatically propose innovative/optimal topologies. Therefore, the topology optimization can be an efficient tool to extract innovative design insights. In general, the topology optimizations become high-dimensional optimization problems. This increases the possibility to represent optimal topologies, while requires a large number of performance evaluations to solve the optimization problems. In this study, we investigate the introduction of dimensionality reduction methods that can replace a high-dimensional design space with a low-dimensional design space in order to reduce the computational cost to solve the topology optimization problems. Proper orthogonal decomposition and active subspace method are considered as the dimensionality reduction methods in this study. As a result, it is confirmed that the computational cost can be reduced by using the dimensionality reduction methods.

In order to construct a surrogate model for a finite element analysis (FEA) model using machine learning, we investigated which sampling method should be used to construct a highly accurate surrogate model with less training data. Random sampling and Latin hypercube sampling were used as methods for predetermining sampling points, and Voronoi sampling and active learning were used as methods for adaptively adding sampling points. In active learning, a Gaussian process regressor (GPR) was used as the learner model, and the variance of the probability distribution output from the GPR was used as the acquisition function. Also, in the other sampling methods, the same GPR kernel configuration used in the active learning was utilized to create surrogate models. Using these four sampling methods, we created surrogate model for the FEA model which is used to predict the strength of rupture disc for air-conditioning compressor and clarified that active learning could create a highly accurate surrogate model with a small number of training data.

This study works on how to simulate a flow field in a data-driven manner using a deep learning method called Physics-Informed Neural Networks (PINNs). This method trains a neural network, which inputs time and space and outputs the corresponding flow quantities by satisfying the Navier-Stokes equations, boundary conditions, and initial conditions. Then it can quickly reproduce a flow field in any time and space. The application of PINNs to engineering problems is an area for further investigation since PINNs need to be re-trained whenever the boundary conditions change, i.e., the training cost should be as low as possible. Hence, this study considers how to reduce the training cost of PINNs for an airfoil by adaptively arranging the collocation points. At present, this paper examines PINNs for a laminar flat plate as a preliminary step. The results show that, for qualitatively accurate PINNs, it is influential to consider the stagnation pressure at the leading edge of the plate as a constraint in the PINNs loss function.

The strength prediction of a fiber-reinforced laminated composite is a big issue to achieve an efficient research and development. This study aims to develop a prediction method of the strength variation of composite laminates as one of the material integration (MI) method by adopting the Bayesian optimization (BO) method. As the BO method, this study adopts a batch Bayesian optimization (BBO) to obtain multiple laminate configuration candidates that maximize the strength based on the results of the strength test with considering empirical constraints such as the contiguous number limit of the same orientation angles. In order to obtain the multiple laminate configurations, an improved genetic algorithm based on the distributed genetic algorithm with adaptive mutation and gene repair strategies is adopted. Through numerical examples based on the open hole tension (OHT) strength test data, efficiency of the proposed method is demonstrated.

In this paper, we developed topology optimization that represents the level-set functions using the radial basis function（RBF）and attempted to speed up the solution search using covariance matrix adaptation evolution strategy（CMA-ES）. By using a continuous and smooth level-set functions represented by RBF to represent the boundary between solid and void, the number of design variables and the accuracy of the finite element analysis can be separated, and the number of design variables can be reduced while maintaining the accuracy. Using thermal cloaks as numerical examples, it was confirmed that the optimal configurations and fitness are almost the same as those of conventional design methods, even when RBF is introduced.

In this study, we design the structure of a piezoelectric energy hevesting device with high power generation performance at a desired frequency using topology optimization. Specifically, a unimorph-type energy hervesting device with a piezoelectric film on one side of a silicon cantilever beam is targeted for design. The structures of the substrate and piezoelectric film parts are simultaneously optimized. We impose constraints to avoid structures where only the piezoelectric film remains in the area where there is no substrate. Several numerical examples are presented using the developed method to confirm effectiveness of the method.

In this study, we performed density-based topology optimization for minimizing equivalent stress. Density-based topology optimization is often employed the optimality criteria (OC) method for design variable update equation. However, the OC method also has several problems. We developed a modified OC method based on the concepts of the conventional OC method and Newton’s method. In the results of the topology optimization analysis for minimizing strain energy using the modified OC method, the number of iterations and parameters settings have been reduced and the dependence on parameter settings has been pursued. Therefore, the modified OC method is also employed for topology optimization to minimize equivalent stress. As a result, the density distribution at final iteration when using the OC method depends on the setting value of the move limit. On the other hand, the density distribution at final iteration when using the modified OC method was found to be less dependent on the parameter.

In this study, we proposed a new acceleration gradient method that introduces the concept of Taylor expansion into Nesterov's acceleration gradient method. The proposed method is called the modified acceleration gradient method. A texture shape optimization analysis is performed using the proposed method to minimize the friction coefficient. The gradient of the Lagrange function with respect to the design variables used in the proposed method can be obtained by the adjoint variable method. The equation of state used in the analysis is the Reynolds equation that determines the pressure on the oil film. As a result, the number of iterations can be significantly reduced in comparison to Nesterov's acceleration gradient method. The optimal oil film thickness distribution in the textured area was also calculated. The texture shape after convergence was asymmetric in the flow direction. This pattern was similar to that observed in shape optimization using Nesterov's acceleration gradient method. Numerical experiments performed to validate the proposed method are described.

Accuracy of estimation or forecast of states or parameters by data assimilation is highly depends on observation condition. Especially, for improving accuracy with limited number of observation sensors, optimization of sensor placement is important. In this study, we conducted the experiments of optimization of sensor position for Kalman Vortex reconstruction problem. We compare the results of assimilation using the optimal observation points (top 20) suggested based on the two different methodologies, Empirical Observability Gramian (EOG) and Ensemble Forecast Sensitivity to Observations (EFSO). EOG is based on concept of observability while EFSO is based on sensitivity to reduction of forecast error by ensemble-based data assimilation. Spatial distribution of optimized sensor position by each methodology looks different and the results of experiment showed that assimilated flow field with the observation optimized by EOG showed smaller RMSE than that optimized by EFSO. Further analysis must be conducted changing the number or spatial interval of sensors.

It is a challenge in clinical practice to estimate Time Enhancement Curves (TEC) of a Region Of Interest ( ROI ) in real time from intraoperative X-ray projection movies. In the past, TEC was estimated by obtaining the Standard Linear Attenuation Coefficient Distribution (SLACD) from a preoperative contrast-enhanced CT and combining it with an intraoperative X-ray projection movie. However, in actual clinical practice, the SLACD is often uncertain due to the unavailability of preoperative contrast-enhanced CT images and the patient's respiratory motion. We developed a method for estimating TECs at a newly defined Node Of Interest (NOIs) by applying Singular Value Decomposition ( SVD ) and prior information to intraoperative X-ray projection movies only. To validate the effectiveness of this method, twin numerical experiments were conducted using a simulated blood vessel model, and the estimation results were compared. The estimation results show that the method is able to accurately estimate the rise time of TECs and the frame of maximum concentration.

Nonlinear finite element analysis with normal vector constraint that is updated automatically was performed. We created a virtual point cloud of a deformed plate, and triangle polygons. The plate created for constructing normal vector constraint was used as a reference solution. We analyzed another plate that had coarse mesh and different distributed load with normal vector constraint to match the deformation to the reference solution. The accuracy of displacement and Cauchy stress was mostly in good agreement.

We are developing a method that estimates cracks that are invisible from the surface based on the surface deformation measured by digital image correlation (DIC). An inverse problem is set up to estimate such invisible cracks from the surface deformation. Surface deformation, measured by the DIC method, contains noise. Inverse problems have an ill condition. The regularization method applied in this study is an extension of the JE-MAP method. The JE-MAP algorithm alternates between Maximum a Posteriori (MAP) estimation and the Grab-cut (GC) method to avoid ill-conditions. The physical constraints on displacement and the forces at the cracks and the crack perimeters (ligaments) are added to the MAP method. The displacement and load at the cracks and the ligaments have a cross-sparse relationship. The MAP method estimates the displacement or the load at the cracks and the ligaments. The estimated result varies greatly at the boundary between the cracks and the ligaments. This boundary is determined by the GC method based on the estimated result. In this study, we further amplified the changes in our estimates at the boundary between the cracks and the ligaments. The amplified results were input into the GC method to improve the boundary-determination accuracy. Our extension of the JE-MAP method was combined with DIC to estimate the cracks in invisible locations.

Data assimilation is a technique for estimating uncertain parameters and states in a simulation by integrating observed data into a numerical simulation. In this study, the applicability of the data assimilation algorithm, Ensemble Smoother with Data Assimilation (ES-MDA), to parameter estimation in elastoplastic finite element analysis was verified through twin experiments using pseudo-observational data. The results confirm the applicability of ES-MDA to parameter estimation in elastic-plastic finite element analysis.

Since the magnetic field is not attenuated or shielded by organic matter, magnetic field positioning is suitable for positioning in vivo. However, since the magnetic field has a larger distance attenuation than when radio waves or sound waves are used, it is difficult to determine the position and direction of the magnet using the inverse analysis method for the measured value of the magnetic field. Inverse analysis requires solving nonlinear equations by iterative calculation．It is important to develop an algorithm that converges with a small number of iterations and a method for setting initial values. We report a solution to the position tracking for a magnet moving in a living body or the field outside the body.

Spar-type offshore wind power generation is a kind of floating wind power generation facilities that, unlike fixed wind turbines, is installed in deep sea water. One of its characteristics is that it is not easily affected by waves. However, in order to ensure stability and safety, it is necessary to conduct analysis using appropriate simulation techniques. In this study, the δ-SPH method, one of particle methods, was used to analyze the wave behavior of two new types of spar-type offshore wind power generation. In the present paper, we studied the changes in wave behavior when the values of the modified artificial viscosity term and the artificial density-diffusion term introduced into the δ-SPH method are varied.

The spin-dynamics simulator for calculating a hysteresis loss is useful for a highly efficient design of the electric motor. We reported a basic calculation method using the Landau-Lifshitz-Gilbert equation and a new treatment of the exchange interaction for particle spins larger than atomic spins. In this report, we introduce a random magnetic field as thermal effect applied for the renormalized exchange interaction.

Meshfree particle methods are known as a powerful tool for complex numerical continuum analyses, including migration or large deformation of boundaries. However, the methods commonly tend to need higher computational costs for stable stencil calculation than mesh-based methods because the computational points, called particles, are heterogeneously distributed in a domain. To overcome this issue, we developed the mesh-constrained discrete point (MCD) approach. The MCD method can perform the stencil calculation efficiently because of constraining the arrangement of discrete points (DPs) using simple background mesh systems such as the Cartesian grids. In this study, we further develop the MCD method to address moving boundary problems. In the developed formulation, the arrangements of DP positions and related calculation masks are updated every time that follows the moving boundary. The validity of the proposed method is investigated in a simple numerical example for a moving body in two-circular channels. The calculation masks for the DPs are adequately updated even when the moving boundary crosses the background mesh.

In electronic products, lately increasing thermal radiation is demanding higher thermal conductivity of polymer composites. However, inaccurate observation of filler dispersion within the polymer do not allow for accurate quantification of Interface Thermal Resistance and subsequently prediction of thermal conductivity. Therefore optimum filler design could not be achieved. Firstly in this report, accurate stereoscopic filler dispersion was observed by FIB-SEM. Secondly, quantification of Interface Thermal Resistance could be achieved by thermal conduction analysis using filler dispersion model. Thirdly, this Interface Thermal Resistance enabled prediction of the thermal bulk conductivity. Lastly, prediction made above could be validated by comparison of predicted value and measured value. This result may lead to optimum filler design and thereby to the development of higher thermal radiation materials.

When electronic components are used over a long period of time, internal cracking and delamination can cause failures. It is important to predict and evaluate the mechanical behavior in the vicinity of cracks, which are the starting point of such failures. It is known that when an electric current flows through a cracked metal, the thermal stress caused by the Joule heat becomes a singular field around the crack. The temperature distribution near the crack can be related to the stress intensity factor by the path integral representing the electric potential distribution (1). In this paper, we investigate the fracture mechanics parameters of cracked copper lines under mechanical and electrical stress. When using the finite element method for research, it is necessary to investigate the difference between the stress intensity factor calculated by the path integral and the stress intensity factor obtained by other methods. Therefore, a finite element analysis of a crack model is performed to investigate the stress intensity factor and J-integral values under independent mechanical and electrical conditions.

Power modules are key products used in various fields such as home appliances, information equipment, factory equipment, and transportation equipment. Research on power modules with long life and high reliability will greatly contribute to the realization of a low-carbon society. As an example, we considered an IGBT (Insulated Gate Bipolar Transistor). An important part of this is the joint between the wire and the semiconductor chip. Failure occurs at this joint due to repeated thermal loads due to operation of the power device. In this study, we focused on the wire lift-off phenomenon in which the Al wire separates from the Si chip due to thermal fatigue at the Al-Si joint, and thermo-elastic-plastic creep analysis of the crack tip is performed using the FEM mode. Regarding the influence of modified strain hardening of Al on thermal fatigue, the evaluation parameter ΔW_in was investigated and report.

Power modules are key energy saving products that are used in all types of power control and contribute to reducing power loss in various types of devices. One of the important parts of a power module is the joint between a wire and a semiconductor chip. This joint is damaged by repeated heat cycles caused by operation of the power device. An example of thermal fatigue damage is the wire-liftoff phenomenon, in which wires peel off from semiconductor chips. To evaluate thermal fatigue for this phenomenon, it is necessary to consider elasto-plastic deformation, thermal deformation, and creep deformation. Therefore, we investigated the use of T*-integral, in which path independence is established even in the presence of these deformations, for thermal fatigue evaluation of Al-Si joints. In this study, T*integral program was developed and the results of functional test of the program for tensile problems with central cracks are reported.

The mean-field theory proposed by Humphreys is frequently used to predict abnormal grain growth caused by nonuniform grain boundary properties. This theory enables the abnormal growth conditions of a particular grain to be described using only three parameters: the size ratio, grain boundary energy ratio, and mobility ratio between the particular grain and its surrounding matrix grains. However, detailed validation of the theory has yet to be reported. In this study, we elucidate the validity of the mean-field theory by performing very large-scale phase-field simulations of 2D and 3D abnormal grain growth based on parallel GPU computing. Systematic simulations are carried out while varying the initial size ratio, boundary energy ratio, and mobility ratio of a particular grain and matrix grains. Comparisons of the simulated theoretical results demonstrate that the abnormal growth behaviors (i.e., whether the abnormal growth occurs and the limiting size that can be reached by an abnormally growing grain) is well described by the mean-field theory.

Accurate evaluation of dendrite growth is essential to improve the quality of cast products. The objective of this study is to develop a data assimilation system to integrate X-ray imaging observations and phase-field simulations of three-dimensional columnar dendrite growth in a thin film. Here, solid fraction in the thickness direction of the thin film is used as observation data.

Various properties of sintered materials strongly depend on their microstructure. Thus, prediction of the microstructural evolutions in the sintering process leads to improve the properties. A phase-field (PF) simulation of solid-state sintering is powerful to predict the microstructural evolution. However, the PF simulation requires material parameters that are largely unknown. On the other hand, data assimilation has attracted attention as an effective methodology to estimate unknown states and parameters. Therefore, in this study, we apply a non-sequential data assimilation method named DMC-BO to the PF simulation of the solid-state sintering to estimate unknown material parameters and improve the prediction accuracy. To validate the application of DMC-BO to the PF simulation of the solid-state sintering, a numerical experiment is conducted. Through the numerical experiment, we demonstrated that the DMC-BO can improve the prediction accuracy of the microstructural evolution in the solid-state sintering process by simultaneously estimating multiple diffusion coefficients and mobilities with reasonable accuracy. Moreover, the result shows the DMC-BO requires a low computational cost for obtaining the estimation.

To improve performance of a high-temperature polycrystalline superconductor, it is effective to predict microstructural evolutions during a solid-state sintering using the phase-field method. However, interfacial and surface properties required for the phase-field simulation of the sintering process are largely unknown. In this study, the surface energies of iron-based polycrystalline superconductor BaFe2As2 are calculated using the first-principles calculation. The results show that the stable suraface termination depends on the chemical potentials of Ba and As atoms. On the basis of the calculated surface energies, the anisotropy function of surface energy for BaFe2As2 that can be incorporated into the phase-field model of the solid-state sintering is calibrated.

In casting processes, semi-solid deformation induces serious solidification defects, such as segregations. In this study, semi-solid deformation is investigated in detail using the multi-phase-field lattice Boltzmann model developed in a previous study. Specifically, we evaluate the changes of local solid fraction caused by the Reynolds’ dilatancy, through simulations of two-dimensional semi-solid deformation using the developed model.

Accurate prediction of the material microstructure formed by additive manufacturing (AM) is key to improving the properties of metal AM products. In this study, a model to simulate the material microstructure formed during the powder bed fusion AM is investigated. In the model, melting and solidification due to laser scanning, liquid flow in melt pool, and grain growth in solidified layer and substrate are modeled in an integrated manner using a multi-phase-field method.

A Multi-phase field lattice Boltzmann method for melting, gas/liquid flow and solidification in powder bed fusion process of Ni alloy additive manufacturing is developed. Improved lattice kinetic scheme is adapted for gas/liquid free surface flow simulation. High speed calculation is achieved by MPI&OpenMP hybrid parallelization. It is confirmed that this method has high capability to simulate the powder bed fusion process in detail.

Recently, there has been an increased usage of fiber-reinforced composites in aerospace and automobile due to their celebrated mechanical properties. Thus, a massive research effort has hitherto been done to develop a method for concurrent optimization of structural topology and fiber orientation. Topology-optimized continuous fiber-reinforced structures tend to show complex morphologies with spatially varying fiber orientation. Due to this nature, it is nearly possible to manufacture the results only through additive manufacturing technology However, a gap must exist between prescribed optimized fiber orientation and fiber orientation of manufactured composites under a limited degree of precision of the manufacturing process. Robust anisotropic topology optimization under such uncertainty, therefore, needs to be developed. This presentation aims to present a novel robust topology optimization methodology for fiber-reinforced materials under fiber orientation uncertainty. Our method is built upon Phase-Field based topology optimization which is suitable for this type of optimization method. The effectiveness of our method is validated through the stiffness maximization problem and the fundamental eigenfrequency maximization problem.

Dendrite morphology formed during solidification of alloys is largely affected by thermosolutal convection. Although the phase-field lattice Boltzmann (PF-LB) model has made it possible to reproduce dendrite growth with themosolutal convection, the large computational cost is a major problem. In this study, to accelerate the PF-LB simulation with thermosolutal convection, the parallel-GPU mother-leaf AMR method is implemented. We confirmed that the developed scheme can significantly speed up PF-LB simulations.

Thermal and/or nuclear power plants utilize heat transfer phenomena caused by phase changes of fluids to transport the enormous amount of heat generated by boilers or reactors. Thus, a detailed understanding of their heat transfer behavior is important for improving plant performance and safety. The two-phase flow generated in the plants is unsteady and multi-scale ranging from mm to several meters, and it was difficult to understand the details by the conventional two-fluid model based on averaging. In this study, we proposed the hybrid method by combining the two-fluid model with the phase field method which is recently known as the attractive method for phase-change simulations. The proposed hybrid method was compared with reference data in the benchmark problems and good agreement between them was obtained.

We verify the interfacial-tension effect and wetting boundary condition of a phase-field model (PFM)-based computational fluid dynamics (CFD) method and examine its applicability for simulating microscopic droplet motion on structured and heterogeneously wettable solid surfaces. Instead of the Cahn-Hilliard equation, the conservative Allen–Cahn (CAC) equation is adopted to calculate the advection and construction of diffusive interfaces. A numerical scheme based on the lattice Boltzmann model is employed to solve the Navier–Stokes equations coupled with the CAC equation for an immiscible incompressible isothermal two-phase fluid system with equal densities and viscosities. Numerical simulations in three dimensions demonstrate that the PFM-based CFD method can be used to evaluate the mobility of droplets on structured and/or partially wetted solid surfaces in various microfluidic devices and processes.