The objective of this study is to improve numerical stability of an elastic-plastic model with memory surface that realizes various hardening behaviors under different ranges of cyclic loading by combination between a primal-dual interior point method and a return mapping algorithm. The primal-dual interior point method allows us to smoothly optimize a minimization problem with inequality constraints such as a yield function and memory surface. More specifically, the inequality condition is replaced with the equal condition by introducing the slack variable and the duality gap is gradually reduced by employing the path-following method. On the other hand, the primal-dual interior method could require bigger computational cost than the conventional return mapping method because of the increase of the unknown variable and the path-following method. Thus, an implicit solution for an elastic-plastic model with the memory surface is proposed by combining with the primal-dual interior point method and the return-mapping algorithm. In addition to the numerical cost, the numerical accuracy of the primal-dual interior point method is evaluated by the comparison with the conventional return mapping algorithm by an iso-error map that has been often applied for the conventional elastic-plastic models. After then, the capability of the proposed implicit method for an elastic-plastic model with the memory surface is demonstrated throughout the simple numerical examples.

An Eulerian fluid-structure interaction (FSI) formulation, which numerically solves fluid and solid in a unified manner with a fixed mesh, is attractive for large deformation problems, high-performance computing, and quick mesh generation even for complex geometries. However, conventional Eulerian methods cannot stably compute FSI problems with the discontinuity of the velocity gradient near the fluid-structure interface. In order to avoid this problem, we propose a novel Eulerian FSI method using marker particles with the Reference map, which is the initial position vector of the solid region. Through the simulation of several benchmark tests, we have confirmed that the proposed method can stably compute the FSI problems mentioned above, and the present numerical results are in quantitatively good agreement with the reference solutions.

This study presents a method of real-time tsunami risk evaluation by combined use of proper orthogonal decomposition (POD) and Bayesian update. The validity of the proposed method is demonstrated through the numerical example targeting plausible tsunamis induced by Nankai-Trough events. First, tsunami simulations are carried out for plausible tsunami scenarios determined by various patterns of fault rupture, and the time histories of wave heights are stored at selected synthetic gauge points. Then, POD is applied to the resulting data matrix of the synthetic dynamics (SD) composed of dynamics modes and coefficients, the latter of which represent scenario-specific information. In the real-time risk evaluation phase, the wave sequences of an actual tsunami event are sequentially measured at the synthetic gauge points and used to estimate the corresponding dynamics coefficients of the constructed SD. At the same time, by the application of Bayesian update, the likelihood of each of the dynamics coefficients pre-calculated for the selected tsunami scenarios is evaluated at each time and sequentially updated to detect the most probable scenario. Finally, the pre-calculated tsunami arrival time and inundation depth distribution corresponding to the detected scenario are determined as risk assessment indices seven minutes after the tsunami generation.

The present paper proposes the novel design framework for thermal porous structure based on two-scale concurrent topology optimization subject to transient heat analysis. The optimization model considers the heat transfer through the microstructure surface to enhance the heat dissipation performance design. In particular, a well-known homogenization method incorporated the size-dependent term of microscopic heat transfer is exploited to obtain the material properties. Meanwhile, the unsteady-state heat condition is applied to the macrostructure. Furthermore, the heat compliance objective function and the derived analytical sensitivity formulations are adopted to determine the two-scale optimal topologies. As a numerical result, the concurrent design of micro- and macrostructures show the remarkable transient effect. It is also indicated that the microstructure size and the volume constraint are significant parameters for the design of heat performance.

This paper presents an example of the verification and validation (V&V) for non-linear finite element analysis of concrete beam with a single-edge notch subjected to three-point bending. The code verification is performed by estimating the energy absorbed to form the fracture surface on the basis of the fracture energy defined as the energy required to generate a unit crack surface. The calculation verification is carried out for demonstrating the low mesh-sensitivity of the computational model for crack propagation analysis. The uncertainty in the experimental and simulation outcomes is quantified by replicate tests and Monte Carlo simulation, respectively, and the computational model is validated by using the area metric defined as the area between the experimental and simulation cumulative distribution functions. Furthermore, a surrogate model based on the response surface methodology is examined for performing the Monte Carlo simulation with a low computational cost.

In this paper, a tensile crack model for a concrete constitutive model is proposed. The method is applied to large-scale finite element (FE) analyses of reinforced concrete (RC) structures. For constitutive modeling of concrete material subjected to multidirectional cyclic loading, Poisson’s effect is considered in the proposed model. In addition, crack strain tensor is introduced as a set of inner variables so that the formulation can be concise and comprehensive. To confirm the basic behavior of the proposed model, computation of stress integration for the tensile crack model and FE analyses of cubic models were conducted. Then, to verify and validate the proposed model, static analyses of a bending failure test of an RC beam were conducted for various element sizes and loading increments. The analysis results indicates that small loading increment is essential to simulate dispersion of cracks and reproduce the load-displacement relationship of the experiment.

Finally, a seismic response analysis of the E-Defense shake table test of a 10-story RC building was conducted. Hysteresis loop had fairly good agreement with the experimental one. In the range where the story drift angle is small, however, inter-story stiffness of the analysis was overestimated, which may be because the degradation of tensile strength caused by the former tensile cracking is not considered in the present model.

In the field of topology optimization for heat conduction problems, the steady-state thermal conditions are usually assumed because of its theoretical ease of handling. However, for design problems such as casting dies and heat-dissipating parts, where not only the spatial distribution of temperature but also its temporal transition is important, a topology optimization method considering unsteady-state conditions is required. With this background, the present study deals with an unsteady-state heat conduction problem with a special objective function, namely minimizing temperature at the targeted time and space. The optimization problem is solved using a gradient-based optimization scheme and its accuracy of sensitivities with respect to design variables is investigated. Finally, the performance of the proposed method and a common problem for unsteady-state thermal problems are discussed through a series of the numerical examples.

The velocity boundary layer, formed on an archery bare-shaft arrow, is computed by using two kinds of finite difference codes; an axisymmetric code and a three-dimensional code. Two types of arrow point, i.e., bullet point and streamlined point, are attached to a cylindrical arrow shaft. The Reynolds number, based on the shaft diameter, is varied in a range 10,000 ≤ Re ≤ 20,000, and the attack angle, α, is fixed at α = 0.0^o. Critical assessment is performed on the grid dependency of velocity profiles, the difference in velocity profiles between axisymmetric and 3D computations, and the effect of interpolation method on the interpolants by comparing the spline and the tri(bi)-cubic interpolations. The results of assessment indicates that the effect of varying the number of grid points, simulation codes and the interpolation method, considered in the present study, is sufficiently small for the purpose of linear stability analysis.

Spatial figures are generally drawn in 2D such as in textbooks. While learning with real objects allows for intuitive understanding, learning only with textbooks requires a higher level of spatial ability. In this paper, an application was developed, that supports learners without enough spatial ability by using AR to visualize 2D figures in 3D, making it easier to grasp the image of the 2D to 3D transformation. The system generates 3D data from the features of a 2D plan view using OpenCV library and machine learning technology, and support learning with generic AR. Demonstration experiments was conducted with 67 and 24 users. In spatial figure problems, the group using AR tended to get higher accuracy than the group without AR in problems using the ratio of the line lengths and using rotations of 3D objects. The effectiveness of the developing system was verified from the questionnaire after the experiment.

This study enhances the efficiency and versatility of the flow simulations for moving and deforming bodies that are typically required for fluid-structured interactions such as flutter. Two of critically time-consuming processes are calculations of spatial grid deformations and nearest wall distances for the turbulence models. Both are formulated as elliptic boundary value problems, and the fast matrix solvers for the linear systems are developed and validated. One method is the flexible GMRES and another is the Residual Cutting Method (RCM). Two types of unstructured grids around practical aircraft model known as NASA Common Research Model (CRM) are used to test the developed method. Both GMRES and RCM are at least 4 times faster than the classical Gauss-Seidel method to achieve practical criteria of convergence. Errors of the nearest wall distance by the present method are within 5% except the portions of large curvature, and they have little effects on the flow simulations around CRM for a cruise condition without large-scale flow separations. Flutter simulations for a single wing are also carried out, and the results well predict the onset conditions of the flutter of the wind-tunnel experiment.

This paper presents a method for the code verification and calculation verification in the verification and validation for non-linear finite element analysis of reinforced concrete beam. The computational model verified in this study is a non-linear finite element analysis using the modified von-Mises damage model for concrete and the von-Mises plasticity model for steel. A reference solution obtained from the beam theory with material nonlinearity is used for the code verification. The mesh sensitivity is evaluated by using the analysis of variance in the calculation verification instead of estimating the mesh convergence rate. Three cases of the reinforced concrete beam are prepared for code and calculation verification, each of which is different in beam size and bar arrangement. The numerical results provide the possibility of the verification for non-linear finite element analysis of reinforced concrete.

In this study, resin permeability analysis of woven composites is performed using a three-scale homogenization method. For this, structures of woven composites are considered in three scales, i.e., whole composites (macro-scale), woven fabric structures made of fiber bundles (meso-scale), and fibers in fiber bundles (micro-scale). Then, the three-scale homogenization method is formulated using the mathematical homogenization method based on the asymptotic expansion of flow velocity and pressure. Boundary value problems in micro- and meso-scales are derived to obtain micro/meso characteristic flow velocities and pressures. The micro/meso characteristic flow velocities are homogenized to obtain meso/macro permeabilities. A localization procedure is also shown to find actual meso/micro flow velocities and pressures occurring in woven composites. As an application of the present method, resin permeability analysis of a plain-woven glass fiber-reinforced plastic composite is conducted. The results show that the present method successfully analyzes the resin permeability tensors of the plain-woven composite and the resin flow through both woven structures and inside fiber bundles.

Uncertainty quantification is an evaluation of the probabilistic effect of uncertainty in the input parameters of a system on its output. Monte Carlo methods are familiar as statistical methods for this purpose. However, they have a problem of slow convergence. On the other hand, non-statistical methods expand the input and output random fields into functions in probability space, respectively, and therefore have high computational efficiency and accuracy. In this paper, we integrate the Non-Intrusive Polynomial Chaos (NIPC) method, one of non-statistical methods, with ADVENTURE_Thermal, a heat conduction parallel analysis tool based on Finite Element Method, and solve a steady-state heat conduction equation with thermal conductivity as a stochastic field. For this problem, we evaluate the computational complexity of the proposed method both theoretically and numerically, and highlight the bottleneck processes for larger scale of the problems. In addition, we propose a new method that can be applied to larger scale problems by reducing the computational complexity of the bottleneck process.

In this research, we propose a topology optimization method for obtaining optimized structures satisfying a self-supporting property. First, we propose an artificial physical field that can detect structural components lacking the self-supporting property. Next, a level set-based topology optimization method is introduced, and we formulate the optimization problem, where the geometrical constraint function is defined with the artificial physical field. As a representative example of the optimization that requires the self-supporting constraint, we target an acoustic cloaking problem, and an objective function is defined with an acoustic pressure. The explicit formula of the design sensitivity is offered, which is based on the concept of the topological derivative. Several numerical examples are offered to confirm the validity and effectiveness of the proposed method. We show the characteristic of the proposed artificial physical field and conduct topology optimization for an acoustic cloaking structure without any unsupported structures.

While s-version of finite element method (SFEM) can achieve high spatial resolution in a local domain by superimposing multiple meshes with different basis functions, it is well known that using Lagrange polynomials as the basis functions of conventional SFEM leads to discontinuous integrand which reduces the accuracy. This study adopts 2nd-order B-spline function as a basis function of SFEM in order to make the integrand continuous and improve the integral accuracy while reducing computational cost. Numerical benchmark tests using manufactured solutions are presented to validate the numerical accuracy of the proposed method.

A weak coupling method or strong coupling method is used for coupled analysis of interaction among multiple fields, and it is important to choose an appropriate method which assures reasonable computation time for a three-dimensional calculation without deteriorating solution accuracy. In this study, we introduce an iterative partitioned coupling (IPC) method into a numerical scheme for computation of magnetohydrodynamic flows to assess reliability of the weak coupling scheme used in our previous work. Under conditions that the effect of the flow field on the electromagnetic field is small, it is shown that the solution obtained by the IPC scheme is more reliable than that obtained by the weak coupling scheme when the time increment is not small enough to yield a solution converged with respect to time. On the other hand, it is confirmed that the solution obtained by the weak coupling scheme agrees well with that obtained by the IPC scheme when the time increment is sufficiently small.

The present study proposes a multi-material topology optimization method considering the physical properties of solid materials and the interface. An extended two-step filtering technique is introduced to define material interface based on Helmholtz-type partial differential equations. Furthermore, the width of the interface region can be controlled based on this approach. To deal with the non-convexity of the problem caused by multi-material topology optimization, a material interpolation function in which the material volume fractions are mutually independent is used: this allows for the commutativity of constituent materials. The minimum mean compliance problem is considered in two different structural models. To solve this problem, sensitivities of the objective function and the constraint condition are derived. The usefulness of the proposed method is verified through several numerical examples.

This study presents a mapping method for evaluating landslide hazards in consideration of the spatial uncertainty of rainfall. Spatial modes of the rainfall in a target area are extracted using a mode decomposition technique, and virtual rainfall events that may occur in the target area is generated using the spatial modes. Slope stability analysis with the assumption of the infinite slope is then performed using the virtual rainfall data, and a landslide hazard map is created. Based on the obtained results, the influence of the rainfall uncertainty on landslide hazard mapping is discussed.