As a cross section of square steel pipe is laterally crushed, the upper/lower plates deform inward and the side plates deform outward from the original shape. When the proposed process method is applied, the upper/lower plates remain flat while the side plates are folded inward. This deformation pattern does not damage the surroundings, and makes it possible to improve impact energy absorption performance by folding the side plates in an overlapping manner. Moreover, common steel pipe structures include pipe intersections and sections where it is necessary to avoid interference with other parts such as piping, wiring, or fork claws. In such cases, the current method is to create an opening by cutting off. As a result, the structural strength will decrease, often requiring that reinforcing materials be installed as a countermeasure. However, if the opening is processed by using the proposed process method in this paper, the crushed part will remain, without a decrease in structural strength or the addition of reinforcing material. This paper discusses the results of experimental and FEM (Finite Element Method) analysis of process conditions for inward deforming side plates of square steel pipes and evaluates the impact energy absorption performance during lateral crushing.

In order to alleviate congestion at the start of large-scale marathons and walking events, efforts are being made on a trial basis to adopt a wave start, in which participants form groups and start in a series of waves, instead of the conventional mass start. In this paper, we conducted an exhaustive search for a crowd-starting scheme that maximizes the event satisfaction felt by participants in a large-scale walking event by using complementary microscopic and macroscopic models that describe the behavior of pedestrians. As a result, we quantitatively clarified how the wave arrangement and the time gap between the start of each wave should be in a wave start.

In this study, an experiment where Superabsorbent Polymer (SAP) particles are dropped into water was conducted. As the particles accumulated on the bottom area, swelling starts. The height change of the particle layer is measured. The swelling behavior of SAP particles are also tracked using OpenPIV. In addition, the swelling process was numerically predicted with a three-dimensional computation method which deals with fluid-solid and solid-solid interactions (MICS) to confirm its applicability. On the macro-scale, MICS is used to simulate a seepage flow through SAP particles layer. As water flow through the layer, it is absorbed by the SAP layer and the particles swell upward. The applicability and improvability of the computations are then discussed.

Research on surrogate models, which are expected to significantly reduce computational time by replacing large-scale numerical simulations that require a large amount of computational time with approximate models such as machine learning models, has been attracting attention. However, if the numerical data generated by the simulations is large, the data generated by the surrogate model will also be large, which may cause time consuming in visualization processing during analysis. If a surrogate model, which we call image-based surrogate model, that also takes visualization processing into consideration can be constructed for large-scale simulation results, it will be possible to directly generate visualization results without simulation data, which is expected to greatly improve efficiency in analysis through visualization. In this study, an image-based surrogate model is constructed by learning multiple visualization images of numerical data and the simulation parameters at that time. The learning model to be developed is constructed based on the adversarial generative network model, and pixel shuffling is applied to the generators that are part of the model to make feature extraction more efficient, thereby speeding up the convergence of learning loss. In our experiments, we applied this method to actual numerical simulations and succeeded in speeding up the process by a factor of approximately 2.7 while maintaining the same level of prediction accuracy as existing learning models.

For large-scale numerical simulations in which data I/O problems emerge as real challenges, there is a growing demand for in-situ visualization, which is expected to significantly reduce data I/O costs by performing visualization simultaneously with simulation. However, in-situ visualization outputs images rendered with pre-defined visualization parameters, thus causing lack of interactivity in visual exploration during the analysis phase. To solve this problem, this work focused on the smart in-situ visualization approach, which tries to automatically determine ‘when’ (time-step) and ‘where’ (viewpoint) to visualize during the simulation run. Although this approach can evaluate and visualize an optimal viewpoint from multiple viewpoints, the cost of evaluating the optimal viewpoint proportionately increases as the number of viewpoints increases. In this paper, we propose a method to reduce the cost of estimating the optimal viewpoint by evaluating and selecting important time domains as the simulation evolves. We also propose a method to increase the efficiency of estimating the camera movement path, which connects the obtained optimal viewpoints. In the experiments, the proposed method was applied to an oral airflow simulation, and its effectiveness was evaluated.

The study aims to develop a new method to estimate the horizontal stiffness of seismic isolation layers in a low-cost and easy way. To properly predict the behavior of seismic isolation buildings, the horizontal stiffness of the seismic isolation layer must be known accurately. However, the horizontal stiffness of the seismic isolation layer of an existing seismic isolation building may differ from that of the design due to age-related deterioration, temperature history, and other factors. Many of the existing estimation methods require time and economic costs. Therefore, in this estimation method, a seismic building response simulation is first performed using seismic acceleration waveforms observed by accelerometers during moderate seismic motion as input. Next, the relationship between the horizontal stiffness and the maximum displacement of the seismic isolation layer is calculated. Finally, the horizontal stiffness of the seismic isolation layer is estimated by comparing the maximum displacement of the seismic isolation layer observed by a scratch plate during an earthquake with the obtained relationship. In this study, the conditions to apply the proposed estimation method are clarified through numerical experiments.

In the present work, we shall propose a simple chaotic masking model by means of the chaos synchronization of a globally coupled map (GCM) model with a sinusoidal mapping to involve a chaotic dynamics. In practice we shall present chaotic synchronization phenomena in GCM model by means of the Lyapunov spectrum analysis and put forward an iterative method to derive the invariant measure of the Frobenius-Perron equation. Then one obtains numerically the Lyapunov exponents under such a chaotic synchronization state. In addition one may confirm that the presently proposed chaotic synchronization model will be applied to a secured chaos masking scheme of an image of the standard image data base in terms of the encoding and the decoding processes. Through our computer simulations, it will be found that our chaotic masking model, which does not require any chaos feedback control in order to achieve synchronization between the transmitter and the receiver, may be considered to possess a capability to be applied to a highly secured communication technology.