An effective capacitive deionization process termed membrane capacitive deionization (MCDI) is newly designed and experimentally tested for seawater desalination. By preventing co-ions to be expelled, MCDI can improve the ion removal performance, but there is a trade-off between blocking co-ion transfer and increasing contact resistance. The conventional MCDI uses 2D-shaped films which increase contact resistance and reduce desalination performance in the trade-off. In this paper, with the 3-D shape of Nafion coated activated carbon cloth, the mentioned problems are expected to be solved making the desalination performance better. We visualized ion concentration and fluid flows with half-MCDI cell that can measure only efficiency of cathode. We found the optimal number of coatings which have the better efficiency than CMX, commercial cation exchange membrane in fixed current conditions of 100uA.

Air purifiers can be placed where the air cleaning is required, making it easy to manage indoor air quality. The position of the air purifier affects the indoor airflow pattern, resulting in different air cleaning efficiency. Many efforts and strategies have been examined through numerical simulations and experiments to find the proper location of the air purifier, but problems still remain due to the various geometrical indoor spaces and arrangements. Herein, we develop an artificial intelligence model to predict the performance of an air purifier depending on the installation location. To obtain the training data, numerical simulations were performed on the different locations of the air purifiers and airflow patterns. The trained artificial intelligence model predicted the air exchange performance depending on the installation location of the air purifier with a prediction accuracy of 92%.

Flow characteristics of jet impingement over concave hemispherical surface with effusion cooling holes is relatively more complex than that of a flat surface, so the experimental validation for computational fluid dynamics (CFD) results is important. In this study, experimental results were compared with simulation results obtained by assuming different turbulence models. The vortex was observed in the region between the central jets where the recirculation structure appeared. The different patterns of vorticity distributions were observed for each turbulence models due to different interaction of the injected jet flow. Among them, the transition k-kl-ω model predicted similarly not only the jet potential core region with higher velocity, but also the recirculation region between the central jets. From the validation, it may be helpful to accurately predict heat and mass transfer in jet impingement/effusion hole system.

Due to increasingly strict emission regulations for carbon-based fuels in the shipping industry, there is a significant motivation to investigate the alternative fuel. Ammonia is one of the attractive alternative fuels as a carbon-free fuel. Since ammonia has different properties such as high vapor pressure and low boiling point compared to conventional fuels, further research into ammonia spray behavior is important. In this work, the spray characteristics of ammonia and other fluids (ethanol, n-decane) were compared by using numerical simulation. The results show that the spray characteristics of ammonia differs from those of the others due to the occurrence of flash boiling. The narrow-dispersed spray with accelerated velocity at the center have been observed for ammonia. It is also found that droplets of ammonia achieve smaller diameter with more uniform distribution, leading to better atomization behavior compared to the others.

We analyzed the low wall-shear stress area in the intracranial aneurysm that occurred at an anterior communicating artery with a special emphasis on vortical structures close to the wall. We reconstructed the aneurysm model from patient CTA data. We assumed blood as an incompressible Newtonian fluid and treated the blood vessel as a solid wall. The pulsatile boundary condition was applied at the inlet of the anterior cerebral artery. From the instantaneous flow field, we computed the histogram of the wall-shear stress over the aneurysm wall and found the low wall-shear stress event (< 0.4 Pa). This extreme event was due to the low wall-shear stress area that occurred at the daughter sac. We found that the merging of two vortices induced the low wall-shear stress area; one arises from the morphological characteristics of the daughter sac, and the other is formed by a jet flow into the aneurysm sac. The latter approaches the daughter sac, which ultimately leads to the strong ejection event near the daughter sac.

We experimentally investigate a rising toroidal bubble impacting a free surface. The toroidal bubble is created by releasing pulsed air. By adjusting the volume and circulation of the toroidal bubble, the characteristics of interactions between the toroidal bubble and the free surface are identified. Because of the impact by the toroidal bubble, the free surface is convexly deformed upwards above the center point of the toroidal bubble, while the edge of the deformed free surface is pulled down. When the circulation of the bubble becomes stronger, the surface which was pulled down breaks eventually, and air above the free surface is entrained into water, forming an unstable toroidal bubble. The deformations at the center and edge of the free surface are in a linear relationship with the Froude number and the Weber number, respectively.

In this study, we numerically simulate the condensational growth of micron-sized particles traveling through a pipe filled with humidified air. Using the finite volume method and Lagrangian particle tracking technique, the mixture of particle-laden flow with moist air in a T-juction pipe is simulated. The condensational growth of particles is calculated by considering the mass transfer of vapor in the air onto the particle surface. The results indicate that the growth rate of the particles increases as the relative humidity of air is higher. Furthermore, the placement of a porous media with low permeability in the pipe could enhance the degree of condensational growth.

Skeletal muscle tissues feature cellular heterogeneity, including differentiated myofibers, myoblasts, and satellite cells. Thanks to the presence of undifferentiated myoblasts and satellite cells, skeletal muscle tissues can self-regenerate after injury. In skeletal muscle regeneration, the collective motions among these cell types must play a significant role, but little is known about the dynamic collective behavior during the regeneration. In this study, we constructed in vitro platform to visualize the migration behavior of skeletal muscle cells in specific conditions that mimic the biochemical environment of injured skeletal muscles. We then visualized the spatiotemporal distribution of stresses arising from the differential collectiveness in the cellular clusters under different conditions. From these analyses, we identified that the heterogeneous population of muscle cells exhibited distinct collective migration patterns in the injury-mimicking condition, suggesting selective activation of a specific cell type by the biochemical cues from the injured skeletal muscles.

In these days, the rapid development in prediction technology using artificial intelligent is being applied in a variety of engineering fields. Especially, dimensionality reduction technologies such as autoencoder and convolutional neural network have enabled the classification and regression of high-dimensional data. In particular, pixel level prediction technology enables semantic segmentation (fine-grained classification), or physical value prediction for each pixel such as depth or surface normal estimation. In this study, the pressure distribution of the ship's surface was estimated at the pixel level based on the artificial neural network. First, a potential flow analysis was performed on the hull form data generated by transforming the baseline hull form data to construct 429 datasets for learning. Thereafter, a neural network with a U-shape structure was configured to learn the pressure value at the node position of the pretreated hull form. As a result, for the hull form included in training set, it was confirmed that the neural network can make a good prediction for pressure distribution. But in case of container ship, which is not included and have different characteristics, the network couldn't give a reasonable result.

Pipe failure due to thermal fatigue and environmental regulations are increasing the importance of pipe monitoring systems in industrial plants. Since most pipe monitoring systems are focus on external crack inspected, it is necessary to temperature and concentration measuring monitoring system inside the pipe. These systems have spatial uncertainty due to sample inspection by one-point measurement. In addition, real-time measurement is not possible due to the limitation of time delay due to contact measurement. In this study, CT-TDLAS (Computed tomography-Tunable diode laser absorption spectroscopy) apply to overcome the limitations of existing methods. Lasers exhibiting an absorption response at a wavelength of 1395 nm were arranged in a lattice pattern on measuring cell. It showed that the inside of the pipe changed to an unstable combustion state over time.