Aortic valve stenosis is a heart valve disease caused by the accumulation of calcium in the valve, which can divide into tricuspid aortic valve (TAV) stenosis and bicuspid aortic valve (BAV) stenosis depending on the shape of natural valve. In this study, pig heart-based TAV and BAV ex vivo models were fabricated, and the flow characteristics behind a valve were analyzed using 4D flow MRI. Flow behind normal TAV was uniformly distributed, while BAV asymmetrically opened with an eccentric strong jet. Especially, BAV ex vivo model exhibited a secondary flow in the region where the valve closed. In addition, BAV had a 26% higher peak velocity while maintaining similar stroke volume compared with normal TAV. This study would be helpful for understanding the flow characteristics for BAV AS patients.

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

Interaction of a droplet and substrate is important to determine the coating and final deposition pattern in inkjet printing system. In particular, an accurate deposition of the droplet should be guaranteed for high-resolution patterning. In this study, we performed high-speed shadowgraph experiments on droplet train impact in inkjet system. From the high-speed images, we observed an unexpected bouncing phenomenon. We have found two factors affecting bouncing regime; the Weber number and the curvature of deposited droplet. Experimental results indicate that there is a critical curvature diameter of deposited droplet, which splits into bouncing and merging regime. From this result, we obtained a power-law behavior between the Weber number and the curvature. The understanding of bouncing phenomena helps to improve the accuracy and productivity of inkjet printing.

Sloshing of the fluid having a free surface produces an impact force on a tank wall subjected to external excitation. This paper investigates the effect of cylindrical structures in a rectangular sloshing tank under translational harmonic excitations. By varying the number of installed cylinders in the tank, the characteristics of the free-surface deformation is experimentally observed, and the peak pressure on the tank wall is extracted by threshold values. To predict the peak pressure, the numerical simulation is also conducted using smoothed particle hydrodynamics (SPH), and the peak values are compared with the experimental results. Furthermore, pressure and velocity fields in the tank and free-surface shape are analyzed at the moment of impact.

For application to drag-based propulsion system, the dynamics of a segmented structure with multiple hinges undergoing oscillatory motion are investigated. The side flaps are connected to a centre rod with elastic plates acting as hinges. The hinges bend to only one direction so that the structure behave asymmetrically between the power stroke and the recovery stroke. An analytical model is proposed, which estimates the asymmetric deformation of the segmented structure coupled with hinges. Using the proposed model, the effects of key geometric and kinematic parameters on the dynamics of the structure are analyzed.

Bubble condensation, which involves the interaction of bubbles within the subcooled liquid flow, plays an important role in the effective control of thermal devices. In this study, numerical simulations are performed using a VOF (Volume of Fluid) model to investigate the effect of tube diameter on bubble condensation. As the tube diameter decreases, condensation bubbles persist for a long time and disappear at a higher position. It is observed that for small tube diameters, the heat transfer coefficients of condensation bubbles, which is a quantitative parameter of condensation rate, are smaller than those for large tube diameters. When the tube diameter is small, the subcooled liquid around the condensing bubble is locally participated in the condensation of the bubble to fill the reduced volume of the bubble due to the generation of a backflow in the narrow space between the bubble and the wall, so that the heat transfer coefficient decreases.

In this study, we investigate the effects of a single roughness element on Venturi cavitation. The single roughness element of hemispherical shape is installed at the throat inlet of a Venturi tube. Since the wake behind the roughness element induces an additional pressure drop, cavitation inception occurs at a higher Cavitation number for the Venturi model with the single roughness element than for the Venturi model with no roughness. Cavitation bubbles form along the wake of the roughness element and lengthen in the streamwise direction as the Cavitation number decreases, forming a longitudinal cavitation. With a further decrease in the Cavitation number, the longitudinal cavitation bubble merges with the sheet cavitation initiated from the exit edge of the Venturi tube throat, followed by the shedding of cloud cavitation. The merging of the longitudinal cavitation and sheet cavitation is accompanied by a sudden decrease in the discharge coefficient and an increase in the pressure loss coefficient as it chokes the flow inside the Venturi tube.

In the study, pool boing critical heat flux (CHF) was experimentally investigated depending on the length of heaters. A smooth silicon oxide surfaces are used as the boiling surfaces. As the results of pool boiling experiments based on distilled water in ambient pressure condition, the CHF decreased as the length of the heater increased. By the high speed imaging, it was shown that the number of vapor columns increased as the length of the heater increased. Comparing the number of vapor columns and the CHF according to the heater length, the change in the CHF according to the heater length was analyzed based on the hydrodynamic instability.

Thrombogenesis, which is the process of blood clot formation, can be initiated by platelet activation. Excessive formation of blood clot in the bloodstream can lead to thrombosis. Therefore, when dealing with patients with disseminated intravascular coagulation (DIC) or children, it is necessary to use small amounts of blood. Hence, it is important to develop methods for the rapid and accurate measurement of the platelet function using a small amount of blood. In this study, 3D printing technology was utilized to facilitate the production of micro channels. The amount of platelet adhesion in smokers and non-smokers was compared by repeatedly exposing the structure of the channel to adjust the number of blood injections and facilitate thrombosis attachment to simple stenosis structures.

We performed numerical simulations of blood flow in an arterial cerebral artery aneurysm to investigate the hemodynamic behavior after coil embolization. A patient-specific model was created based on CTA data. We also conducted the coil embolization simulation to obtain the coil placement within the aneurysm. Blood was assumed to be an incompressible Newtonian fluid, and both the vessel and coil were considered rigid walls. The pulsatile boundary condition was applied at the inlet, and the outflow boundary conditions were used at the outlets. Our findings demonstrated that the coil embolization significantly reduces the blood volume flowrate entering the aneurysm by effectively blocking the inflow jet, leading to a decrease in both TAWSS and WSS, especially at the systolic peak in the impingement zone. While several high OSI regions disappeared over the aneurysm surface, we observed high OSI regions with a relatively small area where the coil did not completely occlude the aneurysm. Overall, these results quantitatively analyzed the effectiveness of coil embolization by focusing on hemodynamic indicators, potentially preventing aneurysm rupture. The present work could contribute to the development of patient-specific coil embolization.

Three design parameters were considered in this study: outlet nozzle angle (30°, 60°, 80°), neck length (1 mm, 3 mm), and flow rate (0.5, 0.6, 0.7, 0.8 lpm). A neck diameter of 0.5 mm induced cavitation flow at a venture nozzle. A secondary transparent chamber was connected after ejection to increase bubble duration and shape visibility. The bubble size was estimated using a Gaussian kernel function to identify bubbles in the acquired images. Data on bubble size were used to obtain Sauter's mean diameter and probability density function to obtain specific bubble state conditions. The degree of bubble generation according to the bubble size was compared for each design variable. The bubble diameter increased as the flow rate increased. The frequency of bubble generation was highest around 20 ㎛. With the same neck length, the smaller the CV number, the larger the average bubble diameter. It is possible to increase the generation frequency of smaller bubbles by the cavitation method by changing the magnification angle and length of the neck. However, if the flow rate is too large, the average bubble diameter tends to increase, so an appropriate flow rate should be selected.

This research developed a measurement technique that can measure the oxygen temperature inside a high temperature furnace. Instead of measuring only changes in frequency components within a small range used in the existing variable laser absorption spectroscopy, laser spectroscopy technology was used to spread out wavelength of the light source passing through the gas Based on a total of 20,000 image data, research was conducted to predict the temperature of a high-temperature furnace using CNN with black and white images in the form of spectral bands by temperature of 25 to 800 degrees. The optimal model was found through Hyper parameter optimization, R2 score is 0.89, and the accuracy of the test data is 88.73%. Based on this research, it is expected that concentration measurement and air-fuel ratio control technology can be applied.

Characterizing the extensional rheological properties of non-Newtonian fluids is crucial in many industrial processes, such as inkjet printing, injection molding, and fiber engineering. However, educational institutions and research laboratories with budget constraints have limited access to an expensive commercial extensional rheometer. In this study, we developed a custom-made extensional rheometer using a CO₂ laser cutting machine and 3D printer. Furthermore, we utilized a smartphone with a low-cost microscopic lens for achieving a high spatial resolution of images. The aqueous polyethylene-oxide (PEO) solutions and a Boger fluid were prepared to characterize their extensional properties. A transition from a visco-capillary to an elasto-capillary regime was observed clearly through the developed rheometer. The extensional relaxation time and viscosity of the aqueous PEO solutions with a zero-shear viscosity of over 300 mPa·s could be quantified in the elasto-capillary regime. The extensional properties of the solutions with relatively small zero shear viscosity could be calculated using a smartphone's slow-motion feature with increasing temporal resolution of the images.

Acquiring experimental data for PIV verification or machine learning training data is resource-demanding, leading to an increasing interest in synthetic particle images as simulation data. Conventional synthetic particle image generation algorithms do not follow physical laws, and the use of CFD is time-consuming and requires computing resources. In this study, we propose a new method for synthetic particle image generation, based on a Physics-Informed Neural Networks(PINN). The PINN is utilized to infer the flow fields, enabling the generation of synthetic particle images that follow physical laws with reduced computation time and have no constraints on spatial resolution compared to CFD. The proposed method is expected to contribute to the verification of PIV algorithms.