6 research outputs found
The Changes of the Stress Coping Skills of the University Students through the Life Event Experiences
The effects of cavitation position on the velocity of a laser-induced microjet extracted using explainable artificial intelligence
The control of the velocity of a high-speed laser-induced microjet is crucial
in applications such as needle-free injection. Previous studies have indicated
that the jet velocity is heavily influenced by the volumes of secondary
cavitation bubbles generated through laser absorption. However, there has been
a lack of investigation of the relationship between the positions of cavitation
bubbles and the jet velocity. In this study, we investigate the effects of
cavitation bubbles on the jet velocity of laser-induced microjets extracted
using explainable artificial intelligence (XAI). An XAI is used to classify the
jet velocity from images of cavitation bubbles and to extract features from the
images through visualization of the classification process. For this purpose,
we run 1000 experiments and collect the corresponding images. The XAI model,
which is a feedforward neural network (FNN), is trained to classify the jet
velocity from the images of cavitation bubbles. After achieving a high
classification accuracy, we analyze the classification process of the FNN. The
predictions of the FNN, when considering the cavitation positions, show a
higher correlation with the jet velocity than the results considering only
cavitation volumes. Further investigation suggested that cavitation that occurs
closer to the laser focus position has a higher acceleration effect. These
results suggest that the velocity of a high-speed microjet is also affected by
the cavitation position.Comment: 11 pages, 13 figures, 4 table
A phase diagram of the pinch-off-type behavior of impulsively-induced viscoelastic liquid jets
In this study, we systematically investigate the jet behaviors of
viscoelastic liquids, focusing on the region of high velocity and high
viscoelasticity, which has not been investigated in previous studies. We
generate viscoelastic jets using an impulsive force and categorize the
resulting jets into two types: pinch-off jets (jets that break up during
elongation after ejection) and no-pinch-off jets (jets that pull back to the
nozzle after maximum elongation or jets that return without elongation after
ejection). We then propose criteria to characterize these regions using the
Weissenberg number and the Reynolds number, which are dimensionless numbers
composed of the rheological properties of the solution and the initial
conditions of the jet injection. It is found that pinch-off jets occur at in regions of high elasticity , and at in regions of low elasticity . We also show that
the phase diagram can be explained by modeling a focused jet using the finitely
extensible non-linear elastic dumbbell model with the Chilcott-Rallison closure
approximation (FENE-CR)