11,629 research outputs found
Effects of polymer additives in the bulk of turbulent thermal convection
We present experimental evidence that a minute amount of polymer additives
can significantly enhance heat transport in the bulk region of turbulent
thermal convection. The effects of polymer additives are found to be the
\textit{suppression} of turbulent background fluctuations that give rise to
incoherent heat fluxes that make no net contribution to heat transport, and at
the same time to \textit{increase} the coherency of temperature and velocity
fields. The suppression of small-scale turbulent fluctuations leads to more
coherent thermal plumes that result in the heat transport enhancement. The fact
that polymer additives can increase the coherency of thermal plumes is
supported by the measurements of a number of local quantities, such as the
extracted plume amplitude and width, the velocity autocorrelation functions and
the velocity-temperature cross-correlation coefficient. The results from local
measurements also suggest the existence of a threshold value for the polymer
concentration, only above which can significant modification of the plume
coherent properties and enhancement of the local heat flux be observed.
Estimation of the plume emission rate suggests that the second effect of
polymer additives is to stabilize the thermal boundary layers.Comment: 8 figures, 11 page
Enhanced and reduced solute transport and flow strength in salt finger convection in porous media
We report a pore-scale numerical study of salt finger convection in porous
media, with a focus on the influence of the porosity in the non-Darcy regime,
which has received little attention in previous research. The numerical model
is based on the lattice Boltzmann method with a multiple-relaxation-time scheme
and employs an immersed boundary method to describe the fluid-solid
interaction. The simulations are conducted in a two-dimensional,
horizontally-periodic domain with an aspect ratio of 4, and the porosity is
varied from 0.7 to 1, while the solute Rayleigh number ranges from 4*10^6 to
4*10^9. Our results show that, for all explored Rayleigh number, solute
transport first enhances unexpectedly with decreasing porosity, and then
decreases when porosity is smaller than a Rayleigh number-dependent value. On
the other hand, while the flow strength decreases significantly as porosity
decreases at low Rayleigh number, it varies weakly with decreasing porosity at
high Rayleigh number and even increases counterintuitively for some porosities
at moderate Rayleigh number. Detailed analysis of the salinity and velocity
fields reveals that the fingered structures are blocked by the porous structure
and can even be destroyed when their widths are larger than the pore scale, but
become more ordered and coherent with the presence of porous media. This
combination of opposing effects explains the complex porosity-dependencies of
solute transport and flow strength. The influence of porous structure
arrangement is also examined, with stronger effects observed for smaller
porosity and higher Rayleigh number. These findings have important implications
for passive control of mass/solute transport in engineering applications
Generalizing 6-DoF Grasp Detection via Domain Prior Knowledge
We focus on the generalization ability of the 6-DoF grasp detection method in
this paper. While learning-based grasp detection methods can predict grasp
poses for unseen objects using the grasp distribution learned from the training
set, they often exhibit a significant performance drop when encountering
objects with diverse shapes and structures. To enhance the grasp detection
methods' generalization ability, we incorporate domain prior knowledge of
robotic grasping, enabling better adaptation to objects with significant shape
and structure differences. More specifically, we employ the physical constraint
regularization during the training phase to guide the model towards predicting
grasps that comply with the physical rule on grasping. For the unstable grasp
poses predicted on novel objects, we design a contact-score joint optimization
using the projection contact map to refine these poses in cluttered scenarios.
Extensive experiments conducted on the GraspNet-1billion benchmark demonstrate
a substantial performance gain on the novel object set and the real-world
grasping experiments also demonstrate the effectiveness of our generalizing
6-DoF grasp detection method.Comment: Accepted at CVPR 202
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