Existence and global attractivity of periodic solution for impulsive stochastic Volterra-Levin equations

In this paper, we consider a class of impulsive stochastic Volterra-Levin equations. By establishing a new integral inequality, some sufficient conditions for the existence and global attractivity of periodic solution for impulsive stochastic Volterra-Levin equations are given. Our results imply that under the appropriate linear periodic impulsive perturbations, the impulsive stochastic Volterra-Levin equations preserve the original periodic property of the nonimpulsive stochastic Volterra-Levin equations. An example is provided to show the effectiveness of the theoretical results

Predictions for combined in-line and cross-flow VIV responses with a novel model for estimation of tension

The dynamic responses of slender cylinders with high aspect ratios undergoing vortex-induced vibrations (VIV) are studied. In detail, a three-dimensional model predicting the VIV responses in both the In-Line and Cross-Flow directions of slender cylinders is proposed based on the nonlinear equation governing the dynamic deformation and a wake oscillator. The tension in the cylinder is estimated according to the incoming stream velocities. To predict the VIV responses, the cylinder is discretized into finite segments, and the vibrations of each segment are estimated from solving the governing equation when the excitation forces are modelled using the Van Der Pol's wake oscillator. Considering that the wake oscillator model estimates the excitation forces according to the dynamics of the cylinder, it reveals the interactions between the flow and the dynamics of the cylinder. In order to verify the model calculating the mean tension, the VIV responses, which has been experimentally tested, is numerically studied. The comparison between the numerically predicted and experimentally measured responses shows that, the approach, especially the novel tension model, proposed herein is reliable as the frequency of vibrations, dominant mode number and vibration amplitude are all in good agreement with the experimental measurements and results from peer-reviewed publications

Polarimetric Pose Prediction

Light has many properties that vision sensors can passively measure. Colour-band separated wavelength and intensity are arguably the most commonly used for monocular 6D object pose estimation. This paper explores how complementary polarisation information, i.e. the orientation of light wave oscillations, influences the accuracy of pose predictions. A hybrid model that leverages physical priors jointly with a data-driven learning strategy is designed and carefully tested on objects with different levels of photometric complexity. Our design significantly improves the pose accuracy compared to state-of-the-art photometric approaches and enables object pose estimation for highly reflective and transparent objects. A new multi-modal instance-level 6D object pose dataset with highly accurate pose annotations for multiple objects with varying photometric complexity is introduced as a benchmark.Comment: Accepted at ECCV 2022; 25 pages (14 main paper + References + 7 Appendix