arXiv subjects

S. Wei

Publications and source records attributed to S. Wei.

5 recordsLinked to original sources

arXiv2025

How Do Water Filled Traffic Barriers Shake a Suspension Bridge?

The present study stems from the realization that the general problem relating to the analysis of wind-induced vibrations in suspension bridges still requires significant attention. Sidewalk railings, overhaul tracks, and deflectors are known to largely affect such dynamics. Here, the influence of a row of water-filled traffic barriers on the response of a sample suspension bridge is investigated numerically. It is shown that the existence of water barriers causes flow separation and non-negligible vortices with respect to the condition with no water barriers. The vortex shedding frequency at the far end is around 41.30 Hz, relatively close to the real vibration frequency. It is also shown how different incoming angles of attack can change the flow field around the bridge cross-section and the vortex detachment frequency.

physics.flu-dyn↗

arXiv2025

Bridging the Atmospheric Circulations of Hot and Warm Giant Exoplanets

We perform high-resolution atmospheric flow simulations of hot and warm giant exoplanets that are tidally locked. The modeled atmospheres are representative of those on KELT-11b and WASP-39b, which possess markedly different equilibrium temperatures but reside in a similar dynamical regime: in this regime, their key dynamical numbers (e.g., Rossby and Froude numbers) are comparable. Despite their temperature difference, both planets exhibit qualitatively similar atmospheric circulation patterns, which are characterized by turbulent equatorial flows, anticyclonic polar vortices, and large-scale Rossby waves that gives rise to quasi-zonal flows in the extra-tropics (i.e., near ~20 degrees). Quantitative differences between the KELT-11b and WASP-39b atmospheres reflect their different Rossby deformation scales, which influence the horizontal length scale of wave--vortex interactions and the overall structure of the circulation.

astro-ph.EP↗

arXiv2021

Machine-Learning Enabled Search for The Next-Generation Catalyst for Hydrogen Evolution Reaction

The development of active catalysts for hydrogen evolution reaction (HER) made from low-cost materials constitutes a crucial challenge in the utilization of hydrogen energy. Earth-abundant molybdenum disulfide (MoS$_2$) has been discovered recently with good activity and stability for HER. In this report, we employed the hydrothermal technique for MoS$_2$ synthesis which is a cost-effective and environmentally friendly approach and has the potential for future mass production. To investigate the structure-property relationship, scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and various electrochemical characterizations have been conducted. A strong correlation between the material structure and the HER performance has been observed. Moreover, machine-learning (ML) techniques were built and subsequently used within a Bayesian Optimization framework to validate the optimal parameter combinations for synthesizing high-quality MoS$_2$ catalyst within the limited parameter space. The model will be able to guide the wet chemical synthesis of MoS$_2$ and produce the most effective HER catalyst eventually.

cond-mat.mtrl-sci↗

arXiv2021

Breaking Barriers in Robotic Soft Tissue Surgery: Conditional Autonomous Intestinal Anastomosis

Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeons skill and experience. Autonomous soft-tissue surgery in unstructured and deformable environments is especially challenging as it necessitates intricate imaging, tissue tracking and surgical planning techniques, as well as a precise execution via highly adaptable control strategies. In the laparoscopic setting, soft-tissue surgery is even more challenging due to the need for high maneuverability and repeatability under motion and vision constraints. We demonstrate the first robotic laparoscopic soft tissue surgery with a level of autonomy of 3 out of 5, which allows the operator to select among autonomously generated surgical plans while the robot executes a wide range of tasks independently. We also demonstrate the first in vivo autonomous robotic laparoscopic surgery via intestinal anastomosis on porcine models. We compared the criteria including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure between the developed system, manual laparoscopic surgery, and robot-assisted surgery (RAS). The ex vivo results indicate that our system outperforms expert surgeons and RAS techniques in terms of consistency and accuracy, and it leads to a remarkable anastomosis quality in living pigs. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.

cs.RO↗

arXiv2016

Classifying Unrooted Gaussian Trees under Privacy Constraints

In this work, our objective is to find out how topological and algebraic properties of unrooted Gaussian tree models determine their security robustness, which is measured by our proposed max-min information (MaMI) metric. Such metric quantifies the amount of common randomness extractable through public discussion between two legitimate nodes under an eavesdropper attack. We show some general topological properties that the desired max-min solutions shall satisfy. Under such properties, we develop conditions under which comparable trees are put together to form partially ordered sets (posets). Each poset contains the most favorable structure as the poset leader, and the least favorable structure. Then, we compute the Tutte-like polynomial for each tree in a poset in order to assign a polynomial to any tree in a poset. Moreover, we propose a novel method, based on restricted integer partitions, to effectively enumerate all poset leaders. The results not only help us understand the security strength of different Gaussian trees, which is critical when we evaluate the information leakage issues for various jointly Gaussian distributed measurements in networks, but also provide us both an algebraic and a topological perspective in grasping some fundamental properties of such models.

cs.IT↗