arXiv subjects

Zhuoran Zeng

Publications and source records attributed to Zhuoran Zeng.

3 recordsLinked to original sources

arXiv2026

Atomic-Scale Insights into Solute Drag Effects on Grain Boundary Motion in Mg-Al and Mg-Ca Alloys

The slip behavior of dislocations and grain boundaries critically governs recrystallization and plastic deformation in Mg alloys and can be strongly influenced by solutes. However, the quantitative effects of solute distribution on defect mobility remain unclear. Using molecular dynamics and Monte Carlo simulations, we systematically investigate how Al and Ca solutes affect the motion of dislocations, low-angle grain boundaries (LAGBs), and high-angle grain boundaries (HAGBs) in Mg. Within the idealized framework of random solid-solution, solute drag is dominated by elastic interactions arising from atomic size mismatch, resulting in a stronger resistance from Ca than from Al. In contrast, under the more realistic condition where solute segregation occurs, the dominant mechanism shifts to chemically driven pinning, whose effectiveness is governed by the attainable segregation density. Owing to strong Ca-Ca repulsion, Al achieves substantially higher segregation concentrations than Ca and therefore exerts much stronger pinning effects. Notably, solute-induced retardation is significantly more pronounced for HAGBs than for LAGBs, leading to amplified solute effects during the late stages of recrystallization, where grain growth is controlled primarily by HAGB migration. These results provide atomic-scale insight into experimentally observed grain refinement in Mg alloys.

cond-mat.mtrl-sci↗

arXiv2022

High Efficiency Pedestrian Crossing Prediction

Predicting pedestrian crossing intention is an indispensable aspect of deploying advanced driving systems (ADS) or advanced driver-assistance systems (ADAS) to real life. State-of-the-art methods in predicting pedestrian crossing intention often rely on multiple streams of information as inputs, each of which requires massive computational resources and heavy network architectures to generate. However, such reliance limits the practical application of the systems. In this paper, driven the the real-world demands of pedestrian crossing intention prediction models with both high efficiency and accuracy, we introduce a network with only frames of pedestrians as the input. Every component in the introduced network is driven by the goal of light weight. Specifically, we reduce the multi-source input dependency and employ light neural networks that are tailored for mobile devices. These smaller neural networks can fit into computer memory and can be transmitted over a computer network more easily, thus making them more suitable for real-life deployment and real-time prediction. To compensate the removal of the multi-source input, we enhance the network effectiveness by adopting a multi-task learning training, named "side task learning", to include multiple auxiliary tasks to jointly learn the feature extractor for improved robustness. Each head handles a specific task that potentially shares knowledge with other heads. In the meantime, the feature extractor is shared across all tasks to ensure the sharing of basic knowledge across all layers. The light weight but high efficiency characteristics of our model endow it the potential of being deployed on vehicle-based systems. Experiments validate that our model consistently delivers outstanding performances.

cs.CV↗

arXiv2022

Physical Reasoning in an Open World

Most work on physical reasoning, both in artificial intelligence and in cognitive science, has focused on closed-world reasoning, in which it is assumed that the problem specification specifies all relevant objects and substance, all their relations in an initial situation, and all exogenous events. However, in many situations, it is important to do open-world reasoning; that is, making valid conclusions from very incomplete information. We have implemented in Prolog an open-world reasoner for a toy microworld of containers that can be loaded, unloaded, sealed, unsealed, carried, and dumped.

cs.AI↗