arXiv subjects

Yunxiao Yan

Publications and source records attributed to Yunxiao Yan.

2 recordsLinked to original sources

arXiv2026

Assessment of turbulent fire dynamics and combustion instabilities using a flamelet model

The Sandia one-meter methane fire plume is an established benchmark for turbulent combustion modeling of large-scale flames. This study investigates the combustion instabilities formed close to the base of the Sandia fire plume. Finite rate chemistry and differential diffusion are considered using a flamelet/progress variable (FPV) approach. The performance of the FPV approach is assessed by comparing with the eddy dissipation model (EDM) and the experimental data for the large-scale fire plume via large eddy simulations (LES). The effects of radiation modeling and mesh resolution on the predictive capability of the model are systematically investigated by comparing the axial and radical velocities against the experimental data at various locations. Although all models successfully capture the primary flow characteristics of fire plumes, the FPV model with differential diffusion yields improved predictions in the near-flame-base region. The formation mechanism of cellular flow structures near the flame base is investigated via a budget analysis of the vorticity equation, and the type of instability governing the formation of the cellular structure is clarified. Finally, the individual effects of finite rate chemistry and differential diffusion on the prediction of the thermo-chemical quantities are quantified. Overall, this study explains the underlying physics governing combustion instabilities at the base of turbulent fire plumes, provides novel insights into the performance of flamelet models for LES of gaseous pool fires, and offers reliable guidance for the high-fidelity numerical simulation of large-scale turbulent buoyancy driven flames.

physics.flu-dyn↗

arXiv2026

ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation

Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their empirical progress remains constrained by the absence of evaluation protocols that are both physically realistic and diagnostically controlled. Simulator-centric benchmarks provide scale and reproducibility, but cannot fully capture the reality gap induced by perception noise, contact dynamics, latency, calibration error, and hardware constraints. Conversely, real-robot evaluations are often fragmented across platforms, scenes, objects, and scoring rules, making fair comparison and failure attribution difficult. We introduce ManipArena, a standardized real-robot evaluation framework for studying manipulation generalization under matched physical conditions. ManipArena comprises 20 tasks, 10,812 expert trajectories, 13.5M frames, and approximately 188 robot hours across tabletop and mobile manipulation. The framework combines schema-defined task variation, stratified in-domain, visualshift, and semantic-OOD trials, subtask-level partial-credit scoring, three-level language annotations, low-level motor signals, and paired real-to-sim environments reconstructed from physical scenes. Using ManipArena, we evaluate seven tabletop configurations spanning VLA and world-action-model policies. The results show that real-robot conclusions depend not only on architecture, but also on model provenance, fine-tuning regime, data sampling, and annotation granularity. ManipArena thus provides a reproducible and interpretable foundation for diagnosing capability boundaries and failure modes in embodied generalization.

cs.RO↗