Thermal rarefied gas flow simulations with moving boundaries based on discrete unified gas kinetic scheme and immersed boundary method
Rarefied gas flows in complex geometries with heat transfer and moving boundaries have
received remarkable attention due to the prevailing of micro/nano science and engineering …
received remarkable attention due to the prevailing of micro/nano science and engineering …
Multibranch semantic image segmentation model based on edge optimization and category perception
Z Yang, Z Cao, J Cao, Z Chen, C Peng - PloS one, 2024 - journals.plos.org
In semantic image segmentation tasks, most methods fail to fully use the characteristics of
different scales and levels but rather directly perform upsampling. This may cause some …
different scales and levels but rather directly perform upsampling. This may cause some …
AP-MIONet: Asymptotic-preserving multiple-input neural operators for capturing the high-field limits of collisional kinetic equations
T Zhang, S Jin - arXiv preprint arXiv:2407.14921, 2024 - arxiv.org
In kinetic equations, external fields play a significant role, particularly when their strength is
sufficient to balance collision effects, leading to the so-called high-field regime. Two typical …
sufficient to balance collision effects, leading to the so-called high-field regime. Two typical …
Neural equilibria for long-term prediction of nonlinear conservation laws
We introduce Neural Discrete Equilibrium (NeurDE), a machine learning (ML) approach for
long-term forecasting of flow phenomena that relies on a" lifting" of physical conservation …
long-term forecasting of flow phenomena that relies on a" lifting" of physical conservation …
APTT: An accuracy-preserved tensor-train method for the Boltzmann-BGK equation
Solving the Boltzmann-BGK equation with traditional numerical methods suffers from high
computational and memory costs due to the curse of dimensionality. In this paper, we …
computational and memory costs due to the curse of dimensionality. In this paper, we …
Separable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation
In this study, we introduce a method based on Separable Physics-Informed Neural Networks
(SPINNs) for effectively solving the BGK model of the Boltzmann equation. While the mesh …
(SPINNs) for effectively solving the BGK model of the Boltzmann equation. While the mesh …
A Micro-Macro Decomposition-Based Asymptotic-Preserving Random Feature Method for Multiscale Radiative Transfer Equations
J Chen, Z Ma, K Wu - arXiv preprint arXiv:2411.04643, 2024 - arxiv.org
This paper introduces the Asymptotic-Preserving Random Feature Method (APRFM) for the
efficient resolution of multiscale radiative transfer equations. The APRFM effectively …
efficient resolution of multiscale radiative transfer equations. The APRFM effectively …
Learning-based Multi-continuum Model for Multiscale Flow Problems
F Wang, Y Wang, WT Leung, Z Xu - arXiv preprint arXiv:2403.14084, 2024 - arxiv.org
Multiscale problems can usually be approximated through numerical homogenization by an
equation with some effective parameters that can capture the macroscopic behavior of the …
equation with some effective parameters that can capture the macroscopic behavior of the …
[HTML][HTML] Artificial intelligence and machine learning in aerodynamics
With the increasing availability of flow data from simulation and experiment, artificial
intelligence and machine learning are revolutionizing the research paradigm in …
intelligence and machine learning are revolutionizing the research paradigm in …