Παρακολούθηση
Luning Sun
Luning Sun
Lawrence Livermore National Lab
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα alumni.nd.edu
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
L Sun, H Gao, S Pan, JX Wang
Computer Methods in Applied Mechanics and Engineering 361, 112732, 2020
8402020
PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain
H Gao, L Sun, JX Wang
Journal of Computational Physics 428, 110079, 2021
5152021
Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels
H Gao, L Sun, JX Wang
Physics of Fluids 33 (7), 2021
1982021
Physics-constrained bayesian neural network for fluid flow reconstruction with sparse and noisy data
L Sun, JX Wang
Theoretical and Applied Mechanics Letters 10 (3), 161-169, 2020
1852020
Machine learning-assisted exploration of thermally conductive polymers based on high-throughput molecular dynamics simulations
R Ma, H Zhang, J Xu, L Sun, Y Hayashi, R Yoshida, J Shiomi, J Wang, ...
Materials Today Physics 28, 100850, 2022
352022
An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions
E Adeli, L Sun, J Wang, AA Taflanidis
Neural Computing and Applications 35 (26), 18971-18987, 2023
152023
Bayesian conditional diffusion models for versatile spatiotemporal turbulence generation
H Gao, X Han, X Fan, L Sun, LP Liu, L Duan, JX Wang
Computer Methods in Applied Mechanics and Engineering 427, 117023, 2024
112024
Bayesian spline learning for equation discovery of nonlinear dynamics with quantified uncertainty
L Sun, D Huang, H Sun, JX Wang
Advances in neural information processing systems 35, 6927-6940, 2022
102022
Unifying predictions of deterministic and stochastic physics in mesh-reduced space with sequential flow generative model
L Sun, X Han, H Gao, JX Wang, L Liu
Advances in Neural Information Processing Systems 36, 2024
92024
A deep learning-based generalized empirical flow model of glottal flow during normal phonation
Y Zhang, W Jiang, L Sun, J Wang, X Zheng, Q Xue
Journal of Biomechanical Engineering 144 (9), 091001, 2022
7*2022
Scientific Machine Learning for Modeling and Discovery of Physical Systems with Quantified Uncertainty
L Sun
University of Notre Dame, 2023
2023
Probabilistic surrogate modeling of unsteady fluid dynamics using deep graph normalizing flows
L Sun, JX Wang
Bulletin of the American Physical Society 67, 2022
2022
Group sparse Bayesian learning for data-driven discovery of explicit model forms with multiple parametric datasets
L Sun, P Du, H Sun, JX Wang
Numerical Algebra, Control and Optimization, 2022
2022
Physics-constrained multi-fidelity convolutional neural networks for surrogate fluid modeling
L Sun, JX Wang
APS Division of Fluid Dynamics Meeting Abstracts, R10. 002, 2020
2020
Super-resolution and Denoising of Fluid Flows Using Physics-informed Convolutional Neural Networks
JX Wang, H Gao, L Sun
APS Division of Fluid Dynamics Meeting Abstracts, R01. 011, 2020
2020
Super-resolution and Denoising of Flow MRI Data using Physics-Constrained Deep Learning
L Sun, JX Wang
APS Division of Fluid Dynamics Meeting Abstracts, C30. 005, 2019
2019
Surrogate Modeling for Fluid Flows Using Physics-Constrained, Label-Free Deep Learning
JX Wang, L Sun, H Gao, S Pan
APS Division of Fluid Dynamics Meeting Abstracts, H41. 009, 2019
2019
NUMERICAL SIMULATION OF IRREGULAR WAVES RUNUP ON A BEACH
L Sun, A Kennedy
Coastal Engineering Proceedings, 41-41, 2018
2018
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