Follow
QiZhi He
Title
Cited by
Cited by
Year
Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport
QZ He, D Barajas-Solano, G Tartakovsky, AM Tartakovsky
Advances in Water Resources 141, 103610, 2020
2312020
An adaptive refinement approach for topology optimization based on separated density field description
Y Wang, Z Kang, Q He
Computers & Structures 117, 10-22, 2013
862013
A physics-constrained data-driven approach based on locally convex reconstruction for noisy database
Q He, JS Chen
Computer Methods in Applied Mechanics and Engineering 363, 112791, 2020
752020
Adaptive topology optimization with independent error control for separated displacement and density fields
Y Wang, Z Kang, Q He
Computers & Structures 135, 50-61, 2014
752014
Physics‐Informed Neural Network Method for Forward and Backward Advection‐Dispersion Equations
QZ He, AM Tartakovsky
Water Resources Research 57 (7), e2020WR029479, 2021
652021
A topology optimization method for geometrically nonlinear structures with meshless analysis and independent density field interpolation
Q He, Z Kang, Y Wang
Computational Mechanics 54, 629-644, 2014
592014
Deep autoencoders for physics-constrained data-driven nonlinear materials modeling
X He, Q He, JS Chen
Computer Methods in Applied Mechanics and Engineering 385, 114034, 2021
512021
Manifold learning based data-driven modeling for soft biological tissues
Q He, DW Laurence, CH Lee, JS Chen
Journal of Biomechanics 117, 110124, 2021
352021
Multi-scale modelling of sandwich structures using hierarchical kinematics
QZ He, H Hu, S Belouettar, G Guinta, K Yu, Y Liu, F Biscani, E Carrera, ...
Composite structures 93 (9), 2375-2383, 2011
352011
Physics-constrained deep neural network method for estimating parameters in a redox flow battery
QZ He, P Stinis, AM Tartakovsky
Journal of Power Sources 528, 231147, 2022
252022
Microstructural analysis of skeletal muscle force generation during aging
Y Zhang, JS Chen, Q He, X He, RR Basava, J Hodgson, U Sinha, S Sinha
International Journal for Numerical Methods in Biomedical Engineering, 2019
252019
Physics-informed machine learning with conditional Karhunen-Loève expansions
AM Tartakovsky, DA Barajas-Solano, Q He
Journal of Computational Physics 426, 109904, 2021
232021
Physics‐Informed Neural Networks of the Saint‐Venant Equations for Downscaling a Large‐Scale River Model
D Feng, Z Tan, QZ He
Water Resources Research 59 (2), e2022WR033168, 2023
192023
A Feature-Encoded Physics-Informed Parameter Identification Neural Network for Musculoskeletal Systems
K Taneja, X He, Q He, X Zhao, YA Lin, KJ Loh, JS Chen
Journal of Biomechanical Engineering 144 (12), 121006, 2022
132022
A hyper-reduction computational method for accelerated modeling of thermal cycling-induced plastic deformations
S Kaneko, H Wei, Q He, JS Chen, S Yoshimura
Journal of the Mechanics and Physics of Solids 151, 104385, 2021
132021
Physics-constrained local convexity data-driven modeling of anisotropic nonlinear elastic solids
X He, Q He, JS Chen, U Sinha, S Sinha
Data-Centric Engineering 1, e19, 2020
122020
Analysis of hot cracking during lap joint laser welding processes using the melting state-based thermomechanical modeling approach
Q He, H Wei, JS Chen, HP Wang, BE Carlson
The International Journal of Advanced Manufacturing Technology 94, 4373-4386, 2018
122018
Modeling density-driven flow in porous media by physics-informed neural networks for CO2 sequestration
H Du, Z Zhao, H Cheng, J Yan, QZ He
Computers and Geotechnics 159, 105433, 2023
112023
Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery
QZ He, Y Fu, P Stinis, A Tartakovsky
Journal of Power Sources, 2022
112022
Improved training of physics-informed neural networks for parabolic differential equations with sharply perturbed initial conditions
Y Zong, QZ He, AM Tartakovsky
Computer Methods in Applied Mechanics and Engineering 414, 116125, 2023
102023
The system can't perform the operation now. Try again later.
Articles 1–20