Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Zhang, Enrui"'
Autor:
Zou, Zongren, Kahana, Adar, Zhang, Enrui, Turkel, Eli, Ranade, Rishikesh, Pathak, Jay, Karniadakis, George Em
We extend a recently proposed machine-learning-based iterative solver, i.e. the hybrid iterative transferable solver (HINTS), to solve the scattering problem described by the Helmholtz equation in an exterior domain with a complex absorbing boundary
Externí odkaz:
http://arxiv.org/abs/2405.12380
Autor:
Jin, Hanxun, Zhang, Enrui, Zhang, Boyu, Krishnaswamy, Sridhar, Karniadakis, George Em, Espinosa, Horacio D.
Machine learning (ML) is emerging as a transformative tool for the design of architected materials, offering properties that far surpass those achievable through lab-based trial-and-error methods. However, a major challenge in current inverse design
Externí odkaz:
http://arxiv.org/abs/2311.13812
Autor:
Yin, Minglang, Zou, Zongren, Zhang, Enrui, Cavinato, Cristina, Humphrey, Jay D., Karniadakis, George Em
Quantifying biomechanical properties of the human vasculature could deepen our understanding of cardiovascular diseases. Standard nonlinear regression in constitutive modeling requires considerable high-quality data and an explicit form of the consti
Externí odkaz:
http://arxiv.org/abs/2305.03184
Publikováno v:
Appl. Mech. Rev., 2023, 75(6), 061001
For many decades, experimental solid mechanics has played a crucial role in characterizing and understanding the mechanical properties of natural and novel materials. Recent advances in machine learning (ML) provide new opportunities for the field, i
Externí odkaz:
http://arxiv.org/abs/2303.07647
Autor:
Kahana, Adar, Zhang, Enrui, Goswami, Somdatta, Karniadakis, George EM, Ranade, Rishikesh, Pathak, Jay
The discovery of fast numerical solvers prompted a clear and rapid shift towards iterative techniques in many applications, especially in computational mechanics, due to the increased necessity for solving very large linear systems. Most numerical so
Externí odkaz:
http://arxiv.org/abs/2210.17392
Autor:
Zhang, Enrui, Kahana, Adar, Kopaničáková, Alena, Turkel, Eli, Ranade, Rishikesh, Pathak, Jay, Karniadakis, George Em
Neural networks suffer from spectral bias having difficulty in representing the high frequency components of a function while relaxation methods can resolve high frequencies efficiently but stall at moderate to low frequencies. We exploit the weaknes
Externí odkaz:
http://arxiv.org/abs/2208.13273
Many genetic mutations adversely affect the structure and function of load-bearing soft tissues, with clinical sequelae often responsible for disability or death. Parallel advances in genetics and histomechanical characterization provide significant
Externí odkaz:
http://arxiv.org/abs/2208.09889
Multiscale modeling is an effective approach for investigating multiphysics systems with largely disparate size features, where models with different resolutions or heterogeneous descriptions are coupled together for predicting the system's response.
Externí odkaz:
http://arxiv.org/abs/2203.00003
Publikováno v:
In IJC Heart & Vasculature December 2024 55
Autor:
Yin, Minglang, Ban, Ehsan, Rego, Bruno V., Zhang, Enrui, Cavinato, Cristina, Humphrey, Jay D., Karniadakis, George Em
Aortic dissection progresses via delamination of the medial layer of the wall. Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro and in silico the progression of dissection driven by quasi-static pressuriza
Externí odkaz:
http://arxiv.org/abs/2108.11985