Abstract：
:We employ physics-informed neural networks (PINNs) to infer properties of biological materials using synthetic data. In particular, we successfully apply PINNs on inferring permeability and viscoelastic modulus from thrombus deformation data, which can be described by the fourth-order Cahn-Hilliard and Navier-Stokes Equations. In PINNs, the partial differential equations are encoded into a loss function, where partial derivatives can be obtained through automatic differentiation (AD). In addition to tackling the challenge of calculating the fourth-order derivative in the Cahn-Hilliard equation with AD, we introduce an auxiliary network along with the main neural network to approximate the second-derivative of the energy potential term. Our model can simultaneously predict unknown material parameters and velocity, pressure, and deformation gradient fields by merely training with partial information among all data, i.e., phase field and pressure measurements, while remaining highly flexible in sampling within the spatio-temporal domain for data acquisition. We validate our model by numerical solutions from the spectral/hp element method (SEM) and demonstrate its robustness by training it with noisy measurements. Our results show that PINNs can infer the material properties from noisy synthetic data, and thus they have great potential for inferring these properties from experimental multi-modality and multi-fidelity data.
journal_name
Comput Methods Appl Mech Engjournal_title
Computer methods in applied mechanics and engineeringauthors
Yin M,Zheng X,Humphrey JD,Em Karniadakis Gdoi
10.1016/j.cma.2020.113603keywords:
["Computational Fluids Dynamics","Inverse Problem","Phase Field Model","Physics-informed Neural Networks","Viscoelastic Porous Material"]subject
Has Abstractpub_date
2021-03-01 00:00:00eissn
0045-7825issn
1879-2138journal_volume
375pub_type
杂志文章相关文献
文献大全abstract：:The transcatheter aortic valve replacement (TAVR) has emerged as a minimally invasive alternative to surgical treatments of valvular heart disease. TAVR offers many advantages, however, the safe anchoring of the transcatheter heart valve (THV) in the patients anatomy is key to a successful procedure. In this paper, we...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2019.07.025
更新日期：2019-12-01 00:00:00
abstract：:This article presents a formulation that extends the multiscale modelling for compressible large-eddy simulation to a vast family of compact nodal numerical methods represented by the high-order flux reconstruction scheme. The theoretical aspects of the proposed formulation are laid down via mathematical derivations w...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2020.112885
更新日期：2020-05-01 00:00:00
abstract：:This study uses a recently developed phase-field approach to model fracture of arterial walls with an emphasis on aortic tissues. We start by deriving the regularized crack surface to overcome complexities inherent in sharp crack discontinuities, thereby relaxing the acute crack surface topology into a diffusive one. ...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2016.04.007
更新日期：2016-12-01 00:00:00
abstract：:We present a constitutive modeling framework for contractile cardiac mechanics by formulating a single variational principle from which incremental stress-strain relations and kinetic rate equations for active contraction and relaxation can all be derived. The variational framework seamlessly incorporates the hyperela...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2016.09.022
更新日期：2017-02-01 00:00:00
abstract：:This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of insp...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2012.01.015
更新日期：2012-05-01 00:00:00
abstract：:We describe an approach to construct hexahedral solid NURBS (Non-Uniform Rational B-Splines) meshes for patient-specific vascular geometric models from imaging data for use in isogeometric analysis. First, image processing techniques, such as contrast enhancement, filtering, classification, and segmentation, are used ...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2007.02.009
更新日期：2007-05-15 00:00:00
abstract：:The vasculature consists of a complex network of vessels ranging from large arteries to arterioles, capillaries, venules, and veins. This network is vital for the supply of oxygen and nutrients to tissues and the removal of carbon dioxide and waste products from tissues. Because of its primary role as a pressure-drive...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2009.02.004
更新日期：2009-09-15 00:00:00
abstract：:Many researchers have proposed the use of biomechanical models for high accuracy soft organ non-rigid image registration, but one main problem in using comprehensive models is the long computation time required to obtain the solution. In this paper we propose to use the Total Lagrangian formulation of the Finite Eleme...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2009.06.012
更新日期：2009-09-01 00:00:00
abstract：:We propose a high dimensional Bayesian inference framework for learning heterogeneous dynamics of a COVID-19 model, with a specific application to the dynamics and severity of COVID-19 inside and outside long-term care (LTC) facilities. We develop a heterogeneous compartmental model that accounts for the heterogeneity...
journal_title：Computer methods in applied mechanics and engineering
pub_type： 杂志文章
doi：10.1016/j.cma.2021.114020
更新日期：2021-11-01 00:00:00
