Investigation into gas production from natural gas hydrate: A review

XS Li, CG Xu, Y Zhang, XK Ruan, G Li, Y Wang - Applied Energy, 2016 - Elsevier
Natural gas hydrates (NGHs), which extensively exist in sea-floor and permafrost regions,
are considered as an alternative energy in the future for the fossil fuels approaching …

[PDF][PDF] Metal hyperaccumulation in plants: a review focusing on phytoremediation technology

H Sarma - Journal of Environmental Science and Technology, 2011 - researchgate.net
A ISTRA ("|" Metal hyperaccumulation is a characteristic present in over 500 plant species
and approximately in 0.2% of all angiosperms. Hyperaccumulators are model plants for …

Physics‐informed deep neural networks for learning parameters and constitutive relationships in subsurface flow problems

AM Tartakovsky, CO Marrero… - Water Resources …, 2020 - Wiley Online Library
We present a physics‐informed deep neural network (DNN) method for estimating hydraulic
conductivity in saturated and unsaturated flows governed by Darcy's law. For saturated flow …

Adversarial uncertainty quantification in physics-informed neural networks

Y Yang, P Perdikaris - Journal of Computational Physics, 2019 - Elsevier
We present a deep learning framework for quantifying and propagating uncertainty in
systems governed by non-linear differential equations using physics-informed neural …

Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport

QZ He, D Barajas-Solano, G Tartakovsky… - Advances in Water …, 2020 - Elsevier
Data assimilation for parameter and state estimation in subsurface transport problems
remains a significant challenge because of the sparsity of measurements, the heterogeneity …

Physics‐informed neural network method for forward and backward advection‐dispersion equations

QZ He, AM Tartakovsky - Water Resources Research, 2021 - Wiley Online Library
We propose a discretization‐free approach based on the physics‐informed neural network
(PINN) method for solving the coupled advection‐dispersion equation (ADE) and Darcy flow …

Learning parameters and constitutive relationships with physics informed deep neural networks

AM Tartakovsky, CO Marrero, P Perdikaris… - arXiv preprint arXiv …, 2018 - arxiv.org
We present a physics informed deep neural network (DNN) method for estimating
parameters and unknown physics (constitutive relationships) in partial differential equation …

Multiphase flow and transport modeling in heterogeneous porous media: challenges and approaches

CT Miller, G Christakos, PT Imhoff, JF McBride… - Advances in Water …, 1998 - Elsevier
We review the current status of modeling multiphase systems, including balance equation
formulation, constitutive relations for both pressure-saturation-conductivity and interphase …

Modelling the fate of oxidisable organic contaminants in groundwater

DA Barry, H Prommer, CT Miller, P Engesgaard… - Advances in Water …, 2002 - Elsevier
Subsurface contamination by organic chemicals is a pervasive environmental problem,
susceptible to remediation by natural or enhanced attenuation approaches or more highly …

[图书][B] Vadose zone processes

JS Selker, JT McCord, CK Keller - 1999 - books.google.com
Vadose Zone Processes provides a unified, up-to-date treatment on the movement of water
through unsaturated media. In addition to covering the basic equations governing the flow …