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Shriram Srinivasan
Shriram Srinivasan
Applied Mathematics and Plasma Physics Group, Theoretical Division, Los Alamos National
Verified email at lanl.gov - Homepage
Title
Cited by
Cited by
Year
A thermodynamic basis for the derivation of the Darcy, Forchheimer and Brinkman models for flows through porous media and their generalizations
S Srinivasan, KR Rajagopal
International Journal of Non-Linear Mechanics 58, 162-166, 2014
592014
Identifying Backbones in Three-Dimensional Discrete Fracture Networks: A Bipartite Graph-Based Approach
JD Hyman, A Hagberg, D Osthus, S Srinivasan, H Viswanathan, ...
Multiscale Modeling & Simulation 16 (4), 1948-1968, 2018
462018
Advancing Graph‐Based Algorithms for Predicting Flow and Transport in Fractured Rock
HS Viswanathan, JD Hyman, S Karra, D O'Malley, S Srinivasan, ...
Water Resources Research 54 (9), 6085-6099, 2018
432018
Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways
S Srinivasan, S Karra, J Hyman, H Viswanathan, G Srinivasan
Computational Geosciences 23 (3), 617-629, 2019
402019
Flow of a fluid through a porous solid due to high pressure gradients
S Srinivasan, A Bonito, KR Rajagopal
Journal of Porous Media 16 (3), 2013
402013
Matrix Diffusion in Fractured Media: New Insights Into Power Law Scaling of Breakthrough Curves
JD Hyman, H Rajaram, S Srinivasan, N Makedonska, S Karra, ...
Geophysical Research Letters 46 (23), 13785-13795, 2019
392019
Study of a variant of Stokes’ first and second problems for fluids with pressure dependent viscosities
S Srinivasan, KR Rajagopal
International Journal of Engineering Science 47 (11-12), 1357-1366, 2009
362009
A machine learning framework for rapid forecasting and history matching in unconventional reservoirs
S Srinivasan, D O’Malley, MK Mudunuru, MR Sweeney, JD Hyman, ...
Scientific Reports 11 (1), 21730, 2021
302021
Role of pressure dependent viscosity in measurements with falling cylinder viscometer
V Průša, S Srinivasan, KR Rajagopal
International Journal of Non-Linear Mechanics 47 (7), 743-750, 2012
262012
Towards real-time forecasting of natural gas production by harnessing graph theory for stochastic discrete fracture networks
S Dana, S Srinivasan, S Karra, N Makedonska, JD Hyman, D O'Malley, ...
Journal of Petroleum Science and Engineering 195, 107791, 2020
252020
Physics-informed machine learning for real-time unconventional reservoir management
MK Mudunuru, D O’Malley, S Srinivasan, JD Hyman, MR Sweeney, ...
CEUR Workshop Proceedings, 1-10, 2020
24*2020
Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics
S Srinivasan, J Hyman, S Karra, D O’Malley, H Viswanathan, ...
Computational Geosciences 22, 1515-1526, 2018
202018
Operation of natural gas pipeline networks with storage under transient flow conditions
SKK Hari, K Sundar, S Srinivasan, A Zlotnik, R Bent
IEEE Transactions on Control Systems Technology 30 (2), 667-679, 2021
192021
Physics-informed machine learning for backbone identification in discrete fracture networks
S Srinivasan, E Cawi, J Hyman, D Osthus, A Hagberg, H Viswanathan, ...
Computational Geosciences 24, 1429-1444, 2020
162020
On the flow of fluids through inhomogeneous porous media due to high pressure gradients
S Srinivasan, KR Rajagopal
International Journal of Non-Linear Mechanics 78, 112-120, 2016
162016
FLOW OF FLUIDS THROUGH POROUS MEDIA DUE TO HIGH PRESSURE GRADIENTS: PART 2− UNSTEADY FLOWS
KR Rajagopal, S Srinivasan
Journal of Porous Media 17 (9), 2014
162014
Flow of “stress power-law” fluids between parallel rotating discs with distinct axes
S Srinivasan, S Karra
International Journal of Non-Linear Mechanics 74, 73-83, 2015
132015
Extracting Hydrocarbon From Shale: An Investigation of the Factors That Influence the Decline and the Tail of the Production Curve
AE Lovell, S Srinivasan, S Karra, D O'Malley, N Makedonska, ...
Water Resources Research 54 (5), 3748-3757, 2018
122018
A note on the flow of a fluid with pressure-dependent viscosity in the annulus of two infinitely long coaxial cylinders
S Srinivasan, KR Rajagopal
Applied Mathematical Modelling 34 (11), 3255-3263, 2010
112010
A physics-informed machine learning workflow to forecast production in a fractured Marcellus shale reservoir
MR Gross, JD Hyman, S Srinivasan, D O’Malley, S Karra, MK Mudunuru, ...
Unconventional Resources Technology Conference, 26–28 July 2021, 3641-3648, 2021
102021
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