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Satish Karra

Pacific Northwest National Laboratory · US
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Area of research
Mechanical Engineering · Environmental Engineering
Research interest
Research interests include Geology, Computer science, Geothermal gradient, Fracture (geology), Fluid dynamics, and Radioactive waste.
h-index
citations
433
works
4
NIH funding
primary concept
email

Recent publications

The FluidFlower Validation Benchmark Study for the Storage of CO$$_2$$
Transport in Porous Media 2023cited by 53position: middledoi
From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers
Reviews of Geophysics 2022cited by 276position: middledoi
N. Ray, T. Banerjee, B. Nadiga, and S. Karra. "On the viability of quantum annealers to solve fluid flows."  Frontiers in Mechanical Engineering , 8, 2022
2022cited by 0position: selected
H. S. Viswanathan, J. Ajo-Franklin, J. Birkholzer, J. W. Carey, Y. Guglielmi, J. Hyman, S. Karra, L. Pyrak-Nolte, H. Rajaram, G. Srinivasan, et al. "From fluid flow to coupled processes in fractured rock: recent advances and new frontiers."  Reviews of Geophysics , page e2021RG000744, 2022 2021
2022cited by 0position: selected
Constraining maximum event magnitude during injection-triggered seismicity
Nature Communications 2021cited by 57position: middledoi
S. Srinivasan, D. O’Malley,M.Mudunuru,M. Sweeney, J. Hyman, S. Karra, L. Frash, J. Carey,M. Gross, G. Guthrie, T. Carr, L. Li, and H. Viswanathan. A machine learning framework for rapid forecasting and history matching in unconventional reservoirs. S cientific Reports , 11(1), 2021
2021cited by 0position: selected
H. Ushijima-Mwesigwa, J. D. Hyman, A. Hagberg, I. Safro, S. Karra, C. W. Gable, M. R. Sweeney, and G. Srinivasan. "Multilevel graph partitioning for three-dimensional discrete fracture network flow simulations."  Mathematical Geosciences , pages 1–26, 2021
2021cited by 0position: selected
Ahmmed, S. Karra, V. V. Vesselinov, and M. K. Mudunuru. "Machine learning to discover mineral trapping signatures due to CO2 injection." International Journal of Greenhouse Gas Control , 109:103382, 2021
2021cited by 0position: selected
Ahmmed, M. Mudunuru, S. Karra, S. James, and V. Vesselinov. "A comparative study of machine learning models for predicting the state of reactive mixing." Journal of Computational Physics , page 110147, 2021
2021cited by 0position: selected
B. Ahmmed, M. K. Mudunuru, S. Karra, S. C. James, H. Viswanathan, and J. A. Dunbar. PFLOTRAN-SIP: A PFLO-TRAN module for simulating spectral-induced polarization of electrical impedance data. Energies, 13(24):6552, 2020
2020cited by 0position: selected
S. Srinivasan, D. O’Malley, J. D. Hyman, S. Karra, H. S. Viswanathan, and G. Srinivasan. Transient flow modeling in fractured media using graphs. Physical Review E, 102:052310, Nov 2020
2020cited by 0position: selected
N. Makedonska, S. Karra, H. S. Viswanathan, and G. Guthrie. Role of interaction between hydraulic and natural fractures on production. Journal of Natural Gas Science and Engineering, 82:103451, 2020
2020cited by 0position: selected
N. Lubbers, A. Agarwal, Y. Chen, S. Son, M.Mehana, Q. Kang, S. Karra, C. Junghans, T. C. Germann, and H. S. Viswanathan. Modeling and scale-bridging using machine learning: nanoconfinement effects in porous media. Scientific Reports, 10(1):1–13, 2020
2020cited by 0position: selected
S. Dana, S. Srinivasan, S. Karra, N. Makedonska, J. D. Hyman, D. O’Malley, H. Viswanathan, and G. Srinivasan. Towards real-time forecasting of natural gas production by harnessing graph theory for stochastic discrete fracture networks. Journal of Petroleum Science and Engineering, 195:107791, 2020
2020cited by 0position: selected
V. Romano, S. Bigi, F. Carnevale, J. D. Hyman, S. Karra, A. J. Valocchi, M. C. Tartarello, and M. Battaglia. Hydraulic characterization of a fault zone from fracture distribution. Journal of Structural Geology, page 104036, 2020
2020cited by 0position: selected
D. Osthus, J. D. Hyman, S. Karra, N. Panda, and G. Srinivasan. A probabilistic clustering approach for identifying primary subnetworks of discrete fracture networks with quantified uncertainty. SIAM/ASA Journal on Uncertainty Quantification, 8(2):573–600, 2020
2020cited by 0position: selected
M. Sweeney, C. Gable, S. Karra, P. Stauffer, R. Pawar, and J. D. Hyman. Upscaled discrete fracture matrix model (UDFM): an octree-refined continuum representation of fractured porous media. Computational Geosciences, 24:293–310, 2020
2020cited by 0position: selected
M. K. Mudunuru, N. Panda, S. Karra, G. Srinivasan, V. T. Chau, E. Rougier, A. Hunter, and H. S. Viswanathan. Surrogate models for estimating failure in brittle and quasi-brittle materials. Applied Sciences, 9(13):2706, 2019
2019cited by 0position: selected
A. Iraola, P. Trinchero, S. Karra, and J. Molinero. Assessing dual continuum method for multicomponent reactive transport. Computers & Geosciences, 130:11–19, 2019
2019cited by 0position: selected
V. Vesselinov, M. Mudunuru, S. Karra, D. O’Malley, and B. Alexandrov. Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing. Journal of Computational Physics, 395:85–104, 2019
2019cited by 0position: selected
S. Srinivasan, S. Karra, J. Hyman, H. Viswanathan, and G. Srinivasan. Model reduction for fractured porous media: a machine learning approach for identifying main flow pathways. Computational Geosciences, 23(3):617–629, 2019
2019cited by 0position: selected
A. Hunter, B. A. Moore, M. Mudunuru, V. Chau, R. Tchoua, C. Nyshadham, S. Karra, D. O’Malley, E. Rougier, H. Viswanathan, et al. Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications. Computational Materials Science, 157:87–98, 2019
2019cited by 0position: selected
S. Rahimi-Aghdam, V.-T. Chau, H. Lee, H. Nguyen, W. Li, S. Karra, E. Rougier, H. Viswanathan, G. Srinivasan, and Z. P. Bažant. Branching of hydraulic cracks enabling permeability of gas or oil shale with closed natural fractures. Proceedings of the National Academy of Sciences, 116(5):1532–1537, 201
2019cited by 0position: selected
Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications
Computational Materials Science 2018cited by 47position: middledoi
S. Srinivasan, J. Hyman, S. Karra, D. O’Malley, H. Viswanathan, and G. Srinivasan. Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics. Computational Geosciences, 22(6):1515–1526, 2018
2018cited by 0position: selected
G. Srinivasan, J. D. Hyman, D. A. Osthus, B. A. Moore, D. O’Malley, S. Karra, E. Rougier, A. A. Hagberg, A. Hunter, and H. S. Viswanathan. Quantifying topological uncertainty in fractured systems using graph theory and machine learning. Scientific Reports, 8(1):11665, 2018
2018cited by 0position: selected
D. R. Harp, J. P. Ortiz, S. Pandey, S. Karra, D. Anderson, C. Bradley, H. Viswanathan, and P. H. Stauffer. Immobile pore-water storage enhancement and retardation of gas transport in fractured rock. Transport in Porous Media, 124(2):369–394, Sep 2018
2018cited by 0position: selected
G. D. Guthrie, R. J. Pawar, J. W. Carey, S. Karra, D. R. Harp, and H. S. Viswanathan. The mechanisms, dynamics, and implications of self-sealing and CO2 resistance in wellbore cements. International Journal of Greenhouse Gas Control, 75:162–179, 2018
2018cited by 0position: selected
S. Karra, D. O’Malley, J. Hyman, H. Viswanathan, and G. Srinivasan. Modeling flow and transport in fracture networks using graphs. Physical Review E, 97(3):033304, 2018
2018cited by 0position: selected
cited by 0position: selecteddoi

Grants

No grants ingested yet.

Frequent collaborators

· 2 papers (2018–2022)G. Srinivasan · University of Massachusetts Amherst2 papers (2018–2022)Daniel M. Tartakovsky · Environmental and Water Resources Engineering1 papers (2022–2022)L. J. Pyrak‐Nolte · Purdue University West Lafayette1 papers (2022–2022)Yves Guglielmi · Lawrence Berkeley National Laboratory1 papers (2022–2022)Maruti Kumar Mudunuru · Pacific Northwest National Laboratory1 papers (2018–2018)Jonathan Ajo‐Franklin · Pacific Northwest National Laboratory1 papers (2022–2022) · 1 papers (2018–2018) · 1 papers (2018–2018)Daniel O’Malley · Purdue University West Lafayette1 papers (2018–2018) · 1 papers (2018–2018)Roselyne Tchoua · DePaul University1 papers (2018–2018)Satish Karra · Pacific Northwest National Laboratory1 papers (None–None)Harihar Rajaram · Johns Hopkins University1 papers (2022–2022)Jens Birkhölzer · University of California, Berkeley1 papers (2022–2022) · 1 papers (2022–2022) · 1 papers (2018–2018)Abigail Hunter · Iowa State University1 papers (2018–2018)Jeffrey D. Hyman · University of Arizona1 papers (2022–2022)
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