Maruti Kumar Mudunuru

According to our database, Maruti Kumar Mudunuru authored at least 22 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems.

N. V. Jagtap, Maruti Kumar Mudunuru, Kalyana B. Nakshatrala

CoRR, 2023

2022

Frost prediction using machine learning and deep neural network models.

Carl J. Talsma, Kurt C. Solander, Maruti Kumar Mudunuru, Brandon Crawford, Michelle R. Powell

Frontiers Artif. Intell., 2022

GeoThermalCloud: Machine Learning for Geothermal Resource Exploration.

Maruti Kumar Mudunuru, Velimir V. Vesselinov, Bulbul Ahmmed

CoRR, 2022

2021

A comparative study of machine learning models for predicting the state of reactive mixing.

B. Ahmmed, Maruti Kumar Mudunuru, Satish Karra, S. C. James, Velimir V. Vesselinov

J. Comput. Phys., 2021

SWAT Watershed Model Calibration using Deep Learning.

Maruti Kumar Mudunuru, K. Son, P. Jiang, X. Chen

CoRR, 2021

AdjointNet: Constraining machine learning models with physics-based codes.

Satish Karra, Bulbul Ahmmed, Maruti Kumar Mudunuru

CoRR, 2021

A deep learning modeling framework to capture mixing patterns in reactive-transport systems.

N. V. Jagtap, Maruti Kumar Mudunuru, K. B. Nakshatrala

CoRR, 2021

2020

Physics-Informed Machine Learning for Real-time Reservoir Management.

Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

2019

Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing.

Velimir V. Vesselinov, Maruti Kumar Mudunuru, Satish Karra, Dan O'Malley, Boian S. Alexandrov

J. Comput. Phys., 2019

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data.

B. Ahmmed, Maruti Kumar Mudunuru, Satish Karra, S. C. James, Hari S. Viswanathan, John A. Dunbar

CoRR, 2019

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing.

Maruti Kumar Mudunuru, Satish Karra

CoRR, 2019

2018

Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico.

B. Yuan, Y. J. Tan, Maruti Kumar Mudunuru, O. E. Marcillo, A. A. Delorey, P. M. Roberts, J. D. Webster, C. N. L. Gammans, Satish Karra, G. D. Guthrie, P. A. Johnson

CoRR, 2018

Estimating Failure in Brittle Materials using Graph Theory.

Maruti Kumar Mudunuru, Nishant Panda, Satish Karra, Gowri Srinivasan, Viet T. Chau, Esteban Rougier, A. Hunter, Hari S. Viswanathan

CoRR, 2018

Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications.

A. Hunter, Bryan A. Moore, Maruti Kumar Mudunuru, Viet T. Chau, Robyn L. Miller, Roselyne B. Tchoua, C. Nyshadham, Satish Karra, Dan O'Malley, Esteban Rougier, Hari S. Viswanathan, Gowri Srinivasan

CoRR, 2018

2017

Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems.

Maruti Kumar Mudunuru, Satish Karra, Nataliia Makedonska, Ting Chen

Stat. Anal. Data Min., 2017

2016

On enforcing maximum principles and achieving element-wise species balance for advection-diffusion-reaction equations under the finite element method.

Maruti Kumar Mudunuru, K. B. Nakshatrala

J. Comput. Phys., 2016

Joint geophysical and flow inversion to characterize fracture networks in subsurface systems.

Maruti Kumar Mudunuru, Satish Karra, Nataliia Makedonska, T. Chen

CoRR, 2016

Interpolation-based reduced-order models to predict transient thermal output for enhanced geothermal systems.

Maruti Kumar Mudunuru, Satish Karra, D. R. Harp, G. D. Guthrie, Hari S. Viswanathan

CoRR, 2016

2015

Material degradation due to moisture and temperature. Part 1: Mathematical model, analysis, and analytical solutions.

C. Xu, Maruti Kumar Mudunuru, K. B. Nakshatrala

CoRR, 2015

On mesh restrictions to satisfy comparison principles, maximum principles, and the non-negative constraint: Recent developments and new results.

Maruti Kumar Mudunuru, K. B. Nakshatrala

CoRR, 2015

2013

A numerical framework for diffusion-controlled bimolecular-reactive systems to enforce maximum principles and the non-negative constraint.

K. B. Nakshatrala, Maruti Kumar Mudunuru, Albert J. Valocchi

J. Comput. Phys., 2013

2011

A framework for coupled deformation-diffusion analysis with application to degradation/healing

Maruti Kumar Mudunuru, K. B. Nakshatrala

CoRR, 2011