B
Banda S. RamaRao
Researcher at Duke University
Publications - 8
Citations - 883
Banda S. RamaRao is an academic researcher from Duke University. The author has contributed to research in topics: Steady state (electronics) & Porous medium. The author has an hindex of 4, co-authored 8 publications receiving 847 citations.
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Pilot Point Methodology for Automated Calibration of an Ensemble of conditionally Simulated Transmissivity Fields: 1. Theory and Computational Experiments
TL;DR: In this article, a new methodology for solution of the inverse problem in groundwater hydrology is proposed and applied to a site in southeastern New Mexico with extensive hydrogeologic data, where the U.S. Department of Energy is conducting probabilistic system assessment for the permanent disposal of transuranic nuclear waste.
Journal ArticleDOI
A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow
D. A. Zimmerman,G. de Marsily,G. de Marsily,C. A. Gotway,Melvin G. Marietta,C. L. Axness,R. L. Beauheim,Rafael L. Bras,Jesús Carrera,Gedeon Dagan,P. B. Davies,D. P. Gallegos,A. Galli,J. Jaime Gómez-Hernández,P. Grindrod,Allan L. Gutjahr,Peter K. Kitanidis,A. M. Lavenue,Dennis McLaughlin,Shlomo P. Neuman,Banda S. RamaRao,C. Ravenne,Yoram Rubin +22 more
TL;DR: In this article, the authors compared seven different inverse approaches for identifying aquifer transmissivity and found that the linearized methods were more accurate than those of nonlinear methods in predicting travel times and travel paths.
Journal ArticleDOI
Pilot Point Methodology for Automated Calibration of an Ensemble of Conditionally Simulated Transmissivity Fields: 2. Application
TL;DR: In this paper, the authors present the application of a methodology to assess spatial variability of the transmissivities within a regional aquifer in the vicinity of the Waste Isolation Pilot Plant (WIPP), the Culebra dolomite.
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Groundwater travel time uncertainty analysis using sensitivity derivatives
TL;DR: In this paper, the first-order second-moment (FOSM) approach and the stochastic approach were used to predict changes in the mean groundwater travel time for selected changes in permeability values within the model.