Associate Professor
Director of Undergraduate Studies for Geoengineering
Distinguished University Teaching Professor
Contact
234 Civil Engineering Building
500 Pillsbury Drive SE
Minneapolis, MN 55455
Associate Professor
Director of Undergraduate Studies for Geoengineering
Distinguished University Teaching Professor
Randal Barnes' research interests traverse mathematical modeling in geological and civil engineering. His recent research work is comprised of three interacting focii. The first research focus is geostatistical site characterization: specifically, optimal sample design and engineering decision-making in the face of spatial variability and parameter uncertainty. The second is the incorporation of uncertainty into quantitative modeling for geoengineering. The third, and most recent, focus is the development and extension of computational aspects of the Analytic Element Method in geoengineering.
B.S., 1978, Civil Engineering, University of Washington
M.S., 1982, Mining Engineering, Colorado School of Mines
Ph.D., 1985, Mining Engineering, Colorado School of Mines
Instructor, Mining Engineering Department, Colorado School of Mines, 1982-85
Civil Engineer, United States Navy, R.O.I.C.C. Bremerton, Washington, 1977-78
Mining Engineering Technician, Phelps Dodge Corporation, Morenci Pit, 1977
University of Minnesota, Horace T. Morse Award for Outstanding Contributions to Undergraduate Education, 2023.
University of Minnesota, John Tate Award, Excellence in Undergraduate Advising, 2008.
Institute of Technology, Charles E. Bowers Faculty Teaching Award, 2005.
Department of Civil, Environmental, and Geo- Engineering, Bonestroo, Rosene, Anderlik and Associates Undergraduate Faculty Award, 2023, 2021, 2019, 2017, 2008, 2007, 2006, 2004, 2002, 2000.
Barnes, E. A., Barnes, R. J., & M. DeMaria. 2023. Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts. Environmental Data Science, 2(15), DOI: https://doi.org/10.1017/eds.2023.7
Barnes, E. A., Barnes, R. J., Martin, Z. K., & RaderJ. K. 2022. This looks like that there: Interpretable neural networks for image tasks when location matters. Artificial Intelligence for the Earth Systems, 1(3), e220001. https://doi.org/10.1175/AIES-D-22-0001.1
Barnes, E. A., & Barnes, R. J. 2021. Controlled abstention neural networks for identifying skillful predictions for classification problems. Journal of Advances in Modeling Earth Systems, 13, e2021MS002573. https://doi.org/10.1029/2021MS002573
de Salles, L. S., Conway, R., Khazanovich, L., Barnes, R., Hoegh, K., da Silva Pereira, D. & Burnham, T. 2021. Non-destructive ultrasonic evaluation of construction variability effect on concrete pavement performance. International Journal of Pavement Research and Technology. 14, 3, 385-396. DOI: 10.1007/s42947-020-1198-2
Barnes, R. J. & Soule, R. 2020. Quo Vadis? Inakeyaa! Inferring Flow Directions Using a Bayesian Approach. Geo-Congress 2020, Mpls. Feb. 25-28, 2020. Geotechnical Special Publication. 321, 78-86. DOI: 10.1061/9780784482841.006
Barnes, R. J. 2018. Shallow unconfined flow on a sloping base redux. Groundwater. 56, 4, 610-617. DOI: 10.1111/gwat.12607
Barnes, E. A. & Barnes, R. J. 2015. Estimating linear trends: Simple linear regression versus epoch differences. Journal of Climate. 28, 24, 9969-9976. DOI: 10.1175/JCLI-D-15-0032.1
Vancura, M., Khazanovich, L. & Barnes, R. J. 2013. Concrete pavement thickness variation assessment with cores and nondestructive testing measurements. Transportation Research Record. 2347, 61-68. DOI: 10.3141/2347-07
Janković, I., Steward, D. R., Barnes, R. J. & Dagan, G. 2009. Is transverse macrodispersivity in three-dimensional groundwater transport equal to zero? A counterexample. Water Resources Research. 45, 8, W08415. DOI: 10.1029/2009WR007741
Erickson, M. L. & Barnes, R. J. 2006. Arsenic concentration variability in public water system wells in Minnesota, USA. Applied Geochemistry. 21, 2, p. 305-317. DOI: 10.1016/j.apgeochem.2005.12.005
Craig, J. R., Janković, I. & Barnes, R. J. 2006. The nested superblock approach for regional-scale analytic element models. Groundwater. 44, 1, p. 76-80. DOI: 10.1111/j.1745-6584.2005.00081.x
Strack, O. D., Barnes, R. J. & Verruijt, A. 2006. Vertically integrated flows, discharge potential, and the dupuit-forchheimer approximation. Groundwater. 44, 1, p. 72-75. DOI: 10.1111/j.1745-6584.2005.00173.x
Erickson, M. & Barnes, R. J. 2005. Erratum: Well characteristics influencing arsenic concentrations in ground water (Water Research (October 2005) 39:16 (4029-4039) DOI: 10.1016/j.watres.2005.07.026). Water Research. 39, 20, p. 5277-5278. DOI: 10.1016/j.watres.2005.10.015
Erickson, M. L. & Barnes, R. J. 2005. Glacial sediment causing regional-scale elevated arsenic in drinking water. Groundwater. 43, 6, p. 796-805. DOI: 10.1111/j.1745-6584.2005.00053.x
Gao, Y., Alexander, E. C. & Barnes, R. J. 2005. Karst database implementation in Minnesota: Analysis of sinkhole distribution. Environmental Geology. 47, 8, p. 1083-1098. DOI: 10.1007/s00254-005-1241-2
Bekele, E. B., Person, M. A., Rostron, B. J. & Barnes, R. J. 2002. Modeling secondary oil migration with core-scale data: Viking Formation, Alberta basin. AAPG Bulletin. 86, 1, p. 55-74. Scopus
Janković, I. & Barnes, R. J. 1999. High-order line elements in modeling two-dimensional groundwater flow. Journal of Hydrology. 226, 3-4, p. 211-223. DOI: 10.1016/S0022-1694(99)00140-7
Strack, O. D., Janković, I. & Barnes, R. J. 1999. The superblock approach for the analytic element method. Journal of Hydrology. 226, 3-4, p. 179-187. DOI: 10.1016/S0022-1694(99)00148-1
Janković, I. & Barnes, R. J. 1999. Three-dimensional flow through large numbers of spheroidal inhomogeneities. Journal of Hydrology. 226, 3-4, p. 224-233. DOI: 10.1016/S0022-1694(99)00141-9
Barnes, R. J. & Janković, I. 1999. Two-dimensional flow through large numbers of circular inhomogeneities. Journal of Hydrology. 226, 3-4, p. 204-210. DOI: 10.1016/S0022-1694(99)00142-0
You, K. & Barnes, R. J. 1997. Infill sampling design for tunnel rock classification. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts. 34, 2, p. 207-215. DOI: 10.1016/S0148-9062(96)00054-X
Watson, A. G. & Barnes, R. J. 1995. Infill sampling criteria to locate extremes. Mathematical Geology. 27, 5, p. 589-608. DOI: 10.1007/BF02093902