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Neretnieks, Ivars (2005) Comments on the paper by Pierre D. Glynn, “Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: Implications for reactive transport modeling and performance assessments of nuclear waste disposal sites”, Computers & Geosciences 29 (2003) 331–349. Computers & Geosciences, 31 (10) 1305-1307 doi:10.1016/j.cageo.2005.06.013

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Reference TypeJournal (article/letter/editorial)
TitleComments on the paper by Pierre D. Glynn, “Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: Implications for reactive transport modeling and performance assessments of nuclear waste disposal sites”, Computers & Geosciences 29 (2003) 331–349
JournalComputers & Geosciences
AuthorsNeretnieks, IvarsAuthor
Year2005 (December)Volume31
Issue10
PublisherElsevier BV
DOIdoi:10.1016/j.cageo.2005.06.013Search in ResearchGate
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Mindat Ref. ID449929Long-form Identifiermindat:1:5:449929:3
GUID0
Full ReferenceNeretnieks, Ivars (2005) Comments on the paper by Pierre D. Glynn, “Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: Implications for reactive transport modeling and performance assessments of nuclear waste disposal sites”, Computers & Geosciences 29 (2003) 331–349. Computers & Geosciences, 31 (10) 1305-1307 doi:10.1016/j.cageo.2005.06.013
Plain TextNeretnieks, Ivars (2005) Comments on the paper by Pierre D. Glynn, “Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: Implications for reactive transport modeling and performance assessments of nuclear waste disposal sites”, Computers & Geosciences 29 (2003) 331–349. Computers & Geosciences, 31 (10) 1305-1307 doi:10.1016/j.cageo.2005.06.013
In(2005, December) Computers & Geosciences Vol. 31 (10) Elsevier BV

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Glynn, Pierre D (2003) Modeling Np and Pu transport with a surface complexation model and spatially variant sorption capacities: implications for reactive transport modeling and performance assessments of nuclear waste disposal sites. Computers & Geosciences, 29 (3) 331-349 doi:10.1016/s0098-3004(03)00009-8
Cao, Zhixian (2007) Comments on the paper by Guy Simpson and Sebastien Castelltort, “Coupled model of surface water flow, sediment transport and morphological evolution”, Computers & Geosciences 32 (2006) 1600–1614. Computers & Geosciences, 33 (7) 976-978 doi:10.1016/j.cageo.2006.11.009
Simpson, Guy D. (2007) Reply by Simpson G.D.H. and Castelltort, S. to comments by Cao, Z. on the paper “Coupled model of surface water flow, sediment transport and morphological evolution” Computers & Geosciences, 32, 1600–1614 (2006) Computers & Geosciences, 33 (7) 979-980 doi:10.1016/j.cageo.2007.03.005
Bacon, Diana H., Peter McGrail, B. (2003) Lessons learned from reactive transport modeling of a low-activity waste glass disposal system. Computers & Geosciences, 29 (3) 361-370 doi:10.1016/s0098-3004(03)00011-6
Browning, Lauren, Murphy, William M. (2003) Reactive transport modeling in the geosciences. Computers & Geosciences, 29 (3) 245 doi:10.1016/s0098-3004(03)00002-5
Syvitski, James P.M. (2008) Predictive modeling in sediment transport and stratigraphy. Computers & Geosciences, 34 (10) 1167-1169 doi:10.1016/j.cageo.2008.02.001
Liu, Piyang, Zhang, Tao, Sun, Shuyu (2019) A tutorial review of reactive transport modeling and risk assessment for geologic CO2 sequestration. Computers & Geosciences, 127. 1-11 doi:10.1016/j.cageo.2019.02.007
Zhao, Zhihong, Jing, Lanru, Neretnieks, Ivars, Moreno, Luis (2011) Analytical solution of coupled stress-flow-transport processes in a single rock fracture. Computers & Geosciences, 37 (9) 1437-1449 doi:10.1016/j.cageo.2011.02.015
Jamie, Majid (2016) Note on: ‘EMLCLLER—A program for computing the EM response of a large loop source over a layered earth model’ by N.P. Singh and T. Mogi, Computers & Geosciences 29 (2003) 1301–1307. Computers & Geosciences, 96. 236-246 doi:10.1016/j.cageo.2016.07.019
Lattner, Andreas D., Cervone, Guido (2012) Ensemble modeling of transport and dispersion simulations guided by machine learning hypotheses generation. Computers & Geosciences, 48. 267-279 doi:10.1016/j.cageo.2012.01.017
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