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| 001 | 903490 | ||
| 005 | 20240712084556.0 | ||
| 024 | 7 | _ | |a 10.1007/s10596-018-9793-x |2 doi |
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| 100 | 1 | _ | |a Poonoosamy, J. |0 P:(DE-Juel1)169154 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Benchmarking of reactive transport codes for 2D simulations with mineral dissolution–precipitation reactions and feedback on transport parameters |
| 260 | _ | _ | |a Bussum |c 2021 |b Baltzer Science Publ. |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Porosity changes due to mineral dissolution–precipitation reactions in porous media and the resulting impact on transport parameters influence the evolution of natural geological environments or engineered underground barrier systems. In the absence of long-term experimental studies, reactive transport codes are used to evaluate the long-term evolution of engineered barrier systems and waste disposal in the deep underground. Examples for such problems are the long-term fate of CO2 in saline aquifers and mineral transformations that cause porosity changes at clay–concrete interfaces. For porosity clogging under a diffusive transport regime and for simple reaction networks, the accuracy of numerical codes can be verified against analytical solutions. For clogging problems with more complex chemical interactions and transport processes, numerical benchmarks are more suitable to assess model performance, the influence of thermodynamic data, and sensitivity to the reacting mineral phases. Such studies increase confidence in numerical model descriptions of more complex, engineered barrier systems. We propose a reactive transport benchmark, considering the advective–diffusive transport of solutes; the effect of liquid-phase density on liquid flow and advective transport; kinetically controlled dissolution–precipitation reactions causing porosity, permeability, and diffusivity changes; and the formation of a solid solution. We present and analyze the results of five participating reactive transport codes (i.e., CORE2D, MIN3P-THCm, OpenGeoSys-GEM, PFLOTRAN, and TOUGHREACT). In all cases, good agreement of the results was obtained. |
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| 700 | 1 | _ | |a Wanner, C. |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Alt Epping, P. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Águila, J. F. |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Samper, J. |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Montenegro, L. |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Xie, M. |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Su, D. |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Mayer, K. U. |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Mäder, U. |0 P:(DE-HGF)0 |b 9 |
| 700 | 1 | _ | |a Van Loon, L. R. |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Kosakowski, G. |0 P:(DE-HGF)0 |b 11 |
| 773 | _ | _ | |a 10.1007/s10596-018-9793-x |g Vol. 25, no. 4, p. 1337 - 1358 |0 PERI:(DE-600)2001545-8 |n 4 |p 1337 - 1358 |t Computational geosciences |v 25 |y 2021 |x 1420-0597 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/903490/files/Poonoosamy2021_Article_BenchmarkingOfReactiveTranspor.pdf |y Restricted |
| 856 | 4 | _ | |y Published on 2018-11-19. Available in OpenAccess from 2019-11-19. |u https://juser.fz-juelich.de/record/903490/files/revised_Poonoosamy_SeSbenchmark_clean.pdf |
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