Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-24T11:46:21.020Z Has data issue: false hasContentIssue false

Determining hydraulic properties of concrete and mortar by inverse modelling

Published online by Cambridge University Press:  28 March 2012

Sébastien Schneider
Affiliation:
Performance Assessments Unit, Belgian Nuclear Research Centre SCKCEN, 2400 Mol, Belgium.
Dirk Mallants
Affiliation:
Performance Assessments Unit, Belgian Nuclear Research Centre SCKCEN, 2400 Mol, Belgium.
Diederik Jacques
Affiliation:
Performance Assessments Unit, Belgian Nuclear Research Centre SCKCEN, 2400 Mol, Belgium.
Get access

Abstract

This paper presents a methodology and results on estimating hydraulic properties of the concrete and mortar considered for the near surface disposal facility in Dessel, Belgium, currently in development by ONDRAF/NIRAS. In a first part, we estimated the van parameters for the water retention curve for concrete and mortar obtained by calibration (i.e. inverse modelling) of the van Genuchten model [1] to experimental water retention data [2]. Data consisted of the degree of saturation measured at different values of relative humidity. In the second part, water retention data and data from a capillary suction experiment on concrete and mortar cores was used jointly to successfully determine the van Genuchten retention parameters and the Mualem hydraulic conductivity parameters (including saturated hydraulic conductivity) by inverse modelling.

Type
Articles
Copyright
Copyright © Materials Research Society 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. van Genuchten, M.Th., Soil Sci. Soc. Am. J., 44, 892 (1980).10.2136/sssaj1980.03615995004400050002xGoogle Scholar
2. ONDRAF/NIRAS, NIROND-TR 2009-17 E V1 (2009) Google Scholar
3. Mualem, Y., Water Resources Research, 12, 513 (1976).10.1029/WR012i003p00513Google Scholar
4. Maierhofer, C., Arndt, R., and Röllig, M., Infrared Physics & Technology, 49, 213, (2007).10.1016/j.infrared.2006.06.007Google Scholar
5. van Genuchten, M.Th., Leij, F.J., and Yates, S.R., EPA Report 600/2-91/065, U.S. Salinity Laboratory, USDA, ARS, Riverside, California, (1991).Google Scholar
6. Rockhold, M.L., Fayer, M.J. and Heller, P.R., Physical and hydraulic properties of sediments and engineered materials associated with grouted double-shell tank waste disposal at Hanford. PNLL Richland, Washington, (1993).10.2172/10102958Google Scholar
7. Šimůnek, J., Šejna, M., and van Genuchten, M. Th., The HYDRUS-1D software for simulating the one-dimensional movement of water, heat, and multiple solutes in variably saturated media. Dep. Environ. Sciences, UCR, Riverside, CA, 281 pp. (2009).Google Scholar
8. Schneider, S., GENAPAC – A genetic algorithm for parameter calibration. SCK•CEN report ER-140, (2010).Google Scholar
9. Goldberg, D. E., and Deb, K., in: Foundations of Genetic Algorithms, edited by Rawlins, G.J.E., Morgan Kaufmann Publishers, San Mateo, CA, p. 69, (1991).Google Scholar
10. Hall, C., Cement and Concrete Research, 37, 378 (2007).10.1016/j.cemconres.2006.10.004Google Scholar
11. Schaap, M.G., Leij, F.J., Soil Sci. Soc. Am. J., 64, 843 (2000).10.2136/sssaj2000.643843xGoogle Scholar
12. Baroghel-Bouny, V., Mainguy, M., Lassabatere, T., and Coussy, O., Cement and Concrete Research 29, 1225 (1999).10.1016/S0008-8846(99)00102-7Google Scholar