Wireless Transmission of Monitoring Data out of an Underground Repository: Results of Field Demonstrations Performed at the HADES Underground Laboratory -13589

ABSTRACT As part of the European 7th framework project MoDeRn, Nuclear Research and Consultancy Group (NRG) performed experiments in order to demonstrate the feasibility of wireless data transmission through the subsurface over large distances by low frequency magnetic fields in the framework of the geological disposal of radioactive waste. The main objective of NRG's contribution is to characterize and optimize the energy use of this technique within the specific context of post-closure monitoring of a repository. For that, measurements have been performed in the HADES Underground Research Laboratory (URL) located at Mol, Belgium, at 225 m depth. The experimental set-up utilizes a loop antenna for the transmitter that has been matched to the existing infrastructure of the HADES. Between 2010 and 2012 NRG carried out several experiments at the HADES URL in order to test the technical set-up and to characterize the propagation behavior of the geological medium and the local background noise pattern. Transmission channels have been identified and data transmission has been demonstrated at several frequencies, with data rates up to 10 bit/s and bit error rates <1%. A mathematical model description that includes the most relevant characteristics of the transmitter, transmission path, and receiver has been developed and applied to analyze possible options to optimize the set-up. With respect to the energy-efficiency, results so far have shown that data transmission over larger distances through the subsurface is a feasible option. To support the conclusions on the energy need per bit of transmitted data, additional experiments are foreseen

Statistical Analysis of a Repository Design in Argillaceous Rock

As part of the PAMINA project, which was conducted within the 6th framework programme of the European Commission, a probabilistic uncertainty and sensitivity analysis has been performed for a generic repository in clay. The objective of the analysis was to test and demonstrate the applicability of combining tools for Performance Assessment calculations and statistical analyses, so to assess the radiological consequences of variations of important system parameters. NRG has performed the PA calculations for a repository design in Boom Clay, assuming an abandonment scenario. The probabilistic analysis focused on variation of the dissolution rate of the emplaced vitrified waste, the apparent diffusion coefficient in the host rock and the composition of the disposal cell sealing plug on the dose rates to the biosphere. JRC-IE performed the statistical analyses. Several methods were applied to quantify the uncertainties and their dependence on the variability of the input parameters. The statistical analysis included an uncertainty evaluation (mean, standard deviation, skewness, kurtosis and percentiles) as well as a sensitivity analysis (R2, SRRC, Smirnow and Mann-Whitney tests, CSM plots and cobweb plots). The paper summarizes the results of the PA calculations and the statistical analyses, and evaluates the applicability and limitations of the applied methodologiesJRC.F.3-Energy securit

Lessons Learnt from Studies on Sensitivity Analysis Techniques in the EU Project PAMINA: Sensitivity Analysis Applied to Different HLW PA Models

International audienc

Lessons Learnt from Studies on Sensitivity Analysis Techniques in the EU Project PAMINA: Sensitivity Analysis Applied to Different HLW PA Models

International audienc

Lessons Learnt from Studies on Sensitivity Analysis Techniques in the EU Project PAMINA: Sensitivity Analysis Applied to Different HLW PA Models

Within the EU project PAMINA different Sensitivity Analysis (SA) techniques have been applied to models that simulate the behaviour of different radioactive waste repositories. This paper summarises the main results and highlights specific aspects of regression/correlation techniques, the use of alternative imputation methods for datasets with missing values, the use of derived input parameters, the use of Monte Carlo filtering techniques in combination with cobweb plots and of variance based techniques.JRC.F.3-Energy securit