Performance of Electrical Spectroscopy using a Resper Probe to Measure the Salinity and Water Content of Concrete or Terrestrial Soil

Details Performance of Electrical Spectroscopy using a Resper Probe to Measure the Salinity and Water Content of Concrete or Terrestrial Soil Performance of Electrical Spectroscopy using a Resper Probe to Measure the Salinity and Water Content of Concrete or Terrestrial Soil

2010-06-22

arxiv.org/abs/1006.4307v5

Ann. of Geophys. (2011) 54 (4), 400 - 413

Physics

Geophysics

45 pages, 5 figures, 1 table

Scientific paper

10.4401/ag-4966

This paper discusses the performance of electrical spectroscopy using a RESPER probe to measure the salinity s and volumetric content {\theta}W of the water in concrete or terrestrial soil. The RESPER probe is an induction device for spectroscopy which performs simultaneous and non invasive measurements of the electrical RESistivity 1/{\sigma} and relative dielectric PERmittivity {\epsilon}r of a subjacent medium. Numerical simulations establish that the RESPER can measure {\sigma} and {\epsilon} with inaccuracies below a predefined limit (10%) up to the high frequency band (HF). Conductivity is related to salinity and dielectric permittivity to volumetric water content using suitably refined theoretical models which are consistent with the predictions of Archie's and Topp's empirical laws. The better the agreement, the lower the hygroscopic water content and the higher s; so closer agreement is found with concrete containing almost no bonded water molecules provided these are characterized by a high {\sigma}. A novelty of the present paper is the application of a mathematical- physical model to the propagation of errors in the measurements, based on a sensitivity functions tool. The inaccuracy of salinity (water content) is the ratio (product) between the conductivity (permittivity) inaccuracy, specified by the probe, and the sensitivity function of salinity (water content) relative to conductivity (permittivity), derived from the constitutive equations of the medium. The main result is the model's prediction that the lower the inaccuracy for the measurements of s and {\theta}W (decreasing by as much as an order of magnitude from 10% to 1%), the higher {\sigma}; so the inaccuracy for soil is lower.

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