Abstract

Thermal desorption is a method of soil treatment that heats soil in order to vaporize and extract contaminants. It relies on temperature measurements to assess the progress of the remediation, but these measurements are generally not numerous because of cost constraints. This paper proposes a low-complexity method to interpolate sparse temperature data over the whole site to generate visual representations that ease the treatment follow-up. The temperatures of the points that are not monitored are approximated by a weighted average of the 3 closest measurements, then a third-degree polynomial is fitted to the data via a finite element method. The resulting approximations yield an overall Root Mean Square Error (RMSE) of the temperature estimation of 35 K, which allows for realistic representations of the temperature at each point of the map with reduced sensor deployment.

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