  The blast furnace (BF) is the fundamental tool used in the iron manufacture.
Due to the difficulty of accessing direct measurements of the inner phenomena,
we determined the density distribution of its internal volume in order to
improve its productivity using muography. This is an imaging technique based on
the differential absorption of a flux of incident particles, muons, by the
target under study, similar to clinical X-ray imaging. Muons are elementary
particles that have the property of passing through dense materials, up to
hundreds of meters away. Their relative absorption and deviation allows the
generation of density distribution images of an object by tracking the number
of muons received by a detector, before and after passing through a structure.
The incident direction of the detected muons is reconstructed by means of a
detector composed of 3 scintillator panels that we moved on 3 positions around
the BF. With this technique, we obtained the first 3D image of the internal
structure of a BF using a Markov Chain Monte Carlo (MCMC) inverse problem
solving algorithm on muon flux data. We were also able to perform a density
monitoring of the BF and some of its operating parameters. We distinguished the
position and shape of the cohesive zone, a key element in the productivity of a
furnace, validating this innovative measurement concept in the application to a
BF and opening the field to a series of future experiments to gain both spatial
and temporal resolution.

Geophysics;High Energy Physics - Experiment;High Energy Physics - Phenomenology;Instrumentation and Detectors