October – 59th Conference of Metallurgists CoM 2020 (virtual)

Joan Boulanger presented a taxonomy of local low-voltage perfluorocarbon emissions in primary aluminium production cells detailing how they occur, the available literature and explaining the cell set-up with a CF4 sensor installed on the cell gas duct coupled with anodic current measurement. The set-up allowed to record and analyze anodic current drop and CF4 concentration raise data. The screening of the data obtained from a primary aluminium production cell equipped with CF4, anodic current, line intensity, and voltage sensors during a six-week measurement campaign shows that the Low-Voltage Anode Effects (LVAE) at the scale of a single anode enshrine typical but various footprints into the anodic current signals. An explanation of the low voltage anode effect apparition mechanism is proposed, and in view of the many patterns and signatures detected, a detection algorithm is being developed with the help of artificial intelligence tools. Anodic currents are efficient to identify cell zones prone to LVAE. This is certainly helpful to assess and optimise feeding schemes. On the other hand, the variety of the patterns imprinted within the anodic current time series by LVAE events exacerbates the challenges to reliably detect those using automated systems.


Jean Bernier presented recent enhancements to the particulate matter measurement by LiDAR. Dust emissions represent an issue for the mining and mineral processing industries whether the source is handling and transportation of powdered materials or wind erosion of stockpiles. In some cases, modulating operations, based on weather conditions, may be the best approach to mitigate these emissions efficiently and to do so, one must rely on real-time distributed data. To address the need for reliable and distributed data, a medium-range (<500 m) dust mapping sensor, based on a LiDAR (Light Detection and Ranging) digital system, was developed and now include real-time calibration of the LiDAR signal for absolute concentration reporting, autonomous detection of dust events within a user-specified region of interest, and alarm broadcasting based on these events. Real-time monitoring of fugitive dust emissions from the unloading of cargo raw materials was carried out. The LiDAR was installed at a port where raw material unloading can generate airborne dust. Real-time dust monitoring capabilities have shown to provide valuable information, and dust control management efforts (before/after dust management mitigation) were quantified.