Search results for "Sulfur recovery"
showing 2 items of 2 documents
RNN- and LSTM-Based Soft Sensors Transferability for an Industrial Process
2021
The design and application of Soft Sensors (SSs) in the process industry is a growing research field, which needs to mediate problems of model accuracy with data availability and computational complexity. Black-box machine learning (ML) methods are often used as an efficient tool to implement SSs. Many efforts are, however, required to properly select input variables, model class, model order and the needed hyperparameters. The aim of this work was to investigate the possibility to transfer the knowledge acquired in the design of a SS for a given process to a similar one. This has been approached as a transfer learning problem from a source to a target domain. The implementation of a transf…
How to tackle the stringent sulfate removal requirements in mine water treatment-A review of potential methods.
2018
Abstract Sulfate (SO₄²⁻) is a ubiquitous anion in natural waters. It is not considered toxic, but it may be detrimental to freshwater species at elevated concentrations. Mining activities are one significant source of anthropogenic sulfate into natural waters, mainly due to the exposure of sulfide mineral ores to weathering. There are several strategies for mitigating sulfate release, starting from preventing sulfate formation in the first place and ending at several end-of-pipe treatment options. Currently, the most widely used sulfate-removal process is precipitation as gypsum (CaSO₄·2H₂O). However, the lowest reachable concentration is theoretically 1500 mg L⁻¹ SO₄²⁻ due to gypsum’s solu…