Experimental investigation of a two-zone model for semi-batch precipitation in stirred-tank reactors

• Published in: Chemical engineering science 2019-11, Vol.207, p.258-270
• Main Authors: Rehage, H., Nikq, F., Kind, M.
• Format: Article
• Language: English
• Subjects: Barium sulfate; Precipitation; Semi-batch; Zone model
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2019.06.024

[Display omitted] •LME model for semi-batch precipitation in stirred-tanks is presented.•Model considers stirrer type, size and rotational speed.•Model accuracy is validated with experimental comparison setup.•Mixing zone parameterized by pipe-in-pipe geometries. A zone model for the semi-batch precipitation process of sparingly soluble salts in stirred-tank reactors is presented. The low product solubility of these substances leads to high levels of supersaturation during the process. Consequently, nucleation and growth rates are fast and solids formation only takes place in a part of the reactor close to the feed pipe. The presented local mixing environment (LME) model extends an existing model for semi-batch processes, which consists of two zones. In the mixing zone, a steady-state plug-flow reactor (PFR) is used to imitate the local flow environment of the feed. The tank is approximated as a well-mixed storage tank outside the mixing zone. Exchange streams between the two zones are estimated by dimensional analysis considering stirrer type, size and rotational speed. The correctness of the two-zone hypothesis and the accuracy of the LME model is validated by barium sulfate precipitation in an experimental comparison setup using different stirrer types, rotational speeds and feed rates. The PFR is represented in the experiments as a pipe-in-pipe reactor in jet-in-cross-flow (JICF) or coaxial-flow (COAX) arrangement. The experimental results show that the semi-batch precipitation of sparingly soluble salts in stirred-tanks can be successfully simplified by the assumption of a PFR mixing zone. The LME model is simple to implement, scalable and reaches acceptable results in the experimental validation. It is therefore a promising model for future application in process simulation of industrial precipitation processes.