Dynamic Simulation and Optimization of a Urea Granulation Circuit

Abstract

A dynamic model for a complete urea granulation circuit is presented in this work. The flowsheet includes a fluidized bed granulator, a cooling unit, a vibrating double-deck screen, and a double-roll crusher. This contribution is based on mathematical models for all the equipments, some of them previous validated against industrial data. All the units are modeled by means of the population balance equation (PBE). In addition, the granulator energy and mass balances for urea and air (used as a cooling medium and fluidization agent) are solved simultaneously with the PBE to properly represent the unit dynamics. Furthermore, mass, energy, and population balances are developed for the cooler. The individual units are successfully integrated under the gPROMS Model Builder Environment, which allows one to have a powerful tool for the circuit simulation and optimization. A sensitivity analysis is performed by running several dynamic and steady-state gPROMS simulations in order to evaluate the influence of different operating variables on the particle size distributions and mass flow rates of the circuit streams, as well as the mass holdup and thermal conditions in the granulator and cooler. The results indicate that both screen deck apertures, together with the crusher lower gap, are the variables that most affect the circuit performance. The circuit stability is also analyzed. Finally, different optimization scenarios are carried out to determine the values of the selected manipulated variables that maximize production on specification, minimize the recycle fraction, and allow a plant revamping. The urea granulation process simulator (including mass, energy, and population balances) constitutes a powerful tool to study the circuit responses under different disturbances, determine the optimal combination of operating and design variables in order to meet the production requirements and explore new process flow diagrams.

Feedback control strategies for a continuous industrial fluidized-bed granulation process

“…Particularly and as the granulation unit constitutes a MIMO system, pairings between potential manipulated and controlled variables should be made such that interactions within control-loops are minimized. In fact, and as demonstrated in previously performed sensitivity analyses [13,63], the granulator fluidized-bed levels, temperatures and top underpressure can be affected in a different extent either by the granulator discharge or fluidization air flowrate (i.e., blower rpm) disturbances.…”

A Validated Flowsheeting Tool for the Study of an Industrial Granulation Process

“…The simulator used in this work includes a fluidized bed granulator model developed in previous contributions. , This model was based on coating as the main size enlargement mechanism and allows the dynamic mass, energy, momentum, and population balances to be solved for all the granulator chambers. Details of the granulator model’s formulation can be found in the Appendix.…”

Experimental investigation of process stability of continuous spray fluidized bed layering with external product separation

“…Schütte et al (1998) presented their data in a patent without further interpretation and without explanations regarding reproducibility. Besides Heinrich et al (2002), Radichkov et al (2006) and Dreyschultze et al (in press), a wide range of authors deal with these oscillations of PSD in simulations (for example Bück et al, 2015;Cotabarren et al, 2010;Dosta et al, 2010;Drechsler et al, 2005;Heinrich et al, 2003;Palis and Kienle, 2012;Palis and Kienle, 2014) or use them to motivate the need of process control or better models (for example Bertin et al, 2013;Cotabarren et al, 2011). But none of these references includes an experimental proof of the occurrence of PSD oscillations.…”