Industrial crystallization process control

Larsen, Paul A.; Patience, Daniel B.; Rawlings, James B.

doi:10.1109/mcs.2006.1657878

Cited by 85 publications

(14 citation statements)

References 54 publications

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“…The SEM-EDX images were processed with ImageJ (Schindelin et al 2012) to measure the pore-and crystal size distribution. The crystal size is of particular interest, since it is reported to correlate with supersaturation (Beck and Andreassen 2012;Larsen et al 2006). Hence, we tested whether the crystal size could be used as an indicator of the prediction of scale rates.…”

Section: Methodsmentioning

confidence: 99%

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Hydrochemical and operational parameters driving carbonate scale kinetics at geothermal facilities in the Bavarian Molasse Basin

2020

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The majority of scales observed at geothermal facilities exploring the Malm Aquifer in the Bavarian Molasse Basin are carbonates. They form due to a disruption of the lime–carbonic acid equilibrium during production caused by a reduction of the partial pressure of carbon dioxide due to pressure change and degassing. These scales are found at the pumps, production pipes, filters, heat exchangers, and occasionally in the injection pipes. In this study, scales of all sections of geothermal facilities were taken. The database consists of scale samples from 13 geothermal pumps, 6,000 m production pipe (sample interval 10 - 12 m), 11 heat exchanger revisions, 2 injection pipes, and numerous filter elements. The samples were analyzed by SEM-EDX, XRD, Raman spectroscopy, and acid digestion to assess their chemical and mineralogical composition. From direct gauge measurements at six facilities during pump changes, scale rates were determined along the production pipes. From indirect measurements (multifinger caliper measurements) scale rates are derived for the region below the pump. Hydrochemical analyses from the wellhead were taken from 13 sites to feed the hydrogeochemical models. The calcite scale rates in the production pipes increase from the pump to the wellhead, where they reach 1.5 - 4.1 $$\mu$$ μ mol/($$\hbox {m}^2\,\cdot$$ m 2 · s). Scale rates below the pump reach up to 1.5 $$\mu$$ μ mol/($$\hbox {m}^2\,\cdot$$ m 2 · s). Given the slight change of hydrochemistry on the rise through the production pipe, where < 4 % of dissolved calcium ions precipitate as scale, scale rates cannot be derived from water samples at the wellhead, but require direct gauge measurements. The small amount of precipitation, together with fully turbulent conditions suggests that all measured rates are controlled by the surface-reaction of calcite crystallization following the nomenclature of Appelo and Postma (2004). Two approaches are used for the modeling of the scale rates. The first approach is based on hydrogeochemical modeling with PHREEQC. Scale rates calculated by this method are one order of magnitude higher than the measured ones. The second approach is based on correlations between the measured scale rates at the wellhead at six facilities and identified thermodynamic scale drivers ($$\Delta$$ Δ log (p$$\hbox {CO}_2$$ CO 2 ), $$\Delta$$ Δ total pressure, $$\Delta$$ Δ pH, and $$\hbox {SI}_{{calcite}}$$ SI calcite ). The correlations allow linear regressions which are used for the prediction of the scale rate at the wellhead, along the whole production pipe, and below. The modeling results show that scale prediction based on the new regressions that rely on thermodynamic scale drivers works better than existing hydrogeochemical models, already without implementation of kinetic parameters ($$\hbox {CO}_2$$ CO 2 -stripping and magnesium inhibition).

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Section: Methodsmentioning

confidence: 99%

“…We have seen in Figure 4 that SI calcite controls the scale rate, and increases towards the wellhead. Furthermore, SI calcite controls also the crystal size (Beck and Andreassen 2012;Larsen et al 2006). A high SI calcite is expected to correlate with a high scale rate and low crystal size.…”

Section: Use Of Operational Parameters For Scale Rate Predictionmentioning

confidence: 99%

Hydrochemical and operational parameters driving carbonate scale kinetics at geothermal facilities in the Bavarian Molasse Basin

2020

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“…The control of crystal size and size distribution is mainly through the control of crystal growth and nucleation. Most of the crystallization processes indirectly affect CSD through real-time temperature control or anti-solvent to follow the supersaturation set in the phase diagram [3,117]. Using the SSC strategy during the crystallization process can keep the supersaturation constant at the set value, and reduce or avoid secondary nucleation during the entire crystallization process to promote crystal growth.…”

Section: Optimization Of the Crystal Size Distributionmentioning

confidence: 99%

Application of PAT-Based Feedback Control Approaches in Pharmaceutical Crystallization

Gao

Zhang

et al. 2021

Crystals

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Crystallization is one of the important unit operations for the separation and purification of solid products in the chemical, pharmaceutical, and pesticide industries, especially for realizing high-end, high-value solid products. The precise control of the solution crystallization process determines the polymorph, crystal shape, size, and size distribution of the crystal product, which is of great significance to improve product quality and production efficiency. In order to develop the crystallization process in a scientific method that is based on process parameters and data, process analysis technology (PAT) has become an important enabling platform. In this paper, we review the development of PAT in the field of crystallization in recent years. Based on the current research status of drug crystallization process control, the monitoring methods and control strategies of feedback control in the crystallization process were systematically summarized. The focus is on the application of model-free feedback control strategies based on the solution and solid information collected by various online monitoring equipment in product engineering, including improving particle size distribution, achieving polymorphic control, and improving purity. In this paper, the challenges of feedback control strategy in the crystallization process are also discussed, and the development trend of the feedback control strategy has been prospected.

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“…Crystallization is a key process extensively used in many pharmaceutical product manufacturing and chemical applications. The process monitoring and control of crystallization techniques in industry have been subjects of study for many years [1]. There are primarily four types of crystallization methods: cooling crystallization, evaporative crystallization, anti-solvent based crystallization, and reactive crystallization [2].…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Visualization of Crystallization Processes Using Electrical Resistance Tomography: CaCO3 and Sucrose Crystallization Case Studies

Rao

Aghajanian

Zhang

et al. 2022

Sensors

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In the current research work, electrical resistance tomography (ERT) was employed for monitoring and visualization of crystallization processes. A first-of-its-kind MATLAB-based interactive GUI application “ERT-Vis” is presented. Two case studies involving varied crystallization methods were undertaken. The experiments were designed and performed involving calcium carbonate reactive (precipitative) crystallization for the high conductivity solution-solute media, and the cooling crystallization of sucrose representing the lower conductivity solution–solute combination. The software successfully provided key insights regarding the process in both crystallization systems. It could detect and separate the solid concentration distributions in the low as well as high conductivity solutions using the visual analytics tools provided. The performance and utility of the software were studied using a software evaluation case study involving domain experts. Participant feedback indicated that ERT-Vis software helps by reconstructing images instantaneously, interactively visualizing, and evaluating the output of the crystallization process monitoring data.

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Industrial crystallization process control

Cited by 85 publications

References 54 publications

Hydrochemical and operational parameters driving carbonate scale kinetics at geothermal facilities in the Bavarian Molasse Basin

Hydrochemical and operational parameters driving carbonate scale kinetics at geothermal facilities in the Bavarian Molasse Basin

Application of PAT-Based Feedback Control Approaches in Pharmaceutical Crystallization

Monitoring and Visualization of Crystallization Processes Using Electrical Resistance Tomography: CaCO3 and Sucrose Crystallization Case Studies

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