001052072 001__ 1052072
001052072 005__ 20260120203627.0
001052072 0247_ $$2doi$$a10.1016/j.seppur.2025.134177
001052072 0247_ $$2ISSN$$a1383-5866
001052072 0247_ $$2ISSN$$a1873-3794
001052072 0247_ $$2datacite_doi$$a10.34734/FZJ-2026-00742
001052072 037__ $$aFZJ-2026-00742
001052072 041__ $$aEnglish
001052072 082__ $$a540
001052072 1001_ $$00000-0002-1820-9369$$aZhai, Song$$b0
001052072 245__ $$aExperimental determination and model-based prediction of flooding points in a pilot-scale continuous liquid-liquid gravity separator
001052072 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2025
001052072 3367_ $$2DRIVER$$aarticle
001052072 3367_ $$2DataCite$$aOutput Types/Journal article
001052072 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1768923176_1107
001052072 3367_ $$2BibTeX$$aARTICLE
001052072 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001052072 3367_ $$00$$2EndNote$$aJournal Article
001052072 500__ $$aFunding: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 466656378 – within the Priority Programme “SPP 2331:Machine Learning in Chemical Engineering”
001052072 520__ $$aLiquid-liquid gravity phase separation is crucial in chemical, biotechnological, metallurgical, and recycling processes. However, fluctuations in the feed stream conditions of the separator significantly affect the coalescence of dispersed drops, leading to the accumulation of a dense-packed zone (DPZ) and flooding. In this study, we investigate the relationship between feed stream conditions, such as temperature, and flooding points in a pilot-scale DN200 liquid–liquid gravity separator. A temperature-controlled experimental setup enabling a temperature range of 20°C to 50 °C was constructed with artificial-intelligence-assisted online measurements of separation curves, drop size distributions, and DPZ heights. Experiments were conducted with 1-octanol dispersed in water at dispersed phase fractions of 0.3 and 0.5. Experimental data show that temperature-dependent coalescence parameters, Sauter mean diameter , and phase fraction primarily influence flooding points. Further, we evaluated the prediction accuracy and consistency of two models from the literature, a lumped zero-dimensional model and the established Henschke model, which require solely feed stream data, geometry data, and physical properties. Both models underestimate experimental flooding points by a mean absolute percentage error and relative standard deviation MAPE ± RSD of (21.5 ± 12.2) % and (24.8 ± 14.8) % for the Henschke and 0D model, respectively. Considering the experimental relative standard error of 8.2 % accounting for 95 % confidence, the prediction accuracy and consistency of both models are reasonable. This study suggests batch settling experiments and endoscope measurements in the feed stream of the liquid–liquid separator to predict its flooding point due to fluctuations in the feed.
001052072 536__ $$0G:(DE-HGF)POF4-2172$$a2172 - Utilization of renewable carbon and energy sources and engineering of ecosystem functions (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001052072 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001052072 7001_ $$aBartkowiak, Niklas$$b1
001052072 7001_ $$00000-0002-2123-4776$$aSibirtsev, Stepan$$b2
001052072 7001_ $$0P:(DE-Juel1)194474$$aJupke, Andreas$$b3$$eCorresponding author$$ufzj
001052072 773__ $$0PERI:(DE-600)2022535-0$$a10.1016/j.seppur.2025.134177$$gVol. 377, p. 134177 -$$p134177 -$$tSeparation and purification technology$$v377$$x1383-5866$$y2025
001052072 8564_ $$uhttps://juser.fz-juelich.de/record/1052072/files/1-s2.0-S1383586625027741-main.pdf$$yOpenAccess
001052072 909CO $$ooai:juser.fz-juelich.de:1052072$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
001052072 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)194474$$aForschungszentrum Jülich$$b3$$kFZJ
001052072 9131_ $$0G:(DE-HGF)POF4-217$$1G:(DE-HGF)POF4-210$$2G:(DE-HGF)POF4-200$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-2172$$aDE-HGF$$bForschungsbereich Erde und Umwelt$$lErde im Wandel – Unsere Zukunft nachhaltig gestalten$$vFür eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten$$x0
001052072 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology$$d2024-12-19
001052072 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001052072 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001052072 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-19
001052072 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-19
001052072 9201_ $$0I:(DE-Juel1)IBG-2-20101118$$kIBG-2$$lPflanzenwissenschaften$$x0
001052072 980__ $$ajournal
001052072 980__ $$aVDB
001052072 980__ $$aUNRESTRICTED
001052072 980__ $$aI:(DE-Juel1)IBG-2-20101118
001052072 9801_ $$aFullTexts