[{"has_accepted_license":"1","language":[{"iso":"eng"}],"department":[{"_id":"DEP4028"},{"_id":"DEP5023"},{"_id":"DEP4018"},{"_id":"DEP1308"}],"title":"Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast ","publication_status":"published","date_created":"2024-06-28T12:57:01Z","conference":{"name":"39th EBC Congress 2024","start_date":"2024-05-26","location":"Lille","end_date":"2024-05-30"},"user_id":"81304","ddc":["600"],"date_updated":"2025-10-17T18:36:48Z","keyword":["surplus yeast","membrane filtration","microfiltration"],"year":"2024","abstract":[{"lang":"eng","text":"The recovery of beer from surplus yeast is to date an economical business case only for large breweries. In this work, a here novel process with rotating ceramic microfiltration membranes is used. This allows a very high lift force to be achieved while still maintaining a small transmembrane pressure to reduce the formation of a fouling layer. The results show that long running times (between cleanings) are possible, limited only by the change in the rheological properties of the suspension due to thickening. From a so-called \"Inflexion Point\" (IF), the filtration behavior changes abruptly. The aim of the work was therefore to use machine learning aided modeling to predict the IF from experimental data in order to optimize the process and to achieve the most economical conditions. The economic efficiency depends on the space-time yields. The results show that a significant improvement in economic efficiency could be possible with the help of modeling and this special kind of filtration technology. However, the economic efficiency depends finally on the conditions in each individual brewery."}],"quality_controlled":"1","citation":{"bjps":"<b>Trilling-Haasler M <i>et al.</i></b> (2024) <i>Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast </i>. .","chicago-de":"Trilling-Haasler, Marc, Jörn Tebbe, Markus Lange-Hegermann und Jan Schneider. 2024. <i>Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast </i>.","ieee":"M. Trilling-Haasler, J. Tebbe, M. Lange-Hegermann, and J. Schneider, <i>Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast </i>. 2024.","van":"Trilling-Haasler M, Tebbe J, Lange-Hegermann M, Schneider J. Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast . 2024.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Trilling-Haasler, Marc</span> ; <span style=\"font-variant:small-caps;\">Tebbe, Jörn</span> ; <span style=\"font-variant:small-caps;\">Lange-Hegermann, Markus</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span>: <i>Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast </i>, 2024","apa":"Trilling-Haasler, M., Tebbe, J., Lange-Hegermann, M., &#38; Schneider, J. (2024). <i>Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast </i>. 39th EBC Congress 2024, Lille.","mla":"Trilling-Haasler, Marc, et al. <i>Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast </i>. 2024.","ama":"Trilling-Haasler M, Tebbe J, Lange-Hegermann M, Schneider J. <i>Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast </i>.; 2024.","chicago":"Trilling-Haasler, Marc, Jörn Tebbe, Markus Lange-Hegermann, and Jan Schneider. <i>Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast </i>, 2024.","short":"M. Trilling-Haasler, J. Tebbe, M. Lange-Hegermann, J. Schneider, Yeast Filtration with Rotating Membrane Filtration –  a New Approach for an Economical Recovery of Beer Form Surplus Yeast , 2024.","ufg":"<b>Trilling-Haasler, Marc u. a.</b>: Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast , o. O. 2024.","havard":"M. Trilling-Haasler, J. Tebbe, M. Lange-Hegermann, J. Schneider, Yeast filtration with rotating membrane filtration –  a new approach for an economical recovery of beer form surplus yeast , 2024."},"_id":"11605","type":"conference_poster","status":"public","author":[{"last_name":"Trilling-Haasler","id":"81622","full_name":"Trilling-Haasler, Marc","orcid":"0000-0002-3685-6383","first_name":"Marc"},{"first_name":"Jörn","last_name":"Tebbe","full_name":"Tebbe, Jörn","id":"85958"},{"first_name":"Markus","last_name":"Lange-Hegermann","id":"71761","full_name":"Lange-Hegermann, Markus"},{"full_name":"Schneider, Jan","id":"13209","last_name":"Schneider","first_name":"Jan","orcid":"0000-0001-6401-8873"}]},{"abstract":[{"lang":"eng","text":"Active learning of physical systems must commonly respect practical safety constraints, which restricts the exploration of the design space. Gaussian Processes (GPs) and their calibrated uncertainty estimations are widely used for this purpose. In many technical applications the design space is explored via continuous trajectories, along which the safety needs to be assessed. This is particularly challenging for strict safety requirements in GP methods, as it employs computationally expensive Monte-Carlo sampling of high quantiles. We address these challenges by providing provable safety bounds based on the adaptively sampled median of the supremum of the posterior GP. Our method significantly reduces the number of samples required for estimating high safety probabilities, resulting in faster evaluation without sacrificing accuracy and exploration speed. The effectiveness of our safe active learning approach is demonstrated through extensive simulations and validated using a real-world engine example."}],"type":"conference_editor_article","_id":"12815","page":"1333-1341","author":[{"id":"85958","full_name":"Tebbe, Jörn","last_name":"Tebbe","first_name":"Jörn"},{"first_name":"Christoph","last_name":"Zimmer","full_name":"Zimmer, Christoph"},{"full_name":"Steland, Ansgar","last_name":"Steland","first_name":"Ansgar"},{"full_name":"Lange-Hegermann, Markus","id":"71761","last_name":"Lange-Hegermann","first_name":"Markus"},{"last_name":"Mies","full_name":"Mies, Fabian","first_name":"Fabian"}],"status":"public","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://proceedings.mlr.press/v238/tebbe24a.html","open_access":"1"}],"date_created":"2025-04-17T07:58:19Z","user_id":"83781","date_updated":"2025-06-25T12:47:19Z","year":"2024","oa":"1","citation":{"van":"Tebbe J, Zimmer C, Steland A, Lange-Hegermann M, Mies F. Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238. MLResearchPress ; 2024. (Proceedings of Machine Learning Research).","ieee":"J. Tebbe, C. Zimmer, A. Steland, M. Lange-Hegermann, and F. Mies, <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>. MLResearchPress , 2024, pp. 1333–1341.","ama":"Tebbe J, Zimmer C, Steland A, Lange-Hegermann M, Mies F. <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>. MLResearchPress ; 2024:1333-1341.","apa":"Tebbe, J., Zimmer, C., Steland, A., Lange-Hegermann, M., &#38; Mies, F. (2024). Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. In <i>International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238</i> (pp. 1333–1341). MLResearchPress .","havard":"J. Tebbe, C. Zimmer, A. Steland, M. Lange-Hegermann, F. Mies, Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning, MLResearchPress , 2024.","ufg":"<b>Tebbe, Jörn u. a.</b>: Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning, o. O. 2024 (Proceedings of Machine Learning Research).","bjps":"<b>Tebbe J <i>et al.</i></b> (2024) <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>. MLResearchPress .","chicago-de":"Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann und Fabian Mies. 2024. <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>. <i>International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238</i>. Proceedings of Machine Learning Research. MLResearchPress .","chicago":"Tebbe, Jörn, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, and Fabian Mies. <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>. <i>International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238</i>. Proceedings of Machine Learning Research. MLResearchPress , 2024.","short":"J. Tebbe, C. Zimmer, A. Steland, M. Lange-Hegermann, F. Mies, Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning, MLResearchPress , 2024.","mla":"Tebbe, Jörn, et al. “Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning.” <i>International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238</i>, MLResearchPress , 2024, pp. 1333–41.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Tebbe, Jörn</span> ; <span style=\"font-variant:small-caps;\">Zimmer, Christoph</span> ; <span style=\"font-variant:small-caps;\">Steland, Ansgar</span> ; <span style=\"font-variant:small-caps;\">Lange-Hegermann, Markus</span> ; <span style=\"font-variant:small-caps;\">Mies, Fabian</span>: <i>Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning</i>, <i>Proceedings of Machine Learning Research</i> : MLResearchPress , 2024"},"publisher":"MLResearchPress ","series_title":"Proceedings of Machine Learning Research","publication_identifier":{"issn":["2640-3498"]},"publication_status":"published","department":[{"_id":"DEP5000"},{"_id":"DEP5023"}],"title":"Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning","publication":"International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238","conference":{"name":"27th International Conference on Artificial Intelligence and Statistics (AISTATS)","location":"Valencia, SPAIN","start_date":"2024-05-02"}}]