Development of an ultrafiltration predictive model to estimate the cost of downstream in biorefineries: Effects of epistemic experimental uncertainties. (1st October 2017)

• Record Type: Journal Article
• Authors: Rosengart, A.; Vizzi, M.; Manenti, F.; Citterio, A.
• Is Part Of: Energy conversion and management. Volume 149(2017)
• Page Start: 875
• Page End: 884
• Publication Date: 2017-10-01
• Subjects: Biorefining -- Ultrafiltration -- Conceptual design -- Possibility theory -- Membranes; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2017.03.043
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Highlights: A general predictive model for fermentation broth crossflow filtration is proposed. The model parameters are selected after extensive and systematic literature review. The model agrees with the pilot plant data of a lactic acid biorefinery. Fuzzy logic is applied to assess uncertainty propagation due to empirical errors. With uncertainty analysis, the model is suitable for conceptual cost estimation. Abstract: Crossflow filtration is a common unit operation for bio-separations, in particular for high volume applications, as biofuel production facilities and other biorefineries. However, the complex mechanism of membrane bio-fouling hinders the development of a general predictive model, to be used for cost and life-cycle evaluations in conceptual design of new processes. To overcome the limited applicability of fully empirical models, a simple though general Darcy model was used to describe flux reduction. The equations representing the additive resistances to flux were defined after a systematic review of the available literature. The developed model was successfully benchmarked with the data from a biorefining pilot plant. Provided the little agreement of literature on the values of the semi-empirical parameters of the model equations, these parameters were considered as fuzzy variables, characterized by an inner uncertainty especially if extended outside their experimental boundaries. Possibility theory was hence applied to study the propagation of uncertainty, from the model parameters to the model output (average flux and filtration cost). The range of variability of the upper cost of filtration was calculated for a biorefinery case study: the resulted estimates are compatible with real industrial filtration costs. The model provides also an indication of the economic risk due to limited experimental knowledge.