Geometry, kinetics and reactor network synthesis: Attainable limits for minimizing residence time in biomethane digesters. (8th May 2020)

• Record Type: Journal Article
• Authors: Abunde Neba, F.; Tornyeviadzi, Hoese M.; Addo, Ahmad; Asiedu, Nana Y.; Morken, John; Østerhus, Stein W.; Seidu, Razak
• Is Part Of: Computers & chemical engineering. Volume 136(2020)
• Publication Date: 2020-05-08
• Subjects: Kinetic modeling -- Process inhibitions -- Digester network synthesis -- Residence time -- Adjoint optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2020.106816
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A new approach to optimize residence time using digester structure synthesis. Kinetic models are used to visualize digestion process as 3D geometric objects. The approach can simultaneously answer different design/optimization questions. Using digester structures minimize residence time compared to single digesters. The framework also extends performance targets of anaerobic treatment process. Abstract: This paper presents a theoretical framework to model anaerobic digester structures and define performance targets using regions of attainability constructed using kinetic models and fundamental processes: mixing and biodegradation. Two digestion cases, diary manure (case 1) and diary manure + lagoon inoculum (case 2) were considered and the following main findings were obtained. Case 1 presents a linear acidogenic and exponential methanogenic uncoupling, an optimized performance target of 216.45% with optimal digester structure consisting of CSTR (continuous stirred reactor) + PFR (plug flow reactor) run in parallel with a CSTR (6 days retention time, RT) or a CSTR with bypass from feed (2 days RT). Case 2 presents a linear methanogenic response, an optimized target of 142.47% with optimal digester structure consisting of a CSTR + PFR with bypass (2 & 6 days RT). The framework presented in this study can be used for simultaneous optimization of performance targets and digester networks.