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Model selection, identification and validation in anaerobic digestion: a review
- Source :
- Water Research, Water Research, 2011, 45 (17), pp.5347-5364. ⟨10.1016/j.watres.2011.08.059⟩, Water Research, IWA Publishing, 2011, 45 (17), pp.5347-5364. ⟨10.1016/j.watres.2011.08.059⟩
- Publication Year :
- 2011
-
Abstract
- International audience; Anaerobic digestion enables waste (water) treatment and energy production in the form of biogas. The successful implementation of this process has lead to an increasing interest worldwide. However, anaerobic digestion is a complex biological process, where hundreds of microbial populations are involved, and whose start-up and operation are delicate issues. In order to better understand the process dynamics and to optimize the operating conditions, the availability of dynamic models is of paramount importance. Such models have to be inferred from prior knowledge and experimental data collected from real plants. Modeling and parameter identification are vast subjects, offering a realm of approaches and methods, which can be difficult to fully understand by scientists and engineers dedicated to the plant operation and improvements. This review article discusses existing modeling frameworks and methodologies for parameter estimation and model validation in the field of anaerobic digestion processes. The point of view is pragmatic, intentionally focusing on simple but efficient methods.
- Subjects :
- Engineering
Identification
Environmental Engineering
Process (engineering)
020209 energy
engineering
[SDV]Life Sciences [q-bio]
02 engineering and technology
010501 environmental sciences
water resources
01 natural sciences
Field (computer science)
environmental
Kinetic parameters
Water Purification
Lead (geology)
Digestion (alchemy)
Biogas
Anaerobic digestion
[SDV.IDA]Life Sciences [q-bio]/Food engineering
0202 electrical engineering, electronic engineering, information engineering
[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering
Anaerobiosis
environmental sciences
Waste Management and Disposal
0105 earth and related environmental sciences
Water Science and Technology
Civil and Structural Engineering
Waste management
business.industry
Ecological Modeling
Model selection
Modeling
Uncertainty
Reproducibility of Results
Pollution
Identification (information)
Models, Chemical
13. Climate action
Biochemical engineering
business
Sensitivity analysis
Subjects
Details
- ISSN :
- 18792448 and 00431354
- Volume :
- 45
- Issue :
- 17
- Database :
- OpenAIRE
- Journal :
- Water research
- Accession number :
- edsair.doi.dedup.....ccf58fb4b99b0c4703e1513a2c257579