Application of inverse methodology to estimate unknown parameters of the mathematical model of biomass solar pyrolysis. (January 2021)
- Record Type:
- Journal Article
- Title:
- Application of inverse methodology to estimate unknown parameters of the mathematical model of biomass solar pyrolysis. (January 2021)
- Main Title:
- Application of inverse methodology to estimate unknown parameters of the mathematical model of biomass solar pyrolysis
- Authors:
- Kaczor, Zuzanna
Buliński, Zbigniew
Sobek, Szymon
Werle, Sebastian - Abstract:
- Abstract: The goal of the work is to determine unknown parameters of reactor heating in the process of biomass solar pyrolysis. The lab-scale reactor is heated by a xenon lamp, but the fraction of heat absorbed by the reactor is unknown, as well as the heat transfer coefficient from the reactor walls to the nitrogen flowing through internal reactor channels, and the overall heat transfer coefficient through the external reactor walls to the surroundings. The missing parameters are impossible to measure, therefore they need to be determined by solving the inverse problem. As the problem is strongly ill-conditioned, since the quantities are directly dependent on each other, two different inverse algorithms were used to retrieve them, namely, the Levenberg-Marquardt method and the Metropolis-Hastings method. The effectiveness of both approaches was assessed and then they were applied to the real data. The inverse problem was implemented in the MatLab software, while validation of the mathematical model and optimisation procedure was carried out with a CFD model built in Ansys Fluent 19.2. Calculations showed that 14.4% of the lamp power penetrates inside the reactor and heat transfer coefficients to the flowing nitrogen equal 8.74 W/m 2 K and 0.965 W/m 2 K to the surroundings. Highlights: Two inverse algorithms were used: Levenberg-Marquardt and Metropolis-Hastings. The validation was carried out with a 3D CFD model. Calculations showed that only 14.4% of the lamp powerAbstract: The goal of the work is to determine unknown parameters of reactor heating in the process of biomass solar pyrolysis. The lab-scale reactor is heated by a xenon lamp, but the fraction of heat absorbed by the reactor is unknown, as well as the heat transfer coefficient from the reactor walls to the nitrogen flowing through internal reactor channels, and the overall heat transfer coefficient through the external reactor walls to the surroundings. The missing parameters are impossible to measure, therefore they need to be determined by solving the inverse problem. As the problem is strongly ill-conditioned, since the quantities are directly dependent on each other, two different inverse algorithms were used to retrieve them, namely, the Levenberg-Marquardt method and the Metropolis-Hastings method. The effectiveness of both approaches was assessed and then they were applied to the real data. The inverse problem was implemented in the MatLab software, while validation of the mathematical model and optimisation procedure was carried out with a CFD model built in Ansys Fluent 19.2. Calculations showed that 14.4% of the lamp power penetrates inside the reactor and heat transfer coefficients to the flowing nitrogen equal 8.74 W/m 2 K and 0.965 W/m 2 K to the surroundings. Highlights: Two inverse algorithms were used: Levenberg-Marquardt and Metropolis-Hastings. The validation was carried out with a 3D CFD model. Calculations showed that only 14.4% of the lamp power penetrates inside the reactor. … (more)
- Is Part Of:
- Renewable energy. Volume 163(2021)
- Journal:
- Renewable energy
- Issue:
- Volume 163(2021)
- Issue Display:
- Volume 163, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 163
- Issue:
- 2021
- Issue Sort Value:
- 2021-0163-2021-0000
- Page Start:
- 858
- Page End:
- 869
- Publication Date:
- 2021-01
- Subjects:
- Inverse problem -- Levenberg-marquardt algorithm -- Metropolis-hastings algorithm -- Biomass pyrolysis -- CFD modelling
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2020.09.018 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
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British Library HMNTS - ELD Digital store - Ingest File:
- 22338.xml