CFD-based optimization of a transient heating process in a natural gas fired furnace using neural networks and genetic algorithms. (25th June 2018)
- Record Type:
- Journal Article
- Title:
- CFD-based optimization of a transient heating process in a natural gas fired furnace using neural networks and genetic algorithms. (25th June 2018)
- Main Title:
- CFD-based optimization of a transient heating process in a natural gas fired furnace using neural networks and genetic algorithms
- Authors:
- Prieler, Rene
Mayrhofer, Markus
Gaber, Christian
Gerhardter, Hannes
Schluckner, Christoph
Landfahrer, Martin
Eichhorn-Gruber, Markus
Schwabegger, Günther
Hochenauer, Christoph - Abstract:
- Highlights: CFD-based investigation of a transient heating process. CFD simulation of the transient heating process by a steady-state consideration. Application of neural networks and response surface method to predict the system response. Optimization of the heating characteristic using a multi-objective genetic algorithm. Abstract: In the present study a transient heating process in a natural gas fired test furnace, used for fire resistance tests of construction and building materials, was investigated by computational fluid dynamics (CFD). To ensure the reproducibility of a fire resistance test, the thermal exposure of the tested fire safety material has to be homogeneous and, thus, the temperature distribution is of high importance. For that purpose, a CFD-based optimization of the transient heating process was carried out using different optimization algorithms. Based on the furnace setup, parameters with a potential to improve the temperature distribution were identified and used for the optimization procedure. CFD results were used to create system response surfaces, which represent the temperature distribution in the furnace as a function of the chosen design parameters. The system response was approximated by neural networks and genetic algorithms, and represents the basis for the optimization. Since the duration of the transient process was 35 min, the calculation time of the gas phase combustion and heat transfer is high. Therefore, a novel CFD-based approach wasHighlights: CFD-based investigation of a transient heating process. CFD simulation of the transient heating process by a steady-state consideration. Application of neural networks and response surface method to predict the system response. Optimization of the heating characteristic using a multi-objective genetic algorithm. Abstract: In the present study a transient heating process in a natural gas fired test furnace, used for fire resistance tests of construction and building materials, was investigated by computational fluid dynamics (CFD). To ensure the reproducibility of a fire resistance test, the thermal exposure of the tested fire safety material has to be homogeneous and, thus, the temperature distribution is of high importance. For that purpose, a CFD-based optimization of the transient heating process was carried out using different optimization algorithms. Based on the furnace setup, parameters with a potential to improve the temperature distribution were identified and used for the optimization procedure. CFD results were used to create system response surfaces, which represent the temperature distribution in the furnace as a function of the chosen design parameters. The system response was approximated by neural networks and genetic algorithms, and represents the basis for the optimization. Since the duration of the transient process was 35 min, the calculation time of the gas phase combustion and heat transfer is high. Therefore, a novel CFD-based approach was used to investigate and improve the process by converting the transient heating problem to steady-state cases. A comparison of the initial and the optimized furnace configuration showed an improved temperature distribution, where the maximum temperature difference in the furnace at the measurement position was decreased from approx. 200 K to 162 K. This approach showed that the transient simulation can be optimized, and further used for other applications where a transient simulation is computationally too demanding. … (more)
- Is Part Of:
- Applied thermal engineering. Volume 138(2018)
- Journal:
- Applied thermal engineering
- Issue:
- Volume 138(2018)
- Issue Display:
- Volume 138, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 138
- Issue:
- 2018
- Issue Sort Value:
- 2018-0138-2018-0000
- Page Start:
- 217
- Page End:
- 234
- Publication Date:
- 2018-06-25
- Subjects:
- Heat engineering -- Periodicals
Heating -- Equipment and supplies -- Periodicals
Periodicals
621.40205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13594311 ↗
http://www.elsevier.com/homepage/elecserv.htt ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.applthermaleng.2018.03.042 ↗
- Languages:
- English
- ISSNs:
- 1359-4311
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1580.101000
British Library DSC - BLDSS-3PM
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- 12290.xml