Automated Simulation Error based Reduction (ASER) of large chemical reaction mechanisms. (2nd November 2019)
- Record Type:
- Journal Article
- Title:
- Automated Simulation Error based Reduction (ASER) of large chemical reaction mechanisms. (2nd November 2019)
- Main Title:
- Automated Simulation Error based Reduction (ASER) of large chemical reaction mechanisms
- Authors:
- Veerappan, Devi Raghavee
Ramanathan, Karthik
Kaisare, Niket S. - Abstract:
- Highlights: An Automated Simulation Error Based Reduction (ASER) approach is proposed. ASER is implemented with Directed Relation Graph and Principal Component Analysis. ASER-DRG-PCA is used to reduce gas-phase H2 –O2, and GaAs deposition mechanisms. Reduced mechanisms with simulation error below the specified limit are generated. Establishes relationship between simulation error and threshold parameter for reduction. Abstract: We propose an Automated Simulation Error based Reduction (ASER) algorithm for determining reduced kinetic models. It directly uses simulation error between detailed and reduced mechanisms for determining the final reduced model. ASER is implemented using Directed Relation Graph (DRG) for species reduction and Principal Component Analysis with concentration sensitivity (PCA-S) for reaction reduction. The thresholds for DRG importance index, and the cutoffs for eigenvalues and eigenvectors in PCA determine the final reduced mechanisms. However, the effect of these thresholds on the reduced mechanism is non-intuitive, as they are not explicitly correlated with the simulation error. ASER indirectly establishes this correlation by starting with large values of thresholds and updating them iteratively until reduced mechanism that meets the user-specified simulation error is obtained. A combination of ASER–DRG followed by ASER–PCA is shown to yield an optimally reduced mechanism. The proposed algorithms are tested using gas-phase H2 -O2 and gas/surface GaAsHighlights: An Automated Simulation Error Based Reduction (ASER) approach is proposed. ASER is implemented with Directed Relation Graph and Principal Component Analysis. ASER-DRG-PCA is used to reduce gas-phase H2 –O2, and GaAs deposition mechanisms. Reduced mechanisms with simulation error below the specified limit are generated. Establishes relationship between simulation error and threshold parameter for reduction. Abstract: We propose an Automated Simulation Error based Reduction (ASER) algorithm for determining reduced kinetic models. It directly uses simulation error between detailed and reduced mechanisms for determining the final reduced model. ASER is implemented using Directed Relation Graph (DRG) for species reduction and Principal Component Analysis with concentration sensitivity (PCA-S) for reaction reduction. The thresholds for DRG importance index, and the cutoffs for eigenvalues and eigenvectors in PCA determine the final reduced mechanisms. However, the effect of these thresholds on the reduced mechanism is non-intuitive, as they are not explicitly correlated with the simulation error. ASER indirectly establishes this correlation by starting with large values of thresholds and updating them iteratively until reduced mechanism that meets the user-specified simulation error is obtained. A combination of ASER–DRG followed by ASER–PCA is shown to yield an optimally reduced mechanism. The proposed algorithms are tested using gas-phase H2 -O2 and gas/surface GaAs deposition mechanisms. … (more)
- Is Part Of:
- Computers & chemical engineering. Volume 130(2019)
- Journal:
- Computers & chemical engineering
- Issue:
- Volume 130(2019)
- Issue Display:
- Volume 130, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 130
- Issue:
- 2019
- Issue Sort Value:
- 2019-0130-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-11-02
- Subjects:
- Mechanism reduction -- Principal Component Analysis -- Directed Relation Graph -- Simulation error -- Semiconductor manufacturing -- Chemical vapor deposition
Chemical engineering -- Data processing -- Periodicals
660.0285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00981354 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compchemeng.2019.106560 ↗
- Languages:
- English
- ISSNs:
- 0098-1354
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.664000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11853.xml