Outlier analysis for a silicon nanoparticle population balance model
View / Open Files
Publication Date
2017Journal Title
Combustion and Flame
ISSN
0010-2180
Publisher
Elsevier BV
Volume
177
Pages
89-97
Type
Article
Metadata
Show full item recordCitation
Mosbach, S., Menz, W., & Kraft, M. (2017). Outlier analysis for a silicon nanoparticle population balance model. Combustion and Flame, 177 89-97. https://doi.org/10.1016/j.combustflame.2016.12.006
Abstract
© 2016 The Combustion Institute We assess the impact of individual experimental observations on a multivariate population balance model for the formation of silicon nanoparticles from the thermal decomposition of silane by means of basic regression influence diagnostics. The nanoparticle model is closely related to one which has been used to simulate soot formation in flames and includes morphological and compositional details which allow re presentation of primary particles within aggregates, and of coagulation, surface growth, and sintering processes. Predicted particle size distributions are optimised against 19 experiments across ranges of initial temperature, pressure, residence time, and initial silane mass fraction. The influence of each experimental observation on the model parameter estimates is then quantified using the Cook distance and DFBETA measures. Seven model parameters are included in the analysis, with five Arrhenius pre-exponential factors in the gas-phase kinetic rate expressions, and two kinetic rate constants in the population balance model. The analysis highlights certain experimental conditions and kinetic parameters which warrant closer inspection due to large influence, thus providing clues as to which aspects of the model require improvement. We find the insights provided can be useful for future model development and planning of experiments.
Sponsorship
This work was partly funded by the Cambridge Australia Trust, by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme, and by the European Union Horizon 2020 Research and Innovation Programme under Grant agreement 646121.
Funder references
National Research Foundation Singapore (via Cambridge Centre for Advanced Research and Education in Singapore (CARES)) (unknown)
National Research Foundation Singapore (via Cambridge Centre for Advanced Research and Education in Singapore (CARES)) (unknown)
European Commission Horizon 2020 (H2020) Industrial Leadership (IL) (646121)
Identifiers
External DOI: https://doi.org/10.1016/j.combustflame.2016.12.006
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284536
Rights
Licence:
http://www.rioxx.net/licenses/all-rights-reserved
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.