Modeling Soot Oxidation and Gasification with Bayesian Statistics [electronic resource]

• Ngôn ngữ: eng
• Ký hiệu phân loại: 642.6 Table service
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. National Nuclear Security Administration ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2017
• Mô tả vật lý: Size: p. 11291-11303 : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 267756
• Chủ đề: 1. 01 coal, lignite, and peat; 2. 97 mathematics and computing; 3. Soot, oxidation, gasification, bayes' law; 4. Statistical modelling, oxidation, gasification, bayesian statistics

Tóm tắt

 This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems. This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents
  second for gasification where soot particles are attacked by H2O or CO2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumption model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies. Significant variation is found in the CO2 gasification rates.