Determining the composition of binary coal blends using Bayes theorem

Binary coal blends were prepared using a typical UK steam coal with four different coals which were then analyzed using random vitrinite reflectance ( R random). Deconvolution of the vitrinite reflectance data was attempted using Bayes Theorem in order to calculate the composition of each blend on a...

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Published inFuel (Guildford) Vol. 82; no. 2; pp. 117 - 125
Main Authors Lester, Edward, Watts, David, Cloke, Mike, Langston, Paul
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 2003
Elsevier
Subjects
Applied sciences
Bayes theorem
Coal and derived products
Coal blends
Coal petrography
Energy
Exact sciences and technology
Fuels
p.f
Structure, chemical and physical properties
Vitrinite reflectance
United Kingdom
Europe
Coal blends
p.f
Vitrinite reflectance
Coal petrography
Bayes theorem
Composition
Iterative method
Vitrinite
Algorithm
Mixture
Coal
Bayes methods
Reflectance
Online AccessGet full text
ISSN0016-2361
1873-7153
DOI10.1016/S0016-2361(02)00223-5

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Abstract Binary coal blends were prepared using a typical UK steam coal with four different coals which were then analyzed using random vitrinite reflectance ( R random). Deconvolution of the vitrinite reflectance data was attempted using Bayes Theorem in order to calculate the composition of each blend on a % vol/vol basis. Modifications were made to the initial Bayes algorithm to take into account experimental error. The effect of using increasing amounts of data on the blend predictions was also investigated. Accurate predictions were achieved when using more than 100 reflectance measurements from each component and iterating the Bayes algorithm more than 100 times.
AbstractList Binary coal blends were prepared using a typical UK steam coal with 4 different coals which were then analysed using vitrinite reflectance. Deconvolution of the vitrinite reflectance data was attempted using Bayes Theorem in order to calculate the composition of each blend on a % vol/vol basis. The effect of using increasing amounts of data on the blend predictions was also investigated. It was found that accurate predictions could be achieved when using more than 100 reflectance measurements from each component and iterating the Bayes algorithm more than 100 times.
Binary coal blends were prepared using a typical UK steam coal with four different coals which were then analyzed using random vitrinite reflectance ( R random). Deconvolution of the vitrinite reflectance data was attempted using Bayes Theorem in order to calculate the composition of each blend on a % vol/vol basis. Modifications were made to the initial Bayes algorithm to take into account experimental error. The effect of using increasing amounts of data on the blend predictions was also investigated. Accurate predictions were achieved when using more than 100 reflectance measurements from each component and iterating the Bayes algorithm more than 100 times.
Author Cloke, Mike
Lester, Edward
Watts, David
Langston, Paul
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Cites_doi 10.1016/S0032-5910(00)00359-4
10.1016/0016-2361(94)90081-7
10.1016/S0166-5162(00)00016-1
10.1098/rstl.1763.0045
10.1016/S0166-5162(99)00036-1
10.1016/0016-2361(94)00014-I
10.1021/ef9501713
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Issue 2
Keywords Coal blends
p.f
Vitrinite reflectance
Coal petrography
Bayes theorem
Composition
Iterative method
Vitrinite
Algorithm
Mixture
Coal
Bayes methods
Reflectance
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West (BIB4) 1997
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Langston (10.1016/S0016-2361(02)00223-5_BIB9) 2002
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Cloke (10.1016/S0016-2361(02)00223-5_BIB10) 1995; 74
Lester (10.1016/S0016-2361(02)00223-5_BIB11) 1996; 10
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Snippet Binary coal blends were prepared using a typical UK steam coal with four different coals which were then analyzed using random vitrinite reflectance ( R...
Binary coal blends were prepared using a typical UK steam coal with 4 different coals which were then analysed using vitrinite reflectance. Deconvolution of...
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SubjectTerms Applied sciences
Bayes theorem
Coal and derived products
Coal blends
Coal petrography
Energy
Exact sciences and technology
Fuels
p.f
Structure, chemical and physical properties
Vitrinite reflectance
Title Determining the composition of binary coal blends using Bayes theorem
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