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Calorific value and compositional ultimate analysis with a case study of a Texas lignite

Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an adequate modeling already described in a previous publication for the case of proximate analysis data.11Olea, R.A., Luppens, J.A., 2015. Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite. International Journal of Coal Geology, 152, 80-93. Here we model the results of calorific value and ultimate analysis. We propose to use two different binary partitions, one per analysis, map the corresponding isometric logratio transformations, and backtransform the results. The methodology is illustrated using the same coal bed in the previous paper modeling proximate analysis data. Results are summarized using probability maps that, in the case of this deposit, show a prominent channel crossing the deposit and separating the best quality coal from that of lower quality

J.J. Egozcue and V. Pawlowsky-Glahn have been supported by the Ministerio de Economía y Competividad (Spain) under the project “CODA-RETOS” (Ref. MTM2015-65016-C2-1-R) and the project “METRICS” (Ref.MTM2012-33236); and by the AGAUR of the Generalitat de Catalunya under the project “COSDA” (Ref: 2014SGR551)

Elsevier

Manager: Ministerio de Economía y Competitividad (Espanya)
Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Author: Olea, Ricardo A.
Luppens, James A.
Egozcue, Juan José
Pawlowsky-Glahn, Vera
Abstract: Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an adequate modeling already described in a previous publication for the case of proximate analysis data.11Olea, R.A., Luppens, J.A., 2015. Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite. International Journal of Coal Geology, 152, 80-93. Here we model the results of calorific value and ultimate analysis. We propose to use two different binary partitions, one per analysis, map the corresponding isometric logratio transformations, and backtransform the results. The methodology is illustrated using the same coal bed in the previous paper modeling proximate analysis data. Results are summarized using probability maps that, in the case of this deposit, show a prominent channel crossing the deposit and separating the best quality coal from that of lower quality
J.J. Egozcue and V. Pawlowsky-Glahn have been supported by the Ministerio de Economía y Competividad (Spain) under the project “CODA-RETOS” (Ref. MTM2015-65016-C2-1-R) and the project “METRICS” (Ref.MTM2012-33236); and by the AGAUR of the Generalitat de Catalunya under the project “COSDA” (Ref: 2014SGR551)
Document access: http://hdl.handle.net/2072/298548
Language: eng
Publisher: Elsevier
Rights: Tots els drets reservats
Subject: Anàlisi multivariable
Multivariate analysis
Geoquímica
Geochemistry
Incertesa -- Models matemàtics
Uncertainty -- Mathematical models
Title: Calorific value and compositional ultimate analysis with a case study of a Texas lignite
Type: info:eu-repo/semantics/article
Repository: Recercat

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