Partial least-squares predictions of nonpetroleum-derived fuel content and resultant properties when blended with petroleum-derived fuels (Record no. 170212)

MARC details
000 -LEADER
fixed length control field 02408nab a2200193 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2009 xxu
245 00 - TITULO
Título Partial least-squares predictions of nonpetroleum-derived fuel content and resultant properties when blended with petroleum-derived fuels
260 ## - PUBLICACION, DISTRIBUCION, ETC
Lugar de publicación, distribución, etc.
Nombre de publicador, distribuidor, etc.
Fecha de publicación, distribución, etc. ene. 2009
270 ## - FECHA DE CARGA
Fecha de carga 27/07/2009 ; 27/07/2009
300 ## - DESCRIPCION FISICA
Otra extensión 8 p. ; 894-902
520 ## - RESUMEN, ETC
Resumen Transcripción del resúmen publicado por el autor: The U.S. Naval Research Laboratory has been engaged in a research program to develop sensor-based technologies to perform rapid automated fuel-quality surveillance. This approach is based on the development of quantitative models from the partial least-squares (PLS) regression of near-infrared (NIR) spectroscopic measurements of a representative calibration set of petroleum-derived fuels. As fuels from nonpetroleum sources become available it will be necessary to extend these chemometric models to accommodate Fischer-Tropsch (FT) synthetic fuels and biofuels. This extension is complicated by the fact that these new fuels will be initially introduced as blending components with petroleum-derived fuels. Chemometric modeling methodologies have been developed to identify and estimate the content of FT and biofuel present; then this information is used to estimate the bulk properties of the blends. With this approach, biodiesel content can be predicted, with respect to absolute error, to within 1.7% of its true value 95% of the time with a lower limit of detection of 1.5% using a single PLS model. The diesel fuel PLS property prediction models are applicable to diesel fuels blended with biodiesel fuel once that particular biodiesel fuel is incorporated in said models. The FT content in blends with petroleum fuels can be predicted, with respect to absolute error, to within 6.9% of its true value 95% of the time with a lower limit of detection of 15% using a series of paired PLS models for identification and quantification. In the presence of FT fuel, the PLS property models can be used after applying a correction factor that is derived from the identity and concentration of the FT fuel present.
773 0# - CORRECCIÓN
Título Energy & fuels
Partes relacionadas 23
942 ## - DESC. DE MATERIAL
Tipo de item KOHA Artículo de Revista
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Cramer, Jeffrey A.
9 (RLIN) 41625
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Morris, Robert E.
9 (RLIN) 35974
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Giordano, Braden
9 (RLIN) 41626
Holdings
Biblioteca propietaria Biblioteca actual Fecha de adquisición Inventario Total de préstamos Inventario Fecha de carga Tipo de item KOHA
Biblioteca Alejandro Angel Bulgheroni Biblioteca Alejandro Angel Bulgheroni 05/03/2026 200045039   200045039 05/03/2026 Artículo de Revista


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