You are being redirected because this document is part of your ASTM Compass® subscription.
    This document is part of your ASTM Compass® subscription.


    Chapter 11 | Spectroscopic Methods for Spark Ignition Fuels

      Format Pages Price  
    PDF (0 B) 8 $25   ADD TO CART
    Complete Source PDF (27.23 MB) 405 $120   ADD TO CART

    Cite this document

    X Add email address send
      .RIS For RefWorks, EndNote, ProCite, Reference Manager, Zoteo, and many others.   .DOCX For Microsoft Word


    Spectral analysis holds significant promise for determining values of bulk properties of spark ignition fuel and as a significant tool for the blending process. Spectral analysis includes various types of infrared and Raman technologies. Properties predicted are octane, volatility, distillation and certain specific chemical groups of interest. Research into spectral analysis of spark ignition fuels started earnestly in the early 1990s, resulting in early adoption, confusion about the technology, and later enhancements to the technology. The main mathematical method is multivariate, including partial least squares and principle component analysis. There are different approaches to predict nonlinear property values. Lean six-sigma measurement studies and control charting allow for establishment and maintenance of confidence in the test method for process control and, ultimately for product certification. Changes in the octane specification from that of a neat subgrade to “as if” specifications for 10 % ethanol blends are addressed, especially in light of the current FTC octane rule. Spectral analysis can be a very useful tool to proactively enhance refinery fuels blending by providing insight into the specific linear contribution of each blend component for each property around a given blend recipe by lean six-sigma design of experiment. This results in more precise blending control and better confidence that a blend is on-spec with minimal property giveaway.


    spark ignition fuel, spectroscopy, infrared, Fourier transform infrared, near infrared, Fourier transform near infrared, Raman, gasoline blending

    Author Information:

    Mertens, Daniel C.
    Horseshoe Bay, TX

    Committee/Subcommittee: D02.04

    DOI: 10.1520/MNL120170015