Title: Methodology for Formulating Diesel Surrogate Fuels with Accurate Compositional, Ignition-Quality, and Volatility Characteristics

Abstract

In this study, a novel approach was developed to formulate surrogate fuels having characteristics that are representative of diesel fuels produced from real-world refinery streams. Because diesel fuels typically consist of hundreds of compounds, it is difficult to conclusively determine the effects of fuel composition on combustion properties. Surrogate fuels, being simpler representations of these practical fuels, are of interest because they can provide a better understanding of fundamental fuel-composition and property effects on combustion and emissions-formation processes in internal-combustion engines. In addition, the application of surrogate fuels in numerical simulations with accurate vaporization, mixing, and combustion models could revolutionize future engine designs by enabling computational optimization for evolving real fuels. Dependable computational design would not only improve engine function, it would do so at significant cost savings relative to current optimization strategies that rely on physical testing of hardware prototypes. The approach in this study utilized the state-of-the-art techniques of 13C and 1H nuclear magnetic resonance spectroscopy and the advanced distillation curve to characterize fuel composition and volatility, respectively. The ignition quality was quantified by the derived cetane number. Two well-characterized, ultra-low-sulfur #2 diesel reference fuels produced from refinery streams were used as target fuels: a 2007 emissions certificationmore » fuel and a Coordinating Research Council (CRC) Fuels for Advanced Combustion Engines (FACE) diesel fuel. A surrogate was created for each target fuel by blending eight pure compounds. The known carbon bond types within the pure compounds, as well as models for the ignition qualities and volatilities of their mixtures, were used in a multiproperty regression algorithm to determine optimal surrogate formulations. The predicted and measured surrogate-fuel properties were quantitatively compared to the measured target-fuel properties, and good agreement was found.« less

Authors:

Mueller, Charles J. ^[1]; Cannella, William J. ^[2]; Bruno, Thomas J. ^[3]; Bunting, Bruce ^[4]; Dettman, Heather D. ^[5]; Franz, James A. ^[6]; Huber, Marcia L. ^[3]; Natarajan, Mani ^[7]; Pitz, William J. ^[8]; Ratcliff, Matthew A. ^[9]; Wright, Ken ^[10]

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+ Show Author Affiliations

1. Sandia National Laboratories, East Avenue, Livermore, California 94550
2. Chevron Corporation, Chevron Way, Richmond, California 94802
3. National Institute of Standards and Technology, Boulder, Colorado 80305
4. Oak Ridge National Laboratory, Bethel Valley Road, Oak Ridge, Tennessee 37831
5. Natural Resources Canada (CanmetENERGY), Devon, Alberta T9G 1A6, Canada
6. Pacific Northwest National Laboratory, Battelle Boulevard, Richland, Washington, 99352
7. Marathon Petroleum Company, Main Street, Findlay, Ohio, 45840
8. Lawrence Livermore National Laboratory, East Avenue, Livermore, California 94550
9. National Renewable Energy Laboratory, Golden, Colorado 80401
10. Phillips 66 Company, Bartlesville, Oklahoma 74003

Publication Date:

Wed Jun 06 00:00:00 EDT 2012

Research Org.:

Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1123362

Alternate Identifier(s):

OSTI ID: 1343049

Report Number(s):

LLNL-JRNL-522072
Journal ID: ISSN 0887-0624

Grant/Contract Number:  

AC52-07NA27344

Resource Type:

Published Article

Journal Name:

Energy and Fuels

Additional Journal Information:

Journal Name: Energy and Fuels Journal Volume: 26 Journal Issue: 6; Journal ID: ISSN 0887-0624

Publisher:

American Chemical Society

Country of Publication:

United States

Language:

English

Subject:

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILITZATION; 37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; surrogate fuel; diesel; regression model; NMR; cetane number; advanced distillation curve