Skip to main content
SpringerLink
Log in

Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Recent efforts in predicting rocket propulsion (RP-1) fuel performance through modeling put greater emphasis on obtaining detailed and accurate fuel properties, as well as elucidating the relationships between fuel compositions and their properties. Herein, we study multidimensional chromatographic data obtained by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC–TOFMS) to analyze RP-1 fuels. For GC × GC separations, RTX-Wax (polar stationary phase) and RTX-1 (non-polar stationary phase) columns were implemented for the primary and secondary dimensions, respectively, to separate the chemical compound classes (alkanes, cycloalkanes, aromatics, etc.), providing a significant level of chemical compositional information. The GC × GC–TOFMS data were analyzed using partial least squares regression (PLS) chemometric analysis to model and predict advanced distillation curve (ADC) data for ten RP-1 fuels that were previously analyzed using the ADC method. The PLS modeling provides insight into the chemical species that impact the ADC data. The PLS modeling correlates compositional information found in the GC × GC–TOFMS chromatograms of each RP-1 fuel, and their respective ADC, and allows prediction of the ADC for each RP-1 fuel with good precision and accuracy. The root-mean-square error of calibration (RMSEC) ranged from 0.1 to 0.5 °C, and was typically below ∼0.2 °C, for the PLS calibration of the ADC modeling with GC × GC–TOFMS data, indicating a good fit of the model to the calibration data. Likewise, the predictive power of the overall method via PLS modeling was assessed using leave-one-out cross-validation (LOOCV) yielding root-mean-square error of cross-validation (RMSECV) ranging from 1.4 to 2.6 °C, and was typically below ∼2.0 °C, at each % distilled measurement point during the ADC analysis.

The application of chemometrics to relate GC × GC–TOFMS chromatograms to advanced distillation curve (ADC) data allows for accurate prediction of distillation curves for kerosene rocket propellant (RP-1) fuels and contributes to the chemical characterization of fuel components and their influence on fuel performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Billingsley MC, Edwards T, Shafer LM, Bruno TJ (2010) Extent and Impacts of Hydrocarbon Fuel Compositional Variability for Aerospace Propulsion Systems, Proc. 46th AIAA/ASME/SAE/ASEE Joint Propulsion Conference

  2. Lovestead TM, Windom BC, Riggs JR, Nickell C, Bruno TJ (2010) Assessment of the compositional variability of RP-1 and RP-2 with the advanced distillation curve approach. Energy Fuel 24:5611–5623. doi:10.1021/ef100994w

    Article  CAS  Google Scholar 

  3. Gough RV, Bruno TJ (2013) Composition-explicit distillation curves of alternative turbine fuels. Energy Fuel 27:294–302. doi:10.1021/ef3016848

    Article  CAS  Google Scholar 

  4. Hsieh PY, Abel KR, Bruno TJ (2013) Analysis of marine diesel fuel with the advanced distillation curve method. Energy Fuel 27:804–810. doi:10.1021/ef3020525

    Article  CAS  Google Scholar 

  5. Burger JL, Bruno TJ (2012) Application of the advanced distillation curve method to the variability of jet fuels. Energy Fuel 26:3661–3671. doi:10.1021/ef3006178

    Article  CAS  Google Scholar 

  6. Begue NJ, Cramer JA, Von Bargen C, Myers KM, Johnson KJ, Morris RE (2011) Automated method for determining hydrocarbon distributions in mobility fuels. Energy Fuel 25:1617–1623. doi:10.1021/ef101635a

    Article  CAS  Google Scholar 

  7. Christensen JH, Tomasi G, Hansen AB (2005) Chemical fingerprinting of petroleum biomarkers using time warping and PCA. Environ Sci Technol 39:255–260. doi:10.1021/es049832d

    Article  CAS  Google Scholar 

  8. Bruno TJ (2006) Improvements in the measurement of distillation curves. 1. A composition-explicit approach. Ind Eng Chem Res 45:4371–4380. doi:10.1021/ie051393j

    Article  CAS  Google Scholar 

  9. Bruno TJ, Smith BL (2006) Improvements in the measurement of distillation curves. 2. Application to aerospace/aviation fuels RP-1 and S-8. Ind Eng Chem Res 45:4381–4388. doi:10.1021/ie051394b

    Article  CAS  Google Scholar 

  10. Bruno TJ, Ott LS, Smith BL, Lovestead TM (2010) Complex fluid analysis with the advanced distillation curve approach. Anal Chem 82:777–783. doi:10.1021/ac902002j

    Article  CAS  Google Scholar 

  11. Smith BL, Bruno TJ (2007) Improvements in the measurement of distillation curves. 4. Application to the aviation turbine fuel jet-A. Ind Eng Chem Res 46:310–320. doi:10.1021/ie060938m

    Article  CAS  Google Scholar 

  12. Ott LS, Smith BL, Bruno TJ (2008) Advanced distillation curve measurements for corrosive fluids: application to two crude oils. Fuel 87:3055–3064. doi:10.1016/j.fuel.2008.04.032

    Article  CAS  Google Scholar 

  13. Ott LS, Hadler AB, Bruno TJ (2008) Variability of the rocket propellants RP-1, RP-2, and TS-5: application of a composition- and enthalpy-explicit distillation curve method. Ind Eng Chem Res 47:9225–9233. doi:10.1021/ie800988u

    Article  CAS  Google Scholar 

  14. Lovestead TM, Bruno TJ (2009) A comparison of the hypersonic vehicle fuel JP-7 to the rocket propellants RP-1 and RP-2 with the advanced distillation curve method. Energy Fuel 23:3637–3644. doi:10.1021/ef900096q

    Article  CAS  Google Scholar 

  15. Windom BC, Bruno TJ (2011) Assessment of the composition and distillation properties of thermally stressed RP-1 and RP-2: application to fuel regenerative cooling. Energy Fuel 25:5200–5214. doi:10.1021/ef201077a

    Article  CAS  Google Scholar 

  16. Smith BL, Bruno TJ (2007) Improvements in the measurement of distillation curves. 3. Application to gasoline and gasoline + methanol mixtures. Ind Eng Chem Res 46:297–309. doi:10.1021/ie060937u

    Article  CAS  Google Scholar 

  17. Windom BC, Bruno TJ (2011) Improvements in the measurement of distillation curves. 5. Reduced pressure advanced distillation curve method. Ind Eng Chem Res 50:1115–1126. doi:10.1021/ie101784g

    Article  CAS  Google Scholar 

  18. Windom BC, Bruno TJ (2013) Application of pressure-controlled advanced distillation curve analysis: virgin and waste oils. Ind Eng Chem Res 52:327–337. doi:10.1021/ie302399v

    CAS  Google Scholar 

  19. Bruno TJ, Wolk A, Naydich A (2009) Stabilization of biodiesel fuel at elevated temperature with hydrogen donors: evaluation with the advanced distillation curve method. Energy Fuel 23:1015–1023. doi:10.1021/ef800740d

    Article  CAS  Google Scholar 

  20. Huber ML, Lemmon EW, Bruno TJ (2009) Effect of RP-1 compositional variability on thermophysical properties. Energy Fuel 23:5550–5555. doi:10.1021/ef900597q

    Article  CAS  Google Scholar 

  21. Omais B, Courtiade M, Charon N, Thiébaut D, Quignard A, Hennion MC (2011) Investigating comprehensive two-dimensional gas chromatography conditions to optimize the separation of oxygenated compounds in a direct coal liquefaction middle distillate. J Chromatogr A 1218:3233–3240. doi:10.1016/j.chroma.2010.12.049

    Article  CAS  Google Scholar 

  22. Kehimkar B, Hoggard JC, Marney LC, Billingsley MC, Fraga CG, Bruno TJ, Synovec RE (2014) Correlation of rocket propulsion fuel properties with chemical composition using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry followed by partial least squares regression analysis. J Chromatogr A 1327:132–140. doi:10.1016/j.chroma.2013.12.060

    Article  CAS  Google Scholar 

  23. Hope JL, Sinha AE, Prazen BJ, Synovec RE (2005) Evaluation of the DotMap algorithm for locating analytes of interest based on mass spectral similarity in data collected using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry. J Chromatogr A 1086:185–192. doi:10.1016/j.chroma.2005.06.026

    Article  CAS  Google Scholar 

  24. Mohler RE, Dombek KM, Hoggard JC, Young ET, Synovec RE (2006) Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry analysis of metabolites in fermenting and respiring yeast cells. Anal Chem 78:2700–2709. doi:10.1021/ac052106o

    Article  CAS  Google Scholar 

  25. Pierce KM, Hoggard JC, Mohler RE, Synovec RE (2008) Recent advancements in comprehensive two-dimensional separations with chemometrics. J Chromatogr A 1184:341–352. doi:10.1016/j.chroma.2007.07.059

    Article  CAS  Google Scholar 

  26. Hoggard JC, Synovec RE (2008) Automated resolution of nontarget analyte signals in GC × GC-TOFMS data using parallel factor analysis. Anal Chem 80:6677–6688. doi:10.1021/ac800624e

    Article  CAS  Google Scholar 

  27. Fraga CG, Prazen BJ, Synovec RE (2000) Comprehensive two-dimensional gas chromatography and chemometrics for the high-speed quantitative analysis of aromatic isomers in a jet fuel using the standard addition method and an objective retention time alignment algorithm. Anal Chem 72:4154–4162. doi:10.1021/ac000303b

    Article  CAS  Google Scholar 

  28. Prazen BJ, Johnson KJ, Weber A, Synovec RE (2001) Two-dimensional gas chromatography and trilinear partial least squares for the quantitative analysis of aromatic and naphthene content in naphtha. Anal Chem 73:5677–5682. doi:10.1021/ac010637g

    Article  CAS  Google Scholar 

  29. Johnson KJ, Synovec RE (2002) Pattern recognition of jet fuels: comprehensive GC × GC with ANOVA-based feature selection and principal component analysis. Chemom Intell Lab Syst 60:225–237. doi:10.1016/S0169-7439(01)00198-8

    Article  CAS  Google Scholar 

  30. Johnson KJ, Prazen BJ, Young DC, Synovec RE (2004) Quantification of naphthalenes in jet fuel with GC × GC/Tri-PLS and windowed rank minimization retention time alignment. J Sep Sci 27:410–416. doi:10.1002/jssc.200301640

    Article  CAS  Google Scholar 

  31. Pierce KM, Kehimkar B, Marney LC, Hoggard JC, Synovec RE (2012) Review of chemometric analysis techniques for comprehensive two dimensional separations data. J Chromatogr A 1255:3–11. doi:10.1016/j.chroma.2012.05.050

    Article  CAS  Google Scholar 

  32. Marney LC, Siegler WC, Parsons BA, Hoggard JC, Wright BW, Synovec RE (2013) Tile-based Fisher-ratio software for improved feature selection analysis of comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry data. Talanta 115:887–895. doi:10.1016/j.talanta.2013.06.038

    Article  CAS  Google Scholar 

  33. Hoggard JC, Siegler WC, Synovec RE (2009) Toward automated peak resolution in complete GC × GC–TOFMS chromatograms by PARAFAC. J Chemom 23:421–431. doi:10.1002/cem.1239

    Article  CAS  Google Scholar 

  34. De Godoy LAF, Ferreira EC, Pedroso MP, de Fidélis CHV, Augusto F, Poppi RJ (2008) Quantification of kerosene in gasoline by comprehensive two-dimensional gas chromatography and N-way multivariate analysis. Anal Lett 41:1603–1614. doi:10.1080/00032710802122222

    Article  Google Scholar 

  35. Pedroso MP, de Godoy LAF, Ferreira EC, Poppi RJ, Augusto F (2008) Identification of gasoline adulteration using comprehensive two-dimensional gas chromatography combined to multivariate data processing. J Chromatogr A 1201:176–182. doi:10.1016/j.chroma.2008.05.092

    Article  CAS  Google Scholar 

  36. De Godoy LAF, Pedroso MP, Ferreira EC, Augusto F, Poppi RJ (2011) Prediction of the physicochemical properties of gasoline by comprehensive two-dimensional gas chromatography and multivariate data processing. J Chromatogr A 1218:1663–1667. doi:10.1016/j.chroma.2011.01.056

    Article  Google Scholar 

  37. Hall GJ, Frysinger GS, Aeppli C, Carmichael CA, Gros J, Lemkau KL, Nelson RK, Reddy CM (2013) Oxygenated weathering products of Deepwater Horizon oil come from surprising precursors. Mar Pollut Bull 75:140–149. doi:10.1016/j.marpolbul.2013.07.048

    Article  CAS  Google Scholar 

  38. Pierce KM, Schale SP (2011) Predicting percent composition of blends of biodiesel and conventional diesel using gas chromatography–mass spectrometry, comprehensive two-dimensional gas chromatography–mass spectrometry, and partial least squares analysis. Talanta 83:1254–1259. doi:10.1016/j.talanta.2010.07.084

    Article  CAS  Google Scholar 

  39. Mogollon NGS, de Ribeiro FAL, Lopez MM, Hantao LW, Poppi RJ, Augusto F (2013) Quantitative analysis of biodiesel in blends of biodiesel and conventional diesel by comprehensive two-dimensional gas chromatography and multivariate curve resolution. Anal Chim Acta 796:130–136. doi:10.1016/j.aca.2013.07.071

    Article  Google Scholar 

  40. Westad F, Afseth NK, Bro R (2007) Finding relevant spectral regions between spectroscopic techniques by use of cross model validation and partial least squares regression. Anal Chim Acta 595:323–327. doi:10.1016/j.aca.2007.02.015

    Article  CAS  Google Scholar 

  41. Rajalahti T, Kvalheim OM (2011) Multivariate data analysis in pharmaceutics: a tutorial review. Int J Pharm 417:280–290. doi:10.1016/j.ijpharm.2011.02.019

    Article  CAS  Google Scholar 

  42. Gowen AA, Downey G, Esquerre C, O’Donnell CP (2011) Preventing over-fitting in PLS calibration models of near-infrared (NIR) spectroscopy data using regression coefficients. J Chemom 25:375–381. doi:10.1002/cem.1349

    Article  CAS  Google Scholar 

  43. Geladi P, Kowalski BR (1986) Partial least-squares regression: a tutorial. Anal Chim Acta 185:1–17. doi:10.1016/0003-2670(86)80028-9

    Article  CAS  Google Scholar 

  44. Mohler RE, Dombek KM, Hoggard JC, Pierce KM, Young ET, Synovec RE (2007) Comprehensive analysis of yeast metabolite GC × GC–TOFMS data: combining discovery-mode and deconvolution chemometric software. Analyst 132:756–767. doi:10.1039/B700061H

    Article  CAS  Google Scholar 

  45. Pierce KM, Hoggard JC (2013) Chromatographic data analysis. Part 3.3.4: handling hyphenated data in chromatography. Anal Methods. doi:10.1039/C3AY40965A

    Google Scholar 

  46. Christian GD (2004) Analytical chemistry, 6th edn. Wiley, New York

    Google Scholar 

Download references

Acknowledgments

The work at the University of Washington (UW) was performed under subcontract to ERC, Incorporated, Air Force Research Laboratory, Edwards AFB, CA. The fuels were provided by the Air Force Research Laboratory/RQRC, Edwards AFB, CA. Certain commercial equipment, instruments or materials are identified in this paper in order to adequately specify the experimental procedure. Such identification does not imply recommendation or endorsement by the University of Washington, the United States Air Force, or the National Institute of Standards and Technology, nor does it imply the materials or equipment identified are necessarily the best available for that purpose.

Author information

Authors and Affiliations

  1. Department of Chemistry, University of Washington, Box 351700, Seattle, WA, 98195, USA

    Benjamin Kehimkar, Brendon A. Parsons, Jamin C. Hoggard & Robert E. Synovec

  2. Air Force Research Laboratory/RQRC, 10 E Saturn Blvd, Edwards AFB, CA, 93524, USA

    Matthew C. Billingsley

  3. Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO, 80305, USA

    Thomas J. Bruno

Authors
  1. Benjamin Kehimkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brendon A. Parsons
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jamin C. Hoggard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matthew C. Billingsley
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas J. Bruno
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Robert E. Synovec
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert E. Synovec.

Additional information

Published in the topical collection Multidimensional Chromatography with guest editors Torsten C. Schmidt, Oliver J. Schmitz, and Thorsten Teutenberg.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kehimkar, B., Parsons, B.A., Hoggard, J.C. et al. Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis. Anal Bioanal Chem 407, 321–330 (2015). https://doi.org/10.1007/s00216-014-8233-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-014-8233-6

Keywords

Search

Navigation