Fuel Pipeline Thermal Conductivity in Automatic Wet Stock Reconciliation Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9728)

Abstract

In the fuel industry, as in any other, it is important to have control over the resources that directly generate profit. In the case of a petrol station this is a gasoline that passes a very complicated path from the terminal, through underground tank up to the tank inside the car. At most stages of its journey, the system can control the volume, height, temperature, the physical processes which is subjected to and based on this, predict its state. This is done by analysing the telemetry data and various types of flow models. In this paper we want to concentrate on one of the most difficult parts of this system. Difficult, because usually undocumented and invisible - a system of piping between the tank and the fuel distributor. Fuel that is located there, is usually beyond the observation of telemetry system and its volume changes over time. We want to focus on the nature of these changes and predict its impact on the balance of the fuel at the station.

Keywords

AWSR Thermal conductivity Reconciliation 

References

  1. 1.
    Brown Jr., G.F., Rogers, W.F.: A bayesian approach to demand estimation and inventory provisioning. Technical report DTIC Document (1972)Google Scholar
  2. 2.
    Cengel, Y.: Introduction to Thermodynamics and Heat Transfer+ EES Software. McGraw Hill Higher Education Press, New York (2007)Google Scholar
  3. 3.
    Gadzhiev, C.M.: Detection of and allowance for loss of petroleum products due to leaks and evaporation in tanks. Meas. Tech. 37(2), 159–161 (1994)CrossRefGoogle Scholar
  4. 4.
    Hestenes, M.R.: Multiplier and gradient methods. J. Optim. Theory Appl. 4(5), 303–320 (1969)MathSciNetCrossRefMATHGoogle Scholar
  5. 5.
    Keating, J.P., Dunn, W.W., Dunn, W.D.: Storage tank and line leakage detection and inventory reconciliation method. US Patent 5,297,42 3 (1994)Google Scholar
  6. 6.
    O’connor, P.M.: Automated statistical inventory reconcilation system for convenience stores and auto/truck service stations. US Patent 5,400,253 (1995)Google Scholar
  7. 7.
    Rogers, W.F.: Exact null distributions and asymptotic expansions for rank test statistics. Ph.D. thesis, Department of Statistics, Stanford University (1971)Google Scholar
  8. 8.
    Rogers, W.F., Collins, J.R., Jones, J.B.: Method and apparatus for monitoring operational performance of fluid storage systems. US Patent 5,757,664 (1998)Google Scholar
  9. 9.
    Rogers, W.F., Collins, J.R., Jones, J.B.: Method and apparatus for monitoring operational performance of fluid storage systems. US Patent 6,401,045 (2002)Google Scholar
  10. 10.
    US Environmental Protection Agency: Standard Test Procedures For Evaluating Leak Detection Methods. Automatic Tank Gauging Systems (1990)Google Scholar
  11. 11.
    US Environmental Protection Agency: Doing Inventory Control Right For Underground Storage Tanks (1993)Google Scholar
  12. 12.
    US Environmental Protection Agency: Guidance for Data Quality Assessment. Practical Methods for Data Analysis (1993)Google Scholar
  13. 13.
    US Environmental Protection Agency: Introduction To Statistical Inventory Reconciliation For Underground Storage Tanks (1995)Google Scholar
  14. 14.
    Williams, B.N., Kauffmann, G.A.: Method and apparatus for continuous tank monitoring. US Patent 5,363,093 (1994)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Pawel Foszner
    • 1
    • 2
  • Aleksandra Gruca
    • 2
  • Jakub Bularz
    • 1
  1. 1.AIUT Sp. z o.o.GliwicePoland
  2. 2.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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