Quantitative Characterization of Multiphase Mixtures Applied to Oil Spill Thickness Measurement

Research output: ThesisDoctoral Thesis


During oil spill incidents, large amounts of oil mixtures spread through open water. Studies have shown that the effectiveness of oil cleaning techniques depends on knowing the actual thickness of oil films. However, under open water conditions, this task is challenging due to wavy sea conditions and varying environmental conditions. This research proposes a new sensing approach that can respond to this need by measuring the thickness of oil included in the multiphase air-oil-water mixture under open water conditions. There are three main contributions of the developed work: first, the proposed method relies on measuring the relative differences between a discrete set of sensing cells, thus, it allows the system to operate without requiring calibration against different types of oil or water. Second, using smart measurement algorithms, the system can operate under dynamic open water conditions and while being dragged. Third, through hardware- and software- based techniques, it mitigates the effect of oil fouling, an issue long considered problematic in the community of oil thickness measurement. In this dissertation, we present the design, implementation, and testing of two sensing systems, the first based on a self-capacitance sensor array and the second based on a dual modality capacitive/ultrasonic sensing platform aimed to provide oil-thickness measurements in real-time. In addition, we present two additional applications to our proposed sensing methodology related to the measurement of oil viscosity in online applications and the characterization of soil water content. The systems and methods presented in this dissertation have a broader impact on the general field of multiphase characterization.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • American University of Beirut
  • Elhajj, Imad H., Supervisor, External person
  • Asmar, Daniel, Supervisor, External person
Award date22 Dec 2020
Publication statusPublished - 12 Jan 2021


  • sensors
  • instrumentation
  • measurement
  • oil thickness


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