Determination of Gas Void Fraction in a Bubble Column Reactor Using Fiber-Optic Distributed Acoustic Sensing

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Abstract

The broad application field of Bubble Column Reactors (BCRs) is contrasted by complex inherent dynamics, which gives rise to the need for intelligent monitoring systems. The latest advances in fiber-optic sensor technology represent a promising approach to enable detailed insights into large-scale geometries. In this work we report on the use of a novel method to non-intrusively determine the gas void fraction in BCRs using Distributed Acoustic Sensing (DAS). This study provides a holistic concept demonstration, covering the physical background, instrumentation, data processing, and testing. The optical fiber used was wound helically around the reactor, allowing the propagation of acoustic emissions to be detected and the speed of sound to be determined. The technology is based on a passive approach and uses the natural sound emissions of the gas bubbles sparged into the vessel. Within the framework of this paper, first tests were carried out on a laboratory-scale 2-meter-high water-air reactor. The application demonstrates encouraging outcomes compared to a reference method based on height expansion. An examination of gas void fractions up to 4% reveals that the DAS measurement underestimates the void fraction by an absolute maximum of 0.62% using a cross-correlation algorithm. The presented conceptional study highlights the significant potential of DAS as a non-intrusive sensing technique for BCRs.

Original languageEnglish
Article number7512610
Number of pages10
JournalIEEE Transactions on Instrumentation and Measurement
Volume74
DOIs
Publication statusPublished - 12 Sept 2025

Fields of science

  • 202012 Electrical measurement technology
  • 202016 Electrical engineering
  • 202027 Mechatronics
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 211908 Energy research
  • 202024 Laser technology
  • 202037 Signal processing
  • 202036 Sensor systems
  • 203016 Measurement engineering
  • 202021 Industrial electronics
  • 204003 Chemical process engineering
  • 104027 Computational chemistry
  • 209006 Industrial biotechnology
  • 207111 Environmental engineering
  • 204 Chemical Process Engineering
  • 104028 Per- and polyfluoroalkyl substances (PFAS)

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

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