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Measuring Three-Dimensional Temperature Distributions in Steel-Concrete Composite Slabs Subjected to Fire Using Distributed Fiber Optic Sensors.

Yi BaoMatthew S HoehlerChristopher M SmithMatthew BundyGenda Chen
Published in: Sensors (Basel, Switzerland) (2020)
Detailed information about temperature distribution can be important to understand structural behavior in fire. This study develops a method to image three-dimensional temperature distributions in steel-concrete composite slabs using distributed fiber optic sensors. The feasibility of the method is explored using six 1.2 m × 0.9 m steel-concrete composite slabs instrumented with distributed sensors and thermocouples subjected to fire for over 3 h. Dense point clouds of temperature in the slabs were measured using the distributed sensors. The results show that the distributed sensors operated at material temperatures up to 960 °C with acceptable accuracy for many structural fire applications. The measured non-uniform temperature distributions indicate a spatially distributed thermal response in steel-concrete composite slabs, which can only be adequately captured using approaches that provide a high density of through-depth data points.
Keyphrases
  • low cost
  • neural network
  • high density
  • optical coherence tomography
  • deep learning
  • machine learning
  • monte carlo
  • optic nerve