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    3D Power Profile Reconstruction Using Distributed Sensing Fiber Optics

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    STRATTON-DISSERTATION-2019.pdf (31.13Mb)
    Date
    2019-04-15
    Author
    Stratton, Charles David
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    Abstract
    When it comes to reactor power monitoring, the old adage is the more information the better. An undetected hot spot or unexpected power shift could cause an early shutdown of the plant and have economic consequences. Distributed sensing fiber optics offer the unique ability to provide a real wealth of information due to having data points distributed all along the fiber. Considering that fiber optic lengths can stretch for kilometers, even crossing oceans, it is understandable that as intrinsic measurement, this device indeed can offer a lot of data. The question is then not only what data is available, but also how to use it. The main objective of this dissertation was to develop the novel 3D power profile reconstruction method on the basis of distributed sensing fiber optics data acquisition technologies. The development and demonstration, both through computational simulations and experimentally, of such a method was the novel high impact contribution from this effort. To meet this objective, the work was divided into three tasks: (1) theoretical reactor power reconstruction method development and computational demonstration; (2) method demonstration via experimental heat source reconstruction, and (3) development of a correlation approach (response function) to radiation dose. Each of these individual research objectives had results that showed they could be implemented successfully,
    URI
    https://hdl.handle.net/1969.1/187920
    Subject
    3D Power Reconstruction
    Reactor Power Monitoring
    Distributed Measurement
    Distributed Sensing
    Distributed Temperature Measurement
    Fiber Optics
    Optical Fibers
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    • Electronic Theses, Dissertations, and Records of Study (2002– )
    Citation
    Stratton, Charles David (2019). 3D Power Profile Reconstruction Using Distributed Sensing Fiber Optics. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /187920.

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