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The Numerical and Experimental Investigation of Heat Transfer for a Staggered Pin Fin Array for Cooling of High-TIT Supercritical Carbon Dioxide Turbines

To push the thermal efficiency of turbomachinery, the turbine inlet temperature must be raised, eventually reaching and surpassing the blade material thermal limits. Internal geometry, such as pin fin arrays, has been the go-to solution for higher thermal environments to remove heat from blades and vanes to prevent material failure. The industry standard for turbomachinery in energy generation uses the steam Rankine or the Brayton cycle. Classically, these cycles have used air as the operating fluid environment. Over the past decade, novel solutions have begun changing how we design cycles, with one promising solution emerging: the supercritical carbon dioxide (sCO2) power cycle. Promising higher cycle efficiency with a smaller footprint has quickly become an attractive alternative for power generation. Although thorough research of pin fin arrays as turbulators in the trailing edge of turbine blade internal design has been a focus of research for the past several decades, in the sCO2 novel working environment, the need to re-visit the heat transfer characterization of internal cooling is necessary. This study was executed two-fold, first numerically and then experimentally. The first objective of this paper is to explore the heat transfer characteristics of sCO2 as the cooling environment in a staggered pin fin array, defined within the supercritical phase, using steady RANS conjugate heat transfer. An adapted correlation for the Nusselt number was derived, dependent on the Reynolds number, to provide a stronger correlation than existing air data-derived correlations in the literature. Taking this numerically derived correlation, the second objective of this paper is to design and run a matching experimental geometry fabricated for testing at target operating conditions of 400 Celsius and 200 bar. This data was then processed in tandem with the numerical and available derived data in the literature for direct comparison.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1059
Date01 January 2023
CreatorsWardell, Ryan J
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceGraduate Thesis and Dissertation 2023-2024

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