OPTICAL ANALYSIS OF TURBULENT SUPERSTRUCTURES IN THERMAL CONVECTION USING TEMPERATURE SENSITIVE PAINT

Abstract

Rayleigh-Bénard convection (RBC) refers to a family of flows generated in a horizontally extended volume with adiabatic sidewalls, wherein the fluid is uniformly heated from below and cooled from above. The resulting fluid motion depends on the system’s Rayleigh number (Ra), Prandtl number (Pr), and aspect ratio (Γ = L/H) between the lateral extension L and the height of the fluid layer H. Typical for the turbulent regime under strong thermal driving is the occurrence of coherent large-scale structures. Specifically, at small Γ, the flow is dominated by “LargeScale Circulations” (LSC), which involve strong sidewall interactions. At higher Γ, as sidewall effects become negligible, so-called “Turbulent Superstructures” (TSS) evolve. This study addresses the long-term development of temperature fields in RBC using a shallow water tank with a heated aluminium base and a water-cooled glass top plate. Variable sidewalls allow the control of Γ (ranging from 4 to 32). With an experimental setup incorporating temperature sensitive paint (TSP) with associated UV-LED illumination (λab ∼ 395 nm) and CCD camera, TSS were observed and studied via their thermal footprint on the top plate for Ra in the range 2.6 × 10^4 < Ra < 1.2 × 10^8. The application of TSP to slowly evolving flows like RBC, with the paint submerged in water for extended periods, represents an innovation in experimental fluid dynamics and comes along with novel challenges. The thesis, carried out at the Department of Experimental Methods within the Institute of Aerodynamics and Flow Technology at DLR Göttingen, Germany, aims to address these challenges and improve the accuracy of the measurements. The work primarily focuses on the development of an accurate calibration method to convert TSP intensity data to temperature. A preliminary analysis of temperature fields is also conducted, including the investigation of the transition from LSC to TSS, achieved by analysis of Probability Density Function (PDF) of temperature fluctuations.