Fluoride-salt-cooled high-temperature reactors (FHRs) are a Gen IV nuclear reactor design that combine the meltdown resistance and online refueling capabilities of pebble-bed cores with the excellent heat transfer properties and atmospheric pressure operation of molten salt coolants. Accurate prediction of the convective heat transfer (directly determined by the Nusselt number) between fuel pebbles and the surrounding coolant is critical to both the safety and efficiency of these reactors. Many classical packed-bed Nusselt correlations widely used in reactor analysis codes (Wakao, KTA, Gunn, Gnielinski, Achenbach, Whitaker, and Petrovic) were developed almost entirely with gas-cooled data (Pr ≈ 0.7), while FHR conditions involve molten salts with Pr ≈ 11–25. Use of these correlations in FHR contexts extrapolates them well beyond their original calibration ranges, introducing uncertainty into reactor design tools at a critical stage of FHR development.

This thesis addresses that gap by analyzing a compiled dataset of high-Pr pebble-bed heat transfer results drawn from three experimental studies (Meng 2012, Liu 2018, Wang 2022) and four CFD studies (Dave 2020, Yuan 2023, Wang 2024, Liu 2025). The compiled dataset spans Re ≈ 50–6600, Pr ≈ 6–24, and porosities ε ≈ 0.26–0.57. Seven classical correlations and four modern high-Pr correlations are benchmarked against each dataset using mean absolute relative error, with results grouped by porosity to expose porosity-dependent biases. The analysis reveals that correlations with explicit porosity dependence (KTA, Gnielinski, Gunn) systematically over-predict at low porosity due to extrapolation of their ε-dependent terms, while Achenbach consistently under-predicts due to its absence of a Pr term. Wakao demonstrates the most consistent behavior across porosity ranges.

A supplementary OpenFOAM single-sphere study evaluates the commonly cited thermal-boundary-layer-thinning argument for high-Pr discrepancies and finds that the argument does not directly extend to laminar single-sphere geometries. This suggests that packed-bed-specific transport mechanisms and configurations, rather than pure boundary-layer scaling, may be driving the observed differences in the packed-bed correlations.

A new correlation of the form Nu = 4.08Re^0.39Pr^0.4 is developed via ordinary least-squares regression in log-space across a selected subset of the compiled dataset (the high porosity cases were determined to be outliers and excluded from the fit). This correlation achieves the lowest mean error in the low and mid-porosity bins, which is the regime most relevant to FHR operation (ε ≈ 0.4). The exponents are consistent with both the transition-regime Re scaling expected in the FHR-relevant Re range of 100–1000 and the high-Pr empirical scaling observed across independent fits in the literature. The proposed correlation may provide an improved tool for FHR thermal-hydraulic analysis within its calibration envelope and may serve as a benchmark for future correlation development as additional high-Pr pebble-bed data becomes available.