The escalating interest in cryogenic technologies for space-related applications has led to an unprecedented demand for reliable prediction methods for cryogenic two-phase flow and heat transfer. Regrettably, existing heat transfer coefficient (HTC) correlations developed for conventional fluids prove inadequate and provide subpar predictions when applied to cryogenic flow boiling conditions. Therefore, it is imperative to develop a set of new HTC correlations specifically tailored for cryogenic flow boiling. In this study, comprehensive databases are constructed consolidating experimental data from previous studies of the present authors and historical data extracted from open literatures, spanning a wide range of operating conditions, flow orientations, and various cryogenic fluids. Subsequently, based on the constructed databases, an assessment of the predictive accuracy of seminal HTC correlations is conducted, followed by the development of new HTC correlations for cryogenic saturated and subcooled flow boiling. The newly developed correlations demonstrate very good predictive accuracy, with an overall mean absolute error (MAE) of 23.84 % and 21.24 % for LN2 saturated and subcooled HTC, respectively, under terrestrial gravity conditions. When assessed against a microgravity dataset, these correlations exhibit equally good predictive accuracy, yielding MAE values of 16.73 % and 25.99 % for LN2 saturated and subcooled HTC, respectively. Furthermore, the universal applicability of the new HTC correlations is ascertained by assessing the correlations across a multitude of cryogenic fluids, including LN2, LHe, LAr, LCH4, and LH2. Impressively, these correlations display outstanding predictive accuracy, with MAE values of 24.01 % and 21.29 % for saturated and subcooled HTC, respectively, underscoring their superior performance across a wide range of cryogenic fluids, validated against 2,445 saturated cryogenic HTC datapoints and 1,553 subcooled cryogenic HTC datapoints. Overall, the new HTC correlations consistently outperform all prior seminal correlations, yielding good predictive accuracy across a diverse spectrum of operating conditions, irrespective of flow orientation and gravity level, for various cryogenic fluids.
