This study aims to quantify second-law performance in a vertically oriented helically coiled tube heat exchanger (HCTHEX) and develop predictive correlations for the dimensionless exergy-destruction fraction across operating conditions and coil pitches, using more than 2,400 CFD simulations.
A steady, fluid-to-fluid CFD model was used with water on both shell and coil sides and laminar treatment over the stated Reynolds-number range. Exergy rates at shell/coil inlets and outlets were evaluated over a heat-exchanger control volume to compute and . Predictability was assessed via global regressions including pitch as an explicit predictor and pitch-specific regressions trained separately at each pitch; all models were trained in log space and evaluated using five-fold cross-validation.
The global baseline power-law shows statistically significant dependence on pitch and Reynolds numbers (e.g. -based: , a = 0.04885, b = 0.04982 and c = 0.7507), but limited cross-validated accuracy (: , ). Among advanced surrogates, LogLog–GPR–ARDSE provides the best global performance for both characteristic-length definitions (for : , . Pitch-specific modeling indicates the best advanced method depends on pitch: GPR–ARDSE is selected at p = 1.80, 1.85 and 2.00, while bagged trees outperform at p = 1.90and 1.95 under the minimum criterion.
Correlations are calibrated to the simulated geometry family and operating ranges and should not be extrapolated without verification.
The correlations enable rapid estimation of from , reducing the need for repeated full exergy accounting during screening and mapping.
This study benchmarks baseline, advanced and pitch-conditioned predictive models for in HCTHEXs using a unified CFD–exergy data set and cross-validation.
