CFD-BASED INVESTIGATION OF HEAT TRANSFER EFFICIENCY IN RENEWABLE ENERGY SYSTEMS

Abstract

This study addresses a persistent problem in renewable-energy subsystems: designers often report heat-transfer gains without fairly accounting for hydraulic penalties, which leads to weak deployment decisions. The purpose was to quantify heat-transfer efficiency using an energy-fair metric and test whether documented gains align with practitioner willingness to adopt. The international energy transition emphasizes reductions in thermal losses and improvements in thermo-hydraulic performance across solar thermal collectors, geothermal borehole heat exchangers (BHEs), and thermal energy storage (TES) modules.Well-constructed CFD provides a “virtual laboratory” to explore feasible designs over realistic operating ranges without incurring prohibitive prototyping or test-rig costs, while still supporting validation against standard correlations and selected experiments. This study used a quantitative, cross-sectional, case-based design integrating validated CFD outputs with a Likert five-point practitioner survey. The sample comprised two technology cases, a rib-augmented solar thermal channel and a coaxial deep borehole heat exchanger, with DOE-style CFD sweeps producing 312 runs and a practitioner sample of 184 responses. Key variables were area-averaged Nusselt number, pressure drop, a thermal-efficiency proxy, and the equal-pumping-power performance evaluation criterion (PEC); predictors included Reynolds number, standardized geometry indices, and their interaction. The analysis plan specified descriptive statistics, HC3-robust regressions with case fixed effects, marginal effects, and subgroup checks, with mesh independence verified at <2 percent drift and heat-balance error ≤0.5 percent. Headline findings show PEC averaged 1.08±0.09, with PEC ≥1.10 concentrated at mid to high Reynolds and moderate geometry; ln(Re) and geometry had positive effects on Nu and PEC, including a significant interaction. Survey constructs were reliable (Cronbach’s α ≥0.80). Perceived efficiency averaged about 4.0 on a five-point scale and correlated with standardized PEC (r≈+0.56), while adoption intention rose from 3.36 in the lowest PEC quartile to 4.18 in the highest. Implications are clear: institutionalize equal-constraint reporting, target moderate augmentation at mid to high Reynolds to maximize PEC beyond 1.10, and couple design with light O&M monitoring to sustain realized gains.