A Dimensionless Similarity Framework for Organic Rankine Cycles: Generalized Performance Maps and Reduced-Pressure Optimality

Abstract

Organic Rankine Cycles (ORCs) have become one of the most promising technologies for converting low- and medium-grade waste heat into useful power. However, conventional ORC analyses are typically performed using dimensional variables and application-specific operating conditions, limiting transferability across working fluids, heat sources, and system capacities. This study presents a dimensionless similarity framework for ORCs based on Buckingham Π analysis, exergy-based normalization, and reduced thermodynamic coordinates. The methodology transforms conventional ORC performance into a generalized dimensionless representation by normalizing net power output with available heat-source exergy and scaling operating conditions using fluid critical properties. The resulting multidimensional framework incorporates reduced evaporator and condenser pressures, heat-source temperature and utilization parameters, reduced critical temperature, component efficiencies, and the acentric factor. Performance surfaces and sensitivity analyses reveal a well-defined reduced-pressure ridge, with the reference optimum centered near ΠP,e≈0.45. Parametric assessment demonstrates that the exact location and width of this ridge are conditional on the governing similarity parameters, while the optimal region remains comparatively confined in reduced-pressure space across the investigated domain. Validation using 100 kW–1 MW waste-heat-recovery systems, R245fa and R1233zd(E), and published experimental data supports substantial performance collapse in reduced coordinates. The framework provides a generalized basis for transferable ORC performance mapping, comparison, and preliminary design.