Validation and Benchmarking of TurboMAP Engine Modeling Framework

This paper presents a structured validation and benchmarking of TurboMAP, an open-source, Python-based, multi–design point (MDP) mid-fidelity engine modeling framework, against the NPSS-based MDP cycle analysis implementation within the Environmental Design Space (EDS). A common LEAP-1B28 baseline, aligned input definitions, and tool-appropriate but comparable designs of experiments (DoE) were used to generate equivalent calibration spaces in both tools. Surrogate models trained on 9,600 DoE cases per tool enabled one-million–case Monte Carlo analyses, from which acceptable calibrated subsets were identified based on ICAO TSFC constraints and tool-specific requirements. The comparison focused primarily on TSFC behavior across the five EDS design points—three of which represent off-design conditions for TurboMAP—to assess how the framework performs across the operating envelope. The results show that TurboMAP closely matches EDS behavior at the aerodynamic design point (ADP) and top of climb (TOC), while larger differences appear at takeoff (TO) and sea-level static (SLS) due to fundamental differences in calibration philosophy. TurboMAP determines key technology-linked variables such as turbine inlet temperature as calculated quantities, whereas EDS constrains these values through technology limits and architectural consistency rules, leading the two solvers to converge toward different combinations of cycle parameters under matched targets. Despite these distinctions, the calibrated engine spaces produced by both tools remain broadly consistent, demonstrating that TurboMAP provides a transparent, reproducible, and technically robust mid-fidelity alternative for cycle analysis in research, policy, and environmental studies.