Measured-Pressure-Constrained Inverse Thermal-Cycle Reconstruction of a Swiwin SW190B Micro-Turbojet

Micro-turbojet experiments frequently provide local, software-referenced measurementsthat must be reconciled before they can be used as thermodynamic cycle states. Thisstudy develops and experimentally demonstrates a measured-pressure-constrained inversethermal-cycle reconstruction for a stationary Swiwin SW190B micro-turbojet. Total/staticpressure pairs were measured at the intake and the compressor exit as well as immediatelydownstream of the final nozzle outlet, while local temperatures, thrust, fuel flow, and rotorspeed were recorded independently. Three quasi-steady states at 38.01 × 103, 67.29 × 103,and 93.22×103 min−1 were retained. Software-zeroed pressure increments were restored toabsolute pressure using a common ambient reference, and the measured compressor totalpressureratio increased from 1.0718 to 1.5298. A two-anchor observation model linked thepressure-constrained compressor total temperature to the local compressor thermocoupleand achieved a threefold leave-one-state-out RMSE of 4.10 °C and MAE of 3.75 °C. Thereduced model was full rank, with condition number 1.63 and parameter correlation −0.309.Conditional Monte Carlo reconstruction yielded cycle-admissibility probabilities of 0.885and 0.985 at intermediate and high power. Thrust and fuel flow were withheld fromthe primary inversion and used as independent cross-sensor checks. A one-parametersoft-constraint diagnostic, in which only the existing aggregate compressor-exit-to-turbineinletpressure-loss term was adjusted globally across the two non-idle states, quantifiedthe influence of those auxiliary outputs without over-parameterizing the available data;the pressure-constrained solution was retained as the primary reconstruction. The novelaspect of this study is the explicit separation of measured signals, installation-dependentobservations, latent cycle states, common-mode pressure uncertainty, and auxiliary-outputinformation within one uncertainty-aware inverse framework. The method provides atransferable basis for thermodynamic reconstruction, measurement consistency assessment,and sensor-information prioritization in compact gas-turbine experiments.