Reliability Based Multi-Objective Thermodynamic Cycle Optimisation of Turbofan Engines Using Luus-Jaakola Algorithm

Aircraft engine design is a complicated process, as it involves huge number of components. The process begins with parametric cycle analysis. It crucial to determine the optimum values parameters that would give robust in early phase development, shorten for cost saving and man-hour reduction. To obtain solution, optimisation program often being executed more than once, especially Reliability Based Design Optimisations (RBDO) Monte-Carlo Simulation (MCS) scheme complex systems which require thousands millions loops be executed. This paper presents fast heuristic technique optimise thermodynamic two-spool separated flow turbofan engines based on energy probability failure criteria Luus-Jaakola algorithm (LJ). A computer called Turbo Jet Engine Optimiser v2.0 (TJEO-2.0) has been developed perform calculation. made up inner outer loops, where LJ used loop variables while analysis done performance. Latin-Hypercube-Sampling (LHS) sample model variations uncertainty results show without reliability may lead high 11% average. thrust obtained quantification was about 25% higher one quantification, at expense less 3% fuel consumption. proposed can solve RBDO problem within 3 min.