Minimum power requirement for a propeller-driven aircraft and optimum cycle parameters of turboprop engines

Abstract

This article presents a methodology to design for optimal performance of turboprop engines matching the power requirements for propeller-driven aircrafts. First, the flight performance analyses were used to assess the relatively significant constraints, and then identify the feasible design space and the ideal design point by adopting KSOPT optimizing technique. Second, a multi-objective deterministic algorithm modified method of feasible direction was used for the Pareto approach optimization of the propulsion cycle for three configurations of turboprops. In this optimization problem the maximum specific power and the minimum power specific fuel consumption are the principal figures of merit. The obtained results were based on a created model from the published data of a particular aircraft. This methodology used in the preliminary design phase has shown its effectiveness in rapidly searching for the ideal match point and identifying a candidate turboprop engine, as well as in the development of a derivative engine.

Optimizations of turboprop engines using the non-dominated sorting genetic algorithm

“…The design point corresponds to the cruise flight condition at an altitude of 28 000 ft and Mach number of 0.475. The off-design operating constraints are known according to the determined flight mission constraints diagram [5]. In fact, an engine design producing less power at takeoff and in cruise will not be acceptable; in addition, the compressor exit temperature and the power turbine entry temperature should not exceed the limits of the blades' materials.…”

“…Also, the basic Allison T56 turboprop has undergone a spectacular growth with increased 'turbine inlet temperature' are conflicting, the optimization does not lead to a single solution, as would be the case when considering each objective separately. Ghenaiet and Boulkeraa [5,6] conducted a bi-objective optimization to get the optimal turboprop cycle parameters by using both the modified method of feasible direction (MMFD) and PIKAIA (PIKAIA is a general purpose genetic algorithm-based optimization subroutine, available from http://www.hao.ucar.edu/Public/models/ Pikaia/Pikaia.html), which seeks to maximize an objective function in a bounded n-dimensional space). These two techniques considered the weighted sum of multi-objectives that, besides their slowness in terms of computation time, do not produce an effective front (well-distributed solutions) even by using small weight coefficients.…”

Optimization of a Turboprop UAV for Maximum Loiter and Specific Power Using Genetic Algorithm

“…high pressure turbine efficiency) with respect to compressor pressure ratio, fan pressure ratio and bypass ratio, burner exit temperature or turbine inlet temperature as key parameters (depending on engine type) for cycle optimization. Fewer examples are found in literature on engine optimization with aircraft considerations [23][24][25][26][27]. Reference [23] examined ultrahigh bypass turbofans for a notional, next-generation, single-aisle transport aircraft and optimized engine parameters for objectives of minimum ramp weight of aircraft, minimum block fuel, minimum noise or NO x .…”