Free-wake models are routinely used in aeroacoustic analysis of helicopter rotors; however, their semiempiricism is accompanied with uncertainty related to the modeling of physical wake parameters. In some cases, analysts have to resort to empirical adaption of these parameters based on previous experimental evidence. This paper investigates the impact of inherent uncertainty in wake aerodynamic modeling on the robustness of helicopter rotor aeroacoustic analysis. A free-wake aeroelastic rotor model is employed to predict high-resolution unsteady airloads, including blade–vortex interactions. A rotor aeroacoustics model, based on integral solutions of the Ffowcs Williams–Hawkings equation, is utilized to calculate aerodynamic noise in the time domain. The individual analytical models are incorporated into an uncertainty analysis numerical procedure, implemented through nonintrusive Polynomial Chaos expansion. The potential sources of uncertainty in wake tip-vortex core growth modeling are identified and their impact on noise predictions is systematically quantified. When experimental data to adjust the tip-vortex core model are not available the uncertainty in acoustic pressure and noise impact at observers dominated by blade–vortex interaction noise can reach up to 25% and 3.50 dB, respectively. A set of generalized uncertainty maps is derived, for use as modeling guidelines for aeroacoustic analysis in the absence of the robust evidence necessary for calibration of semiempirical vortex core models.

Demands for rotorcraft with increased flight speed, improved operational performance and reduced environmental impact have led to a drive in research and development of alternative concepts. Compound rotorcraft overcome the flight speed limitations of conventional helicopters with additional lifting and propulsive components. Further to operational benefits, these augmentations provide additional flight control parameters, resulting in control redundancy. This work aims to investigate the impact of optimal control strategies for a generic coaxial compound rotorcraft, equipped with turboshaft engines, targeting the minimization of mission fuel burn and gaseous emissions. The direct redundant controls considered are: (a) main rotor speed, (b) propeller speed, and (c), fuselage pitch attitude. A simulation tool for coaxial compound rotorcraft analysis has been developed and coupled to a zero-dimensional engine performance model and a stirred-reactor combustor model. Firstly, experimental and flight test data were used to provide extensive validation of the developed models. A parametric analysis was then carried out to gain insight into the effect of the redundant controls. This was followed by the derivation of a generalized set of optimal redundant control allocations using a surrogate-assisted genetic algorithm. Application of the optimal redundant control allocations during realistic operational scenarios has demonstrated reductions in fuel burn and NOX of up to 6.93% and 8.74% respectively. The developed method constitutes a rigorous approach to guide the design of control systems for future advanced rotorcraft.

The progress in aerospace technology over the recent years led to the development of more sophisticated and integrated systems. To cope with this complexity, the aerospace industry is seeing a progressive trend towards adopting Model-Based Systems Engineering (MBSE) in various stages of the product development cycle. The ability to capture emerging behavior, mitigation of risk and improved communication among different stakeholders are some key benefits that MBSE provides over traditional methods for complex systems and processes. This paper attempts to bridge the gap between system architecting and system simulation activities by proposing a methodology to facilitate seamless flow of information between the two development aspects. This methodology was applied to the development of a parallel hybrid-electric version of the ATR 42–500. The use case was designed for a regional mission of 400 nautical miles with the ability to meet regulation requirement of carrying enough reserves for landing at an alternate airport. An integrated systems model, consisting of gas turbine engine, electric powertrain, and flight dynamics, was developed with Simcenter Amesim to analyze the dynamics performance of the aircraft throughout the whole mission. The key metrics evaluated were fuel consumption, take-off weight and the Energy Specific Air Range (ESAR) of the aircraft. As environmental regulations are becoming more stringent, pollutant and noise emissions were considered in the study. The most promising hybrid configurations are recognized, the potential benefits are quantified highlighting the strong potential of System Architecting and System Simulation to provide valuable insights early in the development cycle, reducing the time and cost of product development.

Demands for rotorcraft with increased flight speed, improved operational performance and reduced environmental impact have led to a drive in research and development of alternative concepts. Compound rotorcraft overcome the flight speed limitations of conventional helicopters with additional lifting and propulsive components. Further to operational benefits, these augmentations provide additional flight control parameters, resulting in control redundancy. This work aims to investigate the impact of optimal control strategies for a generic coaxial compound rotorcraft, equipped with turboshaft engines, targeting the minimization of mission fuel burn and gaseous emissions. The direct redundant controls considered are: (a) main rotor speed, (b) propeller speed, and (c), fuselage pitch attitude. A simulation tool for coaxial compound rotorcraft analysis has been developed and coupled to a zero-dimensional engine performance model and a stirred-reactor combustor model. Firstly, experimental and flight test data were used to provide extensive validation of the developed models. A parametric analysis was then carried out to gain insight into the effect of the redundant controls. This was followed by the derivation of a generalized set of optimal redundant control allocations using a surrogate-assisted genetic algorithm. Application of the optimal redundant control allocations during realistic operational scenarios has demonstrated reductions in fuel burn and NOx of up to 6.93% and 8.74% respectively. The developed method constitutes a rigorous approach to guide the design of control systems for future advanced rotorcraft.