Fig 9 - uploaded by Robert Morris
Content may be subject to copyright.
Source publication
The ability to predict rotorcraft ground noise is important in determining and assessing environmental noise impact. The noise generated by rotorcraft can limit their usage and restrict operations, particularly near cities and populated regions. The two primary approaches commonly used to reduce rotorcraft noise are to make vehicle design modificat...
Context in source publication
Context 1
... A and B be paths that are adjacent in the sense that they share a common state such that their join, AB, is a feasible path. Let BIN(A) be the BIN cost of trajectory A. Figure 9 shows why BIN(AB) = BIN(A) + BIN(B) and so simple aggregating by sum is not possible. The yellow box represents a data point where noise is measured. ...
Similar publications
Rotorcrafts are complex machines that requires numerous subsystems to work in harmony. Conceptual design of such systems utilizes multiple disciplines in various fidelity design levels. Conceptual design stage is the place where decision makers may alter major design drivers. Therefore, an evaluation and design space exploration tool is introduced...
Citations
... the ground (in descent or in slow advancing flight) [9]. Among passive techniques aiming at reducing rotorcraft noise footprint, the definition of approach (near ground) optimal flight trajectories that limit the occurrence of strong BVIs events and acoustic prediction techniques suited to this purpose were investigated in the recent past in several papers1011121314151617 . These works follow approaches similar to those introduced by the fixed-wing aircraft research community involved in the identification of noise abatement flight procedures (see, for instance, Refs.181920). ...
... Such approach is applied to avoid the extremely high computational cost required by the direct evaluation of noise hemispheres along the actual unsteady maneuver. The database is obtained either by off-line computations or by measured data [13,17] , and it is defined in a domain of flight parameters that represent the acoustic source state. Several tools devoted to the development of low-noise operating procedures of helicopters (or, more generally, to the assessment of their environmental acoustic impact) consider noise hemisphere databases given in terms of only kinematic flight parameters , like airspeed and flight path angle (see, for instance, Refs. ...
... Several tools devoted to the development of low-noise operating procedures of helicopters (or, more generally, to the assessment of their environmental acoustic impact) consider noise hemisphere databases given in terms of only kinematic flight parameters , like airspeed and flight path angle (see, for instance, Refs. [10,17]). The scope of the present work is the identification of the flight parameters that properly characterize helicopter noise hemispheres , following an approach preliminarily applied in Ref. [25]. ...
Numerical tools aiming at the evaluation of ground acoustic impact of helicopters typically rely on databases given in terms of acoustic disturbance over hemispheres surrounding the helicopter (noise hemispheres). These are evaluated for a discrete number of steady flights falling within the flight envelope. The objective of the present work is the identification of flight parameters to be considered for the characterization of noise hemispheres, particularly when related to unsteady maneuvers. To this purpose, different approaches based on steady flight aeroelastic/aerodynamic/aeroacoustic predictions are examined for assessing their capability of simulating the acoustic impact of helicopters in arbitrary unsteady flight. The numerical investigation demonstrates that at least three parameters, including disk loading, are required to adequately characterize noise hemispheres. Conversely, the similarity of kinematic parameters alone may yield steady flight acoustic predictions poorly correlated with those obtained for unsteady maneuvers.
... Considering arbitrary unsteady flight conditions (including turns, descent angle changes, accelerations and decelerations), the noise source model must be updated in accordance with the instantaneous flight condition experienced by the helicopter during the maneuver. In order to avoid numerically expensive predictions, this is usually accomplished by selecting the near-field model (provided in terms of a hemispheric acoustic map rigidly connected to the helicopter) from an appropriate database related to rectilinear, steady-state flights, defined in a domain of parameters suitably characterizing the noise source state (quasi-steady acoustic approach) [1, 2, 3]. It is worth observing that, these acoustic data could be also useful for developing helicopter in-flight noise monitoring systems, such as the Pilot Acoustic Indicator (PAI), object of the European project MANOEUVRES activities [4], aimed at making the pilot able to adequately react in case of excessive produced acoustic disturbance. ...
This paper investigates different techniques for the evaluation of the acoustic disturbance emit-
ted by helicopters in unsteady maneuvers. Nowadays, the simulation of noise emitted by he-
licopters is of great interest to designers, both for assessing the acoustic impact of helicopter
flight on communities and for identifying optimal-noise trajectories. Typically, these simulations
consists in the atmospheric propagation of a near-field noise model, extracted from an appro-
priate database determined through steady-state flight simulations/measurements. In this work,
two steady-flight/unsteady-flight noise equivalence criteria are examined, in order to assess their
suitability by comparison with noise predictions directly evaluated through a fully-unsteady aeroa-
coustic solver. They differ in the flight parameters used to select the near-field noise model within
the database to be associated to a given unsteady-flight condition.
... Usually, identified minimum noise trajectories correspond to unsteady maneuvers including turns, varying flight-path slope, accelerations and decelerations, which require acoustic source model update accordingly to change of flight conditions. During the optimization process, it is typically derived from an appropriate database of sound spectrum distributions over hemispheres surrounding the helicopter (the socalled noise hemispheres) obtained from rectilinear steady-state flights noise predictions [1,2,3] . However, the noise emitted during complex maneuvers may potentially be strongly affected by unsteady effects inducing inertial and aerodynamic loads variations, as well as by pitch, roll and yaw motions causing shifts in noise directivity [4] . ...
... Usually, this is accomplished in terms of a set of flight parameters chosen to characterize the noise source state. The most common criteria adopted to this scope consider as noise flight parameters either advance ratio and flight-path slope angle (Approach A, in the following), or advance ratio, rotor thrust coefficient, and rotor disk orientation with respect to relative wind (Approach B, in the following) [1,2,3] . The aim of this work is the analysis of the accuracy of such approaches in estimating the noise emitted by maneuvering helicopters through correlation with predictions provided by an acoustic tool suited for the analysis of unsteady helicopter flights. ...
... Commonly, the flight parameters used to characterize the steady flight acoustic noise source locally simulating the unsteady maneuver noise are either advance ratio, µ, and flight-path slope angle, γ, (Approach A), or µ, main rotor thrust coefficient, C T , and tip-path plane orientation with respect to relative wind, α T P P (Approach B) [1,2,3] . In order to assess the accuracy of the approximations introduced by Approaches A and B, for a given unsteady maneuver, acoustic predictions derived from their application are compared with those determined by the fully unsteady solution based on the general aeroacoustic formulation described in Section 3. ...
This paper deals with methodologies for evaluation of acoustic disturbance emitted by helicopter main rotors in unsteady maneuvers. The attention is focused on those techniques applied in minimumnoise, optimal trajectories search tools. Typically, noise optimization processes are based on noise estimations conceived as sequences of steady-state flight acoustic predictions, properly selected from dedicated databases. Introducing a multidisciplinary rotor solution procedure including accurate aerodynamic, aeroelastic and aeroacoustic prediction tools suited for unsteady maneuver analyses, this work presents an assessment of methods used for acoustic disturbance identification based on different characterization parameters for correlating unsteady flight conditions with steady-state flight radiated noise. Only the main rotor component is examined, although tail rotor contribution might be included, as well. The numerical investigation concerns a lightweight helicopter model in unsteady flight, and provides comparisons between noise predicted by the considered methods in terms of sound pressure levels on a hub-centered hemisphere rigidly connected to helicopter.
Artificial Intelligence (AI) has achieved a wide range of successes in autonomous air combat decision-making recently. Previous research demonstrated that AI-enabled air combat approaches could even acquire beyond human-level capabilities. However, there remains a lack of evidence regarding two major difficulties. First, the existing methods with fixed decision intervals are mostly devoted to solving what to act, but merely pay attention to when to act, which occasionally misses optimal decision opportunities. Second, the method of an expert-crafted finite maneuver library leads to a lack of tactics diversity, which is vulnerable to an opponent equipped with new tactics. In view of this, we propose a novel Deep Reinforcement Learning (DRL) and prior knowledge hybrid autonomous air combat tactics discovering algorithm, namely deep E xcitatory-i N hibitory f ACT or I zed maneu VE r ( ENACTIVE ) learning. The algorithm consists of two key modules, i.e., ENHANCE and FACTIVE. Specifically, ENHANCE learns to adjust the air combat decision-making intervals and appropriately seize key opportunities. FACTIVE factorizes maneuvers and then jointly optimizes them with significant tactics diversity increments. Extensive experimental results reveal that the proposed method outperforms state-of-the-art algorithms with a 62% winning rate, and further obtains a margin of a 2.85-fold increase in terms of global tactic space coverage. It also demonstrates that a variety of discovered air combat tactics that are comparable to human experts’ knowledge.
This paper addresses the noise-minimal trajectory optimization problem for a specific type of aircraft: rotorcraft. It relies on a realistic noise footprint computation software provided by industry that is black-box. Locally optimal trajectories are computed through a tailored solution approach based on the Mesh-Adaptive Direct Search algorithm. We propose multiple surrogates defined according to our knowledge of the problem, including a surrogate relying on the physics of the problem (approximating the rotorcraft noise model), and another based on a machine learning (neural network) method. The proposed solution approach is further enhanced by the computation of an appropriate starting guess through a path planning algorithm tailored to the problem, and by the reduction of the variable space domain. The performance of the proposed methodology both in terms of quality of the solutions (trajectories exhibiting significant noise reduction compared to those currently flown in practice) and computing time is illustrated through numerical experiments on real-world case studies.
A new class of electric aircraft is being developed to transport people and goods as a part of the urban and regional transportation infrastructure. To gain public acceptance of these operations, these aircraft need to be much quieter than conventional airplanes and helicopters. This article seeks to review and summarize the aeroacoustic research relevant to this new category of aircraft. First, a brief review of the history of electric aircraft is provided, with an emphasis on how these aircraft differ from conventional aircraft. Next, the physics of rotor noise generation are reviewed, and the noise sources most likely to be of concern for electric aircraft are highlighted. These are divided into deterministic and nondeterministic sources of noise. Deterministic noise is expected to be dominated by the unsteady loading noise caused by the aerodynamic interactions between components. Nondeterministic noise will be generated by the interaction of the rotor or propeller blades with turbulence from ingested wakes, the atmosphere, and self-generated in the boundary layer. The literature for these noise sources is reviewed with a focus on applicability to electric aircraft. Challenges faced by the aeroacoustician in understanding the noise generation of electric aircraft are then identified, as well as the new opportunities for the prediction and reduction of electric aircraft noise that may be enabled by advances in computational aeroacoustics, flight simulation, and autonomy.
This paper investigates different methodologies for the evaluation of the acoustic disturbance emitted by helicopter’s main rotors during unsteady maneuvers. Nowadays, the simulation of noise emitted by helicopters is of great interest to designers, both for the assessment of the acoustic impact of helicopter flight on communities and for the identification of optimal-noise trajectories. Typically, the numerical predictions consist of the atmospheric propagation of a near-field noise model, extracted from an appropriate database determined through steady-state flight simulations/measurements (quasi-steady approach). In this work, three techniques for maneuvering helicopter noise predictions are compared: one considers a fully unsteady solution process, whereas the others are based on quasi-steady approaches. These methods are based on a three-step solution procedure: first, the main rotor aeroelastic response is evaluated by a nonlinear beam-like rotor blade model coupled with a boundary element method for potential flow aerodynamics; then, the aeroacoustic near field is evaluated through the 1A Farassat formulation; finally, the noise is propagated to the ground by a ray tracing model. Only the main rotor component is examined, although tail rotor contribution might be included as well. The numerical investigation examines the differences among the noise predictions provided by the three techniques, focusing on the assessment of the reliability of the results obtained through the two quasi-steady approaches as compared with those from the fully unsteady aeroacoustic solver.
Next generation commercial air transportation will likely see an increased use of rotorcraft, including heli-copter and tilt-rotors. Two advantages of rotorcraft with respect to fixed wing aircraft are the optimized aero-dynamic levitation and the possibility of takeoff and landing without a runway, which minimizes their in-terference with fixed wing traffic. A recurring obsta-cle to rotorcraft integration is the ground noise they generate, particularly near residential areas and hos-pitals. The problem of rotorcraft ground noise can be partially addressed by designing new flight profiles, in particular landing trajectories, that have a lower im-pact in the noise produced by a rotorcraft. In this pa-per we approach this problem computationally by mod-eling a high dimensional environment able to capture many parameters of landing trajectories that contribute to ground noise, and using probabilistic road maps (PRMs), coupled with a robust ground noise simulation system, for identifying noise-minimal approach trajec-tories.
