T HE concept of simultaneous noninterfering (SNI) approaches for rotorcraft is currently being explored in both Europe and the United States. The SNI concept was initially conceived in the United States to enable the integration of both fixed wing and rotorcraft into the terminal airspace system to reduce delays and increase capacity [1]. It comprises primarily specific instrument flight rules (IFR) departure and approach procedures which enable rotorcraft to operate independently from fixed-wing traffic IFR streams. Because of the much lower approach speeds of helicopters, sequencing helicopter operations into the IFR approach stream tends to result in congestion and undesirable delays. At present, helicopter operators often prefer to operate under visual flight rules to avoid complex IFR procedures, but clearly this does not provide a reliable air transport service in all weather conditions. Also, in Europe, research pertaining to SNI operations is well underway, notably in the sixth framework project OPTIMAL (Optimized Procedures and Techniques for Improvement of Approach and Landing) [2]. The main aim of the OPTIMAL project is to increase airport capacity and efficiency, while reducing the noise footprint. A downside of the SNI concept is that new SNI routes will be located in previously unused airspace and consequently may overfly noise-sensitive communities that were not affected by traffic movements before. This, coupled with the fact that helicopter approach operations tend to be relatively noisy, indicates a clear need for optimization of the SNI routes and flight paths such as to reduce the noise impact in the affected residential communities. Optimization of SNI approaches with respect to community noise impact was first explored by Atkins and Xue [3,4]. In [3,4], they present an optimization technique for segmented three-dimensional SNI trajectory design based on an incremental search strategy that combines a k-ary tree with Dijkstra’s algorithm. The objective function is based on a validated rotorcraft noise model as well as terminal area population density data. Fixed-wing airspace corridors were treated as impenetrable obstacles. In this approach, a trajectory is described as a sequence of trimmed flight segments that connect initial approach and landing sites. The number of segments considered in this study remains limited (typicallyfive or less) primarily due to the fact that the computational load increases rapidly with the number of segments. To make the approach numerically tractable, a number of simplifying assumptions were introduced. In particular, it was assumed that transitions between trim states do not appreciably affect solution cost. The optimization of noise abatement procedures for fixed-wing aircraft has received considerablymore attention. In [5], an optimization approach is presented that, similar to [3,4], relies on segmented routes. The segmented routes, optimized using a genetic algorithm, enable a specification of simple procedures that are amenable to fast online computer solutions that can be readily implemented in a guidance system. In [6–8], a noise-optimized approach and departure trajectories are computed based on a direct numerical optimization techniques that enable one to generate (piecewise) continuous optimal trajectories for a point-mass modeled fixed-wing aircraft. The numerical tool that has been used in these particular studies is called NOISHHH. The NOISHHH tool essentially combines a noise model, a dose-response relationship, an emission inventory model, a geographic information system, and a dynamic trajectory optimization algorithm. NOISHHH generates routings and flight paths for both arrivals and departures that minimize the environmental impact in the residential communities surrounding the airport, while satisfying all imposed operational and safety constraints. The present study is aimed at extending the NOISHHH tool to permit the computation of noise-optimized SNI trajectories for rotorcraft. The extension does not only entail a modification of the dynamic vehiclemodel and the operational context, but also involves an adaptation of the implemented noisemodel. The environmentallyoptimized SNI trajectories calculated with the modified version of NOISHHH are illustrated in an example scenario involving an SNI instrument approach of a Robinson R22 helicopter [9] to a helispot on runway 22 of Schiphol airport (Amsterdam) in the Netherlands.
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Nov 1, 2013
Thomas Haberkorn + 3
Open Access