使用飞行模拟和时间精确的空中苏醒来预测船用直升机的运行极限

摘要：

  本文概述了利物浦大学的舰载直升机动态界面模拟设施，重点介绍了通过包含非定常计算流体动力学(CFD)船舶气尾流数据所取得的最新进展。SH-60B型海鹰直升机的飞行实验室模型，在CFD推导的非定常尾迹影响下，在全运动基地模拟器中，飞到23型护卫舰和波浪级辅助加油器的甲板上。利用贝德福德工作负荷评定量表和甲板接口飞行员工作负荷量表，获得了甲板着陆任务的飞行员工作负荷等级，并由此导出了完全模拟的舰载直升机操作极限。对飞行员评级、评论和控制输入的分析，也使主观和客观地评估各种风载条件下的工作负荷成为可能，突出了导致着陆任务困难的主要空气动力尾流特征。获得底层CFD数据后，飞机的操纵质量和飞行员的工作量与尾流的气动特性相关，并能识别导致尾流的船舶几何特征。

I. Introduction

LANDING a helicopter on to the flight deck of a ship can be a formidable task for even the most experienced of pilots. The difficulties associated with the landing task arise due to several environmental factors which are unique to the maritime environment. Sea swell leads to movement of the ship about its principal degrees of freedom (pitch, roll and heave), effectively making the landing spot a moving target; at the same time, air passing over the ship’s superstructure forms large-scale turbulent eddies which pass over the landing deck and perturb the aircraft during approach. This region of disturbed flow is known as the ship’s airwake, and its severity is dependent on the atmospheric wind speed, the ship’s forward speed andthe relativewind-over-deck (WOD) angle. The close proximity of the helicopter to the ship during landing makes this a high-risk maneuver and as both the ship motion and the ship airwake are responsible for increasing pilot workload, it is necessary to develop ship–helicopter operating limits (SHOL) to minimize the risk of accidents.

Figure 1 shows a typical SHOL diagram, with the relative WOD direction (where the wind is coming from) around the circumference and the WOD speed on the radial axis. In accordance with naval terminology, winds from the starboard side are termed “green” and those from port termed “red.” The SHOL boundary is the thick black line which encloses all points that are deemed safe for repeated landings. For example, at a 40
WOD angle the maximum allowable WOD speed would be 35 kt. Landings at conditions outside the boundary are not normally permitted, except in extreme circumstances. Furthermore, during operations (for example if the ship is part of a flotilla or is patrolling near the coast) it is not always possible for a ship to turn to give the incoming pilot a favorable WOD condition, so it is always operationally advantageous to maximize the SHOL envelope.

In the United Kingdom, the Royal Navy (RN) requires SHOL boundaries for each in-service ship–helicopter combination, with additional charts needed for day/night operations and different aircraft weights. The first-of-class flight trials (FOCFT) which are used to determine the SHOL boundaries are performed over a limited time period, typically several weeks, and are at the mercy of the weather; as a result, it is usually impossible to obtain test points at every desired combination of WOD speed and angle. This often leads to overly conservative SHOLs that are limited by scheduling and meteorological constraints, rather than by aircraft or pilot limits. Furthermore, at-sea SHOL testing is inherently hazardous due to the fact that pilots are operating close to their own limits, as well as those of the aircraft. Finally, the dedicated use of naval hardware during SHOL testing ties up helicopters, ships, and personnel for significant periods of time, diverting resources from their primary operational roles.

For the reasons described previously, it has been suggested that modeling and simulation of the ship–helicopter dynamic interface (DI) may be used to augment the SHOL definition process. Potential benefits offered by DI simulation include 1) identification of WOD “hot spots” before at-sea testing which can be used to inform the flight-test program; 2) the ability to assess particular WOD conditions which may have been missed during at-sea testing in order to maximize the operational envelope; 3) investigation of flight deck aerodynamics while new ships are still at the design stage to identify potential improvements to superstructure design, landing spot locations and placement of equipment; 4) a greater understanding of ship airwake turbulence and the mechanisms which cause it; and 5) a realistic simulation environment in which to conduct pilot training exercises.

A great deal of DI modeling and simulation effort has focused on improving the fidelity of piloted flight simulators such that the results from simulated SHOL trials are comparable to those from at-sea flight trials. Indeed, significant progress towards this goal has been made by naval operators in the United Kingdom, United States, and Australia in recent years [3–8]. One aspect of DI modeling which has been identified as particularly important with regards to improving fidelity is the ship airwake [9]. Much of the pilot workload experienced during landing is a direct result of disturbances caused by the airwake, so it follows that accurate modeling of the airwake is a key step in replicating appropriate levels of workload in any DI simulation.

Blackwell et al.and, later, Erm from the Australian Defence Science and Technology Organisation presented one early example of an SH60B/FFG-7 frigate simulation capability, which was based on aerodynamic ship airwake data obtained from wind-tunnel tests on a model frigate. Significant differences were found between airwake velocities predicted by the model and those measured during at-sea tests. The discrepancies were attributed to the use of a windtunnel model whose superstructure was not sufficiently similar to the FFG-7. In addition, simplifications within the helicopter model such as the use of an actuator disk rotor model and the assumption that the airwake velocity at the aircraft center of gravity could be applied over the entire aircraft were identified as deficiencies which required attention. It was recommended that a blade element rotor model which could detect velocity gradients across the rotor would improve the effectiveness of the simulation.

As part of a review of collaborative DI modeling activities, Wilkinson et al. described the development of a ship–helicopter simulation facility based at the United Kingdom’s Defence Evaluation and Research Agency. The airwake module was based on the superposition of basic flow patterns, with turbulent fluctuations provided by scaled random velocity time histories. Because of the empirical nature of this airwake database, the three-dimensional components of turbulence were not correlated. 

From the late 1990s the improvement in computational fluid dynamics (CFD) codes and availability of high-performance computing facilities meant that ship airwake modeling activities increasingly moved from the wind tunnel to computer simulations. Several researchers have published computational studies on ship airwake aerodynamics, withthe results from Polsky, Lee et al., Roper et al. and Forrest and Owen being used to populate look-up tables for shipboard flight simulator investigations.

Bunnell and Roscoe and Thompson presented details of a CFD-based shipboard helicopter flight simulation facility in the Vertical Motion Simulator, located at the NASA Ames Research Center, which was developed as part of the U.S. Joint Shipboard Helicopter Integration Process program. The DI Modeling and Simulation System was configured such that the fidelity levels of the various subsystems could be altered to give an overall fidelity configuration between level A and D, with level A corresponding to full motion base, seat shaker, and high-performance image generator with high-fidelity visual models. A series of simulated UH-60/LHA deck landings were performed by several pilots, with results compared to flight-test data which had been recorded during at-sea landings. Using the five-point deck interface pilot effort scale (DIPES) to rate the difficulty of the deck landings it was found that, compared with the at-sea tests, mean DIPES ratings in the simulator were within 1 point of the corresponding ratings awarded at sea. However, the simulated SHOL was greatly expanded in comparison with the real SHOL, largely due to the fact that insufficient highworkload WOD conditions were encountered during sea trials due to benign environmental conditions. This was highlighted as further evidence of the need for high-fidelity piloted simulation capability.

The most recent example of a piloted ship–helicopter DI simulation environment was presented by Cox and Duncan, who described the United Kingdom’s Ship–Air Interface Framework project. Using a networked “high-level architecture” simulation with time-accurate ship airwake data (some of which was contributed by the current authors), piloted simulation flight trials were conducted for a Merlin helicopter to RN ships including the Type 23 frigate, Wave class auxiliary oiler (AO) and Type 45 destroyer. It was found that moving from a steady-state CFD-based airwake database with statistical turbulence modeling to a time-accurate database provided more realistic turbulent fluctuations, with an improved match between the simulated and at-sea flight-test ratings.

To date, the common approach for CFD-based ship–helicopter flight simulators has been for the ship airwake computations to be performed elsewhere; either in a separate department or by contracting out to other organizations. There is very little evidence in the literature to suggest that DI simulation researchers have examined simulated flight trial results in the context of the underlying aerodynamic airwake data. Given the wealth of information held within the CFD datasets, it is possible that researchers are missing opportunities to gain real insight into the nature of ship airwake turbulence and its impact on helicopter flight dynamics. A better understanding of airwake turbulence and its role in driving pilot workload during ship–helicopter operations presents opportunities for improving the design of ship superstructures and augmented flight control systems, both of which should lead to improved safety and expanded operational capability.

This paper presents the results of a series of piloted flight simulation trials in which an SH-60B Sea Hawk helicopter has been flown to the deck of several different ships, under the influence of unsteady CFD-based ship airwakes. Both the CFD computations and the flight trials have been conducted by the current authors, whereby a key part of the analysis has been returning to the CFD data to understand and explain various phenomena observed during deck landings. Pilot workload ratings have been used to derive, as far as the authors are aware, the first fully simulated SHOL diagrams published in the literature.

The first part of the paper describes the simulator facility, before details of the CFD airwake generation and integration are given. Next, results from the flight trials are presented, in terms of control activity, pilot workload ratings and SHOL diagrams. Finally, some of the underlying CFD airwake data are shown in order to explain certain results from the flight trials.

II. Ship–Helicopter Simulation Approach

A. HELIFLIGHT-R Flight Simulation Facility

Piloted flight trials were conducted in the University of Liverpool’s HELIFLIGHT-R flight simulation facility, shown in Fig. 2. The facility consists of a six-degree-of-freedom, full motion base simulator, driven by several Linux-based PCs running FLIGHTLAB aircraft models through the PilotStation software package. The simulator itself is electrically actuated and capable of peak accelerations up to 1:0 g in heave and 0:7 g in surge and sway. HELIFLIGHT-R has been used successfully in a number of rotorcraft and fixed-wing simulation research projects. During the ship–helicopter trials the simulator was configured in a side-by-side, two-seat helicopter arrangement, with visuals provided by three LCD projectors giving a 220 by 65 deg field of view. Because of the 12 ft projection dome, visuals are projected on to a region close to the pilot’s feet, however, there are no discrete chin windows.

A FLIGHTLAB model of a UH-60 helicopter was used during the current study, with the location of its rear tail-wheel modified to make it representative of an SH-60B Seahawk (Fig. 3). Forces and moments on the four-bladed main rotor were calculated using a blade element model, with a finite-state dynamic inflow model used to account for distortion of air flow into the rotor disk. The tail rotor was modeled as a Bailey rotor disk, described in more detail in [30]. Forces on the fuselage and empennage were calculated from look-up tables of lift, drag and moment coefficients based on local flow velocities...