Marilena D. Pavel

Validation of mathematical models for helicopter flight simulators past, present and future challenges

At the heart of a flight simulator resides the mathematical representation of aircraft behaviour in response to control inputs, atmospheric disturbances and system inputs including failures and malfunctions. While this mathematical model can never be wholly accurate, its fidelity, in comparison with real world behaviour, underpins the usefulness of the flight simulator. The present paper examines the state of the art achieved in validating mathematical models for helicopter simulators, addressing the strengths and weaknesses of the present European standard for the qualification of helicopter flight simulators, JAR FSTD-H (previously JAR-STD-1H/2H/3H). Essential questions are examined, such as: What is the required model fidelity to guarantee a simulation is sufficiently representative to be fit for purpose? Are the tolerances set in the current standards fine enough that they lead to only minor changes in handling qualities? What is an acceptable tuning process for the simulation? What is the effect of modelling fidelity on the overall pilot control strategy? What is the relationship between the settings of the simulator cueing environment and the behaviour of the pilot? What is the industrial experience on qualification of flight simulators that might usefully inform developments? Many of these questions were addressed in Europe in a previous GARTEUR Action Group (AG) HC/AG-12 the results of which are documented in this paper. Solutions are proposed for improving the current JAR-FSTD standard with respect to validation of mathematical models.

Prediction of the Necessary Degrees of Freedom for Helicopter Real-Time Simulation Models

The purpose of this paper is to examine the mathematical modeling of the helicopter flight dynamics for simulator qualification and to reveal new insights into the mathematical models response fidelity. The paper will focus on the qualification process of the simulator mathematical model as given by joint aviation requirement STD-1H, the European standard for helicopter simulator qualification. Using the joint-aviation-requirement tolerances, defined as acceptable differences between the model results, the flight test data, and the critical-pole-distance method developed at Delft University of Technology for predicting the necessary degrees of freedom of a simulation model, the paper will perform a sensitivity study on the pitch tolerances specified by the joint-aviation-requirement regulation, investigating how these tolerances might affect the model level of detail. It will be demonstrated that depending on the rotor system, the tolerances may or may not affect the helicopter flight dynamics behavior. For an articulated centrally hinged rotor, it will be shown that the tolerances have very little effect on the level of detail used in the modeling; for a hingeless rotor, variations in the model from an uncoupled flap-body dynamics to a coupled flap-body result in large variation in the simulation results and handling-qualities characteristics.

Helicopter Gas Turbine Engine Performance Analysis : A Multivariable Approach

Helicopter performance relies heavily on the available output power of the engine(s) installed. A simplistic single-variable analysis approach is often used within the flight-testing community to reduce flight-test data in order to predict the available output power under various atmospheric conditions. This simplistic approach often results in unrealistic predictions. This paper proposes a novel method for analyzing flight-test data of a helicopter gas turbine engine. The so-called “Multivariable Polynomial Optimization under Constraints” method is capable of providing an improved estimation of the engine maximum available power. The Multivariable Polynomial Optimization under Constraints method relies on optimization of a multivariable polynomial model subjected to equalities and inequalities constraints. The Karush–Khun–Tucker optimization method is used with the engine operating limitations serving as inequalities constraints. The proposed Multivariable Polynomial Optimization under Constraints method is applied to a set of flight-test data of a Rolls Royce/Allison MTU250-C20 gas turbine, installed on an MBB BO-105 M helicopter. It is shown that the Multivariable Polynomial Optimization under Constraints method can predict the engine output power under a wider range of atmospheric conditions and that the standard deviation of the output power estimation error is reduced from 13 hp in the single-variable method to only 4.3 hp using the Multivariable Polynomial Optimization under Constraints method (over 300% improvement).

Designing the Ornicopter, a tailless helicopter with active flapping blades: a case study

The Ornicopter concept is a single-rotor, tailless configuration. By actively flapping its blades, the Ornicopter rotor can propel itself to rotate, and hence does not need a tail rotor. In previous research, the Ornicopter concept has been compared with the Bo-105 conventional helicopter from various aspects, while the Ornicopter has the same design parameters as the Bo-105. Comparisons show that the Ornicopter has one major drawback, namely a small flight envelope. To improve the Ornicopter performance and understand how the Ornicopter should be designed, in this paper, the Ornicopter design is unfrozen and optimized for the flight envelope. The optimization result shows that with a proper design, the Ornicopter performance can be improved dramatically. A similar flight envelope as the Bo-105 can be achieved for the Ornicopter. However, the Ornicopter requires higher power than the Bo-105 due to the inherent characteristics of this concept.