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A critical situation can suddenly develop in the ‘pilot (automaton) - aircraft - operational environment’ system behavior as a result of unfavorable mixing and cross-coupling of several demanding operational factors. The latter can include adverse weather effects, pilot (automaton) errors, mechanical failures and hidden design flaws. These factors are typically linked by strong cause-and-effect relationships, which can disturb the normal flow of external forces and moments acting on the aircraft. As a result, a multifactor situation can quickly propagate towards a chain reaction type accident. Specialists (designers, flight test pilots/engineers, regulators, investigators, educators/instructors, line pilots) have limited resources to address multifactor cases during the aircraft life cycle. The main difficulty is combinatorics (‘the curse of dimensionality’) which determines technical, time and budget constraints.

A generic situational model of the “pilot (automaton) - aircraft - operational environment” system is employed as a ‘virtual safety test article’. The goal is to identify a priori potentially catastrophic, safe and interim developments in the system behavior in complex (multi-factor) flight situations. Distinguishing features of the technique include: affordability and autonomy of experimentation (a pilot and special hardware are not required), easy planning and fast-time simulation of a large number of non-standard flight scenarios on a computer, and automated assessment and classification of ‘flights’ using formalized safety criteria. A software tool called VATES, which implements this technique, is demonstrated. Several new graphic-analytical formats designed for system safety knowledge mapping are introduced using realistic situation examples.

In current design practices, safety, operational and handling criteria are often overlooked until late design stages due to the difficulty in capturing such criteria early enough in the design cycle and in the presence of limited and uncertain knowledge. Virtual (flight) testing and evaluation, based on autonomous modeling and simulation, is proposed as a solution to this shortcoming. The methodology enables one to evaluate vehicle behavior in relatively complex situations through a series of specific flight scenarios. Bringing this methodology to conceptual design requires the creation of an automatic link between the design database and the autonomous flight simulation environment. This paper describes the creation of such a link and an implementation of the Virtual Testing and Evaluation methodology with the use of an advanced design concept.

An affordable technique is proposed for fast quantitative analysis of aerobatics and other complex flight domains of highly maneuverable aircraft. A generalized autonomous situational model of the “pilot (automaton) – vehicle – operational environment” system is employed as a “virtual test article”. Using this technique, a systematic knowledge of the system behavior in aerobatic flight can be generated on a computer, much faster than real time. This information can be analyzed via a set of knowledge mapping formats using a 3-D graphics visualization tool. Piloting and programming skills are not required in this process. Possible applications include: aircraft design and education, applied aerodynamics, flight control systems design, planning and rehearsal of flight test and display programs, investigation of aerobatics-related flight accidents and incidents, physics-based pilot training, research into new maneuvers, autonomous flight, and onboard AI.

Flight accidents with modern aircraft are often a result of complex dynamics of the “pilot (automaton1) - vehicle - operational environment” system. When a “critical mass” of the system’s complexity exceeds a certain level, a “chain reaction” of irreversible cause-and-effect links can be spontaneously triggered in the system behavior leading to a catastrophe. An affordable, practically tested technique is proposed to complement current methods of flight accident analysis. A generic situational model of the system behavior and a computer are employed as a virtual test article. This model includes a six-degree-of-freedom non-linear flight dynamics model, a generic situational pilot model (“silicon pilot”), models of anticipated operational factors (conditions), and a tool for flight scenario planning. Available flight recorder data are used to tune the model and reconstruct the accident.

The ultimate goal of knowledge-based aircraft design, pilot training and flight operations is to make flight safety an inherent, built-in feature of the flight vehicle, such as its aerodynamics, strength, economics and comfort are. Individual flight accidents and incidents may vary in terms of quantitative characteristics, circumstances, and other external details. However, their cause-and-effect patterns often reveal invariant structure or essential causal chains which may re-occur in the future for the same or other vehicle types. The identification of invariant logical patterns from flight accident reports, time-histories and other data sources is very important for enhancing flight safety at the level of the ‘pilot - vehicle -operational conditions’ system. The objective of this research project was to develop and assess a method for ‘mining’ knowledge of typical cause-and-effect patterns from flight accidents and incidents.

A knowledge-centered approach to aircraft flight safety enhancement is proposed. Using an example of modeling and simulation of a flight accident, a concept of the Intelligent Situational Awareness and Forecasting Environment (the S.A.F.E. concept) is introduced. The purpose of this type of onboard system is short-term prediction of a tree-network of possible safe and unsafe flightpaths under complex (multi-factor) flight situations. Two notional systems are discussed: the Situational Forecast Display and the Flight Safety Indicator. Potential applications include pilot-vehicle intelligent interface, automatic flight envelope protection, autonomous (robotic) flight, knowledge-centered pilot assistance and pilot training, and automatic resolution of conflicts in close ‘free flight’ navigation space, etc.

A technique is proposed for examining complex behaviors in the “pilot - vehicle - operational conditions” system using an autonomous situational model of flight. The goal is to identify potentially critical flight situations in the system behavior early in the design process. An exhaustive set of flight scenarios can be constructed and modeled on a computer by the designer in accordance with test certification requirements or other inputs. Distinguishing features of the technique include the autonomy of experimentation (the pilot and a flight simulator are not involved) and easy planning and quick modeling of complex multi-factor flight cases. An example of mapping airworthiness requirements into formal scenarios is presented. Simulation results for various flight situations and aircraft types are also demonstrated.