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In this work we discuss some types of simulation architectures and standards, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity x fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“stand-alone”, PIL, HIL, MIL, DIS, HLA, etc.), their standards (OMBA, SIMNET, ALSP, DIS, HLA 1.3, HLA 1516, ASIA, AP2633, etc.) and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry

On several engineering applications high Reliability is one of the most wanted features. The aspects of Reliability play a key role in design projects of aircraft, spacecraft, automotive, medical, bank systems, and so, avoiding loss of life, property, or costly recalls. The highly reliable systems are designed to work continuously, even upon external threats and internal Failures. Very convenient is the fact that the term 'Failure' may have its meaning tailored to the context of interesting, as its general definition refers to it as "any deviation from the specified behavior of a system". The above-mentioned 'deviation' may refer to: performance degradation, operational misbehavior, deviation of environmental qualification levels, Safety hazards, etc. Nevertheless, Reliability is not the only requirement for a modern system. Other features as Availability, Integrity, Security and Safety are always part of the same technical specification, in a same level of importance.

In this work we discuss some types of simulators and simulations, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity × fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“standalone”, PIL, HIL, MIL, DIS, HLA, etc.), their environments (discrete, continuous, hybrid, etc.) and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry

The increasing use of Global Navigation Satellite Systems-GNSS in future Aeronautical Navigation Systems-ANS is a current trend in the aeronautical operation and regulation communities. This trend implies the adoption of elements and interactions of a degree of complexity that is still being discussed around the world. Faced with that, we believe that a requirements based approach is an effective tool to deal with such highly complex and integrated systems. In this work we discuss a requirements based approach to future Aeronautical Navigation Systems based on Global Navigation Satellite Systems. To do that, we first briefly present the concept of Communication, Navigation, Surveillance/Air Traffic Management - CNS/ATM, and the current and potential benefits of the adoption of its paradigms.

In this work we discuss some types of simulation environments and laboratories, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity × fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“stand-alone”, PIL, HIL, MIL, DIS, HLA, etc.), and especially, their environments (discrete, continuous, hybrid, etc.) and laboratories (physical, computational, hybrid, etc.), and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry.

In this work we discuss the fault avoidance and the fault tolerance approaches for increasing the reliability of aerospace and automotive systems. This includes: the basic definitions/concepts (reliability, maintainability, availability, redundancy, etc.), and characteristics (a priori analysis, a posteriori analysis, physical/hardware redundancy, analytical/software redundancy, etc.) of both approaches, their mathematical background and models (exponential, Weilbull, etc.), their basic theory, their methods and techniques (fault trees, dependence diagrams, Markov chains, etc.), some of their standards (SAE-ARP4761, AC 25.1309, etc.) and simulation environments (Cafta, etc.), and their applications to the reliability analysis and reliability improvement of aerospace and automotive vehicles. This is illustrated by some examples driven from the aerospace and automotive industries.