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Companies are gradually developing: 1) complex and/or highly integrated systems including vehicles (as satellites, airplanes, cars, etc.) or equipment (as computers, cell phones, no breaks, etc.) to use under 2) increasingly varied or inhospitable environments, and to survive under 3) increasingly long life cycles and unavoidable changes in staff & facilities & technologies. The overall decision to use (by time, cost, quality, of functions, services, etc.) such end systems under 2 require 4) high Dependability (Reliability, Maintainability, Availability, Correction, Safety, Security, etc.) of them. The overall survival in use (by health monitoring, housekeeping, retrofit, upgrade, etc.) of such end systems under 3 require 5) high Suportability (Maintainability, Adaptability, Availability, Robustness, etc.) of them coupled with the support systems.

Currently, aerospace and automotive industries are developing complexand/or highly integrated systems, whose services require greater confidence to meet a set of specifications that are increasingly demanding, such as successfully operating a communications satellite, a commercial airplane, an automatic automobile, and so on. To meet these requirements and expectations, there is a growing need for fault treatment, up to predict faults and monitor the health of the components, equipment, subsystems or systems used. In the last decades, the approaches of 1) Fault Prevention, 2) Fault Detection/Tolerance and 3) Fault Detection/Correction have been widely studied and explored.

Modeling and Simulation (M&S) of dynamic systems based on computers is a multidisciplinary field that involves several knowledge areas and tools, and is broadly used in all development areas of space industry such as rocket and satellite design and construction. Once space systems are divided into several subsystems for ease of engineering, their models are divided the same way for the same reason. Such models may be done using different computational tools that are based on either physical flows, informational flows, or hybrid flows, depending on the subsystem nature. This is specially true for a satellite propulsion subsystem, and its physical (volume, mass, energy, enthalpy, entropy, linear momentum, etc.) flows. This paper presents the modeling and simulation of a satellite propulsion subsystem by physical and signal flows. To accomplish this task, two different computational tools were used: AMESim and MatLab.

Real-time critical systems are those whose failures may cause loss of transactions/data, missions/batches, vehicles/properties, or even people/human life. Accordingly, some regulations prescribe their maximum acceptable probability of failures to range from about 10−4 to 10−10 failures per hour. Examples of such systems are the ones involving nuclear plants, aircrafts, satellites, automobiles, or traffic controls. They are becoming increasingly complex and/or highly integrated as prescribed by the SAE-ARP-4754A Standard. Those systems include, most of the time, real time critical software that must be specified, designed, implemented, validated, verified and accredited (VVA). To do that, models, specially the V-Model, are frequently adopted, together with methods and tools which perform software VVA to ensure compliance (of correctness, reliability, robustness, etc.) of software to several specific standards such as DO178-B/DO-178C (aviation) or IEC 26262 (automotive) among others.

In this work we discuss current trends driving the aerospace and automotive systems architectures. This includes trends as: 1) pos-globalization and regionalization; 2) the formation of knowledge oligopolies; 3) commonality, standardization and even synergy (of components, tools, development process, certification agents, standards); 4) reuse and scalability; 5) synergy of knowledge and tools convergence; 6) time, cost and quality pressures and innovation speed; 7) environmental and safety issues; and 8) abundance of new technologies versus scarcity of skilled manpower to apply them.

This paper presents the preliminary results of an "a posteriori" exercise of application of a Requirements Traceability Automation Tool (RT tool) to a set of documents. The documents have been prepared according to established Space System Engineering methodologies and with attention to text quality, but without attention to requirements traceability because the processes and methodologies used during their preparation predates the emergence of the processes and methodologies developed by Requirements Engineering (RE). This study is intended to determine some of the benefits of using a RT tool when compared with the previously used processes and methodologies. The set of documents under scrutiny have been prepared in the frame of the development of the CBERS-3 satellite (China-Brazil Earth Resources Satellite) and is composed of system, subsystem and equipment specification and covering documents related to the Electrical Power Subsystem (EPS) of the satellite.

Nowadays, given the shrinking budgets and deadlines of the aerospace and automotive industries, the importance and need of the requirements engineering is becoming more and more evident. This means that progressively more users face a difficult task on the different environments of project development: 1) to write better requirements; and 2) to do it faster than ever. It would be nice if they had some tools to help them and abbreviate such a difficult task. This work summarizes the development of a new tool that does exactly that. Its wizard guides the user through the steps necessary to create good requirements when writting a requirements document, depending on the kind of requirements document desired. For example: there are significant differences between user requirements and system requirements documents. The wizard script is composed by a serie of questions related to the parts of the scheme to build a complete and effective requirement.

This works presents the generation and customization of real time code for embedded controllers using a modeling and simulation environment. When the controller model is considered satisfactory, the developers can use a code generation tool to build a real time source code capable to be migrated to an embedded target processor. The code generation tool used is capable to generate real time code in ANSI C or ADA 95 languages. This process can be customized to adequate to a target processor and/or a Real Time Operating System (RTOS). The code customization can be achieved using a specific Template Programming Language (TPL) that specifies how the code will be generated. This technique makes it possible the instantiation of real time embedded controllers code using the same controller model to a wide variety of target processors and/or RTOSs.

In this work we present a new procedure for customizing, in the desired format, requirements reports generated by a Requirements Engineering Environment. This environment includes tools for: 1- capturing textual and pictoric requirements; 2- templating requirements documents that can be adjustable to the formats required by the certification authorities or system engineering groups; 3- translating features from/to the main word processors used in the industry (Word, Excel, etc. formats); 4- managing requirements configuration. It provides gains of productivity, correctness, reusability, traceability, coverage, etc, improving the efficiency of the projects. The procedure emphasizes items 2 and 3, and is illustrated with 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.