Advanced Caution and Warning System

The current focus of ACAWS is on the needs of the flight controllers. The onboard crew in low-Earth orbit has some of those same needs. Moreover, for future deep-space missions, the crew will need to accomplish many tasks autonomously due to communication time delays. Although we are focusing on flight controller needs, ACAWS technologies can be reused for on-board application, perhaps with a different level of detail and different display formats or interaction methods. We expect that providing similar tools to the flight controllers and the crew could enable more effective and efficient collaboration as well as heightened situational awareness

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Compilation of thesis abstracts, September 2009

NPS Class of September 2009This quarter’s Compilation of Abstracts summarizes cutting-edge, security-related research conducted by NPS students and presented as theses, dissertations, and capstone reports. Each expands knowledge in its field.http://archive.org/details/compilationofsis109452751

Methods for the efficient measurement of phased mission system reliability and component importance

An increasing number of systems operate over a number of consecutive time periods, in which their reliability structure and the consequences of failure differ, in order to perform some overall operation. Each distinct time period is known as a phase and the overall operation is known as a phased mission. Generally, a phased mission fails immediately if the system fails at any point and is considered a success only if all phases are completed without failure. The work presented in this thesis provides efficient methods for the prediction and optimisation of phased mission reliability. A number of techniques and methods for the analysis of phased mission reliability have been previously developed. Due to the component and system failure time dependencies introduced by the phases, the computational expense of these methods is high and this limits the size of the systems that can be analysed in reasonable time frames on modern computers. Two importance measures, which provide an index of the influence of each component on the system reliability, have also been previously developed. This is useful for the optimisation of the reliability of a phased mission, however a much larger number have been developed for non-phased missions and the different perspectives and functions they provide are advantageous. This thesis introduces new methods as well as improvements and extensions to existing methods for the analysis of both non-repairable and repairable systems with an emphasis on improved efficiency in the derivation of phase and mission reliability. New importance measures for phased missions are also presented, including interpretations of those currently available for non-phased missions. These provide a number of interpretations of component importance, allowing those most suitable in a given context to be employed and thus aiding in the optimisation of mission reliability. In addition, an extensive computer code has been produced that implements and tests the majority of the newly developed techniques and methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Methods for the efficient measurement of phased mission system reliability and component importance

An increasing number of systems operate over a number of consecutive time periods, in which their reliability structure and the consequences of failure differ, in order to perform some overall operation. Each distinct time period is known as a phase and the overall operation is known as a phased mission. Generally, a phased mission fails immediately if the system fails at any point and is considered a success only if all phases are completed without failure. The work presented in this thesis provides efficient methods for the prediction and optimisation of phased mission reliability. A number of techniques and methods for the analysis of phased mission reliability have been previously developed. Due to the component and system failure time dependencies introduced by the phases, the computational expense of these methods is high and this limits the size of the systems that can be analysed in reasonable time frames on modern computers. Two importance measures, which provide an index of the influence of each component on the system reliability, have also been previously developed. This is useful for the optimisation of the reliability of a phased mission, however a much larger number have been developed for non-phased missions and the different perspectives and functions they provide are advantageous. This thesis introduces new methods as well as improvements and extensions to existing methods for the analysis of both non-repairable and repairable systems with an emphasis on improved efficiency in the derivation of phase and mission reliability. New importance measures for phased missions are also presented, including interpretations of those currently available for non-phased missions. These provide a number of interpretations of component importance, allowing those most suitable in a given context to be employed and thus aiding in the optimisation of mission reliability. In addition, an extensive computer code has been produced that implements and tests the majority of the newly developed techniques and methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Rotor Fatigue Life Prediction and Design for Revolutionary Vertical Lift Concepts

Despite recent technological advancements, rotorcraft still lag behind their fixed-wing counterparts in the areas of flight safety and operating cost. Competition with fixed-wing aircraft is difficult for applications where vertical takeoff and landing (VTOL) capabilities are not required. Both must be addressed to ensure the continued competitiveness of vertical lift aircraft, especially in the context of new military and civilian rotorcraft programs such as Future Vertical Lift and urban air mobility, which will require orders-of-magnitude improvements in reliability, availability, maintainability, and cost (RAM-C) metrics. Lifecycle costs and accident rates are strongly driven by scheduled replacement or failure of flight-critical components. Rotor blades are life-limited to ensure that they are replaced before fatigue damage exceeds critical levels, but purchasing new blades is extremely costly. Despite aggressive component replacement times, fatigue failure of rotor blades continues to account for a significant proportion of inflight accidents. Fatigue damage in rotorcraft is unavoidable due to the physics of rotary-wing flight, but new engineering solutions to improve fatigue life in the rotor system could improve rotorcraft operating costs and flight safety simultaneously. Existing rotorcraft design methods treat fatigue life as a consequence, rather than a driver, of design. A literature review of rotorcraft design and fatigue design methods is conducted to identify the relevant strengths and weaknesses of traditional processes. In rotorcraft design, physics-based rotor design frameworks are focused primarily on fundamental performance analysis and do not consider secondary characteristics such as reliability or fatigue life. There is a missing link between comprehensive rotor design frameworks and conceptual design tools that prevents physics-based assessment of RAM-C metrics in the early design stages. Traditional fatigue design methods, such as the safe life methodology, which applies the Miner's rule fatigue life prediction model to rotorcraft components, are hindered by a lack of physics-based capabilities in the early design stages. An accurate fatigue life quantification may not be available until the design is frozen and prototypes are flying. These methods are strongly dependent on extrapolations built on historical fatigue data, and make use of deterministic safety factors based on organizational experience to ensure fatigue reliability, which can lead to over-engineering or unreliable predictions when applied to revolutionary vertical lift aircraft. A new preliminary fatigue design methodology is designed to address these concerns. This methodology is based on the traditional safe life methodology, but replaces several key elements with modern tools, techniques, and models. Three research questions are proposed to investigate, refine, and validate different elements of the methodology. The first research question addresses the need to derive physics-based fatigue load spectra more rapidly than modern comprehensive analysis tools allow. The second investigates the application of different probabilistic reliability solution methods to the fatigue life substantiation problem. The third question tests the ability of the preliminary fatigue design methodology to evaluate the relative impact of common preliminary fatigue design variables on the probability of fatigue failure of a conceptual helicopter's rotor blade. Hypotheses are formulated in response to each research question, and a series of experiments are designed to test those hypotheses. In the first experiment, a multi-disciplinary analysis (MDA) environment combining the rotorcraft performance code NDARC, the comprehensive code RCAS, and the beam analysis program VABS, is developed to provide accurate physics-based predictions of rotor blade stress in arbitrary flight conditions. A conceptual single main rotor transport helicopter based on the UH-60A Black Hawk is implemented within the MDA to serve as a test case. To account for the computational expense of the MDA, surrogate modeling techniques, such as response surface equations, artificial neural networks, and Gaussian process models are used to approximate the stress response across the flight envelope of the transport helicopter. The predictive power and learning rates of various surrogate modeling techniques are compared to determine which is the most suitable for predicting fatigue stress. Ultimately, shallow artificial neural networks are found the provide the best compromise between accuracy, training expense, and uncertainty quantification capabilities. Next, structural reliability solution methods are investigated as a means to produce high-reliability fatigue life estimates without requiring deterministic safety factors. The Miner's sum fatigue life prediction model is reformulated as a structural reliability problem. Analytical solutions (FORM and SORM), sampling solutions (Monte Carlo, quasi-Monte Carlo, Latin hypercube sampling, and directional simulation), and hybrid solutions importance sampling) are compared using a notional fatigue life problem. These results are validated using a realistic helicopter fatigue life problem \jnr{which incorporates the fatigue stress surrogate model and is based on a probabilistic definition of the mission spectrum to account for fleet-wide usage variations. Monte Carlo simulation is found to provide the best performance and accuracy when compared to the exact solution. Finally, the capabilities of the preliminary fatigue design methodology are demonstrated using a series of hypothetical fatigue design exercises. First, the methodology is used to predict the impact of rotor blade box spar web thickness on probability of fatigue failure. Modest increases in web thickness are found to reduce probability of failure, but larger increases cause structural instability of the rotor blade in certain flight regimes which increases the fatigue damage rate. Next, a similar study tests the impact of tail rotor cant angle. Positive tail rotor cant is found to improve fatigue life in cases where the center of gravity (CG) of the vehicle is strongly biased towards the tail, but is detrimental if the CG is closer to the main rotor hub station line. Last, the effect of design mission requirements like rate of climb and cruising airspeed is studied. The methodology is not sensitive enough to predict the subtle impact of changes to rate of climb, but does prove that a slower cruising airspeed will decrease probability of fatigue failure of the main rotor blade. The methodology is proven to be capable of quantifying the influence of \jnr{rotor blade design variables, vehicle layout and configuration, and certain design mission requirements}, paving the way for implementation in a rotorcraft design framework. This thesis ends with suggestions for future work to address the most significant limitations of this research, as well as descriptions of the tasks required to apply the methodology to conventional rotorcraft or conceptual revolutionary vertical lift aircraft.Ph.D

Technological roadmap on AI planning and scheduling

At the beginning of the new century, Information Technologies had become basic and indispensable constituents of the production and preparation processes for all kinds of goods and services and with that are largely influencing both the working and private life of nearly every citizen. This development will continue and even further grow with the continually increasing use of the Internet in production, business, science, education, and everyday societal and private undertaking. Recent years have shown, however, that a dramatic enhancement of software capabilities is required, when aiming to continuously provide advanced and competitive products and services in all these fast developing sectors. It includes the development of intelligent systems – systems that are more autonomous, flexible, and robust than today’s conventional software. Intelligent Planning and Scheduling is a key enabling technology for intelligent systems. It has been developed and matured over the last three decades and has successfully been employed for a variety of applications in commerce, industry, education, medicine, public transport, defense, and government. This document reviews the state-of-the-art in key application and technical areas of Intelligent Planning and Scheduling. It identifies the most important research, development, and technology transfer efforts required in the coming 3 to 10 years and shows the way forward to meet these challenges in the short-, medium- and longer-term future. The roadmap has been developed under the regime of PLANET – the European Network of Excellence in AI Planning. This network, established by the European Commission in 1998, is the co-ordinating framework for research, development, and technology transfer in the field of Intelligent Planning and Scheduling in Europe. A large number of people have contributed to this document including the members of PLANET non- European international experts, and a number of independent expert peer reviewers. All of them are acknowledged in a separate section of this document. Intelligent Planning and Scheduling is a far-reaching technology. Accepting the challenges and progressing along the directions pointed out in this roadmap will enable a new generation of intelligent application systems in a wide variety of industrial, commercial, public, and private sectors

Dependability modeling and evaluation – From AADL to stochastic Petri nets

Conduire des analyses de sûreté de fonctionnement conjointement avec d'autres analyses au niveau architectural permet à la fois de prédire les effets des décisions architecturales sur la sûreté de fonctionnement du système et de faire des compromis. Par conséquent, les industriels et les universitaires se concentrent sur la définition d'approches d'ingénierie guidées par des modèles (MDE) et sur l'intégration de diverses analyses dans le processus de développement. AADL (Architecture Analysis and Design Language) a prouvé son aptitude pour la modélisation d'architectures et ce langage est actuellement jugé efficace par les industriels dans de telles approches. Notre contribution est un cadre de modélisation permettant la génération de modèles analytiques de sûreté de fonctionnement à partir de modèles AADL dans l‘objectif de faciliter l'évaluation de mesures de sûreté de fonctionnement comme la fiabilité et la disponibilité. Nous proposons une approche itérative de modélisation. Dans ce contexte, nous fournissons un ensemble de sous-modèles génériques réutilisables pour des architectures tolérantes aux fautes. Le modèle AADL de sûreté de fonctionnement est transformé en un RdPSG (Réseau de Petri Stochastique Généralisé) en appliquant des règles de transformation de modèle. Nous avons implémenté un outil de transformation automatique. Le RdPSG résultant peut être traité par des outils existants pour obtenir des mesures de sûreté de fonctionnement. L'approche est illustrée sur un ensemble du Système Informatique Français de Contrôle de Trafic Aérien. ABSTRACT : Performing dependability evaluation along with other analyses at architectural level allows both predicting the effects of architectural decisions on the dependability of a system and making tradeoffs. Thus, both industry and academia focus on defining model driven engineering (MDE) approaches and on integrating several analyses in the development process. AADL (Architecture Analysis and Design Language) has proved to be efficient for architectural modeling and is considered by industry in the context presented above. Our contribution is a modeling framework allowing the generation of dependability-oriented analytical models from AADL models, to facilitate the evaluation of dependability measures, such as reliability or availability. We propose an iterative approach for system dependability modeling using AADL. In this context, we also provide a set of reusable modeling patterns for fault tolerant architectures. The AADL dependability model is transformed into a GSPN (Generalized Stochastic Petri Net) by applying model transformation rules. We have implemented an automatic model transformation tool. The resulting GSPN can be processed by existing tools to obtain dependability measures. The modeling approach is illustrated on a subsystem of the French Air trafic Control System