Adaptive Computing Systems for Aerospace

RÉSUMÉ En raison de leur complexité croissante, les systèmes informatiques modernes nécessitent de nouvelles méthodologies permettant d’automatiser leur conception et d’améliorer leurs performances. L’espace, en particulier, constitue un environnement très défavorable au maintien de la performance de ces systèmes : sans protection des rayonnements ionisants et des particules, l’électronique basée sur CMOS peut subir des erreurs transitoires, une dégradation des performances et une usure accélérée causant ultimement une défaillance du système. Les approches traditionnellement adoptees pour garantir la fiabilité du système et prolonger sa durée de vie sont basées sur la redondance, généralement établie durant la conception. En revanche, ces solutions sont coûteuses et parfois inefficaces, puisqu'elles augmentent la taille et la complexité du système, l'exposant à des risques plus élevés de surchauffe et d'erreurs. Les conséquences de ces limites sont d'autant plus importantes lorsqu'elles s’appliquent aux systèmes critiques (e.g., contraintes par le temps ou dont l’accès est limité) qui doivent être en mesure de prendre des décisions sans intervention humaine. Sur la base de ces besoins et limites, le développement en aérospatial de systèmes informatiques avec capacités adaptatives peut être considéré comme la solution la plus appropriée pour les dispositifs intégrés à haute performance. L’informatique auto-adaptative offre un potentiel sans égal pour assurer la création d’une génération d’ordinateurs plus intelligents et fiables. Qui plus est, elle répond aux besoins modernes de concevoir et programmer des systèmes informatiques capables de répondre à des objectifs en conflit. En nous inspirant des domaines de l’intelligence artificielle et des systèmes reconfigurables, nous aspirons à développer des systèmes informatiques auto-adaptatifs pour l’aérospatiale qui répondent aux enjeux et besoins actuels. Notre objectif est d’améliorer l’efficacité de ces systèmes, leur tolerance aux pannes et leur capacité de calcul. Afin d’atteindre cet objectif, une analyse expérimentale et comparative des algorithmes les plus populaires pour l’exploration multi-objectifs de l’espace de conception est d’abord effectuée. Les algorithmes ont été recueillis suite à une revue de la plus récente littérature et comprennent des méthodes heuristiques, évolutives et statistiques. L’analyse et la comparaison de ceux-ci permettent de cerner les forces et limites de chacun et d'ainsi définir des lignes directrices favorisant un choix optimal d’algorithmes d’exploration. Pour la création d’un système d’optimisation autonome—permettant le compromis entre plusieurs objectifs—nous exploitons les capacités des modèles graphiques probabilistes. Nous introduisons une méthodologie basée sur les modèles de Markov cachés dynamiques, laquelle permet d’équilibrer la disponibilité et la durée de vie d’un système multiprocesseur. Ceci est obtenu en estimant l'occurrence des erreurs permanentes parmi les erreurs transitoires et en migrant dynamiquement le calcul sur les ressources supplémentaires en cas de défaillance. La nature dynamique du modèle rend celui-ci adaptable à différents profils de mission et taux d’erreur. Les résultats montrent que nous sommes en mesure de prolonger la durée de vie du système tout en conservant une disponibilité proche du cas idéal. En raison des contraintes de temps rigoureuses imposées par les systèmes aérospatiaux, nous étudions aussi l’optimisation de la tolérance aux pannes en présence d'exigences d’exécution en temps réel. Nous proposons une méthodologie pour améliorer la fiabilité du calcul en présence d’erreurs transitoires pour les tâches en temps réel d’un système multiprocesseur homogène avec des capacités de réglage de tension et de fréquence. Dans ce cadre, nous définissons un nouveau compromis probabiliste entre la consommation d’énergie et la tolérance aux erreurs. Comme nous reconnaissons que la résilience est une propriété d’intérêt omniprésente (par exemple, pour la conception et l’analyse de systems complexes génériques), nous adaptons une définition formelle de celle-ci à un cadre probabiliste dérivé à nouveau de modèles de Markov cachés. Ce cadre nous permet de modéliser de façon réaliste l’évolution stochastique et l’observabilité partielle des phénomènes du monde réel. Nous proposons un algorithme permettant le calcul exact efficace de l’étape essentielle d’inférence laquelle est requise pour vérifier des propriétés génériques. Pour démontrer la flexibilité de cette approche, nous la validons, entre autres, dans le contexte d’un système informatisé reconfigurable pour l’aérospatiale. Enfin, nous étendons la portée de nos recherches vers la robotique et les systèmes multi-agents, deux sujets dont la popularité est croissante en exploration spatiale. Nous abordons le problème de l’évaluation et de l’entretien de la connectivité dans le context distribué et auto-adaptatif de la robotique en essaim. Nous examinons les limites des solutions existantes et proposons une nouvelle méthodologie pour créer des géométries complexes connectées gérant plusieurs tâches simultanément. Des contributions additionnelles dans plusieurs domaines sont résumés dans les annexes, nommément : (i) la conception de CubeSats, (ii) la modélisation des rayonnements spatiaux pour l’injection d’erreur dans FPGA et (iii) l’analyse temporelle probabiliste pour les systèmes en temps réel. À notre avis, cette recherche constitue un tremplin utile vers la création d’une nouvelle génération de systèmes informatiques qui exécutent leurs tâches d’une façon autonome et fiable, favorisant une exploration spatiale plus simple et moins coûteuse.----------ABSTRACT Today's computer systems are growing more and more complex at a pace that requires the development of novel and more effective methodologies to automate their design. Space, in particular, represents a challenging environment: without protection from ionizing and particle radiation, CMOS-based electronics are subject to transients faults, performance degradation, accelerated wear, and, ultimately, system failure. Traditional approaches adopted to guarantee reliability and extended lifetime are based on redundancy that is established at design-time. These solutions are expensive and sometimes inefficient, as they increase the complexity and size of a system, exposing it to higher risks of overheating and incurring in radiation-induced errors. Moreover, critical systems---e.g., time-constrained ones and those where access is limited---must be able to cope with pivotal situations without relying on human intervention. Hence, the emerging interest in computer systems with adaptive capabilities as the most suitable solution for novel high-performance embedded devices for aerospace. Self-adaptive computing carries unmatched potential and great promises for the creation of a new generation of smart, more reliable computers, and it addresses the challenge of designing and programming modern and future computer systems that must meet conflicting goals. Drawing from the fields of artificial intelligence and reconfigurable systems, we aim at developing self-adaptive computer systems for aerospace. Our goal is to improve their efficiency, fault-tolerance, and computational capabilities. The first step in this research is the experimental analysis of the most popular multi-objective design-space exploration algorithms for high-level design. These algorithms were collected from the recent literature and include heuristic, evolutionary, and statistical methods. Their comparison provides insights that we use to define guidelines for the choice of the most appropriate optimization algorithms, given the features of the design space. For the creation of a self-managing optimization framework---enabling the adaptive trade-off of multiple objectives---we leverage the tools of probabilistic graphical models. We introduce a mechanism based on dynamic hidden Markov models that balances the availability and lifetime of multiprocessor systems. This is achieved by estimating the occurrence of permanent faults amid transient faults, and by dynamically migrating the computation on excess resources, when failure occurs. The dynamic nature of the model makes it adjustable to different mission profiles and fault rates. The results show that we are able to lead systems to extended lifetimes, while keeping their availability close to ideal. On account of the stringent timing constraints imposed by aerospace systems, we then investigate the optimization of fault-tolerance under real-time requirements. We propose a methodology to improve the reliability of computation in the presence of transient errors when considering the mapping of real-time tasks on a homogeneous multiprocessor system with voltage and frequency scaling capabilities. In this framework, we take advantage of probability theory to define a novel trade-off between power consumption and fault-tolerance. As we recognize that resilience is a pervasive property of interest (e.g., for the design and analysis of generic complex systems), we adapt a formal definition of it to one more probabilistic framework derived from hidden Markov models. This allows us to realistically model the stochastic evolution and partial observability of complex real-world environments. Within this framework, we propose an efficient algorithm for the exact computation of the essential inference step required to construct generic property checking. To demonstrate the flexibility of this approach, we validate it in the context, among others, of a self-aware, reconfigurable computing system for aerospace. Finally, we move the scope of our research towards robotics and multi-agent systems: a topic of thriving popularity for space exploration. We tackle the problem of connectivity assessment and maintenance in the distributed and self-adaptive context of swarm robotics. We review the limitations of existing solutions and propose a novel methodology to create connected complex geometries for multiple task coverage. Additional contributions in the areas of (i) CubeSat design, (ii) the modelling of space radiation for FPGA fault-injection, and (iii) probabilistic timing analysis for real-time systems are summarized in the appendices. In the author's opinion, this research provides a number of useful stepping stones for the creation of a new generation of computing systems that autonomously---and reliably---perform their tasks for longer periods of time, fostering simpler and cheaper space exploration

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Computational approaches and structural prediction of high pressure molecular solids

The objective of this thesis is to study the crystal structures and electronic properties of solids at high pressure using state-of-the-art electronic structure computational methods. The thesis is divided into two main sections. The first part is to examine the performance and reliability of several current density functionals in the description of the electronic structures of small band gap materials and strongly correlated systems. The second part is to compare and evaluate two recently proposed first-principles methods for the prediction of stable structures of solids at high pressure. To accomplish the first goal, first-principle electronic structure calculations employing density functional theory (DFT) and several “correlation corrected” functionals calculations were used to investigate the properties of solid AlH3 and EuO at high pressure. The primary reason to study AlH3 is to resolve a discrepancy between previously predicted superconductivity behavior at 110 GPa but was not observed in experimental resistance measurements. The key to resolve the discrepancy is an accurate calculation of the valence and conduction band energies. The results shows that the Fermi surface is modified by the “improved” functionals over the previous calculations using “standard” gradient corrected functional. These changes in the Fermi surface topology removed the possibility of nesting of the electronic bands, therefore, solid AlH3 above 100 GPa is a poor metal instead of a superconductor. In the second system, we have studied EuO with highly localized electrons in the Eu 4f orbitals. A particular interest in this compound is the report of an anomalous isostructural phase transition with a significant volume reduction at 35-40 GPa and the relationship with the electronic state of Eu at high pressure. Using the Hubbard on-site repulsion model (LDA+U), we successfully predicted the insulator metal transition of EuO at 12 GPa and the trend in the Mössbauer isomer shifts. However, the isostructural transition was not reproduced. The U on-site repulsion to localized Eu 4f orbtials helped to ameliorate some deficiencies of the PBE functional and improved the agreement with experimental observations but not all the properties were correctly reproduced. The second objective of this investigation is to predict energetically stable crystalline structures at high pressure. The reliability and relative efficiency of two recently proposed structure prediction methods, viz, Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) were critically examined. We applied the techniques to two separate systems. The first system is solid CS2. The motivation is that this compound was recently found to be a superconductor with a critical temperature of 6 K from 60 – 120 GPa. However, no crystalline structure was found by experiment in this pressure range. Our calculations suggest the energetic favorable structures contain segregated regions of carbon and sulfur atoms. The sulfur atoms adopt a planar closed pack arrangement forming 2D square or hexagonal networks and the carbon atoms tend to form hexagonal rings. A global minimum crystalline structure with structural features observed in the amorphous structure was found and shown to be superconductive. In the second case, we studied the possibility on the existence of Xe-halides (XeHn (H=Cl, Br and I, n = 1, 2 and 4)) compounds below 60 GPa. We reported the stability, crystal and electronic structures, vibrational and optical spectra of a number of stoichiometric crystalline polymorphs. We found that only XeCl and XeCl2 form thermodynamically stable compounds at pressure exceeding 60 GPa. A stable cubic fcc structure of XeBr2 was found to be a superconductor with critical temperature of 1.4 K. From these studies, we found both merits and shortcomings with the two structural prediction approaches. In the end, we proposed a hybrid approach to assure the same stable structure is predicted from both computational strategies

Intramolecular Hydrogen Bonding 2021

This book describes the results of both theoretical and experimental research on many topical issues in intramolecular hydrogen bonding. Its great advantage is that the presented research results have been obtained using many different techniques. Therefore, it is an excellent review of these methods, while showing their applicability to the current scientific issues regarding intramolecular hydrogen bonds. The experimental techniques used include X-ray diffraction, infrared and Raman spectroscopy (IR), nuclear magnetic resonance spectroscopy (NMR), nuclear quadrupole resonance spectroscopy (NQR), incoherent inelastic neutron scattering (IINS), and differential scanning calorimetry (DSC). The solvatochromic and luminescent studies are also described. On the other hand, theoretical research is based on ab initio calculations and the Car–Parrinello Molecular Dynamics (CPMD). In the latter case, a description of nuclear quantum effects (NQE) is also possible. This book also demonstrates the use of theoretical methods such as Quantum Theory of Atoms in Molecules (QTAIM), Interacting Quantum Atoms (IQA), Natural Bond Orbital (NBO), Non-Covalent Interactions (NCI) index, Molecular Tailoring Approach (MTA), and many others

Bibliography of Lewis Research Center technical publications announced in 1993

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1993. All the publications were announced in the 1993 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

Bibliography of Lewis Research Center technical publications announced in 1985

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1985. All the publications were announced in the 1985 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses