Terrain Referenced Navigation Using SIFT Features in LiDAR Range-Based Data

The use of GNSS in aiding navigation has become widespread in aircraft. The long term accuracy of INS are enhanced by frequent updates of the highly precise position estimations GNSS provide. Unfortunately, operational environments exist where constant signal or the requisite number of satellites are unavailable, significantly degraded, or intentionally denied. This thesis describes a novel algorithm that uses scanning LiDAR range data, computer vision features, and a reference database to generate aircraft position estimations to update drifting INS estimates. The algorithm uses a single calibrated scanning LiDAR to sample the range and angle to the ground as an aircraft flies, forming a point cloud. The point cloud is orthorectified into a coordinate system common to a previously recorded reference of the flyover region. The point cloud is then interpolated into a Digital Elevation Model (DEM) of the ground. Range-based SIFT features are then extracted from both the airborne and reference DEMs. Features common to both the collected and reference range images are selected using a SIFT descriptor search. Geometrically inconsistent features are filtered out using RANSAC outlier removal, and surviving features are projected back to their source coordinates in the original point cloud. The point cloud features are used to calculate a least squares correspondence transform that aligns the collected features to the reference features. Applying the correspondence that best aligns the ground features is then applied to the nominal aircraft position, creating a new position estimate. The algorithm was tested on legacy flight data and typically produces position estimates within 10 meters of truth using threshold conditions

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Atomic imaging of complex molecular

One of the significant challenges of modern science is to track and image chemical reactions as they occur. The molecular movies, the precise spatiotemporal tracking of changes in their molecular dynamics, will provide a wealth of actionable insights into how nature works. Experimental techniques need to resolve the relevant molecular motions in atomic resolution, which includes (10^(-10) m) spatial dimensions and few- to hundreds of femtoseconds (10^(-15) s) temporal resolution. Laser-induced electron diffraction (LIED), a laser-based electron diffraction technique, images even singular molecular structures with combined sub-atomic picometre and femto-to attosecond spatiotemporal resolution. Here, a laser-driven attosecond electron wave packet scatters the parent’s ion after photoionization. The measured diffraction pattern of the electrons provides a unique fingerprint of molecular structure. Taking snapshots of molecular dynamics via the LIED technique is proved to be a potent tool to understand the intertwining of molecules and how they react, change, break, bend, etc. This thesis is especially interested in exploiting advanced LIED imaging techniques to retrieve large complex molecular structures. So far, LIED has successfully retrieved molecular information from small gas-phase molecules like oxygen (O2), nitrogen (N2), acetylene (C2H2), carbon disulfide (CS2), ammonia (NH3) and carbonyl sulfide (OCS). Nevertheless, most biology interesting organic molecules typically exist as liquid or solid at room temperature. In order to accomplish the final goal to extract these larger complex molecular structural information, we need to overcome two main challenges: delivering the liquid or solid samples as a gas-phase jet with sufficient gas density in the experiment and developing a new retrieval algorithm to extract the geometrical information from the diffraction pattern. We tested one of the most simple liquid molecules - water H2O in the reaction chamber as a primary step. We traced the variation of H2O+ cation structure under the different electric fields. To solve the problem of unsatisfactory gas density, we present a novel delivery system utilizing Tesla valves that generates more than an order-of-magnitude denser gaseous beam. Machine learning is well qualified to solve difficulties with manifold degrees of freedom. We use convolutional neural networks (CNNs) combined with LIED techniques to enable atomic-resolution imaging of the complex chiral molecule Fenchone (C10H16O).Uno de los desafíos importantes de la ciencia moderna es rastrear y obtener imágenes de las reacciones químicas a medida que ocurren. Las películas moleculares, el seguimiento espaciotemporal preciso de los cambios en su dinámica molecular, proporcionarán una gran cantidad de conocimientos prácticos sobre cómo funciona la naturaleza. Las técnicas experimentales necesitan resolver los movimientos moleculares relevantes en resolución atómica, que incluye ($10^{-10}$ m) dimensional espacial y resolución temporal de pocos a cientos de femtosegundos ($10^{-15}$ s). La difracción de electrones inducida por láser (LIED-Laser-induced electron diffraction), una técnica de difracción de electrones basada en láser, crea imágenes incluso de estructuras moleculares singulares con una resolución espaciotemporal subatómica combinada de picómetro y femto a attosegundo. Aquí, un paquete de ondas de electrones de attosegundos impulsado por láser dispersa el ion del padre después de la fotoionización. El patrón de difracción medido de los electrones proporciona una huella única de la estructura molecular. Se ha demostrado que tomar instantáneas de la dinámica molecular a través de la técnica LIED es una herramienta potente para comprender el entrelazamiento de las moléculas y cómo reaccionan, cambian, se rompen, se doblan, etc. Esta tesis está especialmente interesada en explotar técnicas avanzadas de imagen LIED para recuperar estructuras moleculares grandes y complejas. Hasta ahora, LIED ha recuperado con éxito información molecular de pequeñas moléculas en fase gaseosa como oxígeno (O2), nitrógeno (N2), acetileno (C2H2), disulfuro de carbono (CS2), amoníaco (NH3) y sulfuro de carbonilo (OCS). Sin embargo, la mayoría de las moléculas orgánicas interesantes para la biología suelen existir como líquidas o sólidas a temperatura ambiente. Para lograr el objetivo final de extraer esta información estructural molecular compleja más grande, debemos superar dos desafíos principales: entregar las muestras líquidas o sólidas como un chorro de fase gaseosa con suficiente densidad de gas en el experimento y desarrollar un nuevo algoritmo de recuperación para extraer la información geométrica del patrón de difracción. Probamos una de las moléculas líquidas más simples: agua H2O en la cámara de reacción como primer paso. Trazamos la variación de la estructura del catión H2O+ bajo los diferentes campos eléctricos. Para resolver el problema de la densidad de gas insatisfactoria, presentamos un novedoso sistema de suministro que utiliza válvulas Tesla que genera más de un haz gaseoso más denso en un orden de magnitud. El aprendizaje automático está bien calificado para resolver dificultades con múltiples grados de libertad. Utilizamos redes neuronales convolucionales (CNN-convolutional neural networks) combinadas con técnicas LIED para permitir imágenes de resolución atómica de la molécula quiral compleja Fenchone (C10H16OPostprint (published version

Acoustic Particle-Image Velocimetry: development and applications

Particle Image Velocimetry (PIV) is a non-intrusive technique for simultaneously measuring the velocities at many points in a fluid flow. The fluid is seeded with tracer particles and the region under investigation is illuminated. An image of the illuminated region is captured and then, a short time period later, a second image is taken. Suitable analysis of these images yields an instantaneous velocity vector map. Until recently, restrictions in the rate at which images could be captured have limited the PIV technique to the analysis of slow flows. However, advances in camera technology have now opened up the possibility of using PIV in the analysis of faster flows. Indeed, image capture rates are now fast enough to enable two images to be captured during a fraction of an acoustic cycle, indicating the potential for using PIV to analyse sound fields. In this thesis, after some aspects of sound field theory have been outlined and following a discussion of the theory of PIV, the development of experimental PIV apparatus for measuring sound fields is described. Measurements of the temporal variation in the velocities of particles within some common sound fields are presented. In particular, the passage of an acoustic pulse is monitored and the sinusoidal motion of particles in a resonating tube is recorded yielding the corresponding standing wave pattern. Finally, the main limitations of the PIV technique when applied to acoustic fields are discussed

Advanced Approaches Applied to Materials Development and Design Predictions

This thematic issue on advanced simulation tools applied to materials development and design predictions gathers selected extended papers related to power generation systems, presented at the XIX International Colloquium on Mechanical Fatigue of Metals (ICMFM XIX), organized at University of Porto, Portugal, in 2018. In this issue, the limits of the current generation of materials are explored, which are continuously being reached according to the frontier of hostile environments, whether in the aerospace, nuclear, or petrochemistry industry, or in the design of gas turbines where efficiency of energy production and transformation demands increased temperatures and pressures. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on failure mechanism modeling and simulation of materials are covered. As the Guest Editors, we would like to thank all the authors who submitted papers to this Special Issue. All the papers published were peer-reviewed by experts in the field whose comments helped to improve the quality of the edition. We also would like to thank the Editorial Board of Materials for their assistance in managing this Special Issue

Remote Sensing of the Oceans

This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements

Eddy current defect response analysis using sum of Gaussian methods

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics

Novel Locomotion Methods in Magnetic Actuation and Pipe Inspection

There is much room for improvement in tube network inspections of jet aircraft. Often, these inspections are incomplete and inconsistent. In this paper, we develop a Modular Robotic Inspection System (MoRIS) for jet aircraft tube networks and a corresponding kinematic model. MoRIS consists of a Base Station for user control and communication, and robotic Vertebrae for accessing and inspecting the network. The presented and tested design of MoRIS can travel up to 9 feet in a tube network. The Vertebrae can navigate in all orientations, including smooth vertical tubes. The design is optimized for nominal 1.5 outside diameter tubes. We developed a model of the Locomotion Vertebra in a tube. We defined the model\u27s coordinate system and its generalized coordinates. We studied the configuration space of the robot, which includes all possible orientations of the Locomotion Vertebra. We derived the expression for the elastic potential energy of the Vertebra\u27s suspensions and minimized it to find the natural settling orientation of the robot. We further explore the effect of the tractive wheel\u27s velocity constraint on locomotion dynamics. Finally, we develop a general model for aircraft tube networks and for a taut tether. Stabilizing bipedal walkers is a engineering target throughout the research community. In this paper, we develop an impulsively actuated walking robot. Through the use of magnetic actuation, for the first time, pure impulsive actuation has been achieved in bipedal walkers. In studying this locomotion technique, we built the world\u27s smallest walker: Big Foot. A dynamical model was developed for Big Foot. A Heel Strike and a Constant Pulse Wave Actuation Schemes were selected for testing. The schemes were validated through simulations and experiments. We showed that there exists two regimes for impulsive actuation. There is a regime for impact-like actuation and a regime for longer duration impulsive actuation