Severe Storms Branch research report (April 1984 April 1985)

The Mesoscale Atmospheric Processes Research Program is a program of integrated studies which are to achieve an improved understanding of the basic behavior of the atmosphere through the use of remotely sensed data and space technology. The program consist of four elements: (1) special observations and analysis of mesoscale systems; (20 the development of quanitative algorithms to use remotely sensed observations; (3) the development of new observing systems; and (4) numerical modeling. The Severe Storms Branch objectives are the improvement of the understanding, diagnosis, and prediction of a wide range of atmospheric storms, which includes severe thunderstorms, tornadoes, flash floods, tropical cyclones, and winter snowstorms. The research often shed light upon various aspects of local weather, such as fog, sea breezes, air pollution, showers, and other products of nonsevere cumulus cloud clusters. The part of the program devoted to boundary layer processes, gust front interactions, and soil moisture detection from satellites gives insights into storm growth and behavior

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

The state-of-the-art progress in cloud detection, identification, and tracking approaches: a systematic review

A cloud is a mass of water vapor floating in the atmosphere. It is visible from the ground and can remain at a variable height for some time. Clouds are very important because their interaction with the rest of the atmosphere has a decisive influence on weather, for instance by sunlight occlusion or by bringing rain. Weather denotes atmosphere behavior and is determinant in several human activities, such as agriculture or energy capture. Therefore, cloud detection is an important process about which several methods have been investigated and published in the literature. The aim of this paper is to review some of such proposals and the papers that have been analyzed and discussed can be, in general, classified into three types. The first one is devoted to the analysis and explanation of clouds and their types, and about existing imaging systems. Regarding cloud detection, dealt with in a second part, diverse methods have been analyzed, i.e., those based on the analysis of satellite images and those based on the analysis of images from cameras located on Earth. The last part is devoted to cloud forecast and tracking. Cloud detection from both systems rely on thresholding techniques and a few machine-learning algorithms. To compute the cloud motion vectors for cloud tracking, correlation-based methods are commonly used. A few machine-learning methods are also available in the literature for cloud tracking, and have been discussed in this paper too

VALIDATION OF COMPUTATIONAL FLUID DYNAMIC SIMULATIONS OF MEMBRANE ARTIFICIAL LUNGS WITH X-RAY IMAGING

The functional performance of membrane oxygenators is directly related to the perfusion dynamics of blood flow through the fiber bundle. Non-uniform flow and design characteristics can limit gas exchange efficiency and influence susceptibility of thrombus development in the fiber membrane. Computational fluid dynamics (CFD) is a powerful tool for predicting properties of the flow field based on prescribed geometrical domains and boundary conditions. Validation of numerical results in membrane oxygenators has been predominantly based on experimental pressure measurements with little emphasis placed on confirmation of the velocity fields due to opacity of the fiber membrane and limitations of optical velocimetric methods. A novel approach was developed using biplane X-ray digital subtraction angiography to visualize flow through a commercial membrane artificial lung at 1–4.5 L/min. Permeability based on the coefficients of the Ergun equation, α and β, were experimentally determined to be 180 and 2.4, respectively, and the equivalent spherical diameter was shown to be approximately equal to the outer fiber diameter. For all flow rates tested, biplane image projections revealed non-uniform radial perfusion through the annular fiber bundle, yet without flow bias due to the axisymmetric position of the outlet. At 1 L/min, approximately 78.2% of the outward velocity component was in the radial (horizontal) plane verses 92.0% at 4.5 L/min. The CFD studies were unable to predict the non-radial component of the outward perfusion. Two-dimensional velocity fields were generated from the radiographs using a cross-correlation tracking algorithm and compared with analogous image planes from the CFD simulations. Velocities in the non-porous regions differed by an average of 11% versus the experimental values, but simulated velocities in the fiber bundle were on average 44% lower than experimental. A corrective factor reduced the average error differences in the porous medium to 6%. Finally, biplane image pairs were reconstructed to show 3-D transient perfusion through the device. The methods developed from this research provide tools for more accurate assessments of fluid flow through membrane oxygenators. By identifying non-invasive techniques to allow direct analysis of numerical and experimental velocity fields, researchers can better evaluate device performance of new prototype designs

VGC 2023 - Unveiling the dynamic Earth with digital methods: 5th Virtual Geoscience Conference: Book of Abstracts

Conference proceedings of the 5th Virtual Geoscience Conference, 21-22 September 2023, held in Dresden. The VGC is a multidisciplinary forum for researchers in geoscience, geomatics and related disciplines to share their latest developments and applications.:Short Courses 9 Workshops Stream 1 10 Workshop Stream 2 11 Workshop Stream 3 12 Session 1 – Point Cloud Processing: Workflows, Geometry & Semantics 14 Session 2 – Visualisation, communication & Teaching 27 Session 3 – Applying Machine Learning in Geosciences 36 Session 4 – Digital Outcrop Characterisation & Analysis 49 Session 5 – Airborne & Remote Mapping 58 Session 6 – Recent Developments in Geomorphic Process and Hazard Monitoring 69 Session 7 – Applications in Hydrology & Ecology 82 Poster Contributions 9

3D visualization of in-flight recorded data.

Human being can easily acquire information by showing the object than reading the description of it. Our brain stores images that the eyes are seeing and by the brain mapping, people can analyze information by imagination in the brain. This is the reason why visualization is important and powerful. It helps people remember the scene later. Visualization transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations (Flurchick, 2001). As a consequence, many computer scientists and programmers take their time to build better visualization of the data for users. For the flight data from an aircraft, it is better to understand data in 3D computer graphics rather than to look at mere numbers. The flight data consists of several fields such as elapsed time, latitude, longitude, altitude, ground speed, roll angle, pitch angle, heading, wind speed, and so on. With these data variables, filtering is the first process for visualization in order to gather important information. The collection of processed data is transformed to 3D graphics form to be rendered by generating Keyhole Mark-up Language (KML) files in the system. KML is an XML grammar and file format for modeling and storing geographic features such as points, lines, images, polygons, and models for display in Google Earth or Google Maps. Like HTML, KML has a tag-based structure with names and attributes used for specific display purposes. In the present work, new approaches to visualize flight using Google Earth are developed. Because of the limitation of the Google Earth API, the Great Circle Distance calculation and trigonometric functions are implemented to handle the position, angles of roll and pitch, and a range of the camera positions to generate several points of view. Currently, visual representation of flight data depends on 2D graphics although an aircraft flies in a 3D space. The graphical interface allows flight analysts to create ground traces in 2D, and flight ribbons and flight paths with altitude in 3D. Additionally, by incorporating weather information, fog and clouds can also be generated as part of the animation effects. With 3D stereoscopic technique, a realistic visual representation of the flights is realized

Earth resources: A continuing bibliography with indexes (issue 59)

This bibliography lists 518 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

Deep learning for internet of underwater things and ocean data analytics

The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes

NASA/MSFC FY-82 atmospheric processes research review

The NASA/MSFC FY-82 Atmospheric Processes Research Program was reviewed. The review covered research tasks in the areas of upper atmosphere, global weather, and severe storms and local weather. Also included was research on aviation safety environmental hazards. The research project summaries, in narrative outline form, supplied by the individual investigators together with the agenda and other information about the review are presented