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The Development of a Plan for the Assessment, Improvement and Deployment of a Radar Acoustic Sounding System (RASS) for Wake Vortex Detection

This report describes the activities completed under a grant from the NASA Langley Research Center to develop a plan for the assessment, improvement, and deployment of a Radar Acoustic Sounding System (RASS) for the detection of wake vortices. A brief review is provided of existing alternative instruments for wake vortex detection. This is followed by a review of previous implementations and assessment of a RASS. As a result of this review, it is concluded that the basic features of a RASS have several advantages over other commonly used wake vortex detection and measurement systems. Most important of these features are the good fidelity of the measurements and the potential for all weather operation. To realize the full potential of this remote sensing instrument, a plan for the development of a RASS designed specifically for wake vortex detection and measurement has been prepared. To keep costs to a minimum, this program would start with the development an inexpensive laboratory-scale version of a RASS system. The new instrument would be developed in several stages, each allowing for a critical assessment of the instrument s potential and limitations. The instrument, in its initial stages of development, would be tested in a controlled laboratory environment. A jet vortex simulator, a prototype version of which has already been fabricated, would be interrogated by the RASS system. The details of the laboratory vortex would be measured using a Particle Image Velocimetry (PIV) system. In the early development stages, the scattered radar signal would be digitized and the signal post-processed to determine how extensively and accurately the RASS could measure properties of the wake vortex. If the initial tests prove to be successful, a real-time, digital signal processing system would be developed as a component of the RASS system. At each stage of the instrument development and testing, the implications of the scaling required for a full-scale instrument would be considered. It is concluded that a RASS system, developed for the specific application of wake vortex detection, could become part of a robust Aircraft Vortex Spacing System (AVOSS). This system, in turn, could contribute to Reduced Spacing Operations (RSO) in US airports and improvements in Terminal Area productivity (TAP).

Morris, Philip J.↗

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗

Electrostatics of Granular Material (EGM): Space Station Experiment

Aggregates were observed to form very suddenly in a lab-contained dust cloud, transforming (within seconds) an opaque monodispersed cloud into a clear volume containing rapidly-settling, long hair-like aggregates. The implications of such a "phase change" led to a series of experiments progressing from the lab, to KC-135, followed by micro-g flights on USML-1 and USML-2, and now EGM slated for Space Station. We attribute the sudden "collapse" of a cloud to the effect of dipoles. This has significant ramifications for all types of cloud systems, and additionally implicates dipoles in the processes of cohesion and adhesion of granular matter. Notably, there is the inference that like-charged grains need not necessarily repel if they are close enough together: attraction or repulsion depends on intergranular distance (the dipole being more powerful at short range), and the D/M ratio for each grain, where D is the dipole moment and M is the net charge. We discovered that these ideas about dipoles, the likely pervasiveness of them in granular material, the significance of the D/M ratio, and the idea of mixed charges on individual grains resulting from tribological processes --are not universally recognized in electrostatics, granular material studies, and aerosol science, despite some early seminal work in the literature, and despite commercial applications of dipoles in such modern uses as "Krazy Glue", housecleaning dust cloths, and photocopying. The overarching goal of EGM is to empirically prove that (triboelectrically) charged dielectric grains of material have dipole moments that provide an "always attractive" intergranular force as a result of both positive and negative charges residing on the surfaces of individual grains. Microgravity is required for this experiment because sand grains can be suspended as a cloud for protracted periods, the grains are free to rotate to express their electrostatic character, and Coulombic forces are unmasked. Suspended grains will be "interrogated" by applied electrical fields. In one module, grains will be immersed in an inhomogeneous electric field and allowed to be attracted towards or repelled from the central electrode of the module: part of the grain's speed will be a function of its net charge (monopole), part will be a function of the dipole. Observed grain position vs. time will provide a curve that can be deconvolved into the dipole and monopole forces responsible, since both have distinctive radial dependencies. In a second approach, the inhomogeneous field will be alternated at low frequency (e.g., every 5-10 seconds) so that the grains are alternately attracted and repelled from the center of the field. The resulting "zigzag" grain motion will gradually drift inwards, then suddenly change to a unidirectional inward path when a critical radial distance is encountered (a sort of "Coulombic event horizon") at which the dipole strength supersedes the monopole strength --thus proving the presence of a dipole, while also quantifying the D/M ratio. In a second module, an homogeneous electric field eliminates dipole effects (both Coulombic and induced) to provide calibration of the monopole and to more readily evaluate net charge statistical variance. In both modules, the e-fields will be exponentially step-ramped in voltage during the experiment, so that the field "nominalizes" grain speed while spreading the response time --effectively forcing each grain to "wait its turn" to be measured. In addition to rigorously quantifying M, D, and the D/M ratio for many hundreds of grains, the experiment will also observe gross electrometric and RF discharge phenomena associated with grain activity. The parameter space will encompass grain charging levels (via intentional triboelectrification), grain size, cloud density, and material type. Results will prove or disprove the dipole hypothesis. In either case, light will be shed on the role of electrostatic forces in governing granular systems. Knowledge so gained can be applied to natural clouds such as protostellar and protoplanetary dust and debris systems, planetary rings, planetary dust palls and aerosols created by volcanic, impact, aeolian, firestorm, or nuclear winter processes. The data are also directly applicable to adhesion, cohesion, transport, dispersion, and collection of granular materials in industrial, agricultural, pharmaceutical applications, and in fields as diverse as dust contamination of space suits on Mars and crop spraying on Earth.

Marshall, J.↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗