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21 records · Page 2

South Pole Lunar Lighting Studies for Driving Exploration on the Lunar Surface

NASA’s Artemis lunar missions will face new exploration challenges due to inherently low sun angles in the lunar south pole region. Whereas the Apollo missions were afforded sunlight for approximately 8 to 50-degrees above the horizon, sunlight for the next lunar missions will only be 1 to 2-degrees about the horizon. With this low angle, long shadows and high contrasts of light and dark areas will be faced by the crew and remote teleop operators while exploring the lunar surface. With this in mind, NASA developed an integrated virtual Lighting and Navigation Simulation to understand these challenges. Two studies have been conducted in this Lunar South Pole environment to evaluate the effects of natural and artificial lighting on driving and navigating a lunar rover across the surface. Early NASA studies, such as this, are used to aid in developing techniques and explore concepts of operations to promote mission success and crew safety. In the Phase One development evaluation, six astronauts were teleported to ten different lighting conditions. For each location, drivers were to drive to an imaginary target approximately 200-meters straight ahead and provide subjective feedback on their ability to drive under the given lighting conditions. Phase Two, a more operational study, four astronauts and a remote operator tested five different Artemis lunar mission scenarios. Results indicated sun direction at such low angles, especially when driving a high speed, can severely impact the crew’s ability to safely drive the rover. In the up-sun situation, with the sun directly in the driver’s eyes and compounded long shadows, the consistent preference among drivers was to initiate a tacking strategy of approximately +/- 20 to 30-degrees to improve visibility. This maneuver does require more time and rover energetics. Conversely, driving down-sun required the crew to tack as well to avoid the shadow of rover blocking the terrain. Less appreciated is how the surrounding landscape is lit. Traveling into shadowed areas, especially while facing a lit terrain beyond the shadowed area, drivers enter at their own risk due to pupil contraction making artificial lights useless. Additionally, the constant transitioning between dark and light areas are mentally taxing to the crew and natural navigational references such as the stars are invisible and therefore unusable. Slope and depth magnitude are very difficult hazards to judge when approaching a shadowed crater. This naturally leads to slower driving speeds than originally anticipated. As for observing scientifically interesting features, assessing them accurately varies greatly by the lighting condition. In most cases, the task can be completed, but the strategy is to use the sun to one’s advantage. Crew workload distribution in the cockpit for driving operations was split amongst crew. The driver primarily focused attention on visual terrain (80%) but referenced displays approximately 20% of the time, while the co-pilot/navigator generally provided directional cues to the driver. These natural lighting conditions present significant challenges for safe rover operations; however, early studies having given investigators a “first-look” into understanding of how operating on the South Lunar Pole can be accomplished.

LTv↗

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗

The NAS Computational Aerosciences Archive

In order to further the state-of-the-art in computational aerosciences (CAS) technology, researchers must be able to gather and understand existing work in the field. One aspect of this information gathering is studying published work available in scientific journals and conference proceedings. However, current scientific publications are very limited in the type and amount of information that they can disseminate. Information is typically restricted to text, a few images, and a bibliography list. Additional information that might be useful to the researcher, such as additional visual results, referenced papers, and datasets, are not available. New forms of electronic publication, such as the World Wide Web (WWW), limit publication size only by available disk space and data transmission bandwidth, both of which are improving rapidly. The Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center is in the process of creating an archive of CAS information on the WWW. This archive will be based on the large amount of information produced by researchers associated with the NAS facility. The archive will contain technical summaries and reports of research performed on NAS supercomputers, visual results (images, animations, visualization system scripts), datasets, and any other supporting meta-information. This information will be available via the WWW through the NAS homepage, located at http://www.nas.nasa.gov/, fully indexed for searching. The main components of the archive are technical summaries and reports, visual results, and datasets. Technical summaries are gathered every year by researchers who have been allotted resources on NAS supercomputers. These summaries, together with supporting visual results and references, are browsable by interested researchers. Referenced papers made available by researchers can be accessed through hypertext links. Technical reports are in-depth accounts of tools and applications research projects performed by NAS staff members and collaborators. Visual results, which may be available in the form of images, animations, and/or visualization scripts, are generated by researchers with respect to a certain research project, depicting dataset features that were determined important by the investigating researcher. For example, script files for visualization systems (e.g. FAST, PLOT3D, AVS) are provided to create visualizations on the user's local workstation to elucidate the key points of the numerical study. Users can then interact with the data starting where the investigator left off. Datasets are intended to give researchers an opportunity to understand previous work, 'mine' solutions for new information (for example, have you ever read a paper thinking "I wonder what the helicity density looks like?"), compare new techniques with older results, collaborate with remote colleagues, and perform validation. Supporting meta-information associated with the research projects is also important to provide additional context for research projects. This may include information such as the software used in the simulation (e.g. grid generators, flow solvers, visualization). In addition to serving the CAS research community, the information archive will also be helpful to students, visualization system developers and researchers, and management. Students (of any age) can use the data to study fluid dynamics, compare results from different flow solvers, learn about meshing techniques, etc., leading to better informed individuals. For these users it is particularly important that visualization be integrated into dataset archives. Visualization researchers can use dataset archives to test algorithms and techniques, leading to better visualization systems, Management can use the data to figure what is really going on behind the viewgraphs. All users will benefit from fast, easy, and convenient access to CFD datasets. The CAS information archive hopes to serve as a useful resource to those interested in computational sciences. At present, only information that may be distributed internationally is made available via the archive. Studies are underway to determine security requirements and solutions to make additional information available. By providing access to the archive via the WWW, the process of information gathering can be more productive and fruitful due to ease of access and ability to manage many different types of information. As the archive grows, additional resources from outside NAS will be added, providing a dynamic source of research results.

Miceli, Kristina D.↗