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At least 811 records · Page 45

Digital Lunar Exploration Sites (DLES)

It has been almost 50 years since humans last set foot on the Moon. With NASA’s Artemis program, the United States and its international and commercial partners are embarking on a new endeavor to explore the lunar surface. Before we return, we will have simulated every aspect of these future missions. Many of these models and simulations (M&S) will rely on well-known and commonly-used technologies, some of which trace their origins back to the Apollo program. However, M&S has advanced significantly, as have the underlying computational capabilities. As a result, we are able to model many more aspects of the Artemis vehicles and support systems with significantly improved detail and confidence. Accurately and efficiently modeling the lunar environment will be critical to simulating the Artemis elements and mission activities. This includes characterizing and modeling lunar topography, smaller craters, exposed surface rocks, lunar regolith, surface lighting, and ambient thermal environment. These are all necessary for understanding fundamental behaviors and performance of vehicles and support systems in the lunar environment and are often determining factors in the selection of exploration sites and defining mission profiles. The Astromaterials Research and Exploration Sciences (ARES) team in the Exploration Integration and Science Directorate at NASA’s Johnson Space Center (JSC) and the NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch at JSC are developing and maintaining the Digital Lunar Exploration Sites (DLES) data, documentation, and software packages. This data is being fed directly into a diverse collection of graphics and simulation environments, where it is used to construct the closest known truth for numerous potential Lunar South Pole landing sites. DLES is available to projects across NASA and particularly the Artemis program to support coordinated digital representations of the lunar environment. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

Lunar↗

Digital Lunar Exploration Sites (DLES)

After an almost 50-year absence, NASA along with a group of international and commercial partners will return humans to the surface of the Moon as part of the Artemis program. As with the preceding Apollo program, modeling and simulation (M&S) will be an enabling technology for achieving the Artemis mission objectives. Fortunately, M&S has advanced considerably in the past half century, permitting much more detailed and encompassing integrated representations of the Artemis systems. One modeling area of critical importance to simulating the Artemis elements and mission activities is the accurate and efficient modeling of the operational lunar environment. This is particularly challenging since the Artemis program is considering exploration sites in the area of the Lunar South Pole (LSP), far away from any previous surface exploration sites. Fortunately, we now have considerably more and better data from recent lunar sensing missions. A planetary science team and a human exploration simulation team at NASA’s Johnson Space Center are developing a suite of products called the Digital Lunar Exploration Sites (DLES). DLES is intended to provide some of the necessary lunar environmental data products. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

DLES↗

Digital Lunar Exploration Sites (DLES)

After an almost 50-year absence, NASA along with a group of international and commercial partners will return humans to the surface of the Moon as part of the Artemis program. As with the preceding Apollo program, modeling and simulation (M&S) will be an enabling technology for achieving the Artemis mission objectives. Fortunately, M&S has advanced considerably in the past half century, permitting much more detailed and encompassing integrated representations of the Artemis systems. One modeling area of critical importance to simulating the Artemis elements and mission activities is the accurate and efficient modeling of the operational lunar environment. This is particularly challenging since the Artemis program is considering exploration sites in the area of the Lunar South Pole (LSP), far away from any previous surface exploration sites. Fortunately, we now have considerably more and better data from recent lunar sensing missions. A planetary science team and a human exploration simulation team at NASA’s Johnson Space Center are developing a suite of products called the Digital Lunar Exploration Sites (DLES). DLES is intended to provide some of the necessary lunar environmental data products. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

DLES↗

Artificial Intelligence Workshop Report

The 4th NASA Science Mission Directorate (SMD) Artificial Intelligence (AI) Workshop, held during March 25-27, 2024, in Huntsville, AL, highlighted the significant potential of AI and machine learning (ML) in scientific research and processes. The workshop, supported by the NASA Office of Chief Science Data Officer (OCSDO), emphasized the critical role of foundation models (FMs) and large language models (LLMs) in advancing scientific disciplines. The event brought together domain scientists, computer scientists, AI experts, program managers, program scientists, and industry partners to address key challenges and explore opportunities in applying these advanced technologies.

Manil Maskey↗

Bio-Optimized Technologies to Keep Thermoplastics out of Landfills and the Environment (BOTTLE)

Plastics have revolutionized modern life, but reliance on these fossil-based materials that persist for centuries is causing a pollution crisis and contributing to greenhouse gas (GHG) emissions. To develop new technologies to address this problem, the Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment (BOTTLE) Consortium will deliver selective, scalable technologies to enable cost-effective recycling, upcycling, and increased energy efficiency. BOTTLE is an interdisciplinary team of experts that aim to develop selective, scalable processes to deconstruct and upcycle today's plastics and thermosets, redesign tomorrow's plastics to be recyclable-by-design (RBD) and derived from both bio-based and plastic waste-based feedstocks, work with industrial partners across the value chain to catalyze the circular economy for plastics, and leverage AMO and BETO investments in analysis-guided R&D, integrated process development, chemical and biological catalysis, materials characterization, modeling, and data science. BOTTLE is guided by techno-economic analysis (TEA) and supply chain-based life-cycle assessment (LCA). BOTTLE comprises members from ten partner institutions. Primary outcomes to date include establishment of a full consortium, impactful, benchmarking analyses that will be important for the plastics recycling and upcycling community, and multiple impactful, high-impact publications across the breadth of our research portfolio.

bio-optimized↗

Invited Review Article: Pump-probe microscopy

Multiphoton microscopy has rapidly gained popularity in biomedical imaging and materials science because of its ability to provide three-dimensional images at high spatial and temporal resolution even in optically scattering environments. Currently the majority of commercial and home-built devices are based on two-photon fluorescence and harmonic generation contrast. These two contrast mechanisms are relatively easy to measure but can access only a limited range of endogenous targets. Recent developments in fast laser pulse generation, pulse shaping, and detection technology have made accessible a wide range of optical contrasts that utilize multiple pulses of different colors. Molecular excitation with multiple pulses offers a large number of adjustable parameters. For example, in two-pulse pump-probe microscopy, one can vary the wavelength of each excitation pulse, the detection wavelength, the timing between the excitation pulses, and the detection gating window after excitation. Such a large parameter space can provide much greater molecular specificity than existing single-color techniques and allow for structural and functional imaging without the need for exogenous dyes and labels, which might interfere with the system under study. In this review, we provide a tutorial overview, covering principles of pump-probe microscopy and experimental setup, challenges associated with signal detection and data processing, and an overview of applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A recommended entry reconstruction process for the Pioneer Venus multi-probe mission

A method for determining the entry trajectories for the Pioneer Venus multi-probe mission is presented that utilizes earth based Doppler and onboard accelerometry as observables to provide updates for the spacecraft state and atmospheric parameters. The evolution of this method, based on error analyses and actual simulation results, is discussed. A derivative of the Viking radio science orbit determination software is recommended for the reconstruction. Telemetry data pre-processing requirements were defined. A cubic spline derivative routine is recommended to extract accelerations from the accumulated velocity decrements.

Findlay, J. T.↗

Recent progress in atomic-scale controlled plasma processing

Atomic-scale control in plasma processing is becoming increasingly critical for fabricating of advanced semiconductor devices, particularly as the industry shifts toward three-dimensional (3D) architectures and high-aspect-ratio (HAR) structures. This review presents a comprehensive overview of recent developments in atomic-scale controlled plasma processes, organized along two key directions: the hierarchical structure of plasma–surface interactions and the generational evolution of atomic layer processing (ALP) technologies. We examined the gas phase, where molecular design enables selective generation of ions and radicals; the boundary layer, where transport phenomena govern species delivery into nanoscale features, and the surface, where temperature-dependent reactions and cyclic processing determine etching selectivity and precision. Building on this foundation, we outline five generations of ALP—from thermal atomic layer deposition to transport-aware, temporally and structurally decoupled processes—highlighting the increasing sophistication of process control. The review further explores the transition from empirical recipe development to science-based, data-driven methodologies. By integrating quantum-chemical modeling, advanced diagnostics, and machine learning, we demonstrated how predictive models can link plasma species composition to process outcomes, enabling autonomous and adaptive control strategies. Finally, this review discusses the broader societal implications of plasma process innovation through the E4 quartet: energy and resource efficiency, environmental sustainability, evolutionary advancement, and educational promotion. These principles guide the development of sustainable and intelligent atomic-scale manufacturing technologies that are not only technically advanced but also socially responsible.

Ishikawa, Kenji [Nagoya Univ. (Japan)] (ORCID:0000↗

Funding for the 2ND IAEA technical meeting on fusion data processing, validation and analysis

The International Atomic Energy Agency (IAEA) will organize the second Technical Meeting on Fusion Da Processing, Validation and Analysis from 30 May to 02 June, 2017, in Cambridge, MA USA. The meeting w be hosted by the MIT Plasma Science and Fusion Center (PSFC). The objective of the meeting is to provide a platform where a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolation needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge based understanding of the physical processes governing the dynamics of these plasmas. The meeting will aim at fostering, in particular, discussions of research and development results that set out or underline trends observed in the current major fusion confinement devices. General information on the IAEA, including its mission and organization, can be found at the IAEA websit Uncertainty quantification (UQ) Model selection, validation, and verification (V&V) Probability theory and statistical analysis Inverse problems & equilibrium reconstru ction Integrated data analysis Real time data analysis Machine learning Signal/image proc essing & pattern recognition Experimental design and synthetic diagnostics Data management

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ground data system architecture for precipitation determination from space-based radar

The Tropical Rain Mapping Radar (Tramar) is proposed as an attached payload as part of the Space Station Earth Observing System Program. Tramar would measure rainfall rates, rain velocity, and rain cell areal extent in the latitude band from 30 deg S to 30 deg N for use in studies of large-scale atmospheric circulation, variations of latent heating, tropical hydrologic processes, and mesoscale precipitation systems. The Tramar science requirements, radar design, and ground data system architecture are examined, including the three-dimensional scan geometry, the radar system performance parameters, the production of earth-gridded maps, and the telemetry, sensor, radiometric, and geophysical data that would be obtained by Tramar.

Hilland, Jeffrey E.↗

Transforming Science Data for GIS: How to Find and Use NASA Earth Observation Data Without Being a Rocket Scientist

NASAs Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a top-down approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.Our alternative is to take a bottom-up approach using eight environmental fields of interest as defined by the Group on Earth Observations (GEO) called Societal Benefit Areas (SBAs): Disaster Resilience (DR) Public Health Surveillance (PHS) Energy and Mineral Resource Management (EMRM) Water Resources Management (WRM) Infrastructure and Transport Management (ITM) Sustainable Urban Development (SUD) Food Security and Sustainable Agriculture (FSSA) Biodiversity and Ecosystems Sustainability (BES).

DAAC↗

Cassini Titan Science Integration: Getting a 'Jumpstart' on the Process

The Cassini spacecraft has been in orbit for five years, returning a wealth of scientific data from Titan and the Saturn system. The mission is a cooperative undertaking between NASA, ESA and the Italian Space Agency and the project is currently planning for a second extension of the mission. The Cassini Solstice Mission (CSM) will extend the mission's lifetime until Saturn's northern summer solstice in 2017. The Titan Orbiter Science Team (TOST) has the task of integrating the science observations for all 126 targeted Titan flybys (44 in the Prime Mission, 26 in the first extension (Equinox Mission), and 56 in the second extension (Solstice Mission)) contained in the chosen trajectory. Cassini science instruments are body-fixed with limited ability to articulate; thus, the spacecraft pointing during the flybys must be allocated among the instruments to accomplish the mission's science goals. The science that can be accomplished on each Titan flyby also critically depends on the closest approach altitude, which is in turn determined by the attitude, but changing the altitude impacts the overall trajectory for the Solstice Mission. During the Prime and Extended missions, TOST has learned that the best way to achieve Cassini's Titan science goals is via a 'jumpstart' process prior to final delivery of the trajectory. The jumpstart is driven by the desire to balance Titan science across the entire set of flybys during the CSM, and to influence any changes (tweaks) to the flyby altitudes. By the end of the jumpstart, TOST produces Master Timelines for each flyby, identifying each flyby's prime science observations and allocating control of the spacecraft attitude to specific instrument teams. In addition, developing timelines early, while the science and operations teams are still fully funded, decreases the future workload in integration and implementation.

Steadman, Kimberly B.↗

SpaceCube 2.0: An Advanced Hybrid Onboard Data Processor

The SpaceCube 2.0 is a compact, high performance, low-power onboard processing system that takes advantage of cutting-edge hybrid (CPU/FPGA/DSP) processing elements. The SpaceCube 2.0 design concept includes two commercial Virtex-5 field-programmable gate array (FPGA) parts protected by gradiation hardened by software" technology, and possesses exceptional size, weight, and power characteristics [5x5x7 in., 3.5 lb (approximately equal to 12.7 x 12.7 x 17.8 cm, 1.6 kg) 5-25 W, depending on the application fs required clock rate]. The two Virtex-5 FPGA parts are implemented in a unique back-toback configuration to maximize data transfer and computing performance. Draft computing power specifications for the SpaceCube 2.0 unit include four PowerPC 440s (1100 DMIPS each), 500+ DSP48Es (2x580 GMACS), 100+ LVDS high-speed serial I/Os (1.25 Gbps each), and 2x190 GFLOPS single-precision (65 GFLOPS double-precision) floating point performance. The SpaceCube 2.0 includes PROM memory for CPU boot, health and safety, and basic command and telemetry functionality; RAM memory for program execution; and FLASH/EEPROM memory to store algorithms and application code for the CPU, FPGA, and DSP processing elements. Program execution can be reconfigured in real time and algorithms can be updated, modified, and/or replaced at any point during the mission. Gigabit Ethernet, Spacewire, SATA and highspeed LVDS serial/parallel I/O channels are available for instrument/sensor data ingest, and mission-unique instrument interfaces can be accommodated using a compact PCI (cPCI) expansion card interface. The SpaceCube 2.0 can be utilized in NASA Earth Science, Helio/Astrophysics and Exploration missions, and Department of Defense satellites for onboard data processing. It can also be used in commercial communication and mapping satellites.

Lin, Michael↗

CloudSat Reflectivity Data Visualization Inside Hurricanes

We have presented methods to rapidly produce visualization and outreach products from CloudSat data for science and the media These methods combine data from several sources in the product generation process In general, the process can be completely automatic, producing products and notifying potential users

remote science↗

Integration of multi-discipline data processing for earth observing systems

The first steps taken to ensure the controlled evolution of existing facilities toward greater interoperability and sharing of resources among NASA-supported earth science and applications data systems (ESADS) are described. Recommendations made by the various panels during the 1987 ESADS Workshop are presented. The panels were concerned with directories and catalogs, data archives, data manipulation software, computational facilities, data storage media, database management, and networking. Consideration was also given to the tracking and tuning of overall development and management coordination issues.

Kahn, Ralph↗

Cassini science planning process

The mission design for Cassini-Huygens calls for a four-year orbital survey of the Saturnian system and the descent into the Titan atmosphere and eventual soft-landing of the Huygens probe. The Cassini orbiter tour consists of 76 orbits around Saturn with 44 close Titan flybys and 8 targeted icy satellite flybys. The Cassini orbiter spacecraft carries twelve scientific instruments that will perform a wide range of observations on a multitude of designated targets. The science opportunities, frequency of encounters, the length of the Tour, and the use of distributed operations pose significant challenges for developing the science plan for the orbiter mission. The Cassini Science Planning Process is the process used to develop and integrate the science and engineering plan that incorporates an acceptable level of science required to meet the primary mission objectives far the orbiter. The bulk of the integrated science and engineering plan will be developed prior to Saturn Orbit Insertion (Sol). The Science Planning Process consists of three elements: 1) the creation of the Tour Atlas, which identifies the science opportunities in the tour, 2) the development of the Science Operations Plan (SOP), which is the conflict-free timeline of all science observations and engineering activities, a constraint-checked spacecraft pointing profile, and data volume allocations to the science instruments, and 3) an Aftermarket and SOP Update process, which is used to update the SOP while in tour with the latest information on spacecraft performance, science opportunities, and ephemerides. This paper will discuss the various elements of the Science Planning Process used on the Cassini Mission to integrate, implement, and adapt the science and engineering activity plans for Tour.

Cassini↗

Small Explorer (SMEX) POsitron Electron Magnet Spectrometer (POEMS)

This report covers the activities of Louisiana State University (LSU) under subcontract 26053-EX between LSU and the Bartol Research Institute (Bartol), which began January 1, 1994. The purpose of this subcontract was for LSU to participate in and support Bartol in the work to define the SMEX (Small Explorer)/POEMS (Positron Electron Magnet Spectrometer) spaceflight mission under NASA Contract NAS5-38098 between NASA and Bartol. The conclusions of this study were that for a 1998 launch into a 600km altitude, 98 degrees, approximately sun synchronous orbit, (a) the total radiation dose would be typically a few k-rad per year, certainly less than 20 k-rad per year for the anticipated shielding and potential solar flare environment, (b) detector counting rates would be dominated by the South Atlantic Anomaly (SAA) and the horns of the Van Allen belts, (c) the galactic electron and positron 'signal' can be extracted from the albedo background and the trapped populations by detailed evaluation of the geomagnetic transmission function (cut-off) for each event, (d) POEMS could make significant contributions to magnetospheric science if sufficient downlink capacity were provided and, (e) a fully functioning, cost efficient, data processing and analysis facility design was developed for the mission. Overall, POEMS was found to be a relatively simple experiment to manifest, operate and analyze and had potential for fundamental new discoveries in cosmic, heliospheric, solar and magnetospheric science.

LHeureux, Jacques↗

Real-time data processing for serial crystallography experiments

We report the use of streaming data interfaces to perform fully online data processing for serial crystallography experiments, without storing intermediate data on disk. The system produces Bragg reflection intensity measurements suitable for scaling and merging, with a latency of less than 1 s per frame. Our system uses the CrystFEL software in combination with the ASAP::O data framework. In a series of user experiments at PETRA III, frames from a 16 megapixel Dectris EIGER2 X detector were searched for peaks, indexed and integrated at the maximum full-frame readout speed of 133 frames per second. The computational resources required depend on various factors, most significantly the fraction of non-blank frames ('hits'). The average single-thread processing time per frame was 242 ms for blank frames and 455 ms for hits, meaning that a single 96-core computing node was sufficient to keep up with the data, with ample headroom for unexpected throughput reductions. Further significant improvements are expected, for example by binning pixel intensities together to reduce the pixel count. We discuss the implications of real-time data processing on the `data deluge' problem from recent and future photon-science experiments, in particular on calibration requirements, computing access patterns and the need for the preservation of raw data.

47 OTHER INSTRUMENTATION↗