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Using Dynamic Interface Modeling and Simulation to Develop a Launch and Recovery Flight Simulation for a UH-60A Blackhawk

Joint Shipboard Helicopter Integration Process (JSHIP) is a Joint Test and Evaluation (JT&E) program sponsored by the Office of the Secretary of Defense (OSD). Under the JSHDP program is a simulation effort referred to as the Dynamic Interface Modeling and Simulation System (DIMSS). The purpose of DIMSS is to develop and test the processes and mechanisms that facilitate ship-helicopter interface testing via man-in-the-loop ground-based flight simulators. Specifically, the DIMSS charter is to develop an accredited process for using a flight simulator to determine the wind-over-the-deck (WOD) launch and recovery flight envelope for the UH-60A ship/helicopter combination. DIMSS is a collaborative effort between the NASA Ames Research Center and OSD. OSD determines the T&E and warfighter training requirements, provides the programmatics and dynamic interface T&E experience, and conducts ship/aircraft interface tests for validating the simulation. NASA provides the research and development element, simulation facility, and simulation technical experience. This paper will highlight the benefits of the NASA/JSHIP collaboration and detail achievements of the project in terms of modeling and simulation. The Vertical Motion Simulator (VMS) at NASA Ames Research Center offers the capability to simulate a wide range of simulation cueing configurations, which include visual, aural, and body-force cueing devices. The system flexibility enables switching configurations io allow back-to-back evaluation and comparison of different levels of cueing fidelity in determining minimum training requirements. The investigation required development and integration of several major simulation system at the VMS. A new UH-60A BlackHawk interchangeable cab that provides an out-the-window (OTW) field-of-view (FOV) of 220 degrees in azimuth and 70 degrees in elevation was built. Modeling efforts involved integrating Computational Fluid Dynamics (CFD) generated data of an LHA ship airwake and integrating a real-time ship motion model developed based on a batch model from Naval Surface Warfare Center. Engineering development and integration of a three degrees-of-freedom (DOF) dynamic seat to simulate high frequency rotor-dynamics dependent motion cues for use in conjunction with the large motion system was accomplished. The development of an LHA visual model in several different levels of resolution and an aural cueing system in which three separate fidelity levels could be selected were developed. VMS also integrated a PC-based E&S simFUSION system to investigate cost effective IG alternatives. The DIMSS project consists of three phases that follow an approved Validation, Verification and accreditation (VV&A) process. The first phase will support the accreditation of the individual subsystems and models. The second will follow the verification and validation of the integrated subsystems and models, and will address fidelity requirements of the integrated models and subsystems. The third and final phase will allow the verification and validation of the full system integration. This VV&A process will address the utility of the simulated WOD launch and recovery envelope. Simulations supporting the first two stages have been completed and the data is currently being reviewed and analyzed.

Sweeney, Christopher↗

Internet Protocol Display Sharing Solution for Mission Control Center Video System

With the advent of broadcast television as a constant source of information throughout the NASA manned space flight Mission Control Center (MCC) at the Johnson Space Center (JSC), the current Video Transport System (VTS) characteristics provides the ability to visually enhance real-time applications as a broadcast channel that decision making flight controllers come to rely on, but can be difficult to maintain and costly. The Operations Technology Facility (OTF) of the Mission Operations Facility Division (MOFD) has been tasked to provide insight to new innovative technological solutions for the MCC environment focusing on alternative architectures for a VTS. New technology will be provided to enable sharing of all imagery from one specific computer display, better known as Display Sharing (DS), to other computer displays and display systems such as; large projector systems, flight control rooms, and back supporting rooms throughout the facilities and other offsite centers using IP networks. It has been stated that Internet Protocol (IP) applications are easily readied to substitute for the current visual architecture, but quality and speed may need to be forfeited for reducing cost and maintainability. Although the IP infrastructure can support many technologies, the simple task of sharing ones computer display can be rather clumsy and difficult to configure and manage to the many operators and products. The DS process shall invest in collectively automating the sharing of images while focusing on such characteristics as; managing bandwidth, encrypting security measures, synchronizing disconnections from loss of signal / loss of acquisitions, performance latency, and provide functions like, scalability, multi-sharing, ease of initial integration / sustained configuration, integration with video adjustments packages, collaborative tools, host / recipient controllability, and the utmost paramount priority, an enterprise solution that provides ownership to the whole process, while maintaining the integrity of the latest technological displayed image devices. This study will provide insights to the many possibilities that can be filtered down to a harmoniously responsive product that can be used in today's MCC environment.

Brown, Michael A.↗

NASA GPU Hackathon Yields Significant Code Improvements

The NASA GPU Hackathon 2020 brought together application developers and computer experts to help get important NASA applications running effectively on graphics processing unit (GPU) nodes. Nine teams of application developers participated in this virtual event, a major impetus for teams to modernize codes of interest for NASA missions to CPU nodes containing GPU accelerators, with a focus on hands-on problem solving. The photo in Figure1 shows 30 of the more than50 participants. The HECC project and NVIDIA jointly organized the event, and HECC provided five Pleiades nodes each with 4 V100 GPUs for teams to use. The virtual event, which took place over four days from September 28–October 7, 2020, used Microsoft Teams and Slack as collaboration tools. Each team consisted of three to six members from NASA Centers and supporting organizations. The teams were paired with one to two mentors from industry, government, and academia. The experience levels of the teams ranged from being GPU novices to advanced CUDA programming experts. OpenACC and the emerging Kokkos API were used in addition to CUDA for GPU programming. During the event, which focused on accelerating AeroSciences and CFD applications, most teams achieved considerable performance improvements on both GPUs and CPUs. For example, a team with no GPU experience completed a first port of a time-critical loop to a GPU. Another team of expert CUDA programmers were able to restructure their algorithm, yielding a factor of five speed-up. And another team sped up some of their CUDA kernels by a factor of 20, which directly translated into their production code. This article highlights some of the many successes resulting from the event.

HECC↗

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗

Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid

As an increasing number of devices in the power-grid rely on high-precision clocks to measure electrical properties and time stamp data, GPS receivers have become a vulnerability on the power-grid. GPS spoofing attacks, in which a fake signal is transmitted, can cause sensor measurement errors that can misinform protective equipment and grid operators for both the transmission and distribution grid. The technology being developed to secure precision clocks in the transmission grid are not appropriate for the distribution grid. Thus, there is a need to developed anomaly detection algorithms that are suitable for the hardware available on the distribution grid. Traditionally, a distributed detection framework is comprised of spatially distributed nodes which acquire observations about a quantity of interest and sends the data to the fusion center, where a global decision is made. Instead the distribution grid has low-power devices, such as smart inverters and microPMUs, that could be used to perform highly parallelized calculations. Having on node calculations is beneficial since it is more network and computation efficient, as the more calculations can be performed where the data is being captured instead of communicating across a slow network to a centralized fusion center. Instead, we could employ an alternate peer-to-peer type of information exchange on the distribution grid that can still reach a global decision. A decentralized approach to anomaly detection makes efficient use of the computational and network bandwidth that exists, and it also lacks the single point of failure of a centralized approach. Thus, a decentralized local information exchange and/or inference is preferred. Lastly, the unreliability of the distribution grid network connections and potential noise or error in the measurements must be considered. In order to produce an effective detection tool, a Byzantine-fault tolerant and asynchronous algorithm must be developed. Thus, the first phase of our project is to develop a distributed, decentralized, asynchronous, Byzantine-fault tolerant, collaborative autonomy-based anomaly detection algorithm to collectively analyze clusters of data for signs of a malicious attack.

97 MATHEMATICS AND COMPUTING↗

Improvements of Nuclear Data Evaluations for Lead Isotopes in Support of Next Generation Lead-Cooled Fast Systems

The neutron evaluation of the isotopes that comprise natural lead were undertaken as a part of DOE-NEUP Project #19-16739. The goal of the project was to update the neutron cross sections to account for new differential measurements and incorporate the most up-to-date physics. Shortcomings in the lead cross sections was made known by several independent reports. The work performed here repeated the simulation of all the “benchmark” validation systems and concluded that the major issue is the scattering cross sections in the major lead isotopes above 100 keV. Re-evaluation of 206,207,208 Pb included both the resolved resonance region and fast region evaluations of the cross sections. Combined these regions cover energies from thermal to 20 MeV. The most drastic improvement is the resolved resonance region evaluation of 208 Pb which is now extended from 1.0 to 1.5 MeV. Parameterization of these resonances in the R-matrix provides a superior reconstruction of not only the experimental cross section but also the scattering distributions via the Blatt-Biedenharn formalism. Fast region evaluations of the three major isotopes were done to include new inelastic experimental data from the neutron Time-of-Flight facility at CERN. The culmination of all the changes to the cross section is a drastic improvement in the scattering kernel as shown in Rensselaer Polytechnic Institute (RPI) Quasi-Differential scattering measurements and improved prediction of keff for fast integral experiments. Alongside the new cross sections, new nuclear data covariance (uncertainties) have been computed and are included in the evaluation. Little is changed in the magnitude of the uncertainties but the correlations within the covariance display non-trivial changes. The new evaluations of 206,207,208 Pb have been submitted to the National Nuclear Data Center to be included in the ENDF/B-VIII.1 library. While the cross sections have been updated extensively, knowledge and modeling of the cross sections between 1.0 and 3.0 MeV for the isotopes remain a challenge. Most notably is the double differential elastic cross section for 208 Pb and 206 Pb. New quasi-differential measurements for pure samples of these two nuclei would go a long way in reducing compensating errors in the evaluations. Qualitatively, the project has produced a prosperous collaboration between the nuclear data group at RPI with staff scientists at Brookhaven National Laboratory, Naval Nuclear Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories. Quantitatively this is reflected in seven conference presentations, at least one journal submission, and one doctoral thesis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Biomedical Research for Human Spaceflight

This invited presentation will offer an overview of the biomedical research – both from a biomedical sciences and engineering perspective – of human physiology and performance during spaceflight. Focused on the unique expertise within the Biomedical Sciences Branch, NASA Johnson Space Center, the talk will elucidate the critical role of biomedical laboratories in synergistic activities in clinical sciences, space physiology, applied research, technology development, and operational support for human space exploration. Together, the efforts within this branch play a crucial role in supporting astronauts' health, performance, and safety. The branch Scientists, Researchers, and Engineers conduct biomedical research in flight on board the International Space Station and on-earth space environment analogs. This dual approach allows for a nuanced understanding of the effects of micro- and planetary gravitation fields on human physiology and the assessment of potential clinical and biomedical interventions (countermeasures) to mitigate astronaut clinical and performance decrements. The talk aims to underscore the synergistic collaborative efforts of biomedical engineers, physiologists, clinicians, and computational researchers, emphasizing these experts' pivotal role in advancing human spaceflight's frontiers.

Biomedical Research↗

A Dose Assessment Model for Radioactive Waste Exposed by Gully Erosion at West Valley - 20513

The Western New York Nuclear Service Center (WNYNSC), located approximately 48 km south of Buffalo, New York, is the site of a former nuclear fuel reprocessing and radioactive waste disposal facility. Spent nuclear fuel was processed there from 1966 to 1972, leaving behind radioactive and chemical wastes in two disposal areas and a waste tank farm. Site operations also resulted in releases of radioactivity to site soils, groundwater, and to surface waters draining the site. The New York State Energy Research and Development Authority (NYSERDA) and the U.S. Department of Energy (DOE) are collaborating in a process of decision making for decommissioning those facilities remaining at the WNYNSC following the completion of Phase 1 decommissioning. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) computer model to assist the agencies in this process. The PPA Model includes a contaminant transport component focusing on the movement of contaminants within and among environmental media including groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The model also includes evaluation of potential exposure and health effects for a Resident Farmer exposure scenario, where the Resident Farmer represents a critical group, described as that group of individuals reasonably expected to receive the greatest exposure to residual radioactivity for any applicable set of circumstances. The West Valley Site is located in the glaciated Allegheny Plateau region of western New York State. The waste reprocessing and disposal areas were constructed on a relatively fat area of plateau dissected by drainages of Buttermilk Creek, including Erdman Brook, Franks Creek, and Quarry Creek. An important aspect of the contaminant transport component of the PPA model is consideration of erosive processes such as slumping of the stream slopes and the advance of gullies from these streams. These erosion processes remove material from the plateau, growing the size of the creek valleys and making them wider and deeper. Of particular interest for the impact of erosion is radioactive waste contained in the Nuclear Regulatory Commission (NRC)-Licensed Disposal Area (NDA), the New York State-Licensed Disposal Area (SDA), and residual radiological inventory in the underground storage tanks at the Waste Tank Farm (WTF). The PPA Model is organized around geographically-defined facilities which were constructed upon the plateau, including the NDA, SDA, and WTF. Ongoing stream erosion processes will potentially transfer radioactive waste and residual inventory from these facilities to the ground surface on adjacent hillslope areas where erosion has breached the facility. Hence, it is important to evaluate the consequences of potential exposures to a Resident Farmer on the hillslopes below a breached facility. Two interrelated aspects of the dose assessment model related to hillslope exposure are discussed: 1) representation of the physical processes related to transport of radionuclides from facilities onto the hillslopes, and from the hillslopes into adjoining creeks where contaminated material migrates downstream with surface water and sediment, and; 2) adaptation of the activities associated with the Resident Farmer scenario to assess potential exposures to contamination in the hillslope areas. This discussion will cover the conceptual basis of the hillslope exposure and transport models, and also implementation in the PPA computer model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗

NASA Tech Briefs, February 2003

opics covered include: Integrated Electrode Arrays for Neuro-Prosthetic Implants; Eroding Potentiometers; Common/Dependent-Pressure-Vessel Nickel-Hydrogen Batteries; 120-GHz HEMT Oscillator With Surface-Wave-Assisted Antenna; 80-GHz MMIC HEMT Voltage-Controlled Oscillator; High-Energy-Density Capacitors; Microscale Thermal-Transpiration Gas Pump; Instrument for Measuring Temperature of Water; Improved Measurement of Coherence in Presence of Instrument Noise; Compact Instruments Measure Helium-Leak Rates; Irreversible Entropy Production in Two-Phase Mixing Layers; Subsonic and Supersonic Effects in Bose-Einstein Condensate; Nanolaminate Mirrors With "Piston" Figure-Control Actuators; Mixed Conducting Electrodes for Better AMTEC Cells; Process for Encapsulating Protein Crystals; Lightweight, Self-Deployable Wheels; Grease-Resistant O Rings for Joints in Solid Rocket Motors; LabVIEW Serial Driver Software for an Electronic Load; Software Computes Tape-Casting Parameters; Software for Tracking Costs of Mars Projects; Software for Replicating Data Between X.500 and LDAP Directories; The Technical Work Plan Tracking Tool; Improved Multiple-DOF SAW Piezoelectric Motors; Propulsion Flight-Test Fixture; Mechanical Amplifier for a Piezoelectric Transducer; Swell Sleeves for Testing Explosive Devices; Linear Back-Drive Differentials; Miniature Inchworm Actuators Fabricated by Use of LIGA; Using ERF Devices to Control Deployments of Space Structures; High-Temperature Switched-Reluctance Electric Motor; System for Centering a Turbofan in a Nacelle During Tests; Fabricating Composite-Material Structures Containing SMA Ribbons; Optimal Feedback Control of Thermal Networks; Artifacts for Calibration of Submicron Width Measurements; Navigating a Mobile Robot Across Terrain Using Fuzzy Logic; Designing Facilities for Collaborative Operations; and Quantitating Iron in Serum Ferritin by Use of ICP-MS.

Source record↗

Global Energy and Water Exchanges Program Surface Radiation Budget Release 4 Integrated Product: Algorithm Theoretical Basis Document

This document represents the Algorithm Theoretical Basis Document (ATBD) describing the NASA Langley Research Center's Surface Radiation budget (SRB) developed in collaboration with the World Research Climate Programme's Global Energy and Water Exchanges Program. The top of atmosphere and surface fluxes span from July 1, 1983 through June 30, 2017. The shortwave or solar wavelengths span the entire record. The thermal infrared or longwave fluxes span globally from January 1, 1988 to December 30, 2009. Before 1988, only the land-only fluxes are available. After 2009 only the ocean fluxes are available. This document describes all the inputs and radiative transfer algorithms used to generate the TOA and surface radiative fluxes. The fluxes include upward and downward, all-sky, clear-sky and pristine sky conditions. Surface net fluxes and cloud radiative effect are computed and presented as part of the analysis. Comparisons to other data products are made to assess the top-of-atmosphere and surface fluxes. Additionally, surface measurements are utilized to validation the surface fluxes. The surface validation analysis shows the the radiative fluxes are improved compared to the previous version. Data set cautions are also presented.

surface radiation budget↗

Integrating Data Centers and Grid Technologies at Scale

This presentation focuses on the challenge of integrating AI-driven data centers with the power grid at scale. It examines the AI data center capacity challenge and the role of new Medium Voltage Direct Current (MVDC) and other grid-enhancing technologies in enabling efficient and reliable power delivery. The session will highlight the National Laboratory of the Rockies' ARIES capabilities and planning tools, along with collaborative examples involving Verrus, Compass, and Schneider through the Agora test bed for grid-friendly data center evaluations, and ON. Energy for UPS evaluation. It will showcase the NLR Stable Grid Platform for studying oscillations caused by large-scale data centers, along with planning tools to assess grid security and reliability. Additionally, the presentation covers reconductoring strategies to increase grid capacity and explores innovative data center architectures, including the Advanced DC Architectures with Power-electronic Transformers (ADAPT) platform, which enables testing of complete DC architectures for data centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗

Towards a More Effective Hybrid Workforce Culture in a Computationally Focused Research Center

It is essential to Sandia National Laboratory’s continued success in scientific and technological advances and mission delivery to embrace a hybrid workforce culture under which current and future employees can thrive. This report focuses on the findings of the Hybrid Work Team for the Center for Computing Research, which met weekly from March to June 2023 and conducted a survey across the Center at Sandia. Conclusions in this report are drawn from the 9 authors of this report, which comprises the Hybrid Work Team, and 15 responses to a center-wide survey, as well as numerous conversations with colleagues. A major finding was widespread dissatisfaction with the quantity, execution, and tooling surrounding formal meetings with remote participants. While there was consensus that remote work enables people to produce high quality individual and technical work, there was also consensus that there was widespread social disconnect, with particular concern about hires that were made after the onset of the Covid-19 pandemic. There were many concerns about tooling and policy to facilitate remote collaboration both within Sandia and with its external collaborators. This report includes recommendations for mitigating these problems. For problems for which obvious recommendations cannot be made, ideas of what a successful solution might look like are presented.

99 GENERAL AND MISCELLANEOUS↗

Geonex: Land Surface Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Nemani, Ramakrishna R.↗

Earth Observations from Geostationary Satellites

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GeoNEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GeoNEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GeoNEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Earth↗

GeoNEX: Land Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

GeoNEX↗

Synaptic changes in rat maculae in space and medical imaging: the link

Two different space life sciences missions (SLS-1 and SLS-2) have demonstrated that the synapses of the hair cells of rat vestibular maculae increase significantly in microgravity. The results also indicate that macular synapses are sensitive to stress. These findings argue that vestibular maculae exhibit neuroplasticity to macroenvironmental and microenvironmental changes. This capability should be clinically relevant to rehabilitative training and/or pharmacological treatments for vestibular disease. The results of this ultrastructural research also demonstrated that type I and type II hair cells are integrated into the same neuronal circuitry. The findings were the basis for development of three-dimensional reconstruction software to learn details of macular wiring. This software, produced for scientific research, has now been adapted to reconstruct the face and skull directly from computerized tomography scans. In collaboration with craniofacial reconstructive surgeons at Stanford University Medical Center, an effort is under way to produce a virtual environment workbench for complex craniofacial surgery. When completed, the workbench will help surgeons train for and simulate surgery. The methods are patient specific. This research illustrates the value of basic research in leading to unanticipated medical applications.

Flight Experiment↗