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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Orion Nebula and Planetary Nebulae

This report summarizes the research performed at Rice University related to NASA-Ames University consortium grant NCC2-5199 during the two year period 1996 September 1 through 1998 August 31. The research program, titled Orion Nebula and Planetary Nebulae, involved the analysis of Hubble Space Telescope (HST) imagery and spectroscopy of the Orion Nebula and of the planetary nebulae NGC 6818 and NGC 6210. In addition, we analyzed infrared spectra of the Orion Nebula taken with the Infrared Space Observatory (ISO) The primary collaborators at NASA-Ames were Drs. R. H. Rubin, A. G. C. M. Tielens, S. W. J. Colgan, and S. D. Lord (Tielens & Lord has since changed institutions). Other collaborators include Drs. P. G. Martin (CITA, Toronto), G. J. Ferland (U. KY), J. A. Baldwin (CTIO, Chile), J. J. Hester (ASU), D. K. Walter (SCSU), and P. Harrington (U. MD). In addition to the Principal Investigator, Professor Reginald J. Dufour of the Department of Space Physics & Astronomy, the research also involved two students, Mr. Matthew Browning and Mr. Brent Buckalew. Mr. Browning will be graduating from Rice in 1999 May with a B.A. degree in Physics and Mr. Buckalew continues as a graduate student in our department, having recently received a NASA GSRP research fellowship (sponsored by Ames). The collaboration was very productive, with two refereed papers already appearing in the literature, several others in preparation, numerous meeting presentations and two press releases. Some of our research accomplishments are highlighted below. Attached to the report are copies of the two major publications. Note that this research continues to date and related extensions of it recently has been awarded time with the HST for 1999-2000.

Dufour, Reginald J.↗
NASA NTRSDate not supplied

Cloud-Based Solutions for Monitoring Coastal Ecosystems and Prioritization of Restoration Efforts Across Belize

In recent years the availability of automated change detection algorithms in Google Earth Engine has permitted cloud-based processing of large time series of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EO) , leveraging the Landsat archive and data from other sensors to detect disturbance in forest ecosystems. Despite the wide adoption of these methods, robust documentation and growing community of users, little research has explored their use in mangrove environments. Mangroves are dynamic environments subject to changes due to not only the natural migration of mudflats but also coastal erosion, urban expansion, aquaculture practices, etc. This work aims to identify best practices for the application of these models to identify and monitor changes in the Belizean mangroves, which experienced an estimated 5.4% decrease in extent between 1980 and 2017 (Cherrington et al. 2020). Partnering directly with the Belizean Forest Department, our team will develop a replicable, efficient methodology to annually update the country’s mangrove extent employing EO-based change detection. This collaboration supports Belize’s marine conservation and climate resilience efforts, such as its Blue Bond agreement with the Nature Conservancy, building on national processes to monitor these critical ecosystems.

Mangroves↗
NASA NTRS2002

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Johnston, William E.↗
DOE OSTI2019

From Structure to Functions: Metagenomics-Enabled Predictive Understanding of Soil Microbial Feedbacks to Climate Change

Understanding the responses, adaptations and feedback mechanisms of biological communities to climate change is critical to project future states of earth and climate systems. Although a significant amount of knowledge is available on the feedbacks of aboveground communities to climate change, the responses of belowground microbial communities are still poorly understood. This is due to challenges in analyzing soil microbial communities in terms of their diversity, structure and function. Thus, the ultimate goal of this study is to advance system-level predictive understanding of the feedbacks of belowground microbial communities to multiple climate change factors and their impacts on soil carbon (C) cycling processes. For this, cutting-edge integrated metagenomic technologies are employed to establish mechanistic linkages among aboveground plant communities, belowground microbial communities, ecosystem processes and functions and climate change. Towards this goal, the following four specific objectives are pursued: (i) To determine the responses of microbial community structure, functions and activities to climate warming, altered precipitation, soil moisture regime and/or clipping in the tundra and temperate grassland ecosystems; (ii) To determine the temperature sensitivity and the effect of substrate priming on recalcitrant C decomposition; (iii) To determine microbiological bases underlying temperature sensitivity of recalcitrant C decomposition; and (iv) To develop integrated bioinformatics and modeling approaches to scale information across different organizational levels towards predictive understanding of ecosystem responses to multiple climate change factors in collaboration with the Knowledge Base (KBase) and integrated into their database. Warming experiments in an Alaskan tundra permafrost soil (AK) as well as an Oklahoma temperate grassland soil (OK) provide a more complete picture of the effects of warming on belowground microbial communities of different (key) soil ecosystems. Numerous research activities have been carried out by the institutions under the support of this program. For brevity, a few key results and their significance are highlighted in this report.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Large Aperture Scanning Lidar Based on Holographic Optical Elements

Lidar remote sensing instruments can make a significant contribution to satisfying many of the required measurements of atmospheric and surface parameters for future spaceborne platforms, including topographic altimeters, atmospheric profiles of, wind, humidity, temperature, trace molecules, aerosols, and clouds. It is highly desirable to have wide measurement swaths for rapid coverage rather than just the narrow ribbon of data that is obtained with a nadir only observation. For most applications global coverage is required, and for wind measurements scanning or pointing is required in order to retrieve the full 3-D wind vector from multiple line-of-sight Doppler measurements. Conventional lidar receivers make up a substantial portion of the instrument's size and weight. Wide angle scanning typically requires a large scanning mirror in front of the receiver telescope, or pointing the entire telescope and aft optics assembly, Either of these methods entails the use of large bearings, motors, gearing and their associated electronics. Spaceborne instruments also need reaction wheels to counter the torque applied to the spacecraft by these motions. NASA has developed simplified conical scanning telescopes using Holographic Optical Elements (HOEs) to reduce the size, mass, angular momentum, and cost of scanning lidar systems. NASA has developed two operating lidar systems based on 40 cm diameter HOEs. The first such system, named Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing (PHASERS) was a joint development between NASA Goddard Space Flight Center (GSFC) and the University of Maryland College Park. PHASERS is based on a reflection HOE for use at the doubled Nd:YAG laser wavelength of 532 nm and has recently undergone a number of design changes in a collaborative effort between GSFC and Saint Anselm College in New Hampshire. The next step was to develop IR transmission HOEs for use with the Nd:YAG fundamental in the Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE). The HOE spins like a compact disk in a large ring ball bearing. In an aircraft the HOE faces down, looking out through a window at an angle of 45 degrees off-nadir. The HOE diffracts 85% of the incident 532 nm light into a 160 micron spot at a focal length of 1 meter. HARLIE is a field deployable lidar measuring aerosol, cloud, and boundary layer backscatter for atmospheric research. It has flown several times and is also used from a ground-based trailer in an upward-looking mode. The HOE generates a 45 degree conical scan pattern by rotating at speeds up to 30 rpm. Like PHASERS, the HOE in HARLIE serves both as the laser collimating lens as well as the receiver telescope primary optic. The telescope is coupled to the receiver package via fiber optic. The transmitter is a diode pumped Nd:YAG laser operating at 1064 nm, delivering 1 mJ pulses at a 5 KHz rep-rate. The receiver has a 200 microradian field-of-view and a 0.5 nm optical bandpass. The photon counting data system utilizes a single Geiger-mode silicon avalanche photodiode detector, This new technology has also presented us with new data visualization challenges as well as new measurement techniques. The backscatter data obtained from a stationary (i.e. ground-based) scanning HOE lidar is on the surface of a cone, which when viewed over many consecutive scans can reveal atmospheric motions on this surface over time as the atmosphere advects over the site. In a moving platform such as an airplane or satellite, the data from consecutive scans cover different areas under the flight path, revealing atmospheric structure in 3-dimensions. An example of a visualization of HARLIE ground-based data is presented, showing aerosol backscatter on a 90 degree conical surface generated from one 360 degree scan of the lidar during the HOLO-1 field campaign on the afternoon of 10 March 1999. Higher backscatter levels are rendered as lighter signal against a dark background. Breaking Kelvin-Helmholtz waves are evident on the north side of the scan at an altitude of 10-11 km. Time series of successive scans made at regular intervals render unique views of atmospheric motions, from which vertical profiles of atmospheric wind vectors can be obtained using a unique data analysis approach. Wind vectors obtained from the lidar were compared with co-located radiosonde wind profiles during an intensive operating period in September-October 2000 at the Atmospheric Radiation Measurement Program's Southern Great Plains Central Facility.

Schwemmer, Geary K.↗
NASA NTRS2009

Management of Service Projects in Support of Space Flight Research

Goal:To provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration . [HRP-47051] Specific Objectives: 1) Develop capabilities, necessary countermeasures, and technologies in support of human space exploration, focusing on mitigating the highest risks to human health and performance. 2) Define and improve human spaceflight medical, environmental, and human factors standards. 3) Develop technologies that serve to reduce medical and environmental risks, to reduce human systems resource requirements (mass, volume, power, data, etc.) and to ensure effective human-system integration across exploration systems. 4) Ensure maintenance of Agency core competencies necessary to enable risk reduction in the following areas: A. Space medicine B. Physiological and behavioral effects of long duration spaceflight on the human body C. Space environmental effects, including radiation, on human health and performance D. Space "human factors" [HRP-47051]. Service projects can form integral parts of research-based project-focused programs to provide specialized functions. Traditional/classic project management methodologies and agile approaches are not mutually exclusive paradigms. Agile strategies can be combined with traditional methods and applied in the management of service projects functioning in changing environments. Creative collaborations afford a mechanism for mitigation of constrained resource limitations.

Love, J.↗
NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗
DOE OSTI2021

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗
NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗
NASA NTRS1998

Global Change Research Related to the Earth's Energy and Hydrologic Cycle

The Institute for Global Change Research and Education (IGCRE) is a joint initiative of the Universities Space Research Association (USRA) and the University of Alabama in Huntsville (UAH) for coordinating and facilitating research and education relevant to global environmental change. Created in 1992 with primary support from the National Aeronautics and Space Administration (NASA), IGCRE fosters participation by university, private sector and government scientists who seek to develop long-term collaborative research in global change science, focusing on the role of water and energy in the Earth's atmosphere and physical climate system. IGCRE is also chartered to address educational needs of Earth system and global change science, including the preparation of future scientists and training of primary and secondary education teachers.

Source record↗
NASA NTRSDate not supplied

Defining Collaborative Control Interactions Using Systems Theory

Human teams collaborate by establishing roles, changing functional authorities, maintaining team cognition, coordinating, and mutually helping one another close control loops. These complex inter-actions are inspiring novel concepts to improve human-machine and multi-machine collaboration. However, these new systems face engineering gaps in modeling, analysis, design, and assurance. As such, few have been fielded in safety-critical domains like aerospace. To analyze safety, this paper introduces a system-theoretic framework to describe interactions that are—or are planned to be—used in multi-controller systems. It outlines a taxonomy of seven structural dimensions that influence controller interactions and nine dynamics observed in collaborative control that are defined using Systems Theory. An analyzed set of 101 controller interactions in aerospace systems demonstrates how to apply the framework and that designers are trying to create more sophisticated systems. This framework provides the foundation to extend system-theoretic hazard analysis techniques to systematically find collabora-tive-control causal factors.

Human machine teaming↗
DOE OSTI2026

American cities in a time of global environmental change: the case of the Baltimore Social-Environmental Collaborative

The Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory seeks a new paradigm for urban climate research. Motivated by deep uncertainties in urban climate and the future of urban systems, BSEC works collaboratively across institutions and stakeholder groups to co-generate the science needed to advance energy security and resilience to extreme events across the city of Baltimore, Maryland, USA, and to do so in a manner that can inform similar efforts in other cities. BSEC begins with stakeholder priorities (health, affordable energy, etc) and designs observation networks and models to deliver climate science to address them. This takes the form of an iterative collaborative cycle, in which an initial research strategy is repeatedly updated in conversation with community partners, and researchers and stakeholders learn from each other. To date, this cycle has included multiple rounds of collaborative deliberation on urban heat mitigation, in which a multicriteria decision tool has been updated with more community-relevant spatial structure and modified optimization metrics. The guiding objective of this cycle is to inform potential ‘secure and resilient pathways’ for energy and infrastructure. In doing so, BSEC addresses fundamental urban science questions in natural and social sciences. It also tests our ability to integrate this science in a manner that advances participatory decision-making for urban resilience.

climate↗
DOE OSTI2020

Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era

The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration. Commensurately, algorithms and statistical models have begun to adapt --- e.g., via the onset of artificial intelligence --- which itself presents new challenges and opportunities for growth. This white paper aims to offer guidance and ideas for how we can evolve our technical and collaborative frameworks to promote efficient algorithmic development and take advantage of opportunities for scientific discovery in the petabyte era. We discuss challenges for discovery in large and complex data sets; challenges and requirements for the next stage of development of statistical methodologies and algorithmic tool sets; how we might change our paradigms of collaboration and education; and the ethical implications of scientists' contributions to widely applicable algorithms and computational modeling. We start with six distinct recommendations that are supported by the commentary following them. This white paper is related to a larger corpus of effort that has taken place within and around the Petabytes to Science Workshops (https://petabytestoscience.github.io/).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

NASA SPoRT Land Information System Products for Soil Moisture Analysis

The NASA Short-term Prediction Research and Transition (SPoRT) Program has been producing a near real-time instance of NASA’s Land Information System (hereafter known as SPoRT-LIS) since 2010, which contains output of soil moisture and temperature at layered depths. The unique configuration of the SPoRT-LIS enables decision-making on operational timescales since it assimilates near real-time observations such as Green Vegetation Fraction from the Visible Infrared Imaging Radiometer Suite and Quantitative Precipitation Estimates from the Multi-Radar Multi-Sensor System. The SPoRT-LIS was developed initially to provide land surface initialization variables for local numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model. The earliest documented uses of the SPoRT-LIS as a tool for local drought analysis came from the National Weather Service Office in Huntsville, AL in 2011, in which data were used to provide recommendations for drought category changes to the U.S. Drought Monitor. Through engagement with SPoRT collaborative partners, use of the SPoRT-LIS has gradually expanded in recent years as a component of drought analysis and feedback to the U.S. Drought Monitor. This effort was aided by feedback from end users who expressed needs for specific soil moisture variables, which led to increased applicability for analysis by others in the drought community. This presentation will provide information on the SPoRT-LIS for drought analysis and the collaborative process that has led to changes in product output to meet user needs, with focus in the Southern Appalachian region. However, applications for hydrology and fire weather will also be discussed.

Land surface modeling↗
DOE OSTI2025

Search for flavor-changing neutral current interactions of the top quark mediated by a Higgs boson in proton-proton collisions at 13 TeV

A search for flavor-changing neutral current interactions of the top quark (𝑡) and the Higgs boson (𝐻) is presented. The search is based on proton-proton collision data collected in 2016–2018 at a center-of-mass energy of 13 TeV with the CMS detector at the LHC, and corresponding to an integrated luminosity of 138 fb −1 . Events containing a pair of leptons with the same-sign electric charge and at least one jet are considered. The results are used to constrain the branching fraction (ℬ) of the top quark decaying to a Higgs boson and an up (𝑢) or charm (𝑐) quark. No significant excess above the estimated background was found. The observed (expected) upper limits at a 95% confidence level are found to be 0.072% (0.059%) for ℬ⁡(𝑡 → 𝐻⁡𝑢) and 0.043% (0.062%) for ℬ⁡(𝑡 → 𝐻⁡𝑐). These results are combined with two other searches performed by the CMS Collaboration for flavor-changing neutral current interactions of top quarks and Higgs bosons in final states where the Higgs boson decays to either a pair of photons or a pair of bottom quarks. The resulting observed (expected) upper limits at the 95% confidence level are 0.019% (0.027%) for ℬ⁡(𝑡 → 𝐻⁡𝑢) and 0.037% (0.035%) for ℬ⁡(𝑡 → 𝐻⁡𝑐).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Exascale Was Not Inevitable; Neither Is What Comes Next

The long, steady advance of supercomputing capabilities historically makes it tempting to assume that similar future improvements are inevitable. In fact, the successful path to exascale systems was far from certain, requiring a shift to accelerator-based designs, an associated end-to-end rethinking of traditional computational approaches, and a fundamental change in how scientists collaborate and interact. Here in this article, we share lessons from the U.S. Department of Energy Exascale Computing Project along with perspectives on how to design and implement scientific applications in the exascale and post-exascale eras.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

NREL Waves to Water Prize Program: Sensitivity Analysis of Alternative Markets

Isle Inc., in collaboration with Engineering for Change (project team), performed a Sensitivity Analysis of market alternatives to evaluate commercialization barriers for the Waves to Water (W2W) competitors. This analysis included interviews with organizations and end-users in three market categories (1) Disaster Relief, (2) Commercial/Industrial, and (1) Municipal, Residential, and Government. For each category, the project team selected organizations that provided a well rounded experience and set of drivers for adopting W2W technologies. In addition to the project team's efforts, fellows from NREL/DOE completed interviews with government organizations to understand their potential to engage with W2W technologies, and these findings are summarized in a separate summary document.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

User Access to Scientific Facilities via 5G: A Cyber Security Thought Experiment

5G is more than an over-the-air radio technology upgrade. It is a strategy to extend Mobile Network Operator service offerings beyond traditional voice, instant messaging and Internet access. 5G Mobile Network Operators will offer new telecommunication services that include enhanced guarantees of confidentiality, integrity and availability. How could such services change the way Science collaborations connect scientists to supercomputers and other scientific facilities? Current scientific collaborations implicitly trust cloud service providers to securely store and process data. The perceived risks of outsourcing Science data security are counterbalanced by assurances that cloud providers operate at a scale that allows them to implement security measures impractical for Science collaborations (e.g. continuous system administrator behavioral monitoring and strict individual separation of duties). If that is true for a cloud service provider like Amazon Web Services (2018 revenue: $25.7 billion), could it also be true for Mobile Network Operators like Verizon Wireless (2018 revenue: $91.7 billion) or AT&T Mobility (2018 revenue: $71.3 billion)? DOE Leadership Class supercomputer facility users currently access them from the public Internet via Secure Shell. The sponsors and operators of the supercomputer facilities have determined that the public Internet path between the Scientist’s Device and the Login Node does not natively provide enough confidentiality or integrity to protect those communications. Therefore, the facilities achieve additional confidentiality and integrity by requiring Secure Shell encryption across those untrusted network paths. Using 5G Network Slice technology, a Mobile Network Operator may offer communication services between supercomputer users and facilities that natively provide confidentiality and integrity guarantees. Sponsors and operators of supercomputer facilities may determine that these guarantees provide enough confidentiality and integrity to protect those communications. If so, a 5G Network Slice could replace an SSH session running over the public Internet. Finally, this use case could be extended to other Office of Science user facility access requirements. Consider microscopy instruments at (e.g.) the Center for Nanoscale Materials or the Environmental Molecular Sciences Laboratory. The embedded systems controlling such instruments may not always support encrypted network access technologies like SSH. 5G Network Slices may offer an alternative to current VPN or SSH tunneling techniques, with additional benefits like guaranteed minimum bandwidth.

5G↗