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Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗
DOE OSTI2020

REopt Lite Overview & Training Exercise

This training exercise provides users with an introduction to and hands-on, interactive exploration of REopt Lite's capabilities. REopt Lite is a free, publicly available techno-economic optimization web tool for distributed energy systems, developed at the National Renewable Energy Laboratory (NREL). REopt Lite helps organizations evaluate the economic viability of grid-connected solar photovoltaics (PV), wind turbines, and battery storage; identify system sizes and battery dispatch strategies to minimize energy costs; and estimate how long a system can sustain critical load during a grid outage. The model is formulated as a mixed-integer linear program based in an underlying application programming interface (API) that is also free and publicly available. This training activity is structured as a group exercise. Participants split into eight groups and each group is assigned a different hypothetical site to model and assess the opportunity for solar PV + battery storage. Groups work together to develop results for their site and then re-convene to compare and discuss results, inputs/drivers of the analysis, and other factors impacting the decision-making process for behind-the-meter solar PV and battery storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1996

Mixed composition materials suitable for vacuum web sputter coating

Ion beam sputter deposition techniques were used to investigate simultaneous sputter etching of two component targets so as to produce mixed composition films. Although sputter deposition has been largely confined to metals and metal oxides, at least one polymeric material, poly-tetra-fluorethylene, has been demonstrated to produce sputtered fragments which repolymerize upon deposition to produce a highly cross-linked fluoropolymer resembling that of the parent target Fluoropolymer-filled silicon dioxide and fluoropolymer-filled aluminum oxide coatings have been deposited by means of ion beam sputter coat deposition resulting in films having material properties suitable for aerospace and commercial applications. The addition of fluoropolymer to silicon dioxide films was found to increase the hydrophobicity of the resulting mixed films; however, adding fluoropolymer to aluminum oxide films resulted in a reduction in hydrophobicity, thought to be caused by aluminum fluoride formation.

Banks, Bruce A.↗
DOE OSTI2019

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗
DOE OSTI2015

An interactive ontology-driven information system for simulating background radiation and generating scenarios for testing special nuclear materials detection algorithms

This paper describes an original approach to generating scenarios for the purpose of testing the algorithms used to detect special nuclear materials (SNM) that incorporates the use of ontologies. Separating the signal of SNM from the background requires sophisticated algorithms. To assist in developing such algorithms, there is a need for scenarios that capture a very wide range of variables affecting the detection process, depending on the type of detector being used. To provide such a cpability, we developed an ontology-driven information system (ODIS) for generating scenarios that can be used in creating scenarios for testing of algorithms for SNM detection. The ontology-driven scenario generator (ODSG) is an ODIS based on information supplied by subject matter experts and other documentation. The details of the creation of the ontology, the development of the ontology-driven information system, and the design of the web user interface (UI) are presented along with specific examples of scenarios generated using the ODSG. We demonstrate that the paradigm behind the ODSG is capable of addressing the problem of semantic complexity at both the user and developer levels. Compared to traditional approaches, an ODIS provides benefits such as faithful representation of the users' domain conceptualization, simplified management of very large and semantically diverse datasets, and the ability to handle frequent changes to the application and the UI. Furthermore, the approach makes possible the generation of a much larger number of specific scenarios based on limited user-supplied information

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗
DOE OSTI2024

Design, Synthesis, and Validation: Genome Scale Optimization of Energy Flux through Compartmentalized Metabolic Networks in a Model Photosynthetic Eukaryotic Microbe (Final Report)

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methodology and modeling, coupled with high throughput genome engineering strategies, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require significant advances in methodological throughput as well as improvements in detailed systems biology understanding of photosynthetic processes and cellular metabolism. The ability of diatoms to thrive in upwelling-induced, periodically nutrient-rich conditions makes them the base for the world’s shortest and most energy-efficient food webs. Diatom photosynthesis is estimated to account for between 25% and 40% of the 45-50 billion tons of organic carbon fixed annually in the sea.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1985

The status of silicon ribbon growth technology for high-efficiency silicon solar cells

More than a dozen methods have been applied to the growth of silicon ribbons, beginning as early as 1963. The ribbon geometry has been particularly intriguing for photovoltaic applications, because it might provide large area, damage free, nearly continuous substrates without the material loss or cost of ingot wafering. In general, the efficiency of silicon ribbon solar cells has been lower than that of ingot cells. The status of some ribbon growth techniques that have achieved laboratory efficiencies greater than 13.5% are reviewed, i.e., edge-defined, film-fed growth (EFG), edge-supported pulling (ESP), ribbon against a drop (RAD), and dendritic web growth (web).

Ciszek, T. F.↗
NASA NTRS2005

Evaluating the Effectiveness of the 2003-2004 NASA CONNECT(trademark)Program

NASA CONNECT is an Emmy-award-winning series of instructional (distance learning) programs for grades 6-8. Produced by the NASA Center for Distance Learning, the nine programs in the 2003-2004 NASA CONNECT series are research-, inquiry-, standards-, teacher-, and technology-based and include a 30-minute program, an educator guide containing a hands-on activity, and a web-based component. The 1,500 randomly selected NASA CONNECT registered users were invited to complete an electronic (self-reported) survey that employed a 5-point Likert-type scale. Regarding NASA CONNECT, respondents reported that the programs (1) enhance the teaching of mathematics, science, and technology (4.53); (2) are aligned with the national mathematics, science, and technology standards (4.52); (3) raise student awareness of careers requiring mathematics, science, and technology (4.48); (4) demonstrate the application of mathematics, science, and technology (4.47); and (5) present women and minorities performing challenging engineering and science tasks (4.50).

Caton, Randall H.↗
DOE OSTI2015

A Collaborative Extensible User Environment for Simulation and Knowledge Management

In scientific simulation, scientists use measured data to create numerical models, execute simulations and analyze results from advanced simulators executing on high performance computing platforms. This process usually requires a team of scientists collaborating on data collection, model creation and analysis, and on authorship of publications and data. This paper shows that scientific teams can benefit from a user environment called Akuna that permits subsurface scientists in disparate locations to collaborate on numerical modeling and analysis projects. The Akuna user environment is built on the Velo framework that provides both a rich client environment for conducting and analyzing simulations and a Web environment for data sharing and annotation. Akuna is an extensible toolset that integrates with Velo, and is designed to support any type of simulator. This is achieved through data-driven user interface generation, use of a customizable knowledge management platform, and an extensible framework for simulation execution, monitoring and analysis. This paper describes how the customized Velo content management system and the Akuna toolset are used to integrate and enhance an effective collaborative research and application environment. The extensible architecture of Akuna is also described and demonstrates its usage for creation and execution of a 3D subsurface simulation.

collaborative science tools↗
DOE OSTI2011

LaserFest Celebration

LaserFest was the yearlong celebration, during 2010, of the 50th anniversary of the demonstration of the first working laser. The goals of LaserFest were: to highlight the impact of the laser in its manifold commercial, industrial and medical applications, and as a tool for ongoing scientific research; to use the laser as one example that illustrates, more generally, the route from scientific innovation to technological application; to use the laser as a vehicle for outreach, to stimulate interest among students and the public in aspects of physical science; to recognize and honor the pioneers who developed the laser and its many applications; to increase awareness among policymakers of the importance of R&D funding as evidenced by such technology as lasers. One way in which LaserFest sought to meet its goals was to encourage relevant activities at a local level all across the country -- and also abroad -- that would be identified with the larger purposes of the celebration and would carry the LaserFest name. Organizers were encouraged to record and advertise these events through a continually updated web-based calendar. Four projects were explicitly detailed in the proposals: 1) LaserFest on the Road; 2) Videos; 3) Educational material; and 4) Laser Days.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2005

Nexus: Planning Tomorrow, Today

To prepare for future human space flight programs, the Mission Operations Laboratory (MOL) at the Marshall Space Flight Center (MSFC) has been investigating new planning and scheduling paradigms. To support and prove this investigation, MOL technologists have developed a working prototype of a scheduling system to support the new paradigms. The new planning and scheduling system is called Nexus and has a web site at http://nexus.nasa.gov/. Nexus is based on a comprehensive modeling schema to capture all scheduling requirements typical to human space missions, an incremental scheduling engine tailored to the modeling schema, and remote access (including Personal Data Assistant (PDA) access) to the scheduling system. This paper describes the proposed paradigm shift and the enabling software. It also describes a typical Nexus demonstration which emphasizes how it works, how it enables the paradigm shift, and possible applications. Demonstrations include access to the full functionally of Nexus from a personal computer and access to limited functionally via a PDA. An appendix includes a description and screen shots of the demonstrations.

Jaap, John↗
NASA NTRS2019

Industrial-Era Decline in Subarctic Atlantic Productivity

Marine phytoplankton play a critical role in modulating marine-based food webs, fishery yields, and the global drawdown of atmospheric CO2. Due to sparse measurements prior to 21st century satellite monitoring, however, little is known of the long-term response of planktonic stocks to climate forcing. Here we produce the first continuous, multi-century record of subarctic Atlantic marine productivity, showing a marked 10 ± 7% decline has occurred across this highly-productive ocean basin over the last two centuries. We support this conclusion through the application of a novel marine-productivity proxy, established using a unique signal of planktonic-derived aerosol commonly identified across an array of Greenlandic ice cores. Utilizing contemporaneous satellite-era observations, we demonstrate this signal’s use as a robust and high-resolution proxy for spatially-integrated marine productivity variations. We show that the initiation of declining subarctic Atlantic productivity broadly coincides with the onset of Arctic surface warming, and that productivity strongly covaries with regional sea-surface temperatures and basin-wide gyre circulation strength over recent decades. Taken together, our results suggest the industrial era productivity decline may be evidence of the predicted5 collapse of northern Atlantic planktonic stocks in response to a weakened Atlantic Meridional Overturning Circulation (AMOC). Continued AMOC weakening, as projected for the 21st century, may therefore result in further productivity declines across this globally-relevant region.

Climate change↗
DOE OSTI2014

Roll-to-roll atomic layer deposition process for flexible electronics encapsulation applications

At present flexible electronic devices are under extensive development and, among them, flexible organic light-emitting diode displays are the closest to a large market deployment. One of the remaining unsolved challenges is high throughput production of impermeable flexible transparent barrier layers that protect sensitive light-emitting materials against ambient moisture. The present studies deal with the adaptation of the atomic layer deposition (ALD) process to high-throughput roll-to-roll production using the spatial ALD concept. We report the development of such a process for the deposition of 20 nm thickness Al{sub 2}O{sub 3} diffusion barrier layers on 500 mm wide polymer webs. The process uses trimethylaluminum and water as precursors at a substrate temperature of 105 °C. The observation of self-limiting film growth behavior and uniformity of thickness confirms the ALD growth mechanism. Water vapor transmission rates for 20 nm Al{sub 2}O{sub 3} films deposited on polyethylene naphthalate (PEN) substrates were measured as a function of substrate residence time, that is, time of exposure of the substrate to one precursor zone. Moisture permeation levels measured at 38 °C/90% relative humidity by coulometric isostatic–isobaric method were below the detection limit of the instrument (<5 × 10{sup −4} g/m{sup 2} day) for films coated at web moving speed of 0.25 m/min. Measurements using the Ca test indicated water vapor transmission rates ∼5 × 10{sup −6} g/m{sup 2} day. Optical measurements on the coated web showed minimum transmission of 80% in the visible range that is the same as the original PEN substrate.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Celebrating 10 Years of the Sub-Seasonal to Seasonal Prediction Project and Looking to the Future

The conference clearly demonstrated the increasing interest and growth of the scientific community working on the development and application of sub-seasonal to seasonal prediction since the start of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) sub-seasonal to seasonal (S2S) prediction project in 2013. The conference, which was held at the University of Reading (United Kingdom), was organized into three main themes as briefly summarized below, with eleven invited talks, 74 oral contributed talks, and 101 posters. The conference also included a two-hour breakout session, wherein eight groups discussed the current state and prospect for S2S prediction, and an early career researcher event. A summary of these discussions and recommendations is presented below. The conference web page (https://research.reading.ac.uk/s2s-summit2023/) is archived at the University of Reading. Introductory comments by representatives of the World Meteorological Organization (WMO) WWRP and WCRP emphasized the importance of the weather–climate linkage, targeted by S2S forecasts (from 2 weeks to a season ahead), addressing the challenges of creating “end-to-end” forecasts that encompass the entire climate-services chain from the prediction science and forecast, to the development and issuing of forecast products tailored to informing user-decisions. They also emphasized the efficacy of multi-model ensemble efforts and databases to foster collaborations internationally and between operational centres and academia. Although the WWRP/WCRP S2S project comes to an end in 2023, S2S prediction will remain an important focus for WWRP and WCRP. In WWRP, a new project called SAGE (Sub-seasonal to seasonal predictions for Agriculture and Environment) will start in 2024. Another important legacy of the S2S project will be the maintenance of the S2S database (Vitart et al. 2017) and the establishment of a WMO Lead Center for sub-seasonal prediction multi-model ensemble (LC-SSPMME) which will provide real-time multi-model S2S climate information. In two keynote presentations, Prof. Brian Hoskins (University of Reading) and Dr. Gilbert Brunet (Australian Bureau of Meteorology) discussed the potential of S2S predictability and the ongoing journey for understanding and improving these predictions. This conference was a sequel to the International Conference on Sub-seasonal to Seasonal Prediction (Robertson et al., 2014) which took place in College Park (Maryland, USA) in February 2014 to celebrate the start of the WWRP/WCRP S2S project, and to WCRP and WWRP conferences in Boulder, USA, in 2018 (Merryfield et al., 2020). A significant development compared to the previous S2S conferences was the large number of presentations on research to operation (R2O) and S2S applications and on the use of artificial intelligence and machine learning (AI/ML) methods for S2S prediction. Some of these methods provide empirical S2S forecasts which are competitive with state-of-the-art dynamical models. Other presentations demonstrated that AI/ML can provide alternative calibration of dynamical model outputs to traditional methods. Several talks and posters highlighted the increasing use of AI/ML, including deep learning, in S2S forecast post-processing and using AI to identify higher flow-dependent skill. Finally, some presentations demonstrated the value of AI/ML methods for a better understanding of S2S sources of predictability and attribution of extreme events.

S. J. Woolnough↗
DOE OSTI2014

SU-D-BRD-04: A Logical Organizational Approach to Clinical Information Management

Purpose: To develop a clinical information management system (CIMS) that collects, organizes physician inputs logically and supports analysis functionality. Methods: In a conventional electronic medical record system (EMR), the document manager component stores data in a pool of standalone .docx or .pdf files. The lack of a content-based logical organization makes cross-checking, reference or automatic inheritance of information challenging. We have developed an information-oriented clinical record system that addresses this shortcoming. In CIMS, a parent library predefines a set of available questions along with the data types of their expected answers. The creation of a questionnaire template is achieved by selecting questions from this parent library to form a virtual group. Instances of the same data field in different documents are linked by their question identifier. This design allows for flexible data sharing and inheritance among various forms using a longitudinal lineage of data indexed according to the modification time stamps of the documents. CIMS is designed with a web portal to facilitate querying, data entry and modification, aggregate report generation, and data adjudication. The current implementation addresses diagnostic data, medical history, vital signs, and various quantities in consult note and treatment summaries. Results: CIMS is currently storing treatment summary information of over 1,000 patients who have received treatment at UCLA Radiation Oncology between March 1, 2013 and January 31, 2014. We are in the process of incorporating a DICOM-RT dosimetry parser and patient reporting applications into CIMS, as well as continuing to define document templates to support additional forms. Conclusion: We are able to devise an alternative storage paradigm which results in an improvement in the accuracy and organizational structure of clinical information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗