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At least 1,495 records · Page 83

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Elisabeth Andrews↗

BERT-based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

hazard analysis↗

The NASA Biological Institutional Scientific Collection (NBISC): Tissue and Microbe Biospecimens to Advance Space Research

The NASA Biological Institutional Scientific Collection (NBISC) is a biorepository of non-human biospecimens from NASA-funded spaceflight investigations and correlative ground studies. The collection has its roots in the 1960s through collaborations by NASA Ames Research Center with other NASA centers, universities, and international space agencies by sharing non-human biospecimens from spaceflight and space-relevant ground experiments. These collaborations have advanced the field of space exploration by helping to maximize the data gained from spaceflight and other NASA-funded experiments. NBISC coordinates closely with the Biospecimen Sharing Program (BSP) which is responsible for organized sample collection from spaceflight and ground rodent experiments. In 2022 NBISC partnered with HRP’s Biospecimen and Tissue Sharing Collection (BTSC) Program to also archive samples from HRP’s Space Radiation Element-funded studies which primarily involve rodents exposed to various radiation protocols at the NASA Space Radiation Laboratory (NSRL) and other analog facilities. To date, more than fifty thousand biospecimens from BTSC have been transferred to NBISC for distribution to the community. In 2023, NBISC embarked on a new Space Biology funded endeavor to create the Space Microbial Culture Collection (SMCC) which will serve as a central repository for microbial isolates associated with space flight, gravitational, and space radiation research. This presentation will highlight several success stories of analyses carried out using archived NBISC samples received by researchers in recent years and will detail the process for proposing and receiving samples from NBISC, BTSC and SMCC. Making available these 150,000+ unique biospecimens to the scientific research community, NBISC not only serves as a repository for storing and distributing non-human biospecimens, but also acts as a resource to enable new discoveries that will benefit NASA and humankind.

Biospecimen↗

The GeneLab Buffet: A Bioinformatic MATRIX of MANGO and TOAST

The GeneLab data repository provides an unparalleled resource for exploring how spaceflight affects organisms with omics-level insights. However, two major interlinked challenges to capitalizing on the information within these data are their vast breadth and the often-specialized expertise that has been required in the past for their analysis. How do you compare responses within and between studies, especially if you are a non-bioinformatics specialist? This presentation will discuss how Space Biology data can be accessed using software to help provide these data resources to address research questions and generate new hypotheses. The presentation will cover a wide range of the available space life science tools but will focus on TOAST, MANGO, the MATRIX, RadBioApp and other interactive relational databases (https://genelab.nasa.gov/external-vis-apps). These exploration environments have been developed to search the GeneLab data repository for new insights that inform how model organisms respond to microgravity, radiation and other factors associated with spaceflight. The presentation will be interactive, and participants will have the opportunity to ask questions and learn more about the data viz and modeling tools that are available to them.

AstroBotany↗

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, to foster collaborations with equity. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within the Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate with community members and set new standards for space-relevant data and metadata. The AWGs welcome any ASGSR members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are encouraged to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗

The TOLNet 2.0 Website: How an API Can Promote Open Science and FAIR Principles

The Tropospheric Ozone Lidar Network (TOLNet) has generated over a decade of ozone vertical profile data products over North America. The science value of the TOLNet data has been demonstrated in numerous peer-reviewed publications on air quality and other ozone relevant research. To support the broad spectrum of data use, the TOLNet team launched a major effort to upgrade the web-based data repository aiming to enhance the data discoverability and to enable machine-to-machine data upload and download processes. Specifically, the TOLNet website included an application programming interface (API), which supports machine-to-machine data search and data download. The API also extracts selected variables from the files, which can be retrieved as JSON objects and used to create data displays without having to download or open the underlying files. The TOLNet science team members can also use the API for automated data upload, including a data file scanning feature to ensure data product integrity. To be presented will include a summary of key features of data repositories, an actual use case of machine-to-machine data access/use, as well as our journey to make TOLNet data more FAIR, i.e., more findable, accessible, interoperable, and (re)usable.

Crystal Gummo↗

The Tables of Aerosol Optics (TAO) Project

The Table of Aerosol Optics (TAO) project is a community repository of optics computations (extinction, absorption, single-scatter albedo, lidar ratio, etc) that are useful for global models and remote sensing applications. TAO expands upon historical efforts (e.g., Hess et al., 1998) by building an open database that uses recent measurements and new computational techniques for non-spherical particles. The ‘open’ aspect of TAO is important, since the size distributions, hygroscopicities, refractive indices, and morphological recommendations of today will undoubtedly yield to different values in the future; the open framework of TAO allows scientists to keep adding new computations to the database as the science evolves. TAO is meant to be a community repository where specialists can put their computations for other scientists to use. So for instance, some groups are advancing new techniques that can accommodate complex fractal aggregates of black carbon, other groups are working on realistic irregular shapes for mineral dust, and different groups are updating the hygroscopicity of various aerosol types using new techniques. The TAO database gives these scientists a place to distribute their products. As TAO grows, modelers and remote sensing specialists will look to TAO as a place to find a wide variety of choices for testing. Meanwhile, global modelers can also use TAO to lobby for new tables that accommodate their needs. Eventually, TAO will provide mass extinction coefficients, mass absorption coefficients, lidar ratios, etc., at popular remote sensing and global modeling wavelengths (0.25-40 µm) for all pertinent species (sulfate, sea salt, BC, OC, BrC, dust, etc.). TAO will also accept computations for aerosol ‘type’ (e.g., biomass burning, urban, background, etc.) that may include regional and seasonal variability. Multiple tables may be created for each species or type to account for the multiple valid size distributions, hygroscopicities, complex refractive indices, and shapes that can be found in the literature.

Greg Schuster↗

BERT-based Topic Modeling and Information Retrieval to Support Fishbone Diagramming for Safe Integration of Unmanned Aircraft Systems in Wildfire Response

Recent concepts for emerging wildfire response operations have included unmanned aircraft systems (UAS) due to their increasing accessibility and capabilities. To integrate UAS into wildfire response safely, researchers have studied the use of large repositories of historic incident reports to improve the scope of root cause analysis. Recent work has emphasized applying state-of-the-art natural language processing techniques to extract useful information from these repositories. However, it has not yet been studied how these results can be interpreted and integrated into the systems engineering process. In this work, we propose a process in which Bidirectional Encoder Representations from Transformers (BERT)-based topic modeling and information retrieval are applied to a relevant set of documents in order to support the development of a fishbone diagram in a semiautomated process. High-level themes in the document set are identified using topic modeling, which are then refined and interpreted by a human analyst. Then, the themes are used to guide a finer search using information retrieval, which returns specific incident reports of relevance. This provides traceability to specific incidents as well as broader categorizations that comprise the fishbone branches. We apply the proposed process to relevant documents from NASA’s Aviation Safety Reporting System (ASRS). The proposed process is widely applicable when relevant documents are available, and the results from this study will be useful to identifying potential causes of wildfire response UAS incidents.

hazard analysis↗

Conclusions of A Mini Technical Interchange Meeting on New Cross Risk Integration Projects Managed By the NASA Space Radiation Element

To enable deep space exploration and sustained human presence in space, the NASA Human Research Program’s (HRP) Space Radiation Element (SRE) funds research to characterize and mitigate adverse health outcomes from exposure to space radiation. Recently, the Space Radiation Element was tasked with supporting multiple HRP Elements with innovative and enabling projects to inform risk characterization, facilitate mitigation activities, and support crew health and performance. These projects, such as precision health initiative, NASA Omics Archive (NOA) and human sample repositories, are agnostic to any HRP Element, hence the name, Cross Risk Integration Projects (CRIP). CRIP serves three broad purposes: Services: Generate samples/data or manage the receipt, inventory, archive and ultimate redistribution of biospecimens created in HRP-funded spaceflight and analog research activities – includes NASA Omics Archive (NOA) project and various human and animal sample repositories. Method Development: Identify and evaluate, new-to-NASA research or analysis methods or techniques – includes TRRaC (Translational Radiation Research and Countermeasures) Project. Enabling Capabilities: Demonstrate real world application by adapting, adopting and/or developing capabilities to benefit crew health & performance and improve risk – includes Precision Health Initiative (Pharmacogenomics) and advanced biological systems and engineered tissue microsystems initiative (tissue chips, organ-on-a-chip). To identify new technologies, future work, and solicitations, the SRE organizes themed sessions at annual HRP Investigators’ Workshops (IWS). These technical interchange meetings (TIMs) provide a venue for the scientific community to present ongoing work and engage in open discussion, limitations of current approaches, and incorporation of novel experimental strategies and other innovative techniques. Here a summary and lessons learned from the SRE-sponsored mini-TIM titled “Space Radiation Cross Risk Integrations Projects” at HRP IWS 2024 will be communicated. The 90-min TIM had 6 speakers who presented impressive novel ideas and work This poster presents the outcomes of the session along with proposed future workshops and other SRE initiatives.

Janapriya Saha↗

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗

Conclusions of a Mini Technical Interchange Meeting on New Cross Risk Integration Projects Managed by the NASA Space Radiation Element

To enable deep space exploration and sustained human presence in space, the NASA Human Research Program’s (HRP) Space Radiation Element (SRE) funds research to characterize and mitigate adverse health outcomes from exposure to space radiation that include risks of carcinogenesis, cardiovascular disease, and central nervous system decrements. Recently, the SRE was tasked with supporting multiple HRP Elements with innovative and enabling projects to inform risk characterization, facilitate mitigation activities, and support crew health and performance. These projects, such as precision health initiative, NASA Omics Archive (NOA) and human sample repositories, are agnostic to any HRP Element, hence the name, Cross-Risk Integration Projects (CRIP). CRIP serves 3 broad purposes: - Services: Generate samples and data and manage the receipt, inventory, archive, and ultimate redistribution of biospecimens created in HRP-funded spaceflight and analog research activities—includes NASA Omics Archive project and various human and animal sample repositories. - Method Development: Identify and evaluate new-to-NASA research or analysis methods or techniques that could fundamentally improve existing or planned research efforts—includes the Translational Radiation Research and Countermeasures Project. - Enabling Capabilities: Demonstrate real-world application by adapting, adopting, and/or developing capabilities to benefit crew health and performance and improve risk mitigation—includes Precision Health Initiative (Pharmacogenomics) and advanced biological systems and engineered tissue microsystems initiative (tissue chips, organ-on-a-chip). To identify new technologies, future work, and solicitations, the SRE organizes themed sessions at annual HRP Investigators’ Workshops (IWS). These technical interchange meetings (TIMs) provide a venue for the scientific community to present ongoing work and engage in open discussion of results, limitations of current approaches, and incorporation of novel experimental strategies, model systems, and other innovative techniques. Here, a summary of the studies presented at the SRE-sponsored mini-TIM at the HRP IWS along with the goals and objectives of the CRIP projects is communicated. The 90-min TIM had 6 speakers who presented impressive novel ideas and work, some of which are funded under CRIP by the Space Radiation Element.

Janapriya Saha↗

Enhancing accessibility and usability of Algorithm Theoretical Basis Documents through the Algorithm Publication Tool

Effective communication of scientific theories is crucial for transforming raw instrument data into valuable Earth observation products. The NASA Earth science data community disseminates this knowledge through Algorithm Theoretical Basis Documents (ATBDs). Historically, these documents lacked a standardized format, were designed for human readability rather than machine interpretation, and were challenging to locate due to the absence of a centralized repository. The Algorithm Publication Tool (APT) transforms how ATBD content is presented, simplifying the processes of creating, updating, and locating these documents. APT offers authors the option to use its user-friendly cloud-based interface or standardized templates for ATBD development. The primary advantage of the interface is its capability to manage the entire ATBD creation process within a single environment, ensuring comprehensive tracking of all activities and facilitating user tasks. Conversely, the use of standardized ATBD templates allows users to create documents using familiar tools like Google Docs, Microsoft Word, or Overleaf for LaTeX. APT also provides a centralized repository, enabling easy search and discovery of published ATBDs. This presentation showcases APT's functionalities, illustrates its contributions to advancing open science, and highlights potential benefits for broader community adoption.

Bradley Baker↗

AI Curation Methods for NASA Scientific Data

The NASA Open Science Data Repository (OSDR) serves as a central hub for sharing and accessing NASA's vast collection of scientific data, supporting researchers across diverse fields. To enhance the efficiency, accuracy, and accessibility of this data, we are leveraging advanced artificial intelligence (AI) techniques as part of the AI for Curation project. By integrating large language models (LLMs) into our data curation workflow, we aim to streamline the entire process—from data submission to user interaction. This initiative focuses on improving key areas, including data ingestion, curation, and user engagement with curated datasets, impacting multiple domains and a wide user base. First, we are developing tools that can automatically parse data in various formats, using LLMs to convert unstructured data into structured, standardized formats. This reduces the manual effort required for curation, allowing curators to focus on more critical scientific analyses. Additionally, AI and machine learning (ML) models are being implemented to automate data validation and verification, ensuring the highest standards of data quality and reliability. Finally, we are creating a conversational AI agent to interact with the curated scientific studies in OSDR, helping users easily navigate the repository and access relevant data. By enhancing data discoverability and accessibility, these advancements will foster new research opportunities and promote the principles of open science.

Walter Alvarado↗

The Fukushima Daiichi Accident Study Information Portal

This paper presents a description of The Fukushima Daiichi Accident Study Information Portal. The Information Portal was created by the Idaho National Laboratory as part of joint NRC and DOE project to assess the severe accident modeling capability of the MELCOR analysis code. The Fukushima Daiichi Accident Study Information Portal was created to collect, store, retrieve and validate information and data for use in reconstructing the Fukushima Daiichi accident. In addition to supporting the MELCOR simulations, the Portal will be the main DOE repository for all data, studies and reports related to the accident at the Fukushima Daiichi nuclear power station. The data is stored in a secured (password protected and encrypted) repository that is searchable and accessible to researchers at diverse locations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Sustaining the National Geothermal Data System: Considerations for a System Wide Approach and Node Maintenance, Geothermal Resources Council 37th Annual Meeting, Las Vegas, Nevada, September 29-October 2, 2013

Since the 2009 American Recovery and Reinvestment Act the U.S. Department of Energy’s Geothermal Technologies Office has funded $33.7 million for multiple data digitization and aggregation projects focused on making vast amounts of geothermal relevant data available to industry for advancing geothermal exploration. These projects are collectively part of the National Geothermal Data System (NGDS), a distributed, networked system for maintaining, sharing, and accessing data in an effort to lower the levelized cost of electricity (LCOE). Determining “who owns” and “who maintains” the NGDS and its data nodes (repositories in the distributed system) is yet to be determined. However, the invest- ment in building and populating the NGDS has been substantial, both in terms of dollars and time; it is critical that this investment be protected by ensuring sustainability of the data, the software and systems, and the accessibility of the data. Only then, will the benefits be fully realized. To keep this operational system sustainable will require four core elements: continued serving of data and applications; maintenance of system operations; a governance structure; and an effective business model. Each of these presents a number of challenges. Data being added to the NGDS are not strictly geothermal but data considered relevant to geothermal exploration and develop- ment, including vast amounts of oil and gas and groundwater wells, among other data. These are relevant to a broader base of users. By diversifying the client base to other users and other fields, the cost of maintaining core infrastructure can be spread across an array of stakeholders and clients. It is presumed that NGDS will continue to provide free and open access to its data resources. The next-phase NGDS operation should be structured to eventually pursue revenue streams to help off-set sustainability expenses as necessary and appropriate, potentially including income from: grants and contracts (agencies, foundations, pri- vate sector), membership, fees for services (consulting, training, customization, ‘app’ development), repository services (data, services, apps, models, documents, multimedia), advertisements, fees for premier services or applications, subscriptions to value added services, licenses, contributions and donations, endow- ments, and sponsorships.

15 GEOTHERMAL ENERGY↗

National Geothermal Data System: Transforming the Discovery, Access, and Analytics of Data for Geothermal Exploration

Compendium of Papers from the 38th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California February 11-13, 2013 The National Geothermal Data System (NGDS) is a distributed, interoperable network of data collected from state geological surveys across all fifty states and the nation’s leading academic geothermal centers. The system serves as a platform for sharing consistent, reliable, geothermal-relevant technical data with users of all types, while supplying tools relevant for their work. As aggregated data supports new scientific findings, this content-rich linked data ultimately broadens the pool of knowledge available to promote discovery and development of commercial-scale geothermal energy production. Most of the up-front risks associated with geothermal development stem from exploration and characterization of subsurface resources. Wider access to distributed data will, therefore, result in lower costs for geothermal development. NGDS is on track to become fully operational by 2014 and will provide a platform for custom applications for accessing geothermal relevant data in the U.S. and abroad. It is being built on the U.S. Geoscience Information Network (USGIN) data integration framework to promote interoperability across the Earth sciences community. The basic structure of the NGDS employs state-of-the art informatics to advance geothermal knowledge. The following four papers comprising this Open-File Report are a compendium of presentations, from the 38th Annual Workshop on Geothermal Reservoir Engineering, taking place February 11-13, 2013 at Stanford University, Stanford, California. “NGDS Geothermal Data Domain: Assessment of Geothermal Community Data Needs,” outlines the efforts of a set of nationwide data providers to supply data for the NGDS. In particular, data acquisition, delivery, and methodology are discussed. The paper addresses the various types of data and metadata required and why simple links to existing data are insufficient for promoting geothermal exploration. Authors of this paper are Arlene Anderson, US DOE Geothermal Technologies Office, David Blackwell, Southern Methodist University (SMU), Cathy Chickering (SMU), Toni Boyd, Oregon Institute of Technology’s GeoHeat Center, Roland Horne, Stanford University, Matthew MacKenzie, Uberity, Joe Moore, University of Utah, Duane Nickull, Uberity, Stephen Richard, Arizona Geological Survey, and Lisa Shevenell, University of Nevada, Reno. “NGDS User Centered Design: Meeting the Needs of the Geothermal Community,” discusses the user- centered design approach taken in the development of a user interface solution for the NGDS. The development process is research based, highly collaborative, and incorporates state-of-the-art practices to ensure a quality user interface for the widest and greatest utility. Authors of this paper are Harold Blackman, Boise State University, Suzanne Boyd, Anthro-Tech, Kim Patten, Arizona Geological Survey, and Sam Zheng, Siemens Corporate Research. “Fueling Innovation and Adoption by Sharing Data on the DOE Geothermal Data Repository Node on the National Geothermal Data System,” describes the motivation behind the development of the Geothermal Data Repository (GDR) and its role in the NGDS. This includes the benefits of using the GDR to share geothermal data of all types and DOE’s data submission process. Authors of this paper are Jon Weers, National Renewable Energy Laboratory and Arlene Anderson, US DOE Geothermal Technologies Office. Finally, “Developing the NGDS Adoption of CKAN for Domestic & International Data Deployment,” provides an overview of the “Node-In-A-Box” software package designed to provide data consumers with a highly functional interface to access the system, and to ease the burden on data providers who wish to publish data in the system. It is important to note that this software package constitutes a reference implementation and that the NGDS architecture is based on open standards, which means other server software can make resources available, and other client applications can utilize NGDS data. Authors of this paper are Ryan Clark, Arizona Geological Survey (AZGS), Christoph Kuhmuench, Siemens Corporate Research, and Stephen Richard, AZGS.

15 GEOTHERMAL ENERGY↗

Technetium Incorporation in Glass for the Hanford Tank Waste Treatment and Immobilization Plant

A priority of the United States Department of Energy (U.S. DOE) is to dispose of nuclear wastes accumulated in 177 underground tanks at the Hanford Nuclear Reservation in eastern Washington State. These nuclear wastes date from the Manhattan Project of World War II and from plutonium production during the Cold War. The DOE plans to separate high-level radioactive wastes from low activity wastes and to treat each of the waste streams by vitrification (immobilization of the nuclides in glass) for disposal. The immobilized low-activity waste will be disposed of here at Hanford and the immobilized high-level waste at the national geologic repository. Included in the inventory of highly radioactive wastes is large volumes of 99Tc (~9 × 10E2 TBq or ~2.5 × 104 Ci or ~1500 kg). A problem facing safe disposal of Tc-bearing wastes is the processing of waste feed into in a chemically durable waste form. Technetium incorporates poorly into silicate glass in traditional glass melting. It readily evaporates during melting of glass feeds and out of the molten glass, leading to a spectrum of high-to-low retention (ca. 20 to 80%) in the cooled glass product. DOE-ORP currently has a program at Pacific Northwest National Laboratory (PNNL), in the Department of Materials Science and Engineering at Rutgers University and in the School of Mechanical and Materials Engineering at Washington State University that seeks to understand aspects of Tc retention by means of studying Tc partitioning, molten salt formation, volatilization pathways, and cold cap chemistry. Another problem involves the stability of Tc in glass in both the national geologic repository and on-site disposal after it has been immobilized. The major environmental concern with 99Tc is its high mobility in addition to a long half-life (2.1×105 yrs). The pertechnetate ion (TcO4-) is highly soluble in water and does not adsorb well onto the surface of minerals and so migrates nearly at the same velocity as groundwater. Long-term corrosion of glass waste forms is an area of current interest to the DOE, but attention to the release of Tc from glass has been little explored. It is expected that the release of Tc from glass should be highly dependent on the local glass structure as well as the chemistry of the surrounding environment, including groundwater pH. Though the speciation of Tc in glass has been previously studied, and the Tc species present in waste glass have been previously reported, environmental Tc release mechanisms are poorly understood. The recent advances in Tc chemistry that have given rise to an understanding of incorporation in the glass giving rise to significantly higher single-pass retention during vitrification are presented. Additionally, possible changes to the baseline flowsheet that allow for relatively minor volumes of Tc reporting to secondary waste treatment will be discussed.

Kruger, Albert A.↗

Annual Technology Baseline (Including Supporting Data); NREL (National Renewable Energy Laboratory)

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), National Renewable Energy Laboratory provides an organized and centralized dataset that was reviewed by internal and external experts. It uses the best information from the Department of Energy laboratory's renewable energy analysts and Energy Information Administration information for conventional technologies. The ATB will be updated annually in order to provide an up-to-date repository of current and future cost and performance data. Going forward, we plan to revise and refine the values using best available information. The ATB includes both a presentation with notes (PDF) and an associated Excel Workbook. The ATB includes the following electricity generation technologies: land-based wind; offshore wind; utility-scale solar PV; concentrating solar power; geothermal power; hydropower plants (upgrades to existing facilities, powering non-powered dams, and new stream-reach development); conventional coal; coal with carbon capture and sequestration; integrated gasification combined cycle coal; natural gas combustion turbines; natural gas combined cycle; conventional biopower. Nuclear laboratory's renewable energy analysts and Energy Information Administration information for conventional technologies. The ATB will be updated annually in order to provide an up-to-date repository of current and future cost and performance data. Going forward, we plan to revise and refine the values using best available information.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗