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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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Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2

Federated learning enables multiple data owners to collaboratively train robust machine learning models without transferring large or sensitive local datasets by only sharing the parameters of the locally trained models. Here, in this article, we elaborate on the design of our Advanced Privacy-Preserving Federated Learning (APPFL) framework, which streamlines end-to-end secure and reliable federated learning experiments across cloud computing facilities and high-performance computing resources by leveraging Globus Compute, a distributed function as a service platform, and Amazon Web Services. We further demonstrate the use case of APPFL in fine-tuning an LLaMA 2 7B model using several cloud resources and supercomputers.

97 MATHEMATICS AND COMPUTING↗

Framework Development Supporting the Safety Portal

In a collaborating scientific research arena it is important to have an environment where analysts have access to a shared repository of information, documents, and software tools, and be able to accurately maintain and track historical changes in models. The new Safety Portal cloud-based environment will be accessible remotely from anywhere regardless of computing platforms given that the platform has available Internet access and proper browser capabilities. Information stored at this environment would be restricted based on user assigned credentials. This report discusses current development of a cloud-based web portal for PRA tools.

97 MATHEMATICS AND COMPUTING↗

Best practices mobile application for D and D KM-IT - 15712

The Deactivation and Decommissioning Knowledge Management Information Tool (D and D KM-IT) is the repository of useful information built specifically for D and D community. The knowledge provided by the D and D KM-IT is the experience and expertise gained by people within the field and fellow employees of the Department of Energy (DOE). This information has been the result of gathering, analyzing, storing, and sharing knowledge to help reduce time spent on discovering previously found data. In order to help in organizing all the data from all the professional contributors, the D and D KM-IT has been divided into 12 different modules. Each individual module pertains to a different area of information for users, such as vendor and technology information, collaboration tools, and even a hotline that contains problems posted by the users. Purpose: - Design and develop the module for the Best Practices on D and D KM-IT mobile platform deployed at https://m.dndkm.org; - The Best Practices mobile module should integrate with existing modules seamlessly; - Use the D and D KM-IT existing database to consume information for the mobile system. jQuery Mobile framework was used to develop Best Practices module for mobile devices. jQuery Mobile framework provides support for responsive web design (RWD). RWD allows adaptation of the layout and user interface of web sites and web apps to different device resolutions, screen densities, and views. UI design was implemented with three fundamental elements: CSS media queries, An adaptable grid, Flexible images and media. Advantages/benefits: - A responsive web design adapts to any-sized screen / resolution and orientation view; - ASP.NET compatible which allows the D and D KM-IT database to support all platforms accessing the system; - Navigating pages is more bandwidth efficient by refreshing data in small section with Ajax instead of reloading the entire page; - Multiple parts of a page can perform different tasks resulting in improved user's experience. Results: - Mobile system is accessible on compatible devices running Android, Apple, Blackberry, Palm, and Windows devices; - Best Practices searches through Characterization, Decontamination, Dismantlement, Material Disposition, and Worker Safety; - Keyword search is enabled for the best practices that are available on both the desktop and mobile systems - Documents are formatted into a PDF file format to ensure compatibility on any device. Conclusion: - Fully integrated with the desktop Best Practices module and displays documents that are uploaded on web platform; - Fast-loading with D and D KM-IT mobile system and downloadable documents; - Responsive design which gives the same user experience when either viewed on smart phone or tablet.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Smart Inverters, Dumb Risk: Taking Control of IBR Security in the Digital Age

This presentation addresses the security challenges posed by Inverter-Based Resources (IBRs) in the modern energy landscape. The presentation highlights the vulnerabilities and risks associated with IBRs, including the potential for cyber-attacks, the impact of insecure defaults, and the systemic risks posed by supply chain dependencies. Key topics covered include: 1) The increasing digital transformation in energy systems and the associated security risks. 2) Specific vulnerabilities in IBRs, including weak passwords, hardcoded credentials, and insecure web application interfaces. 3) The implications of persistent connectivity and the strategic risks posed by foreign-manufactured components. 4) The role of regulatory frameworks, such as NERC CIP, in addressing these challenges and the limitations of current oversight. 5) Practical solutions for mitigating risks, including secure design practices, vendor risk assessments, and the importance of strong passwords and role-based access control. The presentation underscores the necessity of a comprehensive, system-of-systems approach to securing IBRs, emphasizing the need for collaboration across various stakeholders, including operators, developers, and regulators, to ensure the resilience and security of the energy grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Spaceflight Operations Services Grid (SOSG)

In an effort to adapt existing space flight operations services to new emerging Grid technologies we are developing a Grid-based prototype space flight operations Grid. This prototype is based on the operational services being provided to the International Space Station's Payload operations located at the Marshall Space Flight Center, Alabama. The prototype services will be Grid or Web enabled and provided to four user communities through portal technology. Users will have the opportunity to assess the value and feasibility of Grid technologies to their specific areas or disciplines. In this presentation descriptions of the prototype development, User-based services, Grid-based services and status of the project will be presented. Expected benefits, findings and observations (if any) to date will also be discussed. The focus of the presentation will be on the project in general, status to date and future plans. The End-use services to be included in the prototype are voice, video, telemetry, commanding, collaboration tools and visualization among others. Security is addressed throughout the project and is being designed into the Grid technologies and standards development. The project is divided into three phases. Phase One establishes the baseline User-based services required for space flight operations listed above. Phase Two involves applying Gridlweb technologies to the User-based services and development of portals for access by users. Phase Three will allow NASA and end users to evaluate the services and determine the future of the technology as applied to space flight operational services. Although, Phase One, which includes the development of the quasi-operational User-based services of the prototype, development will be completed by March 2004, the application of Grid technologies to these services will have just begun. We will provide status of the Grid technologies to the individual User-based services. This effort will result in an extensible environment that incorporates existing and new spaceflight services into a standards-based framework providing current and future NASA programs with cost savings and new and evolvable methods to conduct science. This project will demonstrate how the use of new programming paradigms such as web and grid services can provide three significant benefits to the cost-effective delivery of spaceflight services. They will enable applications to operate more efficiently by being able to utilize pooled resources. They will also permit the reuse of common services to rapidly construct new and more powerful applications. Finally they will permit easy and secure access to services via a combination of grid and portal technology by a distributed user community consisting of NASA operations centers, scientists, the educational community and even the general population as outreach. The approach will be to deploy existing mission support applications such as the Telescience Resource Kit (TReK) and new applications under development, such as the Grid Video Distribution System (GViDS), together with existing grid applications and services such as high-performance computing and visualization services provided by NASA s Information Power Grid (IPG) in the MSFC s Payload Operations Integration Center (POIC) HOSC Annex. Once the initial applications have been moved to the grid, a process will begin to apply the new programming paradigms to integrate them where possible. For example, with GViDS, instead of viewing the Distribution service as an application that must run on a single node, the new approach is to build it such that it can be dispatched across a pool of resources in response to dynamic loads. To make this a reality, reusable services will be critical, such as a brokering service to locate appropriate resource within the pool. This brokering service can then be used by other applications such as the TReK. To expand further, if the GViDS application is constructed using a services-based mel, then other applications such as the Video Auditorium can then use GViDS as a service to easily incorporate these video streams into a collaborative conference. Finally, as these applications are re-factored into this new services-based paradigm, the construction of portals to integrate them will be a simple process. As a result, portals can be tailored to meet the requirements of specific user communities.

Bradford, Robert N.↗

Mapping Support for Targeted Critical Minerals Exploration and Extraction

The United States’ dependency on imported minerals poses significant risks to economic stability and national security due to potential supply disruptions. Recognizing the strategic importance of critical minerals, the Department of Energy (DOE) emphasizes the need for a secure and resilient supply chain to support emissions reduction, technology development, and capitalization on clean energy opportunities. The DOE’s Office of Manufacturing and Energy Supply Chains (MESC), in collaboration with the Office of Policy (OP), addresses these vulnerabilities by focusing on upstream domestic critical minerals production, balancing extraction with social and environmental goals, including conservation, environmental justice, and respect for Tribal sovereignty. This report showcases a collaborative effort involving Idaho National Laboratory (INL), Argonne National Laboratory (Argonne), National Renewable Energy Laboratory (NREL), and the U.S. Geological Survey (USGS) to map mineral development potential along with key social and environmental datasets. A geographical information system (GIS)-based web map application was developed as a preliminary tool for environmental analysis, integrating 158 geospatial data layers such as critical habitat, land ownership, economic indicators, and environmental concerns. Data were sourced from agencies like the Bureau of Land Management (BLM) and USGS and processed using GIS technology to enhance visualization and analysis. The proposed analysis framework categorizes areas into high, mid, and low concern based on withdrawn lands, special status species, the Economic Development Capacity Index (EDCI) Mining Composite Index, and the Climate and Economic Justice Screening Tool (CEJST). While the application provides broad visualizations, it is not a substitute for detailed environmental reviews required under the National Environmental Policy Act (NEPA). Users must conduct further analyses and engage with tribal entities and other stakeholders for comprehensive planning. A case study of the Idaho Cobalt Belt (ICB) in Lemhi County, Idaho, has been provided in the report to illustrate the tool's practical use. This report introduces a GIS application and framework to support stakeholders in identifying and prioritizing areas for critical mineral exploration, promoting secure supply chains, and advancing the nation's energy independence through responsible resource stewardship.

54 ENVIRONMENTAL SCIENCES↗

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies in their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Featuresexclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies into their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design, although parallels between ORDEM and MEM are also discussed. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Features exclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗

Multi-Disciplinary Analysis for Future Launch Systems Using NASA's Advanced Engineering Environment (AEE)

A new engineering environment constructed for the purposes of analyzing and designing Reusable Launch Vehicles (RLVs) is presented. The new environment has been developed to allow NASA to perform independent analysis and design of emerging RLV architectures and technologies. The new Advanced Engineering Environment (AEE) is both collaborative and distributed. It facilitates integration of the analyses by both vehicle performance disciplines and life-cycle disciplines. Current performance disciplines supported include: weights and sizing, aerodynamics, trajectories, propulsion, structural loads, and CAD-based geometries. Current life-cycle disciplines supported include: DDT&E cost, production costs, operations costs, flight rates, safety and reliability, and system economics. Involving six NASA centers (ARC, LaRC, MSFC, KSC, GRC and JSC), AEE has been tailored to serve as a web-accessed agency-wide source for all of NASA's future launch vehicle systems engineering functions. Thus, it is configured to facilitate (a) data management, (b) automated tool/process integration and execution, and (c) data visualization and presentation. The core components of the integrated framework are a customized PTC Windchill product data management server, a set of RLV analysis and design tools integrated using Phoenix Integration's Model Center, and an XML-based data capture and transfer protocol. The AEE system has seen production use during the Initial Architecture and Technology Review for the NASA 2nd Generation RLV program, and it continues to undergo development and enhancements in support of its current main customer, the NASA Next Generation Launch Technology (NGLT) program.

Monell, D.↗

Tools for Water Ingress Testing

The Safety Storage and Engineering Team, as part of the Production Support Services division (PSS-2), is tasked with ensuring the safety of containers used for handling and storage of nuclear materials. As part of this work, water ingress tests are conducted to evaluate the water-tightness of containers intended for in-glovebox use. In collaboration, the statistics group of the Computer and Computational Sciences Division (CCS-6) provided support in developing a statistically defensible approach for determining appropriate sample sizes for water ingress testing. Water ingress testing involves multiple measurements on multiple containers. Our approach uses a simple random effects model to analyze a pilot data set, implementing prediction limits to evaluate the efficacy of collecting additional data. Although this study capitalizes on available data, our approach can be used with estimates of the ratio of between and within variability and average values, often available from past testing or expert knowledge. An interactive Shiny tool was developed as a final user-friendly product for future testing. The Shiny interface is an open-source package providing a framework for building web applications. Raw data exploration and prediction interval-based sample size assessments can quickly be conducted by the engineering team without needing to interact with the underlying code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗

Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)

The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web , and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic `bottlebrush' polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Virtual Mission Operations Center: Collaborative Environment

The Virtual Mission Operations Center - Collaborative Environment (VMOC-CE) intent is to have a central access point for all the resources used in a collaborative mission operations environment to assist mission operators in communicating on-site and off-site in the investigation and resolution of anomalies. It is a framework that as a minimum incorporates online chat, realtime file sharing and remote application sharing components in one central location. The use of a collaborative environment in mission operations opens up the possibilities for a central framework for other project members to access and interact with mission operations staff remotely. The goal of the Virtual Mission Operations Center (VMOC) Project is to identify, develop, and infuse technology to enable mission control by on-call personnel in geographically dispersed locations. In order to achieve this goal, the following capabilities are needed: Autonomous mission control systems Automated systems to contact on-call personnel Synthesis and presentation of mission control status and history information Desktop tools for data and situation analysis Secure mechanism for remote collaboration commanding Collaborative environment for remote cooperative work The VMOC-CE is a collaborative environment that facilitates remote cooperative work. It is an application instance of the Virtual System Design Environment (VSDE), developed by NASA Goddard Space Flight Center's (GSFC) Systems Engineering Services & Advanced Concepts (SESAC) Branch. The VSDE is a web-based portal that includes a knowledge repository and collaborative environment to serve science and engineering teams in product development. It is a "one stop shop" for product design, providing users real-time access to product development data, engineering and management tools, and relevant design specifications and resources through the Internet. The initial focus of the VSDE has been to serve teams working in the early portion of the system/product lifecycle - concept development, proposal preparation, and formulation. The VMOC-CE expands the application of the VSDE into the operations portion of the system lifecycle. It will enable meaningful and real-time collaboration regardless of the geographical distribution of project team members. Team members will be able to interact in satellite operations, specifically for resolving anomalies, through access to a desktop computer and the Internet. Mission Operations Management will be able to participate and monitor up to the minute status of anomalies or other mission operations issues. In this paper we present the VMOC-CE project, system capabilities, and technologies.

Medina, Barbara↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Host Onboarding Tool (HObT) v1.0.0

The Host OnBoarding Tool (Hobt) is a publicly accessible, web-based software designed to organize and share information about microbial hosts under development at the Agile BioFoundry (ABF). It streamlines the assessment, tracking, and sharing of information related to microbial host development and provides a centralized platform where users can rapidly evaluate hosts' readiness for various bio processes. HObT leverages the Tier System, a standardized host development framework that organizes and assesses microbial hosts based on their readiness for biomanufacturing. Each tier outlines key targets—including genetic tools, growth conditions, omics data, and predictive models—needed to transform new or emerging microbes into established production platforms. By applying clear criteria for advancement, the Tier System helps users quickly evaluate each organism's current development status, identify gaps in available knowledge or tools, and prioritize future strain improvement efforts. Through its user-friendly interface, HObT encourages contributions of new data and insights from researchers, fostering collaboration and accelerating host development. By providing structured guidance for microbial strain advancement, HObT and the Tier System support more systematic, rapid, and cost-effective development of non-traditional microbial hosts, ultimately enhancing the efficiency and impact of biomanufacturing research and applications.

Plahar, Hector [Lawrence Berkeley National Laborat↗

Robotics on KM-IT platform - 19107

The Knowledge Management Information Tool (KM-IT) is a web-based system developed to maintain and preserve the Department of Energy's (DoE's) knowledge base. The system was developed by Florida International University's Applied Research Center (FIU-ARC) with the support of the D and D community including the DOE Office of Environmental Management, and with the collaboration and support of the DoE's Energy Facility Contractors Group (EFCOG) and the former ALARA Centers at Hanford and Savannah. The KM-IT system is a community driven system tailored to serve the technical issues faced by the workforce across the DOE Complex. This KM-IT web-based interactive system is operational and available for use at www.dndkm.org and is currently comprised of the following modules: Web Crawler, Hotline, Technology, Hanford's ALARA Center Reports, Specialist Directory, Lessons Learned, Best Practices, Video/Picture Library, Vendors and Industry News. The Web Crawler dynamically searches through the KM-IT repository as well as the web and displays search results based on the search criteria. The Hotline allows registered users to post questions/problems related to D and D and to receive solutions from a subject-matter specialist. The Technology module serves as repository of D and D technologies and contains technology/ demonstration fact sheets and vendor information. D and D community members can add Lessons Learned, Best Practices, and Pictures/Videos to the D and D repository, after a formal approval process. The Vendor module provides a directory of commercial vendors who provide D and D related technologies, supplies, and services. KM-IT makes an excellent use of the knowledge that exists within the D and D community by allowing D and D project managers around the DOE complex to collaborate by sharing innovative ideas, past experiences, and practices and by maintaining a directory of subject matter specialists. FIU is working on developing a new knowledge base using the existing KM-IT framework to provide focused information on robotics. FIU will develop the robotics technology and vendor modules to provide information related to robotics technologies and its application to many different areas including D and D, remote systems and waste processing. This robotics knowledge base will provide the ability to search through the information repository as well as display customized summary information including robotics technology descriptions, benefits, limitations, videos and pictures. The vendor module will provide information related to industry vendors for these technologies and include updated vendor contact information. The vendor module will also provide a search capability based on keywords as well as categories. The robotics knowledge base will publish commercially available technologies as well as the technologies that are still in the research and development phase with national laboratories and academic universities. The robotics KM-IT will be developed in phases to support all of the features of the KM-IT platform and will be published on www.rkmit.org. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Robotics Technologies on Knowledge Management Information Tool (KM-IT) Platform - 16465

The Knowledge Management Information Tool (KM-IT) is a web-based system developed to maintain and preserve the deactivation and decommissioning (D and D) knowledge base across the Department of Energy (DOE) complex. The system was developed by the Applied Research Center (ARC) at Florida International University (FIU) with the support of the D and D community, including the DOE Office of Environmental Management (DOE EM), and with the active collaboration and support of the DOE's Energy Facility Contractors Group (EFCOG). The KM-IT system is a D and D community driven system tailored to serve the technical issues faced by the D and D workforce across the DOE Complex. New information, including vendors and technologies related to D and D, are researched and added to KM-IT on an ongoing basis. In late 2014, DOE EM provided a database of 471 robotic technologies, originally developed by NuVision Engineering and Cogentus Consulting, with a request to evaluate the potential for integrating the data into the KM-IT framework for ongoing hosting/maintenance of the information. All of the data from the original database as well as photographs, documents, and videos are now available on KM-IT. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Arctic-Boreal vulnerability experiment model benchmarking system

Abstract NASA’s Arctic-Boreal Vulnerability Experiment (ABoVE) integrates field and airborne data into modeling and synthesis activities for understanding Arctic and Boreal ecosystem dynamics. The ABoVE Benchmarking System (ABS) is an operational software package to evaluate terrestrial biosphere models against key indicators of Arctic and Boreal ecosystem dynamics, i.e.: carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance. The ABS utilizes satellite remote sensing data, airborne data, and field data from ABoVE as well as collaborating research networks in the region, e.g.: the Permafrost Carbon Network, the International Soil Carbon Network, the Northern Circumpolar Soil Carbon Database, AmeriFlux sites, the Moderate Resolution Imaging Spectroradiometer, the Orbiting Carbon Observatory 2, and the Soil Moisture Active Passive mission. The ABS is designed to be interactive for researchers interested in having their models accurately represent observations of key Arctic indicators: a user submits model results to the system, the system evaluates the model results against a set of Arctic-Boreal benchmarks outlined in the ABoVE Concise Experiment Plan, and the user then receives a quantitative scoring of model strengths and deficiencies through a web interface. This interactivity allows model developers to iteratively improve their model for the Arctic-Boreal Region by evaluating results from successive model versions. We show here, for illustration, the improvement of the Lund–Potsdam–Jena-Wald Schnee und Landschaft (LPJwsl) version model through the ABoVE ABS as a new permafrost module is coupled to the existing model framework. The ABS will continue to incorporate new benchmarks that address indicators of Arctic-Boreal ecosystem dynamics as they become available.

Stofferahn, Eric (ORCID:0000000169604193)↗