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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Implementing Computer-Based Procedures: Thinking Outside the Paper Margins

In the past year there has been increased interest from the nuclear industry in adopting the use of electronic work packages and computer-based procedures (CBPs) in the field. The goal is to incorporate the use of technology in order to meet the Nuclear Promise requirements of reducing costs and improve efficiency and decrease human error rates of plant operations. Researchers, together with the nuclear industry, have been investigating the benefits an electronic work package system and specifically CBPs would have over current paper-based procedure practices. There are several classifications of CBPs ranging from a straight copy of the paper-based procedure in PDF format to a more intelligent dynamic CBP. A CBP system offers a vast variety of improvements, such as context driven job aids, integrated human performance tools (e.g., placekeeping and correct component verification), and dynamic step presentation. The latter means that the CBP system could only display relevant steps based on operating mode, plant status, and the task at hand. The improvements can lead to reduction of the worker’s workload and human error by allowing the work to focus on the task at hand more. A team of human factors researchers at the Idaho National Laboratory studied and developed design concepts for CBPs for field workers between 2012 and 2016. The focus of the research was to present information in a procedure in a manner that leveraged the dynamic and computational capabilities of a handheld device allowing the worker to focus more on the task at hand than on the administrative processes currently applied when conducting work in the plant. As a part of the research the team identified type of work, instructions, and scenarios where the transition to a dynamic CBP system might not be as beneficial as it would for other types of work in the plant. In most cases the decision to use a dynamic CBP system and utilize the dynamic capabilities gained will be beneficial to the worker. However, tasks that are reliant on the skill of the craft or have a short set of instructions may not provide a way or even need to utilize all the advanced capabilities in a dynamic CBP system. Therefore, a hybrid CBP system that could handle all the classifications of a CBP would be the best solution to take advantage of all that a CBP system offers. The implementation of a CBP system does not automatically improve the quality of procedures. Utilities should look into why each procedure is written the way it currently is on paper. Utilities should take the time before implementation to review, standardize format and update current procedures. Implementation of a CBP system can be a time to break out of traditional procedure writing processes and create new processes and procedures that take advantage of the capabilities a CBP system. This paper will summarize the research on CBPs and provide suggestions to take into consideration when implementing a CBP system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

VERA 3.6 Release

CASL has developed a formalized process to release the Virtual Environment for Reactor Applications (VERA) to non-CASL users through the Radiation Shielding Information Computational Center (RSICC). This milestone represents a major release of VERA with updates that significantly reduce computational resources required and introduce new capabilities related to fuel performance integration. This release will also be used by CASL Test Stands and training activities. VERA 3.6 represents an incremental release, with improvements to core component capabilities, significant performance improvements, and updated documentation. This release followed a significantly revised release process, with formal documentation, testing, readiness reviews, and release authorization. The major tasks that were completed as part of this milestone were: 1) Revision of the VERA RSICC Release Process and Procedures; 2) Identification of the VERA release components; 3) Creation of a Release Candidate; 4) Independent evaluation of the Release Candidate by the Advanced Modeling Applications (AMA) Focus Area; 5) A Release Candidate Readiness Review; 6) Development and execution of a System Test Plan; 7) Updates of manuals and other required documentation; 8) Export Control reviews; 9) A Release Readiness Review; and 10) Delivery of the release package to RSICC. Synopses of the work done to complete each of these major tasks are summarized in Section 2 below. Supporting details are provided in the PHI Kanban ticket #4424 Support VERA 3.6 Release Activities and its child tickets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Localized Fault Recovery for Nested Fork-Join Programs

Nested fork-join programs scheduled using work stealing can automatically balance load and adapt to changes in the execution environment. In this paper, we design an approach to efficiently recover from faults encountered by these programs. Specifically, we focus on localized recovery of the task space in the presence of fail-stop failures. We present an approach to efficiently track, under work stealing, the relationships between the work executed by various threads. This information is used to identify and schedule the tasks to be re-executed without interfering with normal task execution. The algorithm precisely computes the work lost, incurs minimal re-execution overhead, and can recover from an arbitrary number of failures. Experimental evaluation demonstrates low overheads in the absence of failures, recovery overheads on the same order as the lost work, and much lower recovery costs than alternative strategies.

Kestor, Gokcen↗
DOE OSTI2016

Well Integrity for Natural Gas Storage in Depleted Reservoirs and Aquifers

Introduction Motivation The 2015-2016 Aliso Canyon/Porter Ranch natural gas well blowout emitted approximately 100,000 tonnes of natural gas (mostly methane, CH 4 ) over four months. The blowout impacted thousands of nearby residents, who were displaced from their homes. The high visibility of the event has led to increased scrutiny of the safety of natural gas storage at the Aliso Canyon facility, as well as broader concern for natural gas storage integrity throughout the country. Federal Review of Well Integrity In April of 2016, the U.S. Department of Energy (DOE), in conjunction with the U.S. Department of Transportation (DOT) through the Pipeline and Hazardous Materials Safety Administration (PHMSA), announced the formation of a new Interagency Task Force on Natural Gas Storage Safety. The Task Force enlisted a group of scientists and engineers at the DOE National Laboratories to review the state of well integrity in natural gas storage in the U.S. The overarching objective of the review is to gather, analyze, catalogue, and disseminate information and findings that can lead to improved natural gas storage safety and security and thus reduce the risk of future events. The “Protecting our Infrastructure of Pipelines and Enhancing Safety Act of 2016’’ or the ‘‘PIPES Act of 2016,’’which was signed into law on June 22, 2016, created an Aliso Canyon Natural Gas Leak Task Force led by the Secretary of Energy and consisting of representatives from the DOT, Environmental Protection Agency (EPA), Department of Health and Human Services, Federal Energy Regulatory Commission (FERC), Department of Commerce and the Department of Interior. The Task Force was asked to perform an analysis of the Aliso Canyon event and make recommendations on preventing similar incidents in the future. The PIPES Act also required that DOT/PHMSA promulgate minimum safety standards for underground storage that would take effect within two years. Background on the DOE National Laboratories Well Integrity Work Group One of the primary areas that the Task Force is studying is integrity of natural gas wells at storage facilities. The DOE Office of Fossil Energy (FE) took the lead in this area and asked scientists and engineers from the National Energy Technology Laboratory (NETL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL), and Lawrence Berkeley National Laboratory (LBNL)) to form a Work Group to address this area. This Work Group is an expansion of the original “Lab Team” comprising scientists and engineers from SNL, LLNL, and LBNL which was formed to support the State of California’s response to the Aliso Canyon incident and operated under the Governor of California’s Aliso Canyon Emergency Order (1/6/2016). The Lab Team played a key role in advising the State of California’s Department of Conservation (DOC) in its oversight of SoCalGas during and after the incident.

03 NATURAL GAS↗
DOE OSTI2024

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

17 WIND ENERGY↗
DOE OSTI2017

Nitric-glycolic flowsheet evaluation with the slurry-fed melt rate furnace

The Savannah River National Laboratory (SRNL) was tasked to support validation of the Defense Waste Processing Facility (DWPF) melter offgas flammability model for the nitric-glycolic (NG) flowsheet. The work supports Deliverable 4 of the DWPF & Saltstone Facility Engineering Technical Task Request (TTR)1 and is supplemental to the Cold Cap Evaluation Furnace (CEF) testing conducted in 2014.2 The Slurry-fed Melt Rate Furnace (SMRF) was selected for the supplemental testing as it requires significantly less resources than the CEF and could provide a tool for more rapid analysis of melter feeds in the future. The SMRF platform has been used previously to evaluate melt rate behavior of DWPF glasses, but was modified to accommodate analysis of the offgas stream. Additionally, the Melt Rate Furnace (MRF) and Quartz Melt Rate Furnace (QMRF) were utilized for evaluations. MRF data was used exclusively for melt behavior observations and REDuction/OXidation (REDOX) prediction comparisons and will be briefly discussed in conjunction with its support of the SMRF testing. The QMRF was operated similarly to the SMRF for the same TTR task, but will be discussed in a separate future report. The overall objectives of the SMRF testing were to; 1) Evaluate the efficacy of the SMRF as a platform for steady state melter testing with continuous feeding and offgas analysis; and 2) Generate supplemental melter offgas flammability data to support the melter offgas flammability modelling effort for DWPF implementation of the NG flowsheet.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
DOE OSTI2013

Offshore Code Comparison Collaboration, Continuation: Phase II Results of a Floating Semisubmersible Wind System: Preprint

Offshore wind turbines are designed and analyzed using comprehensive simulation tools that account for the coupled dynamics of the wind inflow, aerodynamics, elasticity, and controls of the turbine, along with the incident waves, sea current, hydrodynamics, and foundation dynamics of the support structure. The Offshore Code Comparison Collaboration (OC3), which operated under the International Energy Agency (IEA) Wind Task 23, was established to verify the accuracy of these simulation tools [1]. This work was then extended under the Offshore Code Comparison Collaboration, Continuation (OC4) project under IEA Wind Task 30 [2]. Both of these projects sought to verify the accuracy of offshore wind turbine dynamics simulation tools (or codes) through code-to-code comparison of simulated responses of various offshore structures. This paper describes the latest findings from Phase II of the OC4 project, which involved the analysis of a 5-MW turbine supported by a floating semisubmersible. Twenty-two different organizations from 11 different countries submitted results using 24 different simulation tools. The variety of organizations contributing to the project brought together expertise from both the offshore structure and wind energy communities. Twenty-one different load cases were examined, encompassing varying levels of model complexity and a variety of metocean conditions. Differences in the results demonstrate the importance and accuracy of the various modeling approaches used. Significant findings include the importance of mooring dynamics to the mooring loads, the role nonlinear hydrodynamic terms play in calculating drift forces for the platform motions, and the difference between global (at the platform level) and local (at the member level) modeling of viscous drag. The results from this project will help guide development and improvement efforts for these tools to ensure that they are providing the accurate information needed to support the design and analysis needs of the offshore wind community.

17 WIND ENERGY↗
DOE OSTI2013

Parallel Algorithms for Graph Optimization using Tree Decompositions

Although many NP-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of required dynamic programming tables and excessive running times of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree-decomposition based approach to solve maximum weighted independent set. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.

Weerapurage, Dinesh P↗
DOE OSTI2025

Model-based Hierarchical Reinforcement Learning for Improved Physical Security Design: A Prototype

Prior work in FY24 developed an adversarial AI agent aid in path analysis of physical protection systems. This agent, trained using a model-based reinforcement learning algorithm, was able to successfully learn the most vulnerable path in facilities. It was able to extend the current state of practice for physical protection design by exhibiting dynamic behavior based on current environmental conditions. Whereas PathTrace largely performs a static, graph-based analysis, the AI agent was able to make decisions based on relative position in the facility, current conditions (was the adversarial agnet discovered?), and proximity to secondary targets. The agent demonstrated some novel capabilities, but had limitations that need to be resolved before it can be used for production purposes. For example, the adversarial agent generalizes poorly and takes a relatively long time to train. Nonetheless, there is still considerable promise for developing the adversarial agent further in order to explore even richer, more dynamic behaviors (e.g., adversary motivations, environmental debris, and more). This work considers a complementary idea; development of a planning agent. The planning agent is envisioned as an auto-complete-like tool that can help accelerate security system design by human experts. The agent would respect existing barriers and sensors placed by a human expert while offering cost-effective suggestions (i.e., implicitly balancing effectiveness with cost) to improve the design. The goal is for this agent to be part of an expert’s toolbox, not to totally upend the current state-of-practice, or to displace human experts. The ultimate goal would be concurrent training of both the adversarial and planning agent together, to learn entirely through self-play. This would represent an entirely new way of performing system deign. We selected a hierarchical, model-based reinforcement learning algorithm to serve as the planning agent. This is an extension of concepts used in the prior FY24 adversarial agent work. There, we had a single agent acting an environment. Here, we have two different sub-agents (policies), working together, to form a complete agent. There is a manager policy, which can select abstract goals on slower time scales, and a worker, which performs primitive actions to reach goals selected by the manager. It is worth noting that this class of algorithm is challenging to work with. From our understanding, our work is one of the first successful uses of model-based reinforcement learning (MBRL) in nuclear energy1 , and likely the first hierarchical model-based reinforcement learning application in nuclear energy. Further, this work is one of the first known attempts to apply AI to perform a design tasks in nuclear energy. Consequently, there were significant implementation challenges and the bulk of the work was focused on successful implementation and algorithm design. The results presented here are very low technology readiness level as a consequence of the lack of related literature, but still represent a significant step forward in the pursuit of applied AI for design.

42 ENGINEERING↗
DOE OSTI2012

Parallel Algorithms for Graph Optimization Using Tree Decompositions

Although many $\cal{NP}$-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of the necessary dynamic programming tables and excessive runtimes of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree decomposition-based approach to solve the maximum weighted independent set problem. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗
DOE OSTI2013

Preparation for the Recovery of Spent Nuclear Fuel (SNF) at Andreeva Bay, North West Russia - 13309

Andreeva Bay is located near Murmansk in the Russian Federation close to the Norwegian border. The ex-naval site was used to de-fuel nuclear-powered submarines and icebreakers during the Cold War. Approximately 22,000 fuel assemblies remain in three Dry Storage Units (DSUs) which means that Andreeva Bay has one of the largest stockpiles of highly enriched spent nuclear fuel (SNF) in the world. The high contamination and deteriorating condition of the SNF canisters has made improvements to the management of the SNF a high priority for the international community for safety, security and environmental reasons. International Donors have, since 2002, provided support to projects at Andreeva concerned with improving the management of the SNF. This long-term programme of work has been coordinated between the International Donors and responsible bodies within the Russian Federation. Options for the safe and secure management of SNF at Andreeva Bay were considered in 2004 and developed by a number of Russian Institutes with international participation. This consisted of site investigations, surveys and studies to understand the technical challenges. A principal agreement was reached that the SNF would be removed from the site altogether and transported to Russia's reprocessing facility at Mayak in the Urals. The analytical studies provided the information necessary to develop the construction plan for the site. Following design and regulatory processes, stakeholders endorsed the technical solution in April 2007. This detailed the processes, facilities and equipment required to safely remove the SNF and identified other site services and support facilities required on the site. Implementation of this strategy is now well underway with the facilities in various states of construction. Physical works have been performed to address the most urgent tasks including weather protection over one of the DSUs, installation of shielding over the cells, provision of radiation protection infrastructure and general preparation of the site for construction of the facilities for the removal of the SNF. This paper describes the development and implementation of the strategy and work to improve the safe and secure management of SNF, preparing it for retrieval and removal from Andreeva Bay. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Milestone 2.8: Preliminary Radiolytic Gas Generation Measurements from Helium-Backfilled Samples

The Department of Energy (DOE) is currently managing nearly 13 metric tons of aluminum-clad spent nuclear fuel (ASNF) with the intention of extended (> 50 years) dry storage in helium-backfilled canisters. Due to in-reactor and cooling pond conditions, oxyhydroxide corrosion layers have formed on the surface of the ASNF elements. These corrosion layers are susceptible to radiolysis and the formation of molecular hydrogen gas (H 2 ) due to the fuel’s inherent radiation field. Consequently, a rigorous evaluation of the effect of helium gas on radiolytic H 2 production is necessary to support the Technical Considerations and Challenges for Extended (> 50 yrs) Dry Storage of ASNF program, especially as previous Task 2 - Oxyhydroxide Layer Radiolytic Gas Generation Resolution work demonstrated a significant effect of gas composition on the radiolytic yield (G-value) of H 2 . Here we report preliminary G-values for the radiolytic formation of H 2 from the gamma irradiation of pre-corroded aluminum alloy 1100 coupons flame sealed in helium environments. Irradiations yielded G(H 2 ) values of (5.1 ± 0.5) x 10 –4 and (9.4 ± 0.9) x 10 –4 µmol J –1 for pristine coupons, and (10.1 ± 0.4) x 10 –4 and (15.1 ± 1.2) x 10 –4 µmol J –1 for pre-corroded coupons for 0% and 50% relative humidity, respectively. These helium environment G(H 2 ) values are between 28% and 58% higher than previously reported values for argon environments. This enhancement is attributed to the significant difference in first ionization energy between helium (24.59 eV) and argon (15.76) facilitating additional processes, e.g., Penning ionization. These new preliminary helium environment G(H 2 ) values will be employed by Task 3 - Sealed and Vented System Episodic Breathing and Gas Generation Prediction to model the effect of radiolytic H 2 accumulation in helium environments to evaluate the practicality of the extended storage standard canister design.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2013

Prediction of human observer performance in a 2-alternative forced choice low-contrast detection task using channelized Hotelling observer: Impact of radiation dose and reconstruction algorithms

Purpose: Efficient optimization of CT protocols demands a quantitative approach to predicting human observer performance on specific tasks at various scan and reconstruction settings. The goal of this work was to investigate how well a channelized Hotelling observer (CHO) can predict human observer performance on 2-alternative forced choice (2AFC) lesion-detection tasks at various dose levels and two different reconstruction algorithms: a filtered-backprojection (FBP) and an iterative reconstruction (IR) method. Methods: A 35 Multiplication-Sign 26 cm{sup 2} torso-shaped phantom filled with water was used to simulate an average-sized patient. Three rods with different diameters (small: 3 mm; medium: 5 mm; large: 9 mm) were placed in the center region of the phantom to simulate small, medium, and large lesions. The contrast relative to background was -15 HU at 120 kV. The phantom was scanned 100 times using automatic exposure control each at 60, 120, 240, 360, and 480 quality reference mAs on a 128-slice scanner. After removing the three rods, the water phantom was again scanned 100 times to provide signal-absent background images at the exact same locations. By extracting regions of interest around the three rods and on the signal-absent images, the authors generated 21 2AFC studies. Each 2AFC study had 100 trials, with each trial consisting of a signal-present image and a signal-absent image side-by-side in randomized order. In total, 2100 trials were presented to both the model and human observers. Four medical physicists acted as human observers. For the model observer, the authors used a CHO with Gabor channels, which involves six channel passbands, five orientations, and two phases, leading to a total of 60 channels. The performance predicted by the CHO was compared with that obtained by four medical physicists at each 2AFC study. Results: The human and model observers were highly correlated at each dose level for each lesion size for both FBP and IR. The Pearson's product-moment correlation coefficients were 0.986 [95% confidence interval (CI): 0.958-0.996] for FBP and 0.985 (95% CI: 0.863-0.998) for IR. Bland-Altman plots showed excellent agreement for all dose levels and lesions sizes with a mean absolute difference of 1.0%{+-} 1.1% for FBP and 2.1%{+-} 3.3% for IR. Conclusions: Human observer performance on a 2AFC lesion detection task in CT with a uniform background can be accurately predicted by a CHO model observer at different radiation dose levels and for both FBP and IR methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Radiological Characterization for Decommissioning: International Good Practice and Experience - 18396

The 'Task Group on Radiological Characterization for Decommissioning (TGRCD)' functions under the umbrella of the Nuclear Energy Agency' (NEA) 'Working Party on Decommissioning and Dismantling (WPDD),' which is currently reporting to NEA Radioactive Waste Management Committee (RWMC). The TGRCD task group, which is composed of international experts, has been working since 2014 on a commitment to provide a high-level guidance for characterization practitioners working in nuclear decommissioning. The work has focused on facility characterization from a waste and materials perspective. Radiological characterization is a key activity enabling planning and implementation of decommissioning of nuclear facilities. Effective characterization allows the extent, location and nature of contamination to be determined providing crucial information to facilitate facility dismantling, the management of material and arising waste, protection of workers, the public, the environment and associated cost estimation. The report is written for characterization practitioners who carry out the tactical planning, preparation, optimization and implementation of characterization to support the decommissioning of nuclear facilities and the management of associated materials and waste. It compiles recent experience of NEA member countries in radiological characterization, including the experience of international experts and practitioners; the learning from international case studies and international conferences; and national approaches to the application of international and national regulations, standards and guidance documents. Using this comprehensive approach and evaluation studies, the report identifies relevant good practices and sets out set out practical guidance covering all stages of the characterization process as related to decommissioning. This paper provides a summary of the work conducted and the main findings from the detailed report. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗